Report generated on 07-Dez-2020 at 21:55:12 by pytest-html v2.1.1
Packages | {"pluggy": "0.13.1", "py": "1.9.0", "pytest": "6.1.1"} |
Platform | Linux-5.4.0-56-generic-x86_64-with-glibc2.29 |
Plugins | {"html": "2.1.1", "hypothesis": "4.36.2", "metadata": "1.10.0"} |
Python | 3.8.5 |
65 tests ran in 114.77 seconds.
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65 passed, 0 skipped, 0 failed, 0 errors, 0 expected failures, 0 unexpected passesResult | Test | Duration | Links |
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Passed | tests/test_clustering.py::test_clustering | 2.02 | |
No log output captured. | |||
Passed | tests/test_clustering.py::test_clusteringcase | 0.12 | |
------------------------------Captured stdout call------------------------------ maxradius: 11.45313971598804 | |||
Passed | tests/test_clustering.py::test_clusteringcase_eggbox | 0.01 | |
------------------------------Captured stdout call------------------------------ maxradius: 1.8439766380495826e-10 | |||
Passed | tests/test_clustering.py::test_overclustering_eggbox_txt | 0.29 | |
------------------------------Captured stdout call------------------------------ ==== TEST CASE 20 ===================== manual: r=2.989717e-03 nc=1 reclustered: nc=18 manual: r=2.989717e-03 nc=1 reclustered: nc=18 manual: r=2.270048e-03 nc=1 reclustered: nc=18 ==== TEST CASE 23 ===================== manual: r=1.212573e-05 nc=1 reclustered: nc=18 manual: r=1.353579e-05 nc=1 reclustered: nc=18 manual: r=1.235571e-05 nc=1 reclustered: nc=18 ==== TEST CASE 24 ===================== manual: r=3.947988e-05 nc=1 reclustered: nc=18 manual: r=4.172909e-05 nc=1 reclustered: nc=18 manual: r=7.273383e-05 nc=1 reclustered: nc=18 ==== TEST CASE 27 ===================== manual: r=1.978904e-08 nc=1 reclustered: nc=18 manual: r=1.890650e-08 nc=1 reclustered: nc=18 manual: r=1.605539e-08 nc=1 reclustered: nc=18 ==== TEST CASE 49 ===================== manual: r=6.815424e-05 nc=1 reclustered: nc=18 manual: r=4.236106e-05 nc=1 reclustered: nc=18 manual: r=5.657479e-05 nc=1 reclustered: nc=18 | |||
Passed | tests/test_clustering.py::test_overclustering_eggbox_update | 3.28 | |
------------------------------Captured stdout call------------------------------ ==== TEST CASE 20 ===================== loading... loading... done u0:960 -> u:960 : 881 points are common initialised with: r=3.861322e-01 nc=18 --- intermediate tests how create_new reacts --- updated to (with same data): r=3.861322e-01 nc=18 updated to (with new data): r=3.861322e-01 nc=19 --- end --- setting maxradiussq to None transitioned to : r=4.254452e-01 nc=18 True cluster 1/18: 82 points @ 0.40067 +- 0.01202 , 0.40022 +- 0.01511 cluster 2/18: 44 points @ 0.60378 +- 0.01234 , 0.98922 +- 0.00757 cluster 3/18: 89 points @ 0.59884 +- 0.01297 , 0.19993 +- 0.01399 cluster 4/18: 70 points @ 0.59770 +- 0.01321 , 0.59970 +- 0.01270 cluster 5/18: 66 points @ 0.79962 +- 0.01283 , 0.40189 +- 0.01364 cluster 6/18: 75 points @ 0.20262 +- 0.01346 , 0.20165 +- 0.01254 cluster 7/18: 32 points @ 0.19776 +- 0.01239 , 0.98809 +- 0.00597 cluster 8/18: 31 points @ 0.01257 +- 0.00703 , 0.39886 +- 0.01234 cluster 9/18: 67 points @ 0.79925 +- 0.01331 , 0.80076 +- 0.01356 cluster 10/18: 42 points @ 0.79877 +- 0.01327 , 0.01046 +- 0.00668 cluster 11/18: 41 points @ 0.99046 +- 0.00685 , 0.19675 +- 0.01388 cluster 12/18: 39 points @ 0.39798 +- 0.01322 , 0.00984 +- 0.00698 cluster 13/18: 23 points @ 0.01097 +- 0.00852 , 0.01041 +- 0.00711 cluster 14/18: 73 points @ 0.20029 +- 0.01323 , 0.59918 +- 0.01368 cluster 15/18: 44 points @ 0.98858 +- 0.00665 , 0.60129 +- 0.01259 cluster 16/18: 41 points @ 0.01238 +- 0.00658 , 0.80156 +- 0.01229 cluster 17/18: 84 points @ 0.40175 +- 0.01292 , 0.79791 +- 0.01272 cluster 18/18: 17 points @ 0.98546 +- 0.00732 , 0.98774 +- 0.00694 ==== TEST CASE 23 ===================== loading... loading... done u0:1040 -> u:1040 : 966 points are common initialised with: r=6.160003e-03 nc=1 --- intermediate tests how create_new reacts --- updated to (with same data): r=6.160003e-03 nc=1 updated to (with new data): r=6.160003e-03 nc=18 found lonely points 1039 18 (array([1]), array([1040])) --- end --- setting maxradiussq to None transitioned to : r=3.440933e-01 nc=18 True cluster 1/18: 73 points @ 0.60558 +- 0.03956 , 0.60161 +- 0.03742 cluster 2/18: 79 points @ 0.40034 +- 0.03940 , 0.40519 +- 0.03757 cluster 3/18: 41 points @ 0.97203 +- 0.02060 , 0.20253 +- 0.03872 cluster 4/18: 84 points @ 0.19581 +- 0.04039 , 0.60134 +- 0.03804 cluster 5/18: 87 points @ 0.20159 +- 0.03605 , 0.20771 +- 0.03841 cluster 6/18: 85 points @ 0.80668 +- 0.03802 , 0.40101 +- 0.03809 cluster 7/18: 39 points @ 0.03874 +- 0.02094 , 0.80033 +- 0.03636 cluster 8/18: 80 points @ 0.79850 +- 0.03921 , 0.79083 +- 0.03705 cluster 9/18: 40 points @ 0.96956 +- 0.02038 , 0.60841 +- 0.03341 cluster 10/18: 99 points @ 0.60042 +- 0.03532 , 0.19601 +- 0.03848 cluster 11/18: 19 points @ 0.04123 +- 0.02000 , 0.02673 +- 0.02228 cluster 12/18: 40 points @ 0.40610 +- 0.03892 , 0.03809 +- 0.02090 cluster 13/18: 87 points @ 0.40176 +- 0.03955 , 0.79885 +- 0.03542 cluster 14/18: 52 points @ 0.20797 +- 0.03841 , 0.96717 +- 0.02119 cluster 15/18: 38 points @ 0.59639 +- 0.03805 , 0.96716 +- 0.01828 cluster 16/18: 44 points @ 0.80236 +- 0.04018 , 0.03255 +- 0.01736 cluster 17/18: 21 points @ 0.96129 +- 0.01684 , 0.96388 +- 0.01766 cluster 18/18: 32 points @ 0.03640 +- 0.01610 , 0.39737 +- 0.03884 ==== TEST CASE 24 ===================== loading... loading... done u0:1080 -> u:1080 : 720 points are common initialised with: r=2.523267e-03 nc=1 --- intermediate tests how create_new reacts --- updated to (with same data): r=2.523267e-03 nc=1 updated to (with new data): r=2.523267e-03 nc=19 --- end --- setting maxradiussq to None transitioned to : r=7.393072e-01 nc=18 True cluster 1/18: 50 points @ 0.80133 +- 0.02367 , 0.40736 +- 0.02143 cluster 2/18: 67 points @ 0.40401 +- 0.02029 , 0.40261 +- 0.02217 cluster 3/18: 23 points @ 0.01998 +- 0.01209 , 0.81024 +- 0.01845 cluster 4/18: 60 points @ 0.20213 +- 0.02305 , 0.20032 +- 0.01965 cluster 5/18: 32 points @ 0.60086 +- 0.02176 , 0.98367 +- 0.01059 cluster 6/18: 47 points @ 0.80338 +- 0.02194 , 0.79993 +- 0.01991 cluster 7/18: 36 points @ 0.98306 +- 0.01107 , 0.59781 +- 0.02273 cluster 8/18: 76 points @ 0.59943 +- 0.01980 , 0.19632 +- 0.02156 cluster 9/18: 56 points @ 0.20016 +- 0.01965 , 0.59828 +- 0.02257 cluster 10/18: 9 points @ 0.01908 +- 0.01199 , 0.01513 +- 0.01132 cluster 11/18: 59 points @ 0.39933 +- 0.02184 , 0.80070 +- 0.02167 cluster 12/18: 29 points @ 0.98462 +- 0.01006 , 0.20604 +- 0.02154 cluster 13/18: 30 points @ 0.80514 +- 0.02107 , 0.01876 +- 0.00936 cluster 14/18: 14 points @ 0.98169 +- 0.01256 , 0.97917 +- 0.01043 cluster 15/18: 49 points @ 0.59988 +- 0.02080 , 0.59826 +- 0.02404 cluster 16/18: 22 points @ 0.02401 +- 0.00978 , 0.40533 +- 0.01845 cluster 17/18: 32 points @ 0.20429 +- 0.02222 , 0.97957 +- 0.00988 cluster 18/18: 29 points @ 0.39559 +- 0.02135 , 0.01376 +- 0.01155 ==== TEST CASE 27 ===================== loading... loading... done u0:1160 -> u:1160 : 790 points are common initialised with: r=4.168517e-03 nc=1 --- intermediate tests how create_new reacts --- updated to (with same data): r=4.168517e-03 nc=1 updated to (with new data): r=4.168517e-03 nc=18 found lonely points 879 18 (array([1]), array([1160])) --- end --- setting maxradiussq to None transitioned to : r=4.282518e-01 nc=18 True cluster 1/18: 28 points @ 0.02876 +- 0.01072 , 0.40418 +- 0.02504 cluster 2/18: 72 points @ 0.40427 +- 0.02589 , 0.40337 +- 0.02568 cluster 3/18: 66 points @ 0.80063 +- 0.03025 , 0.79903 +- 0.02314 cluster 4/18: 69 points @ 0.80137 +- 0.02777 , 0.40462 +- 0.02720 cluster 5/18: 31 points @ 0.02746 +- 0.01466 , 0.79860 +- 0.02690 cluster 6/18: 62 points @ 0.59600 +- 0.02452 , 0.59711 +- 0.02909 cluster 7/18: 64 points @ 0.20064 +- 0.02644 , 0.20221 +- 0.02651 cluster 8/18: 36 points @ 0.59915 +- 0.02534 , 0.97793 +- 0.01435 cluster 9/18: 39 points @ 0.97736 +- 0.01458 , 0.59960 +- 0.02338 cluster 10/18: 86 points @ 0.60015 +- 0.02393 , 0.19435 +- 0.02628 cluster 11/18: 32 points @ 0.98151 +- 0.01174 , 0.20348 +- 0.02462 cluster 12/18: 65 points @ 0.19863 +- 0.02526 , 0.59691 +- 0.02542 cluster 13/18: 15 points @ 0.02567 +- 0.01173 , 0.02191 +- 0.01523 cluster 14/18: 41 points @ 0.39375 +- 0.02798 , 0.02135 +- 0.01484 cluster 15/18: 77 points @ 0.40243 +- 0.02649 , 0.80397 +- 0.02748 cluster 16/18: 38 points @ 0.80371 +- 0.02372 , 0.02465 +- 0.01314 cluster 17/18: 18 points @ 0.97856 +- 0.01405 , 0.97604 +- 0.01338 cluster 18/18: 41 points @ 0.19975 +- 0.02576 , 0.97554 +- 0.01299 ==== TEST CASE 42 ===================== loading... loading... done u0:1640 -> u:1640 : 1324 points are common initialised with: r=2.155017e-01 nc=18 --- intermediate tests how create_new reacts --- updated to (with same data): r=2.155017e-01 nc=18 updated to (with new data): r=2.155017e-01 nc=20 --- end --- setting maxradiussq to None transitioned to : r=2.029861e-01 nc=18 True cluster 1/18: 134 points @ 0.20129 +- 0.00945 , 0.20101 +- 0.01049 cluster 2/18: 65 points @ 0.59936 +- 0.00932 , 0.99209 +- 0.00545 cluster 3/18: 85 points @ 0.99089 +- 0.00488 , 0.60043 +- 0.01046 cluster 4/18: 130 points @ 0.60003 +- 0.00928 , 0.20093 +- 0.01017 cluster 5/18: 129 points @ 0.59949 +- 0.00979 , 0.60100 +- 0.01016 cluster 6/18: 70 points @ 0.00947 +- 0.00504 , 0.79955 +- 0.00842 cluster 7/18: 130 points @ 0.40067 +- 0.00968 , 0.40022 +- 0.01000 cluster 8/18: 122 points @ 0.79990 +- 0.00981 , 0.80044 +- 0.00967 cluster 9/18: 65 points @ 0.19964 +- 0.00934 , 0.99144 +- 0.00504 cluster 10/18: 72 points @ 0.00860 +- 0.00543 , 0.40071 +- 0.01088 cluster 11/18: 128 points @ 0.19967 +- 0.01029 , 0.60159 +- 0.01024 cluster 12/18: 79 points @ 0.79941 +- 0.00983 , 0.00749 +- 0.00504 cluster 13/18: 76 points @ 0.99223 +- 0.00521 , 0.19896 +- 0.00995 cluster 14/18: 69 points @ 0.39964 +- 0.00971 , 0.00907 +- 0.00538 cluster 15/18: 126 points @ 0.40202 +- 0.00982 , 0.79926 +- 0.00912 cluster 16/18: 99 points @ 0.80119 +- 0.00999 , 0.39961 +- 0.00929 cluster 17/18: 29 points @ 0.98948 +- 0.00510 , 0.99242 +- 0.00478 cluster 18/18: 32 points @ 0.00711 +- 0.00510 , 0.00782 +- 0.00532 | |||
Passed | tests/test_flatnuts.py::test_detailed_balance | 2.18 | |
------------------------------Captured stdout call------------------------------ ---- seed=1 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 BACKWARD SAMPLING FROM 4 [0.14168242 0.38811823] [0.02821641 0.02835197] -0.1665060917360781 BACKWARD SAMPLING FROM -4 [0.11583903 0.41282151] [-0.02893116 -0.02762223] -0.10171045505355579 BisectSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), None, None, None, 10, array([0.28919725, 0.02611023]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 5, array([0.14454144, 0.1642214 ]), array([ 0.02893116, -0.02762223]), 10, array([0.28919725, 0.02611023]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 2, array([0.05774795, 0.2470881 ]), array([ 0.02893116, -0.02762223]), 5, array([0.14454144, 0.1642214 ]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([1.14374817e-04, 3.02332573e-01]), array([-0.02893116, -0.02762223]), 1, array([0.02881679, 0.27471034]), array([ 0.02893116, -0.02762223]), 2, array([0.05774795, 0.2470881 ]), array([ 0.02893116, -0.02762223]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.02881679 0.27471034] [ 0.02893116 -0.02762223] new direction: [0.02821641 0.02835197] reversing there [ 0.02893116 -0.02762223] making one step from [0.02881679 0.27471034] [ 0.02893116 -0.02762223] --> [0.0570332 0.30306231] [0.02821641 0.02835197] trying new point, [0.0570332 0.30306231] next() call -0.48643206112737647 goals: [('reflect-at', 1, array([0.0570332 , 0.30306231]), array([0.02821641, 0.02835197]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.09073879959282771 goals: [('bisect', 1, array([0.0570332 , 0.30306231]), array([0.02821641, 0.02835197]), None, None, None, 10, array([0.31098087, 0.55823006]), array([0.02821641, 0.02835197]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31098087 0.55823006] [0.02821641 0.02835197] -0.09073879959282771 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31098087, 0.55823006]), array([-0.02821641, -0.02835197]), None, None, None, 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.1016481498381896 goals: [('bisect', 0, array([0.31098087, 0.55823006]), array([-0.02821641, -0.02835197]), 5, array([0.16989883, 0.4164702 ]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.25225605758357234 goals: [('bisect', 5, array([0.16989883, 0.4164702 ]), array([-0.02821641, -0.02835197]), 7, array([0.11346601, 0.35976626]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3588980473806718 goals: [('bisect', 7, array([0.11346601, 0.35976626]), array([-0.02821641, -0.02835197]), 8, array([0.0852496 , 0.33141428]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4864320611273768 goals: [('bisect', 8, array([0.0852496 , 0.33141428]), array([-0.02821641, -0.02835197]), 9, array([0.0570332 , 0.30306231]), array([-0.02821641, -0.02835197]), 10, array([0.02881679, 0.27471034]), array([-0.02821641, -0.02835197]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.02881679 0.27471034] [-0.02821641 -0.02835197] new direction: [-0.02893116 0.02762223] reversing there [-0.02821641 -0.02835197] making one step from [0.02881679 0.27471034] [-0.02821641 -0.02835197] --> [1.14374817e-04 3.02332573e-01] [0.02893116 0.02762223] trying new point, [1.14374817e-04 3.02332573e-01] next() call -0.4884051545701359 goals: [('reflect-at', 10, array([1.14374817e-04, 3.02332573e-01]), array([0.02893116, 0.02762223]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [1.14374817e-04 3.02332573e-01] [-0.02893116 -0.02762223] -0.48840515457013567 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 sampling between (-3, 4) ---- seed=2 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 BACKWARD SAMPLING FROM 4 [0.550579 0.59531977] [0.00022913 0.03999934] -0.2651418446056711 BACKWARD SAMPLING FROM -2 [0.54920422 0.35532371] [0.00022913 0.03999934] -0.4124530140569493 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.54966248, 0.43532239]), array([0.00022913, 0.03999934]), None, None, None, 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3805855729471914 goals: [('bisect', 0, array([0.54966248, 0.43532239]), array([0.00022913, 0.03999934]), 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 7, array([0.55126639, 0.7153178 ]), array([0.00022913, 0.03999934]), 10, array([0.55195379, 0.83531583]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.55080813, 0.63531911]), array([0.00022913, 0.03999934]), 6, array([0.55103726, 0.67531846]), array([0.00022913, 0.03999934]), 7, array([0.55126639, 0.7153178 ]), array([0.00022913, 0.03999934]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.55103726 0.67531846] [0.00022913 0.03999934] new direction: [-0.03532089 0.01877324] reversing there [0.00022913 0.03999934] making one step from [0.55103726 0.67531846] [0.00022913 0.03999934] --> [0.51571637 0.69409169] [-0.03532089 0.01877324] trying new point, [0.51571637 0.69409169] next() call None goals: [('reflect-at', 6, array([0.51571637, 0.69409169]), array([-0.03532089, 0.01877324]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.54989161 0.47532174] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.55080813 0.63531911] [0.00022913 0.03999934] -0.3805855729471914 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.2033543310016853 goals: [('bisect', 0, array([0.55080813, 0.63531911]), array([-0.00022913, -0.03999934]), None, None, None, 5, array([0.54966248, 0.43532239]), array([-0.00022913, -0.03999934]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.54966248 0.43532239] [0.00022913 0.03999934] -0.2033543310016853 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=3 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 BACKWARD SAMPLING FROM 4 [0.23962941 0.66238895] [-0.01281883 0.03789034] -0.3583382577658276 BACKWARD SAMPLING FROM -4 [0.34218007 0.35926626] [-0.01281883 0.03789034] -0.306118410872214 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), None, None, None, 10, array([0.16271642, 0.88973096]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 10, array([0.16271642, 0.88973096]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12894573017062852 goals: [('bisect', 0, array([0.29090474, 0.51082761]), array([-0.01281883, 0.03789034]), 2, array([0.26526707, 0.58660828]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.22561386347891177 goals: [('bisect', 2, array([0.26526707, 0.58660828]), array([-0.01281883, 0.03789034]), 3, array([0.25244824, 0.62449861]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3583382577658276 goals: [('bisect', 3, array([0.25244824, 0.62449861]), array([-0.01281883, 0.03789034]), 4, array([0.23962941, 0.66238895]), array([-0.01281883, 0.03789034]), 5, array([0.22681058, 0.70027928]), array([-0.01281883, 0.03789034]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.22681058 0.70027928] [-0.01281883 0.03789034] new direction: [-0.03961561 -0.00553205] reversing there [-0.01281883 0.03789034] making one step from [0.22681058 0.70027928] [-0.01281883 0.03789034] --> [0.18719497 0.69474723] [-0.03961561 -0.00553205] trying new point, [0.18719497 0.69474723] next() call -0.4916020278270488 goals: [('reflect-at', 5, array([0.18719497, 0.69474723]), array([-0.03961561, -0.00553205]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3490349009639423 goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([-0.03961561, -0.00553205]), None, None, None, 10, array([0.01088307, 0.66708697]), array([ 0.03961561, -0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.01088307 0.66708697] [ 0.03961561 -0.00553205] -0.3490349009639423 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.01088307, 0.66708697]), array([-0.03961561, 0.00553205]), None, None, None, 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4916020278270488 goals: [('bisect', 0, array([0.01088307, 0.66708697]), array([-0.03961561, 0.00553205]), 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 7, array([0.26642619, 0.70581134]), array([0.03961561, 0.00553205]), 10, array([0.38527301, 0.7224075 ]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.18719497, 0.69474723]), array([0.03961561, 0.00553205]), 6, array([0.22681058, 0.70027928]), array([0.03961561, 0.00553205]), 7, array([0.26642619, 0.70581134]), array([0.03961561, 0.00553205]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.22681058 0.70027928] [0.03961561 0.00553205] new direction: [ 0.01281883 -0.03789034] reversing there [0.03961561 0.00553205] making one step from [0.22681058 0.70027928] [0.03961561 0.00553205] --> [0.23962941 0.66238895] [ 0.01281883 -0.03789034] trying new point, [0.23962941 0.66238895] next() call -0.3583382577658272 goals: [('reflect-at', 6, array([0.23962941, 0.66238895]), array([ 0.01281883, -0.03789034]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.04377824648995988 goals: [('bisect', 6, array([0.23962941, 0.66238895]), array([ 0.01281883, -0.03789034]), None, None, None, 10, array([0.29090474, 0.51082761]), array([ 0.01281883, -0.03789034]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.29090474 0.51082761] [-0.01281883 0.03789034] -0.04377824648995989 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=4 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 BACKWARD SAMPLING FROM 4 [0.80905758 0.52184001] [-0.03949306 -0.00634806] -0.33324941010291637 BACKWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16694885584599184 goals: [('bisect', 0, array([0.96702984, 0.54723225]), array([-0.03949306, -0.00634806]), None, None, None, 10, array([0.5720992 , 0.48375165]), array([-0.03949306, -0.00634806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.5720992 0.48375165] [-0.03949306 -0.00634806] -0.16694885584599184 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.49545942179887775 goals: [('bisect', 0, array([0.5720992 , 0.48375165]), array([0.03949306, 0.00634806]), None, None, None, 10, array([0.96702984, 0.54723225]), array([0.03949306, 0.00634806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.96702984 0.54723225] [-0.03949306 -0.00634806] -0.49545942179887775 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 sampling between (-4, 3) ---- seed=5 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 BACKWARD SAMPLING FROM 4 [0.63456332 0.54663199] [ 0.03653803 -0.01627797] -0.22851708746536278 BACKWARD SAMPLING FROM -4 [0.34225906 0.67685573] [ 0.03653803 -0.01627797] -0.4495450053329357 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3970381430661767 goals: [('bisect', 0, array([0.48841119, 0.61174386]), array([ 0.03653803, -0.01627797]), None, None, None, 10, array([0.85379151, 0.44896419]), array([ 0.03653803, -0.01627797]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.85379151 0.44896419] [ 0.03653803 -0.01627797] -0.3970381430661767 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.27535638087505515 goals: [('bisect', 0, array([0.85379151, 0.44896419]), array([-0.03653803, 0.01627797]), None, None, None, 10, array([0.48841119, 0.61174386]), array([-0.03653803, 0.01627797]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.48841119 0.61174386] [ 0.03653803 -0.01627797] -0.2753563808750551 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -13..2 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-13, 2) ---- seed=6 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 BACKWARD SAMPLING FROM 4 [0.03716733 0.66306682] [0.036206 0.01700369] -0.3330755453049499 BACKWARD SAMPLING FROM -4 [0.25248069 0.52703731] [-0.036206 0.01700369] -0.041010950598001826 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.10765668, 0.59505206]), array([-0.036206 , 0.01700369]), None, None, None, 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4080091653243474 goals: [('bisect', 0, array([0.10765668, 0.59505206]), array([-0.036206 , 0.01700369]), 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 7, array([0.14578533, 0.71407788]), array([0.036206 , 0.01700369]), 10, array([0.25440334, 0.76508895]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4914817954950847 goals: [('bisect', 5, array([0.07337333, 0.68007051]), array([0.036206 , 0.01700369]), 6, array([0.10957933, 0.6970742 ]), array([0.036206 , 0.01700369]), 7, array([0.14578533, 0.71407788]), array([0.036206 , 0.01700369]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.14578533 0.71407788] [0.036206 0.01700369] new direction: [ 0.02481099 -0.03137538] reversing there [0.036206 0.01700369] making one step from [0.14578533 0.71407788] [0.036206 0.01700369] --> [0.17059633 0.6827025 ] [ 0.02481099 -0.03137538] trying new point, [0.17059633 0.6827025 ] next() call -0.4318041009131332 goals: [('reflect-at', 7, array([0.17059633, 0.6827025 ]), array([ 0.02481099, -0.03137538]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12809180647624227 goals: [('bisect', 7, array([0.17059633, 0.6827025 ]), array([ 0.02481099, -0.03137538]), None, None, None, 10, array([0.2450293 , 0.58857635]), array([ 0.02481099, -0.03137538]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.2450293 0.58857635] [ 0.02481099 -0.03137538] -0.12809180647624227 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), None, None, None, 10, array([0.00308062, 0.90233018]), array([0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 10, array([0.00308062, 0.90233018]), array([0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.30534071772163773 goals: [('bisect', 0, array([0.2450293 , 0.58857635]), array([-0.02481099, 0.03137538]), 2, array([0.19540732, 0.65132712]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4318041009131337 goals: [('bisect', 2, array([0.19540732, 0.65132712]), array([-0.02481099, 0.03137538]), 3, array([0.17059633, 0.6827025 ]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.17059633, 0.6827025 ]), array([-0.02481099, 0.03137538]), 4, array([0.14578533, 0.71407788]), array([-0.02481099, 0.03137538]), 5, array([0.12097434, 0.74545327]), array([-0.02481099, 0.03137538]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.14578533 0.71407788] [-0.02481099 0.03137538] new direction: [-0.036206 -0.01700369] reversing there [-0.02481099 0.03137538] making one step from [0.14578533 0.71407788] [-0.02481099 0.03137538] --> [0.10957933 0.6970742 ] [-0.036206 -0.01700369] trying new point, [0.10957933 0.6970742 ] next() call -0.4914817954950847 goals: [('reflect-at', 4, array([0.10957933, 0.6970742 ]), array([-0.036206 , -0.01700369]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1187311667407582 goals: [('bisect', 4, array([0.10957933, 0.6970742 ]), array([-0.036206 , -0.01700369]), None, None, None, 10, array([0.10765668, 0.59505206]), array([ 0.036206 , -0.01700369]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.10765668 0.59505206] [-0.036206 0.01700369] -0.11873116674075794 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=7 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 BACKWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 BACKWARD SAMPLING FROM -3 [0.91202793 0.42346309] [0.02932044 0.02720867] -0.48912121118231033 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), None, None, None, 10, array([0.75799217, 0.87256348]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 5, array([0.86799084, 0.70552968]), array([-0.02199973, 0.03340676]), 10, array([0.75799217, 0.87256348]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 2, array([0.93399004, 0.60530939]), array([-0.02199973, 0.03340676]), 5, array([0.86799084, 0.70552968]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), 1, array([0.95598978, 0.57190263]), array([-0.02199973, 0.03340676]), 2, array([0.93399004, 0.60530939]), array([-0.02199973, 0.03340676]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.95598978 0.57190263] [-0.02199973 0.03340676] new direction: [-0.03029182 0.0261229 ] reversing there [-0.02199973 0.03340676] making one step from [0.95598978 0.57190263] [-0.02199973 0.03340676] --> [0.92569796 0.59802553] [-0.03029182 0.0261229 ] trying new point, [0.92569796 0.59802553] next() call None goals: [('reflect-at', 1, array([0.92569796, 0.59802553]), array([-0.03029182, 0.0261229 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), None, None, None, -9, array([0.82401288, 0.23783502]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -5, array([0.91201182, 0.37146206]), array([0.02199973, 0.03340676]), -9, array([0.82401288, 0.23783502]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -3 next() call None goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -3, array([0.95601129, 0.43827559]), array([0.02199973, 0.03340676]), -5, array([0.91201182, 0.37146206]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -3 -5 continue bisect at -2 next() call -0.4882763953959062 goals: [('bisect', 0, array([0.97798951, 0.53849587]), array([-0.02199973, 0.03340676]), -2, array([0.97801102, 0.47168235]), array([0.02199973, 0.03340676]), -3, array([0.95601129, 0.43827559]), array([0.02199973, 0.03340676]), -1), ('sample-at', -9)] bisecting ... 0 -2 -3 bisecting gave reflection point -3 [0.95601129 0.43827559] [0.02199973 0.03340676] new direction: [ 0.01936874 -0.03499789] reversing there [0.02199973 0.03340676] making one step from [0.95601129 0.43827559] [0.02199973 0.03340676] --> [0.97538002 0.4032777 ] [-0.01936874 0.03499789] trying new point, [0.97538002 0.4032777 ] next() call None goals: [('reflect-at', -3, array([0.97538002, 0.4032777 ]), array([-0.01936874, 0.03499789]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] reversing at -2... -7 steps to do at -2 -> [from -3, delta=-7] targeting 4. goals: [('sample-at', 4)] reversing at 0... 4 steps to do at 0 -> [from 1, delta=4] targeting -3. goals: [('sample-at', -3)] reversing at -2... -1 steps to do at -2 -> [from -3, delta=-1] targeting -2. goals: [('sample-at', -2)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -2 [0.97801102 0.47168235] [0.02199973 0.03340676] -0.4882763953959062 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -2)] not done yet, continue expanding to -2... goals: [('expand-to', -2), ('sample-at', -2)] next() call -0.49675589327088776 goals: [('bisect', 0, array([0.97801102, 0.47168235]), array([-0.02199973, -0.03340676]), None, None, None, -2, array([0.97798951, 0.53849587]), array([ 0.02199973, -0.03340676]), -1), ('sample-at', -2)] bisecting ... 0 None -2 successfully went all the way in one jump! goals: [('sample-at', -2)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.97798951 0.53849587] [-0.02199973 0.03340676] -0.49675589327088776 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=8 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 BACKWARD SAMPLING FROM 3 [0.95807852 0.45023536] [ 0.02962799 -0.02687344] -0.48991371862053074 BACKWARD SAMPLING FROM -3 [0.78031056 0.61147602] [ 0.02962799 -0.02687344] -0.45977857566680347 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), None, None, None, 10, array([0.83452552, 0.26212126]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 10, array([0.83452552, 0.26212126]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4375602772906623 goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), 2, array([0.92845053, 0.4771088 ]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.48991371862053074 goals: [('bisect', 2, array([0.92845053, 0.4771088 ]), array([ 0.02962799, -0.02687344]), 3, array([0.95807852, 0.45023536]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.95807852, 0.45023536]), array([ 0.02962799, -0.02687344]), 4, array([0.98770652, 0.42336192]), array([ 0.02962799, -0.02687344]), 5, array([0.98266549, 0.39648847]), array([-0.02962799, -0.02687344]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.98770652 0.42336192] [ 0.02962799 -0.02687344] new direction: [-0.03704999 -0.01507642] reversing there [ 0.02962799 -0.02687344] making one step from [0.98770652 0.42336192] [ 0.02962799 -0.02687344] --> [0.95065653 0.4082855 ] [-0.03704999 -0.01507642] trying new point, [0.95065653 0.4082855 ] next() call None goals: [('reflect-at', 4, array([0.95065653, 0.4082855 ]), array([-0.03704999, -0.01507642]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.45977857566680347 goals: [('bisect', 0, array([0.86919454, 0.53085569]), array([ 0.02962799, -0.02687344]), None, None, None, -3, array([0.78031056, 0.61147602]), array([ 0.02962799, -0.02687344]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.95807852 0.45023536] [ 0.02962799 -0.02687344] -0.48991371862053074 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.38965049563602216 goals: [('bisect', 0, array([0.95807852, 0.45023536]), array([-0.02962799, 0.02687344]), None, None, None, 3, array([0.86919454, 0.53085569]), array([-0.02962799, 0.02687344]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.78031056 0.61147602] [ 0.02962799 -0.02687344] -0.45977857566680347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.38965049563602216 goals: [('bisect', 0, array([0.78031056, 0.61147602]), array([-0.02962799, 0.02687344]), None, None, None, -3, array([0.86919454, 0.53085569]), array([-0.02962799, 0.02687344]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.86919454 0.53085569] [ 0.02962799 -0.02687344] -0.38965049563602216 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=9 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 BACKWARD SAMPLING FROM 4 [0.11061846 0.39718082] [ 0.03024815 -0.02617344] -0.13826553062534178 BACKWARD SAMPLING FROM -4 [0.13136677 0.60656837] [-0.03024815 -0.02617344] -0.1505888292401249 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.01037415, 0.50187459]), array([-0.03024815, -0.02617344]), None, None, None, 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2179104295369838 goals: [('bisect', 0, array([0.01037415, 0.50187459]), array([-0.03024815, -0.02617344]), 5, array([0.14086662, 0.37100737]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43132376818592777 goals: [('bisect', 5, array([0.14086662, 0.37100737]), array([ 0.03024815, -0.02617344]), 7, array([0.20136292, 0.31866048]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.20136292, 0.31866048]), array([ 0.03024815, -0.02617344]), 8, array([0.23161108, 0.29248704]), array([ 0.03024815, -0.02617344]), 10, array([0.29210739, 0.24014015]), array([ 0.03024815, -0.02617344]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.23161108 0.29248704] [ 0.03024815 -0.02617344] new direction: [0.02396606 0.03202542] reversing there [ 0.03024815 -0.02617344] making one step from [0.23161108 0.29248704] [ 0.03024815 -0.02617344] --> [0.25557714 0.32451246] [0.02396606 0.03202542] trying new point, [0.25557714 0.32451246] next() call -0.41760827984962573 goals: [('reflect-at', 8, array([0.25557714, 0.32451246]), array([0.02396606, 0.03202542]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20128562729667512 goals: [('bisect', 8, array([0.25557714, 0.32451246]), array([0.02396606, 0.03202542]), None, None, None, 10, array([0.30350927, 0.38856331]), array([0.02396606, 0.03202542]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.30350927 0.38856331] [0.02396606 0.03202542] -0.20128562729667512 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), None, None, None, 10, array([0.06384864, 0.06830907]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 10, array([0.06384864, 0.06830907]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.41760827984962573 goals: [('bisect', 0, array([0.30350927, 0.38856331]), array([-0.02396606, -0.03202542]), 2, array([0.25557714, 0.32451246]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.25557714, 0.32451246]), array([-0.02396606, -0.03202542]), 3, array([0.23161108, 0.29248704]), array([-0.02396606, -0.03202542]), 5, array([0.18367895, 0.22843619]), array([-0.02396606, -0.03202542]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.23161108 0.29248704] [-0.02396606 -0.03202542] new direction: [-0.03024815 0.02617344] reversing there [-0.02396606 -0.03202542] making one step from [0.23161108 0.29248704] [-0.02396606 -0.03202542] --> [0.20136292 0.31866048] [-0.03024815 0.02617344] trying new point, [0.20136292 0.31866048] next() call -0.43132376818592777 goals: [('reflect-at', 3, array([0.20136292, 0.31866048]), array([-0.03024815, 0.02617344]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -9.773773097349783e-05 goals: [('bisect', 3, array([0.20136292, 0.31866048]), array([-0.03024815, 0.02617344]), None, None, None, 10, array([0.01037415, 0.50187459]), array([0.03024815, 0.02617344]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.01037415 0.50187459] [-0.03024815 -0.02617344] -9.773773097350387e-05 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 sampling between (0, 3) ---- seed=10 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 BACKWARD SAMPLING FROM 4 [0.041974 0.66760798] [0.00950643 0.03885393] -0.3520363250591377 BACKWARD SAMPLING FROM -4 [0.03407747 0.35677655] [-0.00950643 0.03885393] -0.25699258899589295 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), None, None, None, 10, array([0.0990126 , 0.90073154]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 10, array([0.0990126 , 0.90073154]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.10128899988595243 goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), 2, array([0.02296113, 0.58990012]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.2077471298760972 goals: [('bisect', 2, array([0.02296113, 0.58990012]), array([0.00950643, 0.03885393]), 3, array([0.03246757, 0.62875405]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3520363250591377 goals: [('bisect', 3, array([0.03246757, 0.62875405]), array([0.00950643, 0.03885393]), 4, array([0.041974 , 0.66760798]), array([0.00950643, 0.03885393]), 5, array([0.05148044, 0.7064619 ]), array([0.00950643, 0.03885393]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.05148044 0.7064619 ] [0.00950643 0.03885393] new direction: [0.03538475 0.01865259] reversing there [0.00950643 0.03885393] making one step from [0.05148044 0.7064619 ] [0.00950643 0.03885393] --> [0.08686519 0.7251145 ] [0.03538475 0.01865259] trying new point, [0.08686519 0.7251145 ] next() call None goals: [('reflect-at', 5, array([0.08686519, 0.7251145 ]), array([0.03538475, 0.01865259]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.008901001072892184 goals: [('bisect', 0, array([0.00394827, 0.51219226]), array([0.00950643, 0.03885393]), None, None, None, -1, array([0.00555817, 0.47333834]), array([-0.00950643, 0.03885393]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.041974 0.66760798] [0.00950643 0.03885393] -0.3520363250591377 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.001865935484349968 goals: [('bisect', 0, array([0.041974 , 0.66760798]), array([-0.00950643, -0.03885393]), None, None, None, 4, array([0.00394827, 0.51219226]), array([-0.00950643, -0.03885393]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.00555817 0.47333834] [-0.00950643 0.03885393] -0.008901001072892184 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.0018659354843499343 goals: [('bisect', 0, array([0.00555817, 0.47333834]), array([ 0.00950643, -0.03885393]), None, None, None, -1, array([0.00394827, 0.51219226]), array([-0.00950643, -0.03885393]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.00394827 0.51219226] [0.00950643 0.03885393] -0.0018659354843499343 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=11 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 BACKWARD SAMPLING FROM 4 [0.37163231 0.33297767] [-0.01214282 -0.03811236] -0.4177610370777551 BACKWARD SAMPLING FROM -4 [0.4687749 0.63787653] [-0.01214282 -0.03811236] -0.3474991729078387 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), None, None, None, 10, array([0.29877537, 0.10430352]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 10, array([0.29877537, 0.10430352]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.18142810704210527 goals: [('bisect', 0, array([0.4202036, 0.4854271]), array([-0.01214282, -0.03811236]), 2, array([0.39591796, 0.40920238]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.28136395006049925 goals: [('bisect', 2, array([0.39591796, 0.40920238]), array([-0.01214282, -0.03811236]), 3, array([0.38377513, 0.37109002]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.4177610370777551 goals: [('bisect', 3, array([0.38377513, 0.37109002]), array([-0.01214282, -0.03811236]), 4, array([0.37163231, 0.33297767]), array([-0.01214282, -0.03811236]), 5, array([0.35948949, 0.29486531]), array([-0.01214282, -0.03811236]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.35948949 0.29486531] [-0.01214282 -0.03811236] new direction: [-0.0041129 0.03978799] reversing there [-0.01214282 -0.03811236] making one step from [0.35948949 0.29486531] [-0.01214282 -0.03811236] --> [0.35537659 0.3346533 ] [-0.0041129 0.03978799] trying new point, [0.35537659 0.3346533 ] next() call -0.4048904116037848 goals: [('reflect-at', 5, array([0.35537659, 0.3346533 ]), array([-0.0041129 , 0.03978799]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07015589586681098 goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([-0.0041129 , 0.03978799]), None, None, None, 10, array([0.3348121 , 0.53359324]), array([-0.0041129 , 0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.3348121 0.53359324] [-0.0041129 0.03978799] -0.07015589586681098 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.3348121 , 0.53359324]), array([ 0.0041129 , -0.03978799]), None, None, None, 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.40489041160378453 goals: [('bisect', 0, array([0.3348121 , 0.53359324]), array([ 0.0041129 , -0.03978799]), 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 7, array([0.36360238, 0.25507732]), array([ 0.0041129 , -0.03978799]), 10, array([0.37594108, 0.13571335]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.35537659, 0.3346533 ]), array([ 0.0041129 , -0.03978799]), 6, array([0.35948949, 0.29486531]), array([ 0.0041129 , -0.03978799]), 7, array([0.36360238, 0.25507732]), array([ 0.0041129 , -0.03978799]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.35948949 0.29486531] [ 0.0041129 -0.03978799] new direction: [0.01214282 0.03811236] reversing there [ 0.0041129 -0.03978799] making one step from [0.35948949 0.29486531] [ 0.0041129 -0.03978799] --> [0.37163231 0.33297767] [0.01214282 0.03811236] trying new point, [0.37163231 0.33297767] next() call -0.4177610370777547 goals: [('reflect-at', 6, array([0.37163231, 0.33297767]), array([0.01214282, 0.03811236]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.0909401530019027 goals: [('bisect', 6, array([0.37163231, 0.33297767]), array([0.01214282, 0.03811236]), None, None, None, 10, array([0.4202036, 0.4854271]), array([0.01214282, 0.03811236]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.4202036 0.4854271] [-0.01214282 -0.03811236] -0.09094015300190272 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=12 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 BACKWARD SAMPLING FROM 4 [0.13496481 0.43820812] [-0.03208755 -0.02388282] -0.05683571304926094 BACKWARD SAMPLING FROM -4 [0.39166522 0.62927067] [-0.03208755 -0.02388282] -0.2855871537311189 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26331502, 0.53373939]), array([-0.03208755, -0.02388282]), None, None, None, 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.09704380253434214 goals: [('bisect', 0, array([0.26331502, 0.53373939]), array([-0.03208755, -0.02388282]), 5, array([0.10287726, 0.4143253 ]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.22332799455138033 goals: [('bisect', 5, array([0.10287726, 0.4143253 ]), array([-0.03208755, -0.02388282]), 7, array([0.03870216, 0.36655966]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3094040970833373 goals: [('bisect', 7, array([0.03870216, 0.36655966]), array([-0.03208755, -0.02388282]), 8, array([0.00661461, 0.34267684]), array([-0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.41076953729758614 goals: [('bisect', 8, array([0.00661461, 0.34267684]), array([-0.03208755, -0.02388282]), 9, array([0.02547294, 0.31879402]), array([ 0.03208755, -0.02388282]), 10, array([0.05756049, 0.2949112 ]), array([ 0.03208755, -0.02388282]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.05756049 0.2949112 ] [ 0.03208755 -0.02388282] new direction: [ 0.02655384 -0.02991477] reversing there [ 0.03208755 -0.02388282] making one step from [0.05756049 0.2949112 ] [ 0.03208755 -0.02388282] --> [0.08411434 0.26499643] [ 0.02655384 -0.02991477] trying new point, [0.08411434 0.26499643] next() call None goals: [('reflect-at', 10, array([0.08411434, 0.26499643]), array([ 0.02655384, -0.02991477]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.02547294 0.31879402] [ 0.03208755 -0.02388282] -0.41076953729758614 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.04889673193185484 goals: [('bisect', 0, array([0.02547294, 0.31879402]), array([-0.03208755, 0.02388282]), None, None, None, 9, array([0.26331502, 0.53373939]), array([0.03208755, 0.02388282]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.26331502 0.53373939] [-0.03208755 -0.02388282] -0.04889673193185484 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=13 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 BACKWARD SAMPLING FROM 4 [0.40042197 0.52612745] [-0.00300128 -0.03988724] -0.08870192535855582 BACKWARD SAMPLING FROM -4 [0.2145617 0.65653403] [0.03957308 0.00582848] -0.32930462797788607 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), None, None, None, 10, array([0.76858485, 0.73813277]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 5, array([0.57071944, 0.70899036]), array([0.03957308, 0.00582848]), 10, array([0.76858485, 0.73813277]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 2, array([0.45200019, 0.69150491]), array([0.03957308, 0.00582848]), 5, array([0.57071944, 0.70899036]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.37285403, 0.67984795]), array([0.03957308, 0.00582848]), 1, array([0.41242711, 0.68567643]), array([0.03957308, 0.00582848]), 2, array([0.45200019, 0.69150491]), array([0.03957308, 0.00582848]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.41242711 0.68567643] [0.03957308 0.00582848] new direction: [-0.00300128 -0.03988724] reversing there [0.03957308 0.00582848] making one step from [0.41242711 0.68567643] [0.03957308 0.00582848] --> [0.40942582 0.64578919] [-0.00300128 -0.03988724] trying new point, [0.40942582 0.64578919] next() call -0.3494958457329673 goals: [('reflect-at', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), None, None, None, 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.08133824843659004 goals: [('bisect', 1, array([0.40942582, 0.64578919]), array([-0.00300128, -0.03988724]), 5, array([0.39742069, 0.48624021]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.18596233939691564 goals: [('bisect', 5, array([0.39742069, 0.48624021]), array([-0.00300128, -0.03988724]), 7, array([0.39141812, 0.40646572]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.297950107279207 goals: [('bisect', 7, array([0.39141812, 0.40646572]), array([-0.00300128, -0.03988724]), 8, array([0.38841683, 0.36657848]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4497216900962508 goals: [('bisect', 8, array([0.38841683, 0.36657848]), array([-0.00300128, -0.03988724]), 9, array([0.38541555, 0.32669123]), array([-0.00300128, -0.03988724]), 10, array([0.38241426, 0.28680399]), array([-0.00300128, -0.03988724]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.38241426 0.28680399] [-0.00300128 -0.03988724] new direction: [0.02675467 0.02973529] reversing there [-0.00300128 -0.03988724] making one step from [0.38241426 0.28680399] [-0.00300128 -0.03988724] --> [0.40916893 0.31653928] [0.02675467 0.02973529] trying new point, [0.40916893 0.31653928] next() call None goals: [('reflect-at', 10, array([0.40916893, 0.31653928]), array([0.02675467, 0.02973529]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.38541555 0.32669123] [-0.00300128 -0.03988724] -0.4497216900962508 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call None goals: [('bisect', 0, array([0.38541555, 0.32669123]), array([0.00300128, 0.03988724]), None, None, None, 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 0 None 9 continue bisect at 4 next() call -0.08133824843659004 goals: [('bisect', 0, array([0.38541555, 0.32669123]), array([0.00300128, 0.03988724]), 4, array([0.39742069, 0.48624021]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 0 4 9 continue bisect at 6 next() call -0.13584941721527394 goals: [('bisect', 4, array([0.39742069, 0.48624021]), array([0.00300128, 0.03988724]), 6, array([0.40342325, 0.5660147 ]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 4 6 9 continue bisect at 7 next() call -0.22278072400674448 goals: [('bisect', 6, array([0.40342325, 0.5660147 ]), array([0.00300128, 0.03988724]), 7, array([0.40642454, 0.60590194]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 6 7 9 continue bisect at 8 next() call -0.3494958457329673 goals: [('bisect', 7, array([0.40642454, 0.60590194]), array([0.00300128, 0.03988724]), 8, array([0.40942582, 0.64578919]), array([0.00300128, 0.03988724]), 9, array([0.41242711, 0.68567643]), array([0.00300128, 0.03988724]), 1), ('sample-at', 9)] bisecting ... 7 8 9 bisecting gave reflection point 9 [0.41242711 0.68567643] [0.00300128 0.03988724] new direction: [-0.03957308 -0.00582848] reversing there [0.00300128 0.03988724] making one step from [0.41242711 0.68567643] [0.00300128 0.03988724] --> [0.37285403 0.67984795] [-0.03957308 -0.00582848] trying new point, [0.37285403 0.67984795] next() call -0.47382613413670327 goals: [('reflect-at', 9, array([0.37285403, 0.67984795]), array([-0.03957308, -0.00582848]), 1), ('sample-at', 9)] goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.37285403 0.67984795] [0.03957308 0.00582848] -0.47382613413670277 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: 0..7 sampling between (0, 7) ---- seed=14 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 BACKWARD SAMPLING FROM 4 [0.21608397 0.61107718] [-0.021002 0.03404285] -0.17757288486701345 BACKWARD SAMPLING FROM -4 [0.38409999 0.33873435] [-0.021002 0.03404285] -0.39884901225457176 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30009198, 0.47490577]), array([-0.021002 , 0.03404285]), None, None, None, 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2822762805921456 goals: [('bisect', 0, array([0.30009198, 0.47490577]), array([-0.021002 , 0.03404285]), 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 7, array([0.15307796, 0.71320574]), array([-0.021002 , 0.03404285]), 10, array([0.09007195, 0.8153343 ]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.41639365668362777 goals: [('bisect', 5, array([0.19508196, 0.64512003]), array([-0.021002 , 0.03404285]), 6, array([0.17407996, 0.67916288]), array([-0.021002 , 0.03404285]), 7, array([0.15307796, 0.71320574]), array([-0.021002 , 0.03404285]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.15307796 0.71320574] [-0.021002 0.03404285] new direction: [ 0.01597666 -0.03667078] reversing there [-0.021002 0.03404285] making one step from [0.15307796 0.71320574] [-0.021002 0.03404285] --> [0.16905462 0.67653496] [ 0.01597666 -0.03667078] trying new point, [0.16905462 0.67653496] next() call -0.40384711686066294 goals: [('reflect-at', 7, array([0.16905462, 0.67653496]), array([ 0.01597666, -0.03667078]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07885688368045461 goals: [('bisect', 7, array([0.16905462, 0.67653496]), array([ 0.01597666, -0.03667078]), None, None, None, 10, array([0.21698461, 0.56652261]), array([ 0.01597666, -0.03667078]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.21698461 0.56652261] [ 0.01597666 -0.03667078] -0.07885688368045461 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), None, None, None, 10, array([0.05721797, 0.93323043]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 10, array([0.05721797, 0.93323043]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.2616431298568962 goals: [('bisect', 0, array([0.21698461, 0.56652261]), array([-0.01597666, 0.03667078]), 2, array([0.18503128, 0.63986417]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.40384711686066294 goals: [('bisect', 2, array([0.18503128, 0.63986417]), array([-0.01597666, 0.03667078]), 3, array([0.16905462, 0.67653496]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.16905462, 0.67653496]), array([-0.01597666, 0.03667078]), 4, array([0.15307796, 0.71320574]), array([-0.01597666, 0.03667078]), 5, array([0.13710129, 0.74987652]), array([-0.01597666, 0.03667078]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.15307796 0.71320574] [-0.01597666 0.03667078] new direction: [ 0.021002 -0.03404285] reversing there [-0.01597666 0.03667078] making one step from [0.15307796 0.71320574] [-0.01597666 0.03667078] --> [0.17407996 0.67916288] [ 0.021002 -0.03404285] trying new point, [0.17407996 0.67916288] next() call -0.41639365668362777 goals: [('reflect-at', 4, array([0.17407996, 0.67916288]), array([ 0.021002 , -0.03404285]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05289910562998976 goals: [('bisect', 4, array([0.17407996, 0.67916288]), array([ 0.021002 , -0.03404285]), None, None, None, 10, array([0.30009198, 0.47490577]), array([ 0.021002 , -0.03404285]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30009198 0.47490577] [-0.021002 0.03404285] -0.05289910562998988 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -1..14 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-1, 14) ---- seed=15 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 BACKWARD SAMPLING FROM 4 [0.10549014 0.35468978] [ 0.03996334 -0.00171217] -0.2695023366962361 BACKWARD SAMPLING FROM -4 [0.21421657 0.36838711] [-0.03996334 -0.00171217] -0.23946877171984182 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36218247700975736 goals: [('bisect', 0, array([0.05436321, 0.36153845]), array([-0.03996334, -0.00171217]), None, None, None, 10, array([0.34527018, 0.34441678]), array([ 0.03996334, -0.00171217]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.34527018 0.34441678] [ 0.03996334 -0.00171217] -0.36218247700975736 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2411227034306628 goals: [('bisect', 0, array([0.34527018, 0.34441678]), array([-0.03996334, 0.00171217]), None, None, None, 10, array([0.05436321, 0.36153845]), array([0.03996334, 0.00171217]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.05436321 0.36153845] [-0.03996334 -0.00171217] -0.2411227034306628 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=16 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 BACKWARD SAMPLING FROM 4 [0.37021116 0.58652334] [0.03673002 0.01584 ] -0.16210675630294513 BACKWARD SAMPLING FROM -4 [0.076371 0.45980334] [0.03673002 0.01584 ] -0.0231134050599264 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22329108, 0.52316334]), array([0.03673002, 0.01584 ]), None, None, None, 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.213778728689882 goals: [('bisect', 0, array([0.22329108, 0.52316334]), array([0.03673002, 0.01584 ]), 5, array([0.40694118, 0.60236334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.33998787578479583 goals: [('bisect', 5, array([0.40694118, 0.60236334]), array([0.03673002, 0.01584 ]), 7, array([0.48040122, 0.63404334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.41452505049277283 goals: [('bisect', 7, array([0.48040122, 0.63404334]), array([0.03673002, 0.01584 ]), 8, array([0.51713124, 0.64988334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4966839593077631 goals: [('bisect', 8, array([0.51713124, 0.64988334]), array([0.03673002, 0.01584 ]), 9, array([0.55386126, 0.66572334]), array([0.03673002, 0.01584 ]), 10, array([0.59059129, 0.68156334]), array([0.03673002, 0.01584 ]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.59059129 0.68156334] [0.03673002 0.01584 ] new direction: [-0.02554864 -0.0307777 ] reversing there [0.03673002 0.01584 ] making one step from [0.59059129 0.68156334] [0.03673002 0.01584 ] --> [0.56504265 0.65078563] [-0.02554864 -0.0307777 ] trying new point, [0.56504265 0.65078563] next() call -0.44384043934656114 goals: [('reflect-at', 10, array([0.56504265, 0.65078563]), array([-0.02554864, -0.0307777 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.56504265 0.65078563] [-0.02554864 -0.0307777 ] -0.44384043934656114 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), None, None, None, 10, array([0.82052904, 0.95856267]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 5, array([0.69278584, 0.80467415]), array([0.02554864, 0.0307777 ]), 10, array([0.82052904, 0.95856267]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 2, array([0.61613992, 0.71234104]), array([0.02554864, 0.0307777 ]), 5, array([0.69278584, 0.80467415]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.56504265, 0.65078563]), array([0.02554864, 0.0307777 ]), 1, array([0.59059129, 0.68156334]), array([0.02554864, 0.0307777 ]), 2, array([0.61613992, 0.71234104]), array([0.02554864, 0.0307777 ]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.59059129 0.68156334] [0.02554864 0.0307777 ] new direction: [-0.03673002 -0.01584 ] reversing there [0.02554864 0.0307777 ] making one step from [0.59059129 0.68156334] [0.02554864 0.0307777 ] --> [0.55386126 0.66572334] [-0.03673002 -0.01584 ] trying new point, [0.55386126 0.66572334] next() call -0.49668395930776266 goals: [('reflect-at', 1, array([0.55386126, 0.66572334]), array([-0.03673002, -0.01584 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.03163620782532951 goals: [('bisect', 1, array([0.55386126, 0.66572334]), array([-0.03673002, -0.01584 ]), None, None, None, 10, array([0.22329108, 0.52316334]), array([-0.03673002, -0.01584 ]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22329108 0.52316334] [0.03673002 0.01584 ] -0.03163620782532942 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -13..2 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-13, 2) ---- seed=17 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 BACKWARD SAMPLING FROM 4 [0.15857392 0.61472483] [-0.03402277 0.02103452] -0.1770951824864543 BACKWARD SAMPLING FROM -4 [0.43075609 0.44644868] [-0.03402277 0.02103452] -0.12862220436569055 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.294665 , 0.53058676]), array([-0.03402277, 0.02103452]), None, None, None, 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2381390123527663 goals: [('bisect', 0, array([0.294665 , 0.53058676]), array([-0.03402277, 0.02103452]), 5, array([0.12455114, 0.63575935]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.3968831438195334 goals: [('bisect', 5, array([0.12455114, 0.63575935]), array([-0.03402277, 0.02103452]), 7, array([0.0565056 , 0.67782839]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.49458344541998867 goals: [('bisect', 7, array([0.0565056 , 0.67782839]), array([-0.03402277, 0.02103452]), 8, array([0.02248283, 0.69886291]), array([-0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.02248283, 0.69886291]), array([-0.03402277, 0.02103452]), 9, array([0.01153994, 0.71989743]), array([0.03402277, 0.02103452]), 10, array([0.04556272, 0.74093195]), array([0.03402277, 0.02103452]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.01153994 0.71989743] [0.03402277 0.02103452] new direction: [0.01297498 0.03783715] reversing there [0.03402277 0.02103452] making one step from [0.01153994 0.71989743] [0.03402277 0.02103452] --> [0.02451492 0.75773458] [0.01297498 0.03783715] trying new point, [0.02451492 0.75773458] next() call None goals: [('reflect-at', 9, array([0.02451492, 0.75773458]), array([0.01297498, 0.03783715]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.02248283 0.69886291] [-0.03402277 0.02103452] -0.49458344541998867 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.055108102135022076 goals: [('bisect', 0, array([0.02248283, 0.69886291]), array([ 0.03402277, -0.02103452]), None, None, None, 8, array([0.294665 , 0.53058676]), array([ 0.03402277, -0.02103452]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.294665 0.53058676] [-0.03402277 0.02103452] -0.055108102135022076 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -7..8 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-7, 8) ---- seed=18 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 BACKWARD SAMPLING FROM 4 [0.49132867 0.52290346] [-0.03976139 0.00436252] -0.12725903771293967 BACKWARD SAMPLING FROM -4 [0.80941982 0.48800328] [-0.03976139 0.00436252] -0.3293792332040737 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.0620527440819295 goals: [('bisect', 0, array([0.65037424, 0.50545337]), array([-0.03976139, 0.00436252]), None, None, None, 10, array([0.25276031, 0.5490786 ]), array([-0.03976139, 0.00436252]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.25276031 0.5490786 ] [-0.03976139 0.00436252] -0.0620527440819295 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21186506822282286 goals: [('bisect', 0, array([0.25276031, 0.5490786 ]), array([ 0.03976139, -0.00436252]), None, None, None, 10, array([0.65037424, 0.50545337]), array([ 0.03976139, -0.00436252]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.65037424 0.50545337] [-0.03976139 0.00436252] -0.21186506822282286 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-2, 5) ---- seed=19 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 BACKWARD SAMPLING FROM 4 [0.36264649 0.61284195] [0.03668081 0.01595363] -0.22492257200551513 BACKWARD SAMPLING FROM -4 [0.06920002 0.48521291] [0.03668081 0.01595363] -0.005127547303597255 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21592326, 0.54902743]), array([0.03668081, 0.01595363]), None, None, None, 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.28708492992102647 goals: [('bisect', 0, array([0.21592326, 0.54902743]), array([0.03668081, 0.01595363]), 5, array([0.3993273 , 0.62879559]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43453496563722904 goals: [('bisect', 5, array([0.3993273 , 0.62879559]), array([0.03668081, 0.01595363]), 7, array([0.47268891, 0.66070285]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.47268891, 0.66070285]), array([0.03668081, 0.01595363]), 8, array([0.50936972, 0.67665648]), array([0.03668081, 0.01595363]), 10, array([0.58273134, 0.70856374]), array([0.03668081, 0.01595363]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.50936972 0.67665648] [0.03668081 0.01595363] new direction: [-0.02514398 -0.03110917] reversing there [0.03668081 0.01595363] making one step from [0.50936972 0.67665648] [0.03668081 0.01595363] --> [0.48422574 0.64554731] [-0.02514398 -0.03110917] trying new point, [0.48422574 0.64554731] next() call -0.38203753202294766 goals: [('reflect-at', 8, array([0.48422574, 0.64554731]), array([-0.02514398, -0.03110917]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.18094748307481168 goals: [('bisect', 8, array([0.48422574, 0.64554731]), array([-0.02514398, -0.03110917]), None, None, None, 10, array([0.43393777, 0.58332898]), array([-0.02514398, -0.03110917]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.43393777 0.58332898] [-0.02514398 -0.03110917] -0.18094748307481168 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), None, None, None, 10, array([0.68537759, 0.89442064]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 10, array([0.68537759, 0.89442064]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.38203753202294766 goals: [('bisect', 0, array([0.43393777, 0.58332898]), array([0.02514398, 0.03110917]), 2, array([0.48422574, 0.64554731]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.48422574, 0.64554731]), array([0.02514398, 0.03110917]), 3, array([0.50936972, 0.67665648]), array([0.02514398, 0.03110917]), 5, array([0.55965768, 0.73887481]), array([0.02514398, 0.03110917]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.50936972 0.67665648] [0.02514398 0.03110917] new direction: [-0.03668081 -0.01595363] reversing there [0.02514398 0.03110917] making one step from [0.50936972 0.67665648] [0.02514398 0.03110917] --> [0.47268891 0.66070285] [-0.03668081 -0.01595363] trying new point, [0.47268891 0.66070285] next() call -0.434534965637229 goals: [('reflect-at', 3, array([0.47268891, 0.66070285]), array([-0.03668081, -0.01595363]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05335753996074122 goals: [('bisect', 3, array([0.47268891, 0.66070285]), array([-0.03668081, -0.01595363]), None, None, None, 10, array([0.21592326, 0.54902743]), array([-0.03668081, -0.01595363]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.21592326 0.54902743] [0.03668081 0.01595363] -0.05335753996074123 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=20 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 BACKWARD SAMPLING FROM 4 [0.19493603 0.67431541] [ 0.03976161 -0.00436054] -0.3988233188094961 BACKWARD SAMPLING FROM -1 [0.00387202 0.69611812] [-0.03976161 -0.00436054] -0.48078647770574867 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36832687557067506 goals: [('bisect', 0, array([0.03588959, 0.69175758]), array([ 0.03976161, -0.00436054]), None, None, None, 10, array([0.43350569, 0.64815216]), array([ 0.03976161, -0.00436054]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.43350569 0.64815216] [ 0.03976161 -0.00436054] -0.36832687557067506 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4602811582030628 goals: [('bisect', 0, array([0.43350569, 0.64815216]), array([-0.03976161, 0.00436054]), None, None, None, 10, array([0.03588959, 0.69175758]), array([-0.03976161, 0.00436054]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.03588959 0.69175758] [ 0.03976161 -0.00436054] -0.4602811582030628 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=21 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 BACKWARD SAMPLING FROM 4 [0.2415294 0.51588884] [-0.01518562 -0.03700536] -0.032323918419140216 BACKWARD SAMPLING FROM -4 [0.17116112 0.6361286 ] [0.0365741 0.01619676] -0.24628550700212182 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.30227189, 0.66391029]), array([-0.01518562, -0.03700536]), None, None, None, 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.031189595628649723 goals: [('bisect', 0, array([0.30227189, 0.66391029]), array([-0.01518562, -0.03700536]), 5, array([0.22634378, 0.47888348]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.132317524420316 goals: [('bisect', 5, array([0.22634378, 0.47888348]), array([-0.01518562, -0.03700536]), 7, array([0.19597254, 0.40487276]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.2345797760024729 goals: [('bisect', 7, array([0.19597254, 0.40487276]), array([-0.01518562, -0.03700536]), 8, array([0.18078691, 0.36786739]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.3713075523755122 goals: [('bisect', 8, array([0.18078691, 0.36786739]), array([-0.01518562, -0.03700536]), 9, array([0.16560129, 0.33086203]), array([-0.01518562, -0.03700536]), 10, array([0.15041567, 0.29385667]), array([-0.01518562, -0.03700536]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.15041567 0.29385667] [-0.01518562 -0.03700536] new direction: [-0.02472709 0.03144155] reversing there [-0.01518562 -0.03700536] making one step from [0.15041567 0.29385667] [-0.01518562 -0.03700536] --> [0.12568857 0.32529821] [-0.02472709 0.03144155] trying new point, [0.12568857 0.32529821] next() call -0.3894077367200711 goals: [('reflect-at', 10, array([0.12568857, 0.32529821]), array([-0.02472709, 0.03144155]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.12568857 0.32529821] [-0.02472709 0.03144155] -0.3894077367200711 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), None, None, None, 10, array([0.37295952, 0.01088276]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 5, array([0.24932405, 0.16809049]), array([ 0.02472709, -0.03144155]), 10, array([0.37295952, 0.01088276]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 2, array([0.17514276, 0.26241512]), array([ 0.02472709, -0.03144155]), 5, array([0.24932405, 0.16809049]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.12568857, 0.32529821]), array([ 0.02472709, -0.03144155]), 1, array([0.15041567, 0.29385667]), array([ 0.02472709, -0.03144155]), 2, array([0.17514276, 0.26241512]), array([ 0.02472709, -0.03144155]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.15041567 0.29385667] [ 0.02472709 -0.03144155] new direction: [0.01518562 0.03700536] reversing there [ 0.02472709 -0.03144155] making one step from [0.15041567 0.29385667] [ 0.02472709 -0.03144155] --> [0.16560129 0.33086203] [0.01518562 0.03700536] trying new point, [0.16560129 0.33086203] next() call -0.3713075523755125 goals: [('reflect-at', 1, array([0.16560129, 0.33086203]), array([0.01518562, 0.03700536]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3815164574899263 goals: [('bisect', 1, array([0.16560129, 0.33086203]), array([0.01518562, 0.03700536]), None, None, None, 10, array([0.30227189, 0.66391029]), array([0.01518562, 0.03700536]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30227189 0.66391029] [-0.01518562 -0.03700536] -0.38151645748992763 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 sampling between (-3, 0) ---- seed=22 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 BACKWARD SAMPLING FROM 4 [0.05625556 0.43234909] [-0.03805125 -0.01233299] -0.05879042044402399 BACKWARD SAMPLING FROM -4 [0.36066552 0.53101304] [-0.03805125 -0.01233299] -0.07706241401616516 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.26560598511461014 goals: [('bisect', 0, array([0.20846054, 0.48168106]), array([-0.03805125, -0.01233299]), None, None, None, 10, array([0.17205191, 0.35835112]), array([ 0.03805125, -0.01233299]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.17205191 0.35835112] [ 0.03805125 -0.01233299] -0.26560598511461014 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.025922691544438898 goals: [('bisect', 0, array([0.17205191, 0.35835112]), array([-0.03805125, 0.01233299]), None, None, None, 10, array([0.20846054, 0.48168106]), array([0.03805125, 0.01233299]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.20846054 0.48168106] [-0.03805125 -0.01233299] -0.025922691544438898 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=23 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 BACKWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 BACKWARD SAMPLING FROM -4 [0.3745104 0.64096191] [-0.03836626 0.01131504] -0.3185072622476324 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), None, None, None, 10, array([0.16261722, 0.79937253]), array([0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 5, array([0.02921407, 0.74279731]), array([-0.03836626, 0.01131504]), 10, array([0.16261722, 0.79937253]), array([0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 2, array([0.14431285, 0.70885217]), array([-0.03836626, 0.01131504]), 5, array([0.02921407, 0.74279731]), array([-0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), 1, array([0.18267911, 0.69753713]), array([-0.03836626, 0.01131504]), 2, array([0.14431285, 0.70885217]), array([-0.03836626, 0.01131504]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.18267911 0.69753713] [-0.03836626 0.01131504] new direction: [0.00426897 0.03977155] reversing there [-0.03836626 0.01131504] making one step from [0.18267911 0.69753713] [-0.03836626 0.01131504] --> [0.18694807 0.73730868] [0.00426897 0.03977155] trying new point, [0.18694807 0.73730868] next() call None goals: [('reflect-at', 1, array([0.18694807, 0.73730868]), array([0.00426897, 0.03977155]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.24938536408337458 goals: [('bisect', 0, array([0.22104536, 0.68622209]), array([-0.03836626, 0.01131504]), None, None, None, -9, array([0.56634169, 0.58438669]), array([-0.03836626, 0.01131504]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.56634169 0.58438669] [-0.03836626 0.01131504] -0.24938536408337458 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.45791383918711764 goals: [('bisect', 0, array([0.56634169, 0.58438669]), array([ 0.03836626, -0.01131504]), None, None, None, -9, array([0.22104536, 0.68622209]), array([ 0.03836626, -0.01131504]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22104536 0.68622209] [-0.03836626 0.01131504] -0.45791383918711764 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=24 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 BACKWARD SAMPLING FROM 4 [0.16900014 0.35473942] [-0.01277137 0.03790636] -0.2780384655059737 BACKWARD SAMPLING FROM -4 [0.05921351 0.52405108] [ 0.01933277 -0.03501777] -0.008983803050778645 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), None, None, None, 10, array([0.32987225, 0.03380233]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 10, array([0.32987225, 0.03380233]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4480575304829881 goals: [('bisect', 0, array([0.13654458, 0.38398001]), array([ 0.01933277, -0.03501777]), 2, array([0.17521011, 0.31394447]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.17521011, 0.31394447]), array([ 0.01933277, -0.03501777]), 3, array([0.19454288, 0.2789267 ]), array([ 0.01933277, -0.03501777]), 5, array([0.23320842, 0.20889117]), array([ 0.01933277, -0.03501777]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.19454288 0.2789267 ] [ 0.01933277 -0.03501777] new direction: [-0.01277137 0.03790636] reversing there [ 0.01933277 -0.03501777] making one step from [0.19454288 0.2789267 ] [ 0.01933277 -0.03501777] --> [0.18177151 0.31683306] [-0.01277137 0.03790636] trying new point, [0.18177151 0.31683306] next() call -0.43589702340056663 goals: [('reflect-at', 3, array([0.18177151, 0.31683306]), array([-0.01277137, 0.03790636]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08868070867983059 goals: [('bisect', 3, array([0.18177151, 0.31683306]), array([-0.01277137, 0.03790636]), None, None, None, 10, array([0.0923719 , 0.58217758]), array([-0.01277137, 0.03790636]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.0923719 0.58217758] [-0.01277137 0.03790636] -0.08868070867983059 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.0923719 , 0.58217758]), array([ 0.01277137, -0.03790636]), None, None, None, 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.156265316684782 goals: [('bisect', 0, array([0.0923719 , 0.58217758]), array([ 0.01277137, -0.03790636]), 5, array([0.15622876, 0.39264578]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.43589702340056663 goals: [('bisect', 5, array([0.15622876, 0.39264578]), array([ 0.01277137, -0.03790636]), 7, array([0.18177151, 0.31683306]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.18177151, 0.31683306]), array([ 0.01277137, -0.03790636]), 8, array([0.19454288, 0.2789267 ]), array([ 0.01277137, -0.03790636]), 10, array([0.22008563, 0.20311399]), array([ 0.01277137, -0.03790636]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.19454288 0.2789267 ] [ 0.01277137 -0.03790636] new direction: [-0.01933277 0.03501777] reversing there [ 0.01277137 -0.03790636] making one step from [0.19454288 0.2789267 ] [ 0.01277137 -0.03790636] --> [0.17521011 0.31394447] [-0.01933277 0.03501777] trying new point, [0.17521011 0.31394447] next() call -0.44805753048298835 goals: [('reflect-at', 8, array([0.17521011, 0.31394447]), array([-0.01933277, 0.03501777]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17758018669487677 goals: [('bisect', 8, array([0.17521011, 0.31394447]), array([-0.01933277, 0.03501777]), None, None, None, 10, array([0.13654458, 0.38398001]), array([-0.01933277, 0.03501777]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.13654458 0.38398001] [ 0.01933277 -0.03501777] -0.17758018669487663 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=25 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 BACKWARD SAMPLING FROM 4 [0.78739516 0.44532469] [-0.02068224 -0.03423806] -0.34736293667574614 BACKWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.87012414, 0.58227693]), array([-0.02068224, -0.03423806]), None, None, None, 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3927441882386654 goals: [('bisect', 0, array([0.87012414, 0.58227693]), array([-0.02068224, -0.03423806]), 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 7, array([0.72534842, 0.34261051]), array([-0.02068224, -0.03423806]), 10, array([0.66330169, 0.23989633]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.46785931365597694 goals: [('bisect', 5, array([0.76671291, 0.41108663]), array([-0.02068224, -0.03423806]), 6, array([0.74603067, 0.37684857]), array([-0.02068224, -0.03423806]), 7, array([0.72534842, 0.34261051]), array([-0.02068224, -0.03423806]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.72534842 0.34261051] [-0.02068224 -0.03423806] new direction: [-0.02832621 -0.02824227] reversing there [-0.02068224 -0.03423806] making one step from [0.72534842 0.34261051] [-0.02068224 -0.03423806] --> [0.69702221 0.31436824] [-0.02832621 -0.02824227] trying new point, [0.69702221 0.31436824] next() call None goals: [('reflect-at', 7, array([0.69702221, 0.31436824]), array([-0.02832621, -0.02824227]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.8080774 0.47956275] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.74603067 0.37684857] [-0.02068224 -0.03423806] -0.46785931365597694 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.4631766689679939 goals: [('bisect', 0, array([0.74603067, 0.37684857]), array([0.02068224, 0.03423806]), None, None, None, 6, array([0.87012414, 0.58227693]), array([0.02068224, 0.03423806]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.87012414 0.58227693] [-0.02068224 -0.03423806] -0.46317666896799403 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=26 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 BACKWARD SAMPLING FROM 4 [0.14894378 0.53733047] [-0.03974779 0.00448475] -0.028511673439282487 BACKWARD SAMPLING FROM -4 [0.46692612 0.50145249] [-0.03974779 0.00448475] -0.10903637436373395 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.055592009781843664 goals: [('bisect', 0, array([0.30793495, 0.51939148]), array([-0.03974779, 0.00448475]), None, None, None, 10, array([0.08954298, 0.56423895]), array([0.03974779, 0.00448475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.08954298 0.56423895] [0.03974779 0.00448475] -0.055592009781843664 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.052112335894670306 goals: [('bisect', 0, array([0.08954298, 0.56423895]), array([-0.03974779, -0.00448475]), None, None, None, 10, array([0.30793495, 0.51939148]), array([ 0.03974779, -0.00448475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.30793495 0.51939148] [-0.03974779 0.00448475] -0.05211233589467034 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-1, 6) ---- seed=27 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 BACKWARD SAMPLING FROM 1 [0.22291152 0.30845627] [ 0.03615567 -0.01711045] -0.48345727148351275 BACKWARD SAMPLING FROM -4 [0.04213315 0.3940085 ] [ 0.03615567 -0.01711045] -0.14131507902115056 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), None, None, None, 10, array([0.54831257, 0.15446226]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 5, array([0.36753421, 0.24001449]), array([ 0.03615567, -0.01711045]), 10, array([0.54831257, 0.15446226]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 2, array([0.25906719, 0.29134583]), array([ 0.03615567, -0.01711045]), 5, array([0.36753421, 0.24001449]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.48345727148351275 goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), 1, array([0.22291152, 0.30845627]), array([ 0.03615567, -0.01711045]), 2, array([0.25906719, 0.29134583]), array([ 0.03615567, -0.01711045]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.25906719 0.29134583] [ 0.03615567 -0.01711045] new direction: [0.03637517 0.01663872] reversing there [ 0.03615567 -0.01711045] making one step from [0.25906719 0.29134583] [ 0.03615567 -0.01711045] --> [0.29544236 0.30798455] [0.03637517 0.01663872] trying new point, [0.29544236 0.30798455] next() call None goals: [('reflect-at', 2, array([0.29544236, 0.30798455]), array([0.03637517, 0.01663872]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.039546759765486834 goals: [('bisect', 0, array([0.18675584, 0.32556672]), array([ 0.03615567, -0.01711045]), None, None, None, -7, array([0.06633386, 0.44533984]), array([-0.03615567, -0.01711045]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.22291152 0.30845627] [ 0.03615567 -0.01711045] -0.48345727148351275 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.3977760002874148 goals: [('bisect', 0, array([0.22291152, 0.30845627]), array([-0.03615567, 0.01711045]), None, None, None, 1, array([0.18675584, 0.32556672]), array([-0.03615567, 0.01711045]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.06633386 0.44533984] [-0.03615567 -0.01711045] -0.039546759765486834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.39777600028741444 goals: [('bisect', 0, array([0.06633386, 0.44533984]), array([0.03615567, 0.01711045]), None, None, None, -7, array([0.18675584, 0.32556672]), array([-0.03615567, 0.01711045]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18675584 0.32556672] [ 0.03615567 -0.01711045] -0.3977760002874148 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=28 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 BACKWARD SAMPLING FROM 4 [0.88862101 0.55003599] [ 0.03990182 -0.0028009 ] -0.4261186566116443 BACKWARD SAMPLING FROM -4 [0.56940648 0.57244321] [ 0.03990182 -0.0028009 ] -0.2277121021981689 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.39396757347735606 goals: [('bisect', 0, array([0.72901374, 0.5612396 ]), array([ 0.03990182, -0.0028009 ]), None, None, None, 10, array([0.87196809, 0.53323058]), array([-0.03990182, -0.0028009 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.87196809 0.53323058] [-0.03990182 -0.0028009 ] -0.39396757347735606 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3126091293887884 goals: [('bisect', 0, array([0.87196809, 0.53323058]), array([0.03990182, 0.0028009 ]), None, None, None, 10, array([0.72901374, 0.5612396 ]), array([-0.03990182, 0.0028009 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72901374 0.5612396 ] [ 0.03990182 -0.0028009 ] -0.31260912938878843 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-7, 0) ---- seed=29 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 BACKWARD SAMPLING FROM 4 [0.37471154 0.68199235] [-0.01950188 0.03492387] -0.4842195850803701 BACKWARD SAMPLING FROM -4 [0.53072657 0.40260139] [-0.01950188 0.03492387] -0.25941645597282265 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), None, None, None, 10, array([0.25770027, 0.89153558]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 10, array([0.25770027, 0.89153558]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.24278535636599288 goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), 2, array([0.4137153 , 0.61214461]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3480663501867237 goals: [('bisect', 2, array([0.4137153 , 0.61214461]), array([-0.01950188, 0.03492387]), 3, array([0.39421342, 0.64706848]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.48421958508036966 goals: [('bisect', 3, array([0.39421342, 0.64706848]), array([-0.01950188, 0.03492387]), 4, array([0.37471154, 0.68199235]), array([-0.01950188, 0.03492387]), 5, array([0.35520966, 0.71691623]), array([-0.01950188, 0.03492387]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.35520966 0.71691623] [-0.01950188 0.03492387] new direction: [-0.01424107 0.03737903] reversing there [-0.01950188 0.03492387] making one step from [0.35520966 0.71691623] [-0.01950188 0.03492387] --> [0.34096859 0.75429526] [-0.01424107 0.03737903] trying new point, [0.34096859 0.75429526] next() call None goals: [('reflect-at', 5, array([0.34096859, 0.75429526]), array([-0.01424107, 0.03737903]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.1121758213412904 goals: [('bisect', 0, array([0.45271906, 0.54229687]), array([-0.01950188, 0.03492387]), None, None, None, -1, array([0.47222094, 0.507373 ]), array([-0.01950188, 0.03492387]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.37471154 0.68199235] [-0.01950188 0.03492387] -0.48421958508036966 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.12484009194327635 goals: [('bisect', 0, array([0.37471154, 0.68199235]), array([ 0.01950188, -0.03492387]), None, None, None, 4, array([0.45271906, 0.54229687]), array([ 0.01950188, -0.03492387]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.47222094 0.507373 ] [-0.01950188 0.03492387] -0.1121758213412904 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.12484009194327632 goals: [('bisect', 0, array([0.47222094, 0.507373 ]), array([ 0.01950188, -0.03492387]), None, None, None, -1, array([0.45271906, 0.54229687]), array([ 0.01950188, -0.03492387]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.45271906 0.54229687] [-0.01950188 0.03492387] -0.12484009194327632 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=30 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 BACKWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 BACKWARD SAMPLING FROM -4 [0.59432576 0.53279516] [ 0.01245444 -0.03801167] -0.19005558113344231 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), None, None, None, 10, array([7.68687984e-01, 6.31822760e-04]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 5, array([0.70641576, 0.19069016]), array([ 0.01245444, -0.03801167]), 10, array([7.68687984e-01, 6.31822760e-04]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 2, array([0.66905243, 0.30472516]), array([ 0.01245444, -0.03801167]), 5, array([0.70641576, 0.19069016]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), 1, array([0.65659798, 0.34273682]), array([ 0.01245444, -0.03801167]), 2, array([0.66905243, 0.30472516]), array([ 0.01245444, -0.03801167]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.65659798 0.34273682] [ 0.01245444 -0.03801167] new direction: [-0.03320369 -0.02230504] reversing there [ 0.01245444 -0.03801167] making one step from [0.65659798 0.34273682] [ 0.01245444 -0.03801167] --> [0.62339429 0.32043178] [-0.03320369 -0.02230504] trying new point, [0.62339429 0.32043178] next() call None goals: [('reflect-at', 1, array([0.62339429, 0.32043178]), array([-0.03320369, -0.02230504]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), None, None, None, -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call -0.2319571892828859 goals: [('bisect', 0, array([0.64414354, 0.38074849]), array([ 0.01245444, -0.03801167]), -5, array([0.58187131, 0.57080682]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -7 next() call -0.42459225549601265 goals: [('bisect', -5, array([0.58187131, 0.57080682]), array([ 0.01245444, -0.03801167]), -7, array([0.55696242, 0.64683016]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... -5 -7 -9 continue bisect at -8 next() call None goals: [('bisect', -7, array([0.55696242, 0.64683016]), array([ 0.01245444, -0.03801167]), -8, array([0.54450798, 0.68484182]), array([ 0.01245444, -0.03801167]), -9, array([0.53205353, 0.72285349]), array([ 0.01245444, -0.03801167]), -1), ('sample-at', -9)] bisecting ... -7 -8 -9 bisecting gave reflection point -8 [0.54450798 0.68484182] [ 0.01245444 -0.03801167] new direction: [-0.01383172 -0.03753243] reversing there [ 0.01245444 -0.03801167] making one step from [0.54450798 0.68484182] [ 0.01245444 -0.03801167] --> [0.53067626 0.64730939] [0.01383172 0.03753243] trying new point, [0.53067626 0.64730939] next() call -0.4120593466482403 goals: [('reflect-at', -8, array([0.53067626, 0.64730939]), array([0.01383172, 0.03753243]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.2842013875070083 goals: [('bisect', -8, array([0.53067626, 0.64730939]), array([0.01383172, 0.03753243]), None, None, None, -9, array([0.51684455, 0.60977695]), array([0.01383172, 0.03753243]), -1), ('sample-at', -9)] bisecting ... -8 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.51684455 0.60977695] [0.01383172 0.03753243] -0.2842013875070083 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), None, None, None, -9, array([0.64132998, 0.94756887]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 None -9 continue bisect at -5 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -5, array([0.58600312, 0.79743913]), array([-0.01383172, -0.03753243]), -9, array([0.64132998, 0.94756887]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -5 -9 continue bisect at -3 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -3, array([0.55833969, 0.72237426]), array([-0.01383172, -0.03753243]), -5, array([0.58600312, 0.79743913]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -3 -5 continue bisect at -2 next() call None goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -2, array([0.54450798, 0.68484182]), array([-0.01383172, -0.03753243]), -3, array([0.55833969, 0.72237426]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -2 -3 continue bisect at -1 next() call -0.4120593466482403 goals: [('bisect', 0, array([0.51684455, 0.60977695]), array([-0.01383172, -0.03753243]), -1, array([0.53067626, 0.64730939]), array([-0.01383172, -0.03753243]), -2, array([0.54450798, 0.68484182]), array([-0.01383172, -0.03753243]), -1), ('sample-at', -9)] bisecting ... 0 -1 -2 bisecting gave reflection point -2 [0.54450798 0.68484182] [-0.01383172 -0.03753243] new direction: [ 0.01245444 -0.03801167] reversing there [-0.01383172 -0.03753243] making one step from [0.54450798 0.68484182] [-0.01383172 -0.03753243] --> [0.55696242 0.64683016] [-0.01245444 0.03801167] trying new point, [0.55696242 0.64683016] next() call -0.42459225549601265 goals: [('reflect-at', -2, array([0.55696242, 0.64683016]), array([-0.01245444, 0.03801167]), -1), ('sample-at', -9)] goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.38522198158313203 goals: [('bisect', -2, array([0.55696242, 0.64683016]), array([-0.01245444, 0.03801167]), None, None, None, -9, array([0.64414354, 0.38074849]), array([-0.01245444, 0.03801167]), -1), ('sample-at', -9)] bisecting ... -2 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64414354 0.38074849] [ 0.01245444 -0.03801167] -0.38522198158313303 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -15..0 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-15, 0) ---- seed=31 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 BACKWARD SAMPLING FROM 4 [0.20783379 0.63322006] [0.03312527 0.02242134] -0.24344226375583042 BACKWARD SAMPLING FROM -4 [0.05716835 0.45384931] [-0.03312527 0.02242134] -0.028257682631574084 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.07533272, 0.54353469]), array([0.03312527, 0.02242134]), None, None, None, 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.33183373572512614 goals: [('bisect', 0, array([0.07533272, 0.54353469]), array([0.03312527, 0.02242134]), 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 7, array([0.30720959, 0.7004841 ]), array([0.03312527, 0.02242134]), 10, array([0.4065854 , 0.76774813]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4338904075452583 goals: [('bisect', 5, array([0.24095906, 0.65564141]), array([0.03312527, 0.02242134]), 6, array([0.27408433, 0.67806275]), array([0.03312527, 0.02242134]), 7, array([0.30720959, 0.7004841 ]), array([0.03312527, 0.02242134]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.30720959 0.7004841 ] [0.03312527 0.02242134] new direction: [0.01886481 0.03527207] reversing there [0.03312527 0.02242134] making one step from [0.30720959 0.7004841 ] [0.03312527 0.02242134] --> [0.32607441 0.73575617] [0.01886481 0.03527207] trying new point, [0.32607441 0.73575617] next() call None goals: [('reflect-at', 7, array([0.32607441, 0.73575617]), array([0.01886481, 0.03527207]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.17470852 0.61079872] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.27408433 0.67806275] [0.03312527 0.02242134] -0.4338904075452583 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.026528374387011194 goals: [('bisect', 0, array([0.27408433, 0.67806275]), array([-0.03312527, -0.02242134]), None, None, None, 6, array([0.07533272, 0.54353469]), array([-0.03312527, -0.02242134]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.07533272 0.54353469] [0.03312527 0.02242134] -0.026528374387011194 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-2, 5) ---- seed=32 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 BACKWARD SAMPLING FROM 4 [0.57413119 0.44042355] [-0.00874449 -0.03903247] -0.20918022823021926 BACKWARD SAMPLING FROM -1 [0.61785366 0.63558591] [-0.00874449 -0.03903247] -0.42066580339605575 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60910917, 0.59655344]), array([-0.00874449, -0.03903247]), None, None, None, 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.28137754791921 goals: [('bisect', 0, array([0.60910917, 0.59655344]), array([-0.00874449, -0.03903247]), 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 7, array([0.54789771, 0.32332614]), array([-0.00874449, -0.03903247]), 10, array([0.52166422, 0.20622872]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.39173967918225305 goals: [('bisect', 5, array([0.5653867 , 0.40139108]), array([-0.00874449, -0.03903247]), 6, array([0.5566422 , 0.36235861]), array([-0.00874449, -0.03903247]), 7, array([0.54789771, 0.32332614]), array([-0.00874449, -0.03903247]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.54789771 0.32332614] [-0.00874449 -0.03903247] new direction: [-0.03993719 0.00224073] reversing there [-0.00874449 -0.03903247] making one step from [0.54789771 0.32332614] [-0.00874449 -0.03903247] --> [0.50796052 0.32556687] [-0.03993719 0.00224073] trying new point, [0.50796052 0.32556687] next() call None goals: [('reflect-at', 7, array([0.50796052, 0.32556687]), array([-0.03993719, 0.00224073]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.58287569 0.47945602] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.5566422 0.36235861] [-0.00874449 -0.03903247] -0.39173967918225305 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.3020390652147834 goals: [('bisect', 0, array([0.5566422 , 0.36235861]), array([0.00874449, 0.03903247]), None, None, None, 6, array([0.60910917, 0.59655344]), array([0.00874449, 0.03903247]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60910917 0.59655344] [-0.00874449 -0.03903247] -0.3020390652147834 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=33 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 BACKWARD SAMPLING FROM 4 [0.1119679 0.53337938] [-0.03413556 0.02085099] -0.020195695214487927 BACKWARD SAMPLING FROM -4 [0.38505235 0.36657146] [-0.03413556 0.02085099] -0.2966723492317622 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.31828011334541667 goals: [('bisect', 0, array([0.24851013, 0.44997542]), array([-0.03413556, 0.02085099]), None, None, None, 10, array([0.09284544, 0.65848532]), array([0.03413556, 0.02085099]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.09284544 0.65848532] [0.03413556 0.02085099] -0.31828011334541667 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.062159372957623346 goals: [('bisect', 0, array([0.09284544, 0.65848532]), array([-0.03413556, -0.02085099]), None, None, None, 10, array([0.24851013, 0.44997542]), array([ 0.03413556, -0.02085099]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.24851013 0.44997542] [-0.03413556 0.02085099] -0.06215937295762336 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-2, 5) ---- seed=34 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 BACKWARD SAMPLING FROM 4 [0.00576602 0.5067828 ] [ 0.02461744 -0.03152747] -0.0005917034778301611 BACKWARD SAMPLING FROM -2 [0.14193864 0.69594763] [-0.02461744 -0.03152747] -0.49001670522119156 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.42756666673695237 goals: [('bisect', 0, array([0.09270376, 0.63289269]), array([-0.02461744, -0.03152747]), None, None, None, 10, array([0.15347069, 0.31761797]), array([ 0.02461744, -0.03152747]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.15347069 0.31761797] [ 0.02461744 -0.03152747] -0.42756666673695237 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.22505281963979504 goals: [('bisect', 0, array([0.15347069, 0.31761797]), array([-0.02461744, 0.03152747]), None, None, None, 10, array([0.09270376, 0.63289269]), array([0.02461744, 0.03152747]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.09270376 0.63289269] [-0.02461744 -0.03152747] -0.22505281963979504 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-1, 6) ---- seed=35 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 BACKWARD SAMPLING FROM 4 [0.12229223 0.6737271 ] [-0.00640292 0.03948421] -0.3847415272663998 BACKWARD SAMPLING FROM -4 [0.17351559 0.35785345] [-0.00640292 0.03948421] -0.26762436346562096 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), None, None, None, 10, array([0.08387471, 0.91063235]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 10, array([0.08387471, 0.91063235]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12136585946729678 goals: [('bisect', 0, array([0.14790391, 0.51579028]), array([-0.00640292, 0.03948421]), 2, array([0.13509807, 0.59475869]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.23354566196277238 goals: [('bisect', 2, array([0.13509807, 0.59475869]), array([-0.00640292, 0.03948421]), 3, array([0.12869515, 0.6342429 ]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3847415272663993 goals: [('bisect', 3, array([0.12869515, 0.6342429 ]), array([-0.00640292, 0.03948421]), 4, array([0.12229223, 0.6737271 ]), array([-0.00640292, 0.03948421]), 5, array([0.11588931, 0.71321131]), array([-0.00640292, 0.03948421]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.11588931 0.71321131] [-0.00640292 0.03948421] new direction: [-0.01879284 -0.03531047] reversing there [-0.00640292 0.03948421] making one step from [0.11588931 0.71321131] [-0.00640292 0.03948421] --> [0.09709647 0.67790084] [-0.01879284 -0.03531047] trying new point, [0.09709647 0.67790084] next() call -0.400322736376469 goals: [('reflect-at', 5, array([0.09709647, 0.67790084]), array([-0.01879284, -0.03531047]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -2.7636297378795028e-05 goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([-0.01879284, -0.03531047]), None, None, None, 10, array([0.00313227, 0.5013485 ]), array([-0.01879284, -0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.00313227 0.5013485 ] [-0.01879284 -0.03531047] -2.7636297378795028e-05 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00313227, 0.5013485 ]), array([0.01879284, 0.03531047]), None, None, None, 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.400322736376469 goals: [('bisect', 0, array([0.00313227, 0.5013485 ]), array([0.01879284, 0.03531047]), 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 7, array([0.13468215, 0.74852178]), array([0.01879284, 0.03531047]), 10, array([0.19106067, 0.85445318]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.09709647, 0.67790084]), array([0.01879284, 0.03531047]), 6, array([0.11588931, 0.71321131]), array([0.01879284, 0.03531047]), 7, array([0.13468215, 0.74852178]), array([0.01879284, 0.03531047]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.11588931 0.71321131] [0.01879284 0.03531047] new direction: [ 0.00640292 -0.03948421] reversing there [0.01879284 0.03531047] making one step from [0.11588931 0.71321131] [0.01879284 0.03531047] --> [0.12229223 0.6737271 ] [ 0.00640292 -0.03948421] trying new point, [0.12229223 0.6737271 ] next() call -0.3847415272663989 goals: [('reflect-at', 6, array([0.12229223, 0.6737271 ]), array([ 0.00640292, -0.03948421]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.014054442900799765 goals: [('bisect', 6, array([0.12229223, 0.6737271 ]), array([ 0.00640292, -0.03948421]), None, None, None, 10, array([0.14790391, 0.51579028]), array([ 0.00640292, -0.03948421]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.14790391 0.51579028] [-0.00640292 0.03948421] -0.01405444290079977 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=36 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 BACKWARD SAMPLING FROM 4 [0.7232834 0.53653594] [-0.02732618 -0.02921096] -0.27825536957064223 BACKWARD SAMPLING FROM -4 [0.57499771 0.55650503] [0.03837737 0.0112773 ] -0.20522140882168874 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), None, None, None, 10, array([0.8877191 , 0.71438717]), array([-0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 5, array([0.92039405, 0.65800069]), array([0.03837737, 0.0112773 ]), 10, array([0.8877191 , 0.71438717]), array([-0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 2, array([0.80526193, 0.6241688 ]), array([0.03837737, 0.0112773 ]), 5, array([0.92039405, 0.65800069]), array([0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4533621249956772 goals: [('bisect', 0, array([0.72850719, 0.60161421]), array([0.03837737, 0.0112773 ]), 1, array([0.76688456, 0.61289151]), array([0.03837737, 0.0112773 ]), 2, array([0.80526193, 0.6241688 ]), array([0.03837737, 0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.80526193 0.6241688 ] [0.03837737 0.0112773 ] new direction: [-0.02732618 -0.02921096] reversing there [0.03837737 0.0112773 ] making one step from [0.80526193 0.6241688 ] [0.03837737 0.0112773 ] --> [0.77793575 0.59495785] [-0.02732618 -0.02921096] trying new point, [0.77793575 0.59495785] next() call -0.41530443247762705 goals: [('reflect-at', 2, array([0.77793575, 0.59495785]), array([-0.02732618, -0.02921096]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3969974267345493 goals: [('bisect', 2, array([0.77793575, 0.59495785]), array([-0.02732618, -0.02921096]), None, None, None, 10, array([0.55932632, 0.3612702 ]), array([-0.02732618, -0.02921096]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.55932632 0.3612702 ] [-0.02732618 -0.02921096] -0.3969974267345493 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.55932632, 0.3612702 ]), array([0.02732618, 0.02921096]), None, None, None, 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.24284891598495364 goals: [('bisect', 0, array([0.55932632, 0.3612702 ]), array([0.02732618, 0.02921096]), 5, array([0.69595722, 0.50732498]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.33574054173486656 goals: [('bisect', 5, array([0.69595722, 0.50732498]), array([0.02732618, 0.02921096]), 7, array([0.75060958, 0.56574689]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4153044324776268 goals: [('bisect', 7, array([0.75060958, 0.56574689]), array([0.02732618, 0.02921096]), 8, array([0.77793575, 0.59495785]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.77793575, 0.59495785]), array([0.02732618, 0.02921096]), 9, array([0.80526193, 0.6241688 ]), array([0.02732618, 0.02921096]), 10, array([0.83258811, 0.65337976]), array([0.02732618, 0.02921096]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.80526193 0.6241688 ] [0.02732618 0.02921096] new direction: [-0.03837737 -0.0112773 ] reversing there [0.02732618 0.02921096] making one step from [0.80526193 0.6241688 ] [0.02732618 0.02921096] --> [0.76688456 0.61289151] [-0.03837737 -0.0112773 ] trying new point, [0.76688456 0.61289151] next() call -0.4533621249956771 goals: [('reflect-at', 9, array([0.76688456, 0.61289151]), array([-0.03837737, -0.0112773 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.39442946604858065 goals: [('bisect', 9, array([0.76688456, 0.61289151]), array([-0.03837737, -0.0112773 ]), None, None, None, 10, array([0.72850719, 0.60161421]), array([-0.03837737, -0.0112773 ]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72850719 0.60161421] [0.03837737 0.0112773 ] -0.39442946604858076 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (-1, 0) ---- seed=37 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 BACKWARD SAMPLING FROM 4 [0.8979157 0.491777 ] [-0.03939692 0.00691971] -0.40397152289437405 BACKWARD SAMPLING FROM -4 [0.7869089 0.43641935] [0.03939692 0.00691971] -0.360144051361222 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.23267087672305614 goals: [('bisect', 0, array([0.9444966 , 0.46409817]), array([0.03939692, 0.00691971]), None, None, None, 10, array([0.66153415, 0.53329524]), array([-0.03939692, 0.00691971]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.66153415 0.53329524] [-0.03939692 0.00691971] -0.23267087672305614 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4621486800079553 goals: [('bisect', 0, array([0.66153415, 0.53329524]), array([ 0.03939692, -0.00691971]), None, None, None, 10, array([0.9444966 , 0.46409817]), array([-0.03939692, -0.00691971]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.9444966 0.46409817] [0.03939692 0.00691971] -0.46214868000795534 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-3, 0) ---- seed=38 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 BACKWARD SAMPLING FROM 4 [0.5006498 0.516994 ] [-0.03324607 -0.02224182] -0.12893506266001822 BACKWARD SAMPLING FROM -4 [0.65441475 0.53949241] [0.01523716 0.03698417] -0.23362496788797535 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21488037935387833 goals: [('bisect', 0, array([0.6336341 , 0.60596128]), array([-0.03324607, -0.02224182]), None, None, None, 10, array([0.30117336, 0.38354308]), array([-0.03324607, -0.02224182]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.30117336 0.38354308] [-0.03324607 -0.02224182] -0.21488037935387833 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.34109350056274995 goals: [('bisect', 0, array([0.30117336, 0.38354308]), array([0.03324607, 0.02224182]), None, None, None, 10, array([0.6336341 , 0.60596128]), array([0.03324607, 0.02224182]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.6336341 0.60596128] [-0.03324607 -0.02224182] -0.34109350056274995 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 sampling between (-7, 0) ---- seed=39 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 BACKWARD SAMPLING FROM 4 [0.76168405 0.53559656] [0.03992051 0.00252049] -0.3059202287204628 BACKWARD SAMPLING FROM -4 [0.44231997 0.51543261] [0.03992051 0.00252049] -0.10080054489174596 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60200201, 0.52551458]), array([0.03992051, 0.00252049]), None, None, None, 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.33944630091534117 goals: [('bisect', 0, array([0.60200201, 0.52551458]), array([0.03992051, 0.00252049]), 5, array([0.80160456, 0.53811705]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.41175585311595747 goals: [('bisect', 5, array([0.80160456, 0.53811705]), array([0.03992051, 0.00252049]), 7, array([0.88144558, 0.54315804]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4505393331216953 goals: [('bisect', 7, array([0.88144558, 0.54315804]), array([0.03992051, 0.00252049]), 8, array([0.92136609, 0.54567853]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4910752823977196 goals: [('bisect', 8, array([0.92136609, 0.54567853]), array([0.03992051, 0.00252049]), 9, array([0.9612866 , 0.54819902]), array([0.03992051, 0.00252049]), 10, array([0.99879289, 0.55071952]), array([-0.03992051, 0.00252049]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.99879289 0.55071952] [-0.03992051 0.00252049] new direction: [0.03741642 0.01414255] reversing there [-0.03992051 0.00252049] making one step from [0.99879289 0.55071952] [-0.03992051 0.00252049] --> [0.96379069 0.56486207] [-0.03741642 0.01414255] trying new point, [0.96379069 0.56486207] next() call None goals: [('reflect-at', 10, array([0.96379069, 0.56486207]), array([-0.03741642, 0.01414255]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.9612866 0.54819902] [0.03992051 0.00252049] -0.4910752823977196 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.1893406326438129 goals: [('bisect', 0, array([0.9612866 , 0.54819902]), array([-0.03992051, -0.00252049]), None, None, None, 9, array([0.60200201, 0.52551458]), array([-0.03992051, -0.00252049]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60200201 0.52551458] [0.03992051 0.00252049] -0.1893406326438129 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -7..8 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-7, 8) ---- seed=40 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 BACKWARD SAMPLING FROM 4 [0.50385595 0.57055786] [ 0.00847644 -0.03909156] -0.18916555089029924 BACKWARD SAMPLING FROM -4 [0.6223453 0.49577156] [-0.02398644 0.03201016] -0.19388033318836445 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), None, None, None, 10, array([0.28653508, 0.94391384]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 5, array([0.4064673 , 0.78386302]), array([-0.02398644, 0.03201016]), 10, array([0.28653508, 0.94391384]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 2, array([0.47842664, 0.68783254]), array([-0.02398644, 0.03201016]), 5, array([0.4064673 , 0.78386302]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.42971710884526637 goals: [('bisect', 0, array([0.52639952, 0.62381221]), array([-0.02398644, 0.03201016]), 1, array([0.50241308, 0.65582238]), array([-0.02398644, 0.03201016]), 2, array([0.47842664, 0.68783254]), array([-0.02398644, 0.03201016]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.47842664 0.68783254] [-0.02398644 0.03201016] new direction: [ 0.00847644 -0.03909156] reversing there [-0.02398644 0.03201016] making one step from [0.47842664 0.68783254] [-0.02398644 0.03201016] --> [0.48690307 0.64874098] [ 0.00847644 -0.03909156] trying new point, [0.48690307 0.64874098] next() call -0.39508578257867283 goals: [('reflect-at', 2, array([0.48690307, 0.64874098]), array([ 0.00847644, -0.03909156]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.490019265835001 goals: [('bisect', 2, array([0.48690307, 0.64874098]), array([ 0.00847644, -0.03909156]), None, None, None, 10, array([0.55471457, 0.3360085 ]), array([ 0.00847644, -0.03909156]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.55471457 0.3360085 ] [ 0.00847644 -0.03909156] -0.490019265835001 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.55471457, 0.3360085 ]), array([-0.00847644, 0.03909156]), None, None, None, 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.14361883567172593 goals: [('bisect', 0, array([0.55471457, 0.3360085 ]), array([-0.00847644, 0.03909156]), 5, array([0.51233238, 0.5314663 ]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2729878665259479 goals: [('bisect', 5, array([0.51233238, 0.5314663 ]), array([-0.00847644, 0.03909156]), 7, array([0.49537951, 0.60964942]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3950857825786728 goals: [('bisect', 7, array([0.49537951, 0.60964942]), array([-0.00847644, 0.03909156]), 8, array([0.48690307, 0.64874098]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.48690307, 0.64874098]), array([-0.00847644, 0.03909156]), 9, array([0.47842664, 0.68783254]), array([-0.00847644, 0.03909156]), 10, array([0.4699502, 0.7269241]), array([-0.00847644, 0.03909156]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.47842664 0.68783254] [-0.00847644 0.03909156] new direction: [ 0.02398644 -0.03201016] reversing there [-0.00847644 0.03909156] making one step from [0.47842664 0.68783254] [-0.00847644 0.03909156] --> [0.50241308 0.65582238] [ 0.02398644 -0.03201016] trying new point, [0.50241308 0.65582238] next() call -0.42971710884526587 goals: [('reflect-at', 9, array([0.50241308, 0.65582238]), array([ 0.02398644, -0.03201016]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3301665303326673 goals: [('bisect', 9, array([0.50241308, 0.65582238]), array([ 0.02398644, -0.03201016]), None, None, None, 10, array([0.52639952, 0.62381221]), array([ 0.02398644, -0.03201016]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.52639952 0.62381221] [-0.02398644 0.03201016] -0.33016653033266774 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-6, 1) ---- seed=41 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 BACKWARD SAMPLING FROM 3 [0.03489126 0.69191375] [-0.02717748 0.02934935] -0.4609947924113364 BACKWARD SAMPLING FROM -4 [0.22513362 0.48646827] [-0.02717748 0.02934935] -0.027631419475083484 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), None, None, None, 10, array([0.1553511 , 0.89735923]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 10, array([0.1553511 , 0.89735923]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.33226605088879657 goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), 2, array([0.06206874, 0.6625644 ]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4609947924113364 goals: [('bisect', 2, array([0.06206874, 0.6625644 ]), array([-0.02717748, 0.02934935]), 3, array([0.03489126, 0.69191375]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.03489126, 0.69191375]), array([-0.02717748, 0.02934935]), 4, array([0.00771378, 0.7212631 ]), array([-0.02717748, 0.02934935]), 5, array([0.0194637 , 0.75061246]), array([0.02717748, 0.02934935]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.00771378 0.7212631 ] [-0.02717748 0.02934935] new direction: [ 0.03817639 -0.01193998] reversing there [-0.02717748 0.02934935] making one step from [0.00771378 0.7212631 ] [-0.02717748 0.02934935] --> [0.04589017 0.70932312] [ 0.03817639 -0.01193998] trying new point, [0.04589017 0.70932312] next() call None goals: [('reflect-at', 4, array([0.04589017, 0.70932312]), array([ 0.03817639, -0.01193998]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.022720784505758807 goals: [('bisect', 0, array([0.1164237 , 0.60386569]), array([-0.02717748, 0.02934935]), None, None, None, -3, array([0.19795614, 0.51581763]), array([-0.02717748, 0.02934935]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.03489126 0.69191375] [-0.02717748 0.02934935] -0.4609947924113364 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.14162825608964924 goals: [('bisect', 0, array([0.03489126, 0.69191375]), array([ 0.02717748, -0.02934935]), None, None, None, 3, array([0.1164237 , 0.60386569]), array([ 0.02717748, -0.02934935]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.19795614 0.51581763] [-0.02717748 0.02934935] -0.022720784505758807 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.14162825608964924 goals: [('bisect', 0, array([0.19795614, 0.51581763]), array([ 0.02717748, -0.02934935]), None, None, None, -3, array([0.1164237 , 0.60386569]), array([ 0.02717748, -0.02934935]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.1164237 0.60386569] [-0.02717748 0.02934935] -0.14162825608964924 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-2, 1) ---- seed=42 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 BACKWARD SAMPLING FROM 4 [0.60933098 0.49592681] [-0.03066574 -0.02568292] -0.18584950597376992 BACKWARD SAMPLING FROM -4 [0.77492096 0.53144407] [0.00613482 0.03952675] -0.31261037020419746 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4031802276107923 goals: [('bisect', 0, array([0.73199394, 0.59865848]), array([-0.03066574, -0.02568292]), None, None, None, 10, array([0.42533653, 0.3418293 ]), array([-0.03066574, -0.02568292]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.42533653 0.3418293 ] [-0.03066574 -0.02568292] -0.4031802276107923 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38957627172501086 goals: [('bisect', 0, array([0.42533653, 0.3418293 ]), array([0.03066574, 0.02568292]), None, None, None, 10, array([0.73199394, 0.59865848]), array([0.03066574, 0.02568292]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.73199394 0.59865848] [-0.03066574 -0.02568292] -0.38957627172501086 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (0, 1) ---- seed=43 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 BACKWARD SAMPLING FROM 4 [0.25118164 0.52498669] [ 0.03403177 -0.02101996] -0.039350293891790226 BACKWARD SAMPLING FROM -4 [0.02107251 0.69314638] [-0.03403177 -0.02101996] -0.4665410967293263 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.23153067175015277 goals: [('bisect', 0, array([0.11505457, 0.60906654]), array([ 0.03403177, -0.02101996]), None, None, None, 10, array([0.45537225, 0.39886693]), array([ 0.03403177, -0.02101996]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.45537225 0.39886693] [ 0.03403177 -0.02101996] -0.23153067175015277 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.15531265150360327 goals: [('bisect', 0, array([0.45537225, 0.39886693]), array([-0.03403177, 0.02101996]), None, None, None, 10, array([0.11505457, 0.60906654]), array([-0.03403177, 0.02101996]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.11505457 0.60906654] [ 0.03403177 -0.02101996] -0.15531265150360327 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=44 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 BACKWARD SAMPLING FROM 4 [0.47062097 0.66599703] [-0.02002389 -0.03462721] -0.4551797092301754 BACKWARD SAMPLING FROM -4 [0.22797682 0.51785252] [0.03283351 0.02284646] -0.02997062159932815 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), None, None, None, 10, array([0.68764589, 0.83770303]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 10, array([0.68764589, 0.83770303]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.39034946973740525 goals: [('bisect', 0, array([0.35931084, 0.60923838]), array([0.03283351, 0.02284646]), 2, array([0.42497785, 0.65493131]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.49985733022926904 goals: [('bisect', 2, array([0.42497785, 0.65493131]), array([0.03283351, 0.02284646]), 3, array([0.45781135, 0.67777777]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.45781135, 0.67777777]), array([0.03283351, 0.02284646]), 4, array([0.49064486, 0.70062424]), array([0.03283351, 0.02284646]), 5, array([0.52347836, 0.7234707 ]), array([0.03283351, 0.02284646]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.49064486 0.70062424] [0.03283351 0.02284646] new direction: [-0.02002389 -0.03462721] reversing there [0.03283351 0.02284646] making one step from [0.49064486 0.70062424] [0.03283351 0.02284646] --> [0.47062097 0.66599703] [-0.02002389 -0.03462721] trying new point, [0.47062097 0.66599703] next() call -0.455179709230175 goals: [('reflect-at', 4, array([0.47062097, 0.66599703]), array([-0.02002389, -0.03462721]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08322252232880438 goals: [('bisect', 4, array([0.47062097, 0.66599703]), array([-0.02002389, -0.03462721]), None, None, None, 10, array([0.35047762, 0.45823376]), array([-0.02002389, -0.03462721]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.35047762 0.45823376] [-0.02002389 -0.03462721] -0.08322252232880438 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35047762, 0.45823376]), array([0.02002389, 0.03462721]), None, None, None, 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3172442164483675 goals: [('bisect', 0, array([0.35047762, 0.45823376]), array([0.02002389, 0.03462721]), 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 7, array([0.49064486, 0.70062424]), array([0.02002389, 0.03462721]), 10, array([0.55071653, 0.80450587]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.455179709230175 goals: [('bisect', 5, array([0.45059708, 0.63136981]), array([0.02002389, 0.03462721]), 6, array([0.47062097, 0.66599703]), array([0.02002389, 0.03462721]), 7, array([0.49064486, 0.70062424]), array([0.02002389, 0.03462721]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.49064486 0.70062424] [0.02002389 0.03462721] new direction: [-0.03283351 -0.02284646] reversing there [0.02002389 0.03462721] making one step from [0.49064486 0.70062424] [0.02002389 0.03462721] --> [0.45781135 0.67777777] [-0.03283351 -0.02284646] trying new point, [0.45781135 0.67777777] next() call -0.49985733022926904 goals: [('reflect-at', 7, array([0.45781135, 0.67777777]), array([-0.03283351, -0.02284646]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.21371493658412127 goals: [('bisect', 7, array([0.45781135, 0.67777777]), array([-0.03283351, -0.02284646]), None, None, None, 10, array([0.35931084, 0.60923838]), array([-0.03283351, -0.02284646]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.35931084 0.60923838] [0.03283351 0.02284646] -0.2137149365841216 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-6, 1) ---- seed=45 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 BACKWARD SAMPLING FROM 4 [0.54665538 0.34968996] [ 0.02554647 -0.0307795 ] -0.4318299192036039 BACKWARD SAMPLING FROM -4 [0.34228361 0.59592598] [ 0.02554647 -0.0307795 ] -0.1736014655895373 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), None, None, None, 10, array([0.6999342 , 0.16501293]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 10, array([0.6999342 , 0.16501293]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.22125039734136934 goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), 2, array([0.49556244, 0.41124896]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.31437162423426 goals: [('bisect', 2, array([0.49556244, 0.41124896]), array([ 0.02554647, -0.0307795 ]), 3, array([0.52110891, 0.38046946]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.4318299192036037 goals: [('bisect', 3, array([0.52110891, 0.38046946]), array([ 0.02554647, -0.0307795 ]), 4, array([0.54665538, 0.34968996]), array([ 0.02554647, -0.0307795 ]), 5, array([0.57220185, 0.31891045]), array([ 0.02554647, -0.0307795 ]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.57220185 0.31891045] [ 0.02554647 -0.0307795 ] new direction: [-0.03976603 -0.00432004] reversing there [ 0.02554647 -0.0307795 ] making one step from [0.57220185 0.31891045] [ 0.02554647 -0.0307795 ] --> [0.53243582 0.31459041] [-0.03976603 -0.00432004] trying new point, [0.53243582 0.31459041] next() call None goals: [('reflect-at', 5, array([0.53243582, 0.31459041]), array([-0.03976603, -0.00432004]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.087909125121415 goals: [('bisect', 0, array([0.4444695 , 0.47280797]), array([ 0.02554647, -0.0307795 ]), None, None, None, -1, array([0.41892303, 0.50358747]), array([ 0.02554647, -0.0307795 ]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.54665538 0.34968996] [ 0.02554647 -0.0307795 ] -0.4318299192036037 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.10801914778494678 goals: [('bisect', 0, array([0.54665538, 0.34968996]), array([-0.02554647, 0.0307795 ]), None, None, None, 4, array([0.4444695 , 0.47280797]), array([-0.02554647, 0.0307795 ]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.41892303 0.50358747] [ 0.02554647 -0.0307795 ] -0.087909125121415 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.10801914778494684 goals: [('bisect', 0, array([0.41892303, 0.50358747]), array([-0.02554647, 0.0307795 ]), None, None, None, -1, array([0.4444695 , 0.47280797]), array([-0.02554647, 0.0307795 ]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.4444695 0.47280797] [ 0.02554647 -0.0307795 ] -0.10801914778494684 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=46 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 BACKWARD SAMPLING FROM 4 [0.15144064 0.55838923] [0.0271438 0.02938051] -0.05408341768692817 BACKWARD SAMPLING FROM -4 [0.06570974 0.32334517] [-0.0271438 0.02938051] -0.3922454873386127 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.04286545, 0.4408672 ]), array([0.0271438 , 0.02938051]), None, None, None, 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.11224029674516076 goals: [('bisect', 0, array([0.04286545, 0.4408672 ]), array([0.0271438 , 0.02938051]), 5, array([0.17858444, 0.58776974]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2955054800380875 goals: [('bisect', 5, array([0.17858444, 0.58776974]), array([0.0271438 , 0.02938051]), 7, array([0.23287203, 0.64653076]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4206137842727819 goals: [('bisect', 7, array([0.23287203, 0.64653076]), array([0.0271438 , 0.02938051]), 8, array([0.26001583, 0.67591127]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.26001583, 0.67591127]), array([0.0271438 , 0.02938051]), 9, array([0.28715963, 0.70529177]), array([0.0271438 , 0.02938051]), 10, array([0.31430343, 0.73467228]), array([0.0271438 , 0.02938051]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.28715963 0.70529177] [0.0271438 0.02938051] new direction: [ 0.02281179 -0.03285761] reversing there [0.0271438 0.02938051] making one step from [0.28715963 0.70529177] [0.0271438 0.02938051] --> [0.30997142 0.67243417] [ 0.02281179 -0.03285761] trying new point, [0.30997142 0.67243417] next() call -0.41971042152871735 goals: [('reflect-at', 9, array([0.30997142, 0.67243417]), array([ 0.02281179, -0.03285761]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2988925458881023 goals: [('bisect', 9, array([0.30997142, 0.67243417]), array([ 0.02281179, -0.03285761]), None, None, None, 10, array([0.33278321, 0.63957656]), array([ 0.02281179, -0.03285761]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.33278321 0.63957656] [ 0.02281179 -0.03285761] -0.2988925458881023 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), None, None, None, 10, array([0.1046653 , 0.96815261]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 5, array([0.21872426, 0.80386459]), array([-0.02281179, 0.03285761]), 10, array([0.1046653 , 0.96815261]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 2, array([0.28715963, 0.70529177]), array([-0.02281179, 0.03285761]), 5, array([0.21872426, 0.80386459]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.41971042152871735 goals: [('bisect', 0, array([0.33278321, 0.63957656]), array([-0.02281179, 0.03285761]), 1, array([0.30997142, 0.67243417]), array([-0.02281179, 0.03285761]), 2, array([0.28715963, 0.70529177]), array([-0.02281179, 0.03285761]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.28715963 0.70529177] [-0.02281179 0.03285761] new direction: [-0.0271438 -0.02938051] reversing there [-0.02281179 0.03285761] making one step from [0.28715963 0.70529177] [-0.02281179 0.03285761] --> [0.26001583 0.67591127] [-0.0271438 -0.02938051] trying new point, [0.26001583 0.67591127] next() call -0.4206137842727819 goals: [('reflect-at', 2, array([0.26001583, 0.67591127]), array([-0.0271438 , -0.02938051]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.04462731870887185 goals: [('bisect', 2, array([0.26001583, 0.67591127]), array([-0.0271438 , -0.02938051]), None, None, None, 10, array([0.04286545, 0.4408672 ]), array([-0.0271438 , -0.02938051]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04286545 0.4408672 ] [0.0271438 0.02938051] -0.04462731870887193 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=47 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 BACKWARD SAMPLING FROM 4 [0.56078481 0.55029357] [-0.02119426 0.03392349] -0.18885784622089788 BACKWARD SAMPLING FROM -1 [0.66675612 0.38067612] [-0.02119426 0.03392349] -0.40025922669221325 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64556185, 0.41459961]), array([-0.02119426, 0.03392349]), None, None, None, 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.23423540704363024 goals: [('bisect', 0, array([0.64556185, 0.41459961]), array([-0.02119426, 0.03392349]), 5, array([0.53959055, 0.58421707]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.4126483656060907 goals: [('bisect', 5, array([0.53959055, 0.58421707]), array([-0.02119426, 0.03392349]), 7, array([0.49720203, 0.65206405]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.49720203, 0.65206405]), array([-0.02119426, 0.03392349]), 8, array([0.47600776, 0.68598754]), array([-0.02119426, 0.03392349]), 10, array([0.43361924, 0.75383452]), array([-0.02119426, 0.03392349]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.47600776 0.68598754] [-0.02119426 0.03392349] new direction: [-0.02911927 -0.02742386] reversing there [-0.02119426 0.03392349] making one step from [0.47600776 0.68598754] [-0.02119426 0.03392349] --> [0.44688849 0.65856368] [-0.02911927 -0.02742386] trying new point, [0.44688849 0.65856368] next() call -0.4141351863645779 goals: [('reflect-at', 8, array([0.44688849, 0.65856368]), array([-0.02911927, -0.02742386]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20998692233081806 goals: [('bisect', 8, array([0.44688849, 0.65856368]), array([-0.02911927, -0.02742386]), None, None, None, 10, array([0.38864994, 0.60371597]), array([-0.02911927, -0.02742386]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.38864994 0.60371597] [-0.02911927 -0.02742386] -0.20998692233081806 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), None, None, None, 10, array([0.67984268, 0.87795454]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 10, array([0.67984268, 0.87795454]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4141351863645779 goals: [('bisect', 0, array([0.38864994, 0.60371597]), array([0.02911927, 0.02742386]), 2, array([0.44688849, 0.65856368]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.44688849, 0.65856368]), array([0.02911927, 0.02742386]), 3, array([0.47600776, 0.68598754]), array([0.02911927, 0.02742386]), 5, array([0.53424631, 0.74083525]), array([0.02911927, 0.02742386]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.47600776 0.68598754] [0.02911927 0.02742386] new direction: [ 0.02119426 -0.03392349] reversing there [0.02911927 0.02742386] making one step from [0.47600776 0.68598754] [0.02911927 0.02742386] --> [0.49720203 0.65206405] [ 0.02119426 -0.03392349] trying new point, [0.49720203 0.65206405] next() call -0.4126483656060907 goals: [('reflect-at', 3, array([0.49720203, 0.65206405]), array([ 0.02119426, -0.03392349]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2995403926532866 goals: [('bisect', 3, array([0.49720203, 0.65206405]), array([ 0.02119426, -0.03392349]), None, None, None, 10, array([0.64556185, 0.41459961]), array([ 0.02119426, -0.03392349]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64556185 0.41459961] [-0.02119426 0.03392349] -0.2995403926532865 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=48 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 BACKWARD SAMPLING FROM 4 [0.70528601 0.43395284] [-0.03985609 -0.00338995] -0.3032420227989266 BACKWARD SAMPLING FROM -4 [0.90468504 0.44962923] [0.03979681 0.00402662] -0.44094269508821465 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.20193125737173862 goals: [('bisect', 0, array([0.86471039, 0.44751263]), array([-0.03985609, -0.00338995]), None, None, None, 10, array([0.46614944, 0.41361315]), array([-0.03985609, -0.00338995]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.46614944 0.41361315] [-0.03985609 -0.00338995] -0.20193125737173862 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.40829857363895855 goals: [('bisect', 0, array([0.46614944, 0.41361315]), array([0.03985609, 0.00338995]), None, None, None, 10, array([0.86471039, 0.44751263]), array([0.03985609, 0.00338995]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.86471039 0.44751263] [-0.03985609 -0.00338995] -0.40829857363895855 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 sampling between (-6, 1) ---- seed=49 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 BACKWARD SAMPLING FROM 4 [0.69043306 0.40704478] [ 0.00178908 -0.03995997] -0.3463573209308397 BACKWARD SAMPLING FROM -4 [0.55985875 0.65300213] [ 0.03994662 -0.00206584] -0.44934157693712723 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.68327676, 0.56688466]), array([ 0.00178908, -0.03995997]), None, None, None, 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4604163445319175 goals: [('bisect', 0, array([0.68327676, 0.56688466]), array([ 0.00178908, -0.03995997]), 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 7, array([0.69580029, 0.28716487]), array([ 0.00178908, -0.03995997]), 10, array([0.70116752, 0.16728496]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.69222214, 0.36708481]), array([ 0.00178908, -0.03995997]), 6, array([0.69401122, 0.32712484]), array([ 0.00178908, -0.03995997]), 7, array([0.69580029, 0.28716487]), array([ 0.00178908, -0.03995997]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.69401122 0.32712484] [ 0.00178908 -0.03995997] new direction: [-0.03993708 -0.00224268] reversing there [ 0.00178908 -0.03995997] making one step from [0.69401122 0.32712484] [ 0.00178908 -0.03995997] --> [0.65407414 0.32488216] [-0.03993708 -0.00224268] trying new point, [0.65407414 0.32488216] next() call None goals: [('reflect-at', 6, array([0.65407414, 0.32488216]), array([-0.03993708, -0.00224268]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.68506584 0.52692469] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.69222214 0.36708481] [ 0.00178908 -0.03995997] -0.4604163445319175 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.2893530363157967 goals: [('bisect', 0, array([0.69222214, 0.36708481]), array([-0.00178908, 0.03995997]), None, None, None, 5, array([0.68327676, 0.56688466]), array([-0.00178908, 0.03995997]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.68327676 0.56688466] [ 0.00178908 -0.03995997] -0.2893530363157967 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -2..5 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -10..5 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-10, 5) ---- seed=50 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 BACKWARD SAMPLING FROM 4 [0.13808816 0.33647507] [0.00832488 0.03912411] -0.3437892113032023 BACKWARD SAMPLING FROM -4 [0.38118457 0.49530887] [-0.03142766 -0.02474474] -0.07292592188692902 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), None, None, None, 10, array([0.05880269, 0.14888252]), array([ 0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 10, array([0.05880269, 0.14888252]), array([ 0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.31177413021896305 goals: [('bisect', 0, array([0.25547392, 0.39632991]), array([-0.03142766, -0.02474474]), 2, array([0.1926186 , 0.34684043]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4086155422937598 goals: [('bisect', 2, array([0.1926186 , 0.34684043]), array([-0.03142766, -0.02474474]), 3, array([0.16119094, 0.32209569]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.16119094, 0.32209569]), array([-0.03142766, -0.02474474]), 4, array([0.12976328, 0.29735095]), array([-0.03142766, -0.02474474]), 5, array([0.09833562, 0.27260621]), array([-0.03142766, -0.02474474]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.12976328 0.29735095] [-0.03142766 -0.02474474] new direction: [0.00832488 0.03912411] reversing there [-0.03142766 -0.02474474] making one step from [0.12976328 0.29735095] [-0.03142766 -0.02474474] --> [0.13808816 0.33647507] [0.00832488 0.03912411] trying new point, [0.13808816 0.33647507] next() call -0.3437892113032023 goals: [('reflect-at', 4, array([0.13808816, 0.33647507]), array([0.00832488, 0.03912411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08108221261480617 goals: [('bisect', 4, array([0.13808816, 0.33647507]), array([0.00832488, 0.03912411]), None, None, None, 10, array([0.18803745, 0.57121976]), array([0.00832488, 0.03912411]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.18803745 0.57121976] [0.00832488 0.03912411] -0.08108221261480617 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18803745, 0.57121976]), array([-0.00832488, -0.03912411]), None, None, None, 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.20416293012453088 goals: [('bisect', 0, array([0.18803745, 0.57121976]), array([-0.00832488, -0.03912411]), 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 7, array([0.12976328, 0.29735095]), array([-0.00832488, -0.03912411]), 10, array([0.10478864, 0.17997861]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3437892113032023 goals: [('bisect', 5, array([0.14641304, 0.37559918]), array([-0.00832488, -0.03912411]), 6, array([0.13808816, 0.33647507]), array([-0.00832488, -0.03912411]), 7, array([0.12976328, 0.29735095]), array([-0.00832488, -0.03912411]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.12976328 0.29735095] [-0.00832488 -0.03912411] new direction: [0.03142766 0.02474474] reversing there [-0.00832488 -0.03912411] making one step from [0.12976328 0.29735095] [-0.00832488 -0.03912411] --> [0.16119094 0.32209569] [0.03142766 0.02474474] trying new point, [0.16119094 0.32209569] next() call -0.4086155422937598 goals: [('reflect-at', 7, array([0.16119094, 0.32209569]), array([0.03142766, 0.02474474]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16697705808604757 goals: [('bisect', 7, array([0.16119094, 0.32209569]), array([0.03142766, 0.02474474]), None, None, None, 10, array([0.25547392, 0.39632991]), array([0.03142766, 0.02474474]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25547392 0.39632991] [-0.03142766 -0.02474474] -0.1669770580860475 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=51 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 BACKWARD SAMPLING FROM 1 [0.32904737 0.68139295] [-0.0142563 0.03737322] -0.4654286221899625 BACKWARD SAMPLING FROM -4 [0.40032887 0.49452683] [-0.0142563 0.03737322] -0.08050604831793806 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), None, None, None, 10, array([0.20074067, 0.98224803]), array([-0.0142563 , -0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 5, array([0.27202217, 0.83088585]), array([-0.0142563 , 0.03737322]), 10, array([0.20074067, 0.98224803]), array([-0.0142563 , -0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 2, array([0.31479107, 0.71876618]), array([-0.0142563 , 0.03737322]), 5, array([0.27202217, 0.83088585]), array([-0.0142563 , 0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4654286221899625 goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), 1, array([0.32904737, 0.68139295]), array([-0.0142563 , 0.03737322]), 2, array([0.31479107, 0.71876618]), array([-0.0142563 , 0.03737322]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.31479107 0.71876618] [-0.0142563 0.03737322] new direction: [-0.039365 -0.00709908] reversing there [-0.0142563 0.03737322] making one step from [0.31479107 0.71876618] [-0.0142563 0.03737322] --> [0.27542607 0.7116671 ] [-0.039365 -0.00709908] trying new point, [0.27542607 0.7116671 ] next() call None goals: [('reflect-at', 2, array([0.27542607, 0.7116671 ]), array([-0.039365 , -0.00709908]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.27101878092937887 goals: [('bisect', 0, array([0.34330367, 0.64401973]), array([-0.0142563 , 0.03737322]), None, None, None, -7, array([0.44309777, 0.38240716]), array([-0.0142563 , 0.03737322]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.32904737 0.68139295] [-0.0142563 0.03737322] -0.4654286221899625 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.31819972792644835 goals: [('bisect', 0, array([0.32904737, 0.68139295]), array([ 0.0142563 , -0.03737322]), None, None, None, 1, array([0.34330367, 0.64401973]), array([ 0.0142563 , -0.03737322]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.44309777 0.38240716] [-0.0142563 0.03737322] -0.27101878092937887 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.31819972792644835 goals: [('bisect', 0, array([0.44309777, 0.38240716]), array([ 0.0142563 , -0.03737322]), None, None, None, -7, array([0.34330367, 0.64401973]), array([ 0.0142563 , -0.03737322]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.34330367 0.64401973] [-0.0142563 0.03737322] -0.31819972792644835 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=52 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 BACKWARD SAMPLING FROM 4 [0.36003865 0.56081047] [ 0.037317 -0.01440282] -0.11103783451846358 BACKWARD SAMPLING FROM -4 [0.06150263 0.67603307] [ 0.037317 -0.01440282] -0.3892367900814762 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17868949115336583 goals: [('bisect', 0, array([0.21077064, 0.61842177]), array([ 0.037317 , -0.01440282]), None, None, None, 10, array([0.58394066, 0.47439353]), array([ 0.037317 , -0.01440282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.58394066 0.47439353] [ 0.037317 -0.01440282] -0.17868949115336583 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19750857452717718 goals: [('bisect', 0, array([0.58394066, 0.47439353]), array([-0.037317 , 0.01440282]), None, None, None, 10, array([0.21077064, 0.61842177]), array([-0.037317 , 0.01440282]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.21077064 0.61842177] [ 0.037317 -0.01440282] -0.19750857452717718 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=53 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 BACKWARD SAMPLING FROM 4 [0.72477641 0.45751322] [-0.0304715 -0.02591308] -0.28521449853834674 BACKWARD SAMPLING FROM -1 [0.87713391 0.58707862] [-0.0304715 -0.02591308] -0.4794655207604886 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.84666241, 0.56116554]), array([-0.0304715 , -0.02591308]), None, None, None, 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2995114075574864 goals: [('bisect', 0, array([0.84666241, 0.56116554]), array([-0.0304715 , -0.02591308]), 5, array([0.69430491, 0.43160014]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.38125233905933353 goals: [('bisect', 5, array([0.69430491, 0.43160014]), array([-0.0304715 , -0.02591308]), 7, array([0.63336191, 0.37977398]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4486963615420411 goals: [('bisect', 7, array([0.63336191, 0.37977398]), array([-0.0304715 , -0.02591308]), 8, array([0.60289041, 0.3538609 ]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.60289041, 0.3538609 ]), array([-0.0304715 , -0.02591308]), 9, array([0.57241891, 0.32794783]), array([-0.0304715 , -0.02591308]), 10, array([0.54194741, 0.30203475]), array([-0.0304715 , -0.02591308]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.57241891 0.32794783] [-0.0304715 -0.02591308] new direction: [-0.00163041 -0.03996676] reversing there [-0.0304715 -0.02591308] making one step from [0.57241891 0.32794783] [-0.0304715 -0.02591308] --> [0.5707885 0.28798107] [-0.00163041 -0.03996676] trying new point, [0.5707885 0.28798107] next() call None goals: [('reflect-at', 9, array([0.5707885 , 0.28798107]), array([-0.00163041, -0.03996676]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.60289041 0.3538609 ] [-0.0304715 -0.02591308] -0.4486963615420411 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.40518390734034826 goals: [('bisect', 0, array([0.60289041, 0.3538609 ]), array([0.0304715 , 0.02591308]), None, None, None, 8, array([0.84666241, 0.56116554]), array([0.0304715 , 0.02591308]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.84666241 0.56116554] [-0.0304715 -0.02591308] -0.40518390734034826 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=54 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 BACKWARD SAMPLING FROM 4 [0.29205086 0.4590631 ] [-0.03203303 0.0239559 ] -0.06359472404742703 BACKWARD SAMPLING FROM -1 [0.45221599 0.3392836 ] [-0.03203303 0.0239559 ] -0.4251216837222281 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.13707944044464876 goals: [('bisect', 0, array([0.42018297, 0.3632395 ]), array([-0.03203303, 0.0239559 ]), None, None, None, 10, array([0.0998527 , 0.60279851]), array([-0.03203303, 0.0239559 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.0998527 0.60279851] [-0.03203303 0.0239559 ] -0.13707944044464876 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.32206980281714764 goals: [('bisect', 0, array([0.0998527 , 0.60279851]), array([ 0.03203303, -0.0239559 ]), None, None, None, 10, array([0.42018297, 0.3632395 ]), array([ 0.03203303, -0.0239559 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.42018297 0.3632395 ] [-0.03203303 0.0239559 ] -0.32206980281714764 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (-1, 0) ---- seed=55 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 BACKWARD SAMPLING FROM 4 [0.06288283 0.47543852] [ 0.01800544 -0.0357184 ] -0.00951795620141871 BACKWARD SAMPLING FROM -2 [0.04514983 0.68974891] [-0.01800544 -0.0357184 ] -0.45107737484070604 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00913894, 0.61831211]), array([-0.01800544, -0.0357184 ]), None, None, None, 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.04869226052335881 goals: [('bisect', 0, array([0.00913894, 0.61831211]), array([-0.01800544, -0.0357184 ]), 5, array([0.08088827, 0.43972012]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2236987612488 goals: [('bisect', 5, array([0.08088827, 0.43972012]), array([ 0.01800544, -0.0357184 ]), 7, array([0.11689915, 0.36828332]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3595309576523012 goals: [('bisect', 7, array([0.11689915, 0.36828332]), array([ 0.01800544, -0.0357184 ]), 8, array([0.13490459, 0.33256492]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.13490459, 0.33256492]), array([ 0.01800544, -0.0357184 ]), 9, array([0.15291004, 0.29684652]), array([ 0.01800544, -0.0357184 ]), 10, array([0.17091548, 0.26112812]), array([ 0.01800544, -0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.15291004 0.29684652] [ 0.01800544 -0.0357184 ] new direction: [-0.03842475 0.01111479] reversing there [ 0.01800544 -0.0357184 ] making one step from [0.15291004 0.29684652] [ 0.01800544 -0.0357184 ] --> [0.11448528 0.30796131] [-0.03842475 0.01111479] trying new point, [0.11448528 0.30796131] next() call -0.46753918956341406 goals: [('reflect-at', 9, array([0.11448528, 0.30796131]), array([-0.03842475, 0.01111479]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41206085167620243 goals: [('bisect', 9, array([0.11448528, 0.30796131]), array([-0.03842475, 0.01111479]), None, None, None, 10, array([0.07606053, 0.31907609]), array([-0.03842475, 0.01111479]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.07606053 0.31907609] [-0.03842475 0.01111479] -0.41206085167620243 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), None, None, None, 10, array([0.46030805, 0.20792822]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 5, array([0.26818429, 0.26350216]), array([ 0.03842475, -0.01111479]), 10, array([0.46030805, 0.20792822]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 2, array([0.15291004, 0.29684652]), array([ 0.03842475, -0.01111479]), 5, array([0.26818429, 0.26350216]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.46753918956341406 goals: [('bisect', 0, array([0.07606053, 0.31907609]), array([ 0.03842475, -0.01111479]), 1, array([0.11448528, 0.30796131]), array([ 0.03842475, -0.01111479]), 2, array([0.15291004, 0.29684652]), array([ 0.03842475, -0.01111479]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.15291004 0.29684652] [ 0.03842475 -0.01111479] new direction: [-0.01800544 0.0357184 ] reversing there [ 0.03842475 -0.01111479] making one step from [0.15291004 0.29684652] [ 0.03842475 -0.01111479] --> [0.13490459 0.33256492] [-0.01800544 0.0357184 ] trying new point, [0.13490459 0.33256492] next() call -0.3595309576523012 goals: [('reflect-at', 2, array([0.13490459, 0.33256492]), array([-0.01800544, 0.0357184 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.17501371251886214 goals: [('bisect', 2, array([0.13490459, 0.33256492]), array([-0.01800544, 0.0357184 ]), None, None, None, 10, array([0.00913894, 0.61831211]), array([0.01800544, 0.0357184 ]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.00913894 0.61831211] [-0.01800544 -0.0357184 ] -0.17501371251886214 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=56 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 BACKWARD SAMPLING FROM 4 [0.39113326 0.5298137 ] [0.03582093 0.01780059] -0.08760332684710367 BACKWARD SAMPLING FROM -4 [0.10456585 0.38740895] [0.03582093 0.01780059] -0.16392632784250208 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41695714617072094 goals: [('bisect', 0, array([0.24784955, 0.45861133]), array([0.03582093, 0.01780059]), None, None, None, 10, array([0.60605882, 0.63661727]), array([0.03582093, 0.01780059]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.60605882 0.63661727] [0.03582093 0.01780059] -0.41695714617072094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05212748066477112 goals: [('bisect', 0, array([0.60605882, 0.63661727]), array([-0.03582093, -0.01780059]), None, None, None, 10, array([0.24784955, 0.45861133]), array([-0.03582093, -0.01780059]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.24784955 0.45861133] [0.03582093 0.01780059] -0.05212748066477112 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -5..10 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd new NUTS range: -5..26 NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd NUTS step: tree depth 5, rwd sampling between (-5, 26) ---- seed=57 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 BACKWARD SAMPLING FROM 3 [0.54397394 0.66303317] [-0.00732732 0.03932315] -0.4802014861520403 BACKWARD SAMPLING FROM -4 [0.59526516 0.38777109] [-0.00732732 0.03932315] -0.3346119116596618 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), None, None, None, 10, array([0.49268272, 0.93829524]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 10, array([0.49268272, 0.93829524]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.34326862471080793 goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), 2, array([0.55130126, 0.62371001]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4802014861520402 goals: [('bisect', 2, array([0.55130126, 0.62371001]), array([-0.00732732, 0.03932315]), 3, array([0.54397394, 0.66303317]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.54397394, 0.66303317]), array([-0.00732732, 0.03932315]), 4, array([0.53664662, 0.70235632]), array([-0.00732732, 0.03932315]), 5, array([0.52931931, 0.74167947]), array([-0.00732732, 0.03932315]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.53664662 0.70235632] [-0.00732732 0.03932315] new direction: [-0.03991081 -0.00266972] reversing there [-0.00732732 0.03932315] making one step from [0.53664662 0.70235632] [-0.00732732 0.03932315] --> [0.49673582 0.69968659] [-0.03991081 -0.00266972] trying new point, [0.49673582 0.69968659] next() call None goals: [('reflect-at', 4, array([0.49673582, 0.69968659]), array([-0.03991081, -0.00266972]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.23927607150196617 goals: [('bisect', 0, array([0.56595589, 0.5450637 ]), array([-0.00732732, 0.03932315]), None, None, None, -3, array([0.58793784, 0.42709424]), array([-0.00732732, 0.03932315]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.54397394 0.66303317] [-0.00732732 0.03932315] -0.4802014861520402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.18553725262780735 goals: [('bisect', 0, array([0.54397394, 0.66303317]), array([ 0.00732732, -0.03932315]), None, None, None, 3, array([0.56595589, 0.5450637 ]), array([ 0.00732732, -0.03932315]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.58793784 0.42709424] [-0.00732732 0.03932315] -0.23927607150196617 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.18553725262780735 goals: [('bisect', 0, array([0.58793784, 0.42709424]), array([ 0.00732732, -0.03932315]), None, None, None, -3, array([0.56595589, 0.5450637 ]), array([ 0.00732732, -0.03932315]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.56595589 0.5450637 ] [-0.00732732 0.03932315] -0.18553725262780735 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-5, 2) ---- seed=58 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 BACKWARD SAMPLING FROM 4 [0.52440832 0.43628484] [ 0.03982568 -0.00373027] -0.18824731253691152 BACKWARD SAMPLING FROM -4 [0.20580285 0.46612699] [ 0.03982568 -0.00373027] -0.03551966453010344 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3840192746128853 goals: [('bisect', 0, array([0.36510558, 0.45120592]), array([ 0.03982568, -0.00373027]), None, None, None, 10, array([0.76336242, 0.41390323]), array([ 0.03982568, -0.00373027]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.76336242 0.41390323] [ 0.03982568 -0.00373027] -0.3840192746128853 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.09641182642477081 goals: [('bisect', 0, array([0.76336242, 0.41390323]), array([-0.03982568, 0.00373027]), None, None, None, 10, array([0.36510558, 0.45120592]), array([-0.03982568, 0.00373027]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.36510558 0.45120592] [ 0.03982568 -0.00373027] -0.09641182642477078 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=59 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 BACKWARD SAMPLING FROM 4 [0.4021635 0.49826765] [ 0.03647074 -0.01642819] -0.08090525343003006 BACKWARD SAMPLING FROM -4 [0.11039762 0.62969317] [ 0.03647074 -0.01642819] -0.2163478092623813 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.318567864176321 goals: [('bisect', 0, array([0.25628056, 0.56398041]), array([ 0.03647074, -0.01642819]), None, None, None, 10, array([0.62098791, 0.39969851]), array([ 0.03647074, -0.01642819]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.62098791 0.39969851] [ 0.03647074 -0.01642819] -0.318567864176321 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.08400852608514758 goals: [('bisect', 0, array([0.62098791, 0.39969851]), array([-0.03647074, 0.01642819]), None, None, None, 10, array([0.25628056, 0.56398041]), array([-0.03647074, 0.01642819]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25628056 0.56398041] [ 0.03647074 -0.01642819] -0.08400852608514758 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -5..2 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-5, 2) ---- seed=60 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 BACKWARD SAMPLING FROM 4 [0.48306538 0.65962424] [ 0.03997068 -0.00153133] -0.43517479808588755 BACKWARD SAMPLING FROM -4 [0.16329997 0.6718749 ] [ 0.03997068 -0.00153133] -0.3825957187127649 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32318268, 0.66574957]), array([ 0.03997068, -0.00153133]), None, None, None, 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.44920044099302747 goals: [('bisect', 0, array([0.32318268, 0.66574957]), array([ 0.03997068, -0.00153133]), 5, array([0.52303606, 0.6580929 ]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.482220565464306 goals: [('bisect', 5, array([0.52303606, 0.6580929 ]), array([ 0.03997068, -0.00153133]), 7, array([0.60297742, 0.65503024]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.60297742, 0.65503024]), array([ 0.03997068, -0.00153133]), 8, array([0.64294809, 0.6534989 ]), array([ 0.03997068, -0.00153133]), 10, array([0.72288945, 0.65043624]), array([ 0.03997068, -0.00153133]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.64294809 0.6534989 ] [ 0.03997068 -0.00153133] new direction: [0.0021526 0.03994204] reversing there [ 0.03997068 -0.00153133] making one step from [0.64294809 0.6534989 ] [ 0.03997068 -0.00153133] --> [0.64510069 0.69344094] [0.0021526 0.03994204] trying new point, [0.64510069 0.69344094] next() call None goals: [('reflect-at', 8, array([0.64510069, 0.69344094]), array([0.0021526 , 0.03994204]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 7... 3 steps to do at 7 -> [from 8, delta=3] targeting 5. goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 7 [0.60297742 0.65503024] [ 0.03997068 -0.00153133] -0.482220565464306 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 7)] not done yet, continue expanding to 7... goals: [('expand-to', 7), ('sample-at', 7)] next() call -0.39563502198066103 goals: [('bisect', 0, array([0.60297742, 0.65503024]), array([-0.03997068, 0.00153133]), None, None, None, 7, array([0.32318268, 0.66574957]), array([-0.03997068, 0.00153133]), 1), ('sample-at', 7)] bisecting ... 0 None 7 successfully went all the way in one jump! goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.32318268 0.66574957] [ 0.03997068 -0.00153133] -0.39563502198066103 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=61 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 BACKWARD SAMPLING FROM 4 [0.72389146 0.54491217] [-0.03835883 0.01134021] -0.28722320791367995 BACKWARD SAMPLING FROM -4 [0.91257131 0.47071355] [ 0.03991597 -0.00259145] -0.4271143991277972 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2813698847877405 goals: [('bisect', 0, array([0.87732677, 0.49955131]), array([-0.03835883, 0.01134021]), None, None, None, 10, array([0.49373851, 0.61295345]), array([-0.03835883, 0.01134021]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.49373851 0.61295345] [-0.03835883 0.01134021] -0.2813698847877405 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38485364567003044 goals: [('bisect', 0, array([0.49373851, 0.61295345]), array([ 0.03835883, -0.01134021]), None, None, None, 10, array([0.87732677, 0.49955131]), array([ 0.03835883, -0.01134021]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.87732677 0.49955131] [-0.03835883 0.01134021] -0.38485364567003044 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -1..14 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-1, 14) ---- seed=62 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 BACKWARD SAMPLING FROM 4 [0.01633454 0.33005865] [-0.00435504 -0.03976221] -0.3611341698842485 BACKWARD SAMPLING FROM -4 [0.05117488 0.64815636] [-0.00435504 -0.03976221] -0.2756882768233669 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), None, None, None, 10, array([0.00979571, 0.09148537]), array([ 0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 10, array([0.00979571, 0.09148537]), array([ 0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.10250385662007835 goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), 2, array([0.02504463, 0.40958308]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.21204660991891755 goals: [('bisect', 2, array([0.02504463, 0.40958308]), array([-0.00435504, -0.03976221]), 3, array([0.02068959, 0.36982087]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.3611341698842485 goals: [('bisect', 3, array([0.02068959, 0.36982087]), array([-0.00435504, -0.03976221]), 4, array([0.01633454, 0.33005865]), array([-0.00435504, -0.03976221]), 5, array([0.0119795 , 0.29029644]), array([-0.00435504, -0.03976221]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.0119795 0.29029644] [-0.00435504 -0.03976221] new direction: [ 0.03630756 -0.01678574] reversing there [-0.00435504 -0.03976221] making one step from [0.0119795 0.29029644] [-0.00435504 -0.03976221] --> [0.04828706 0.2735107 ] [ 0.03630756 -0.01678574] trying new point, [0.04828706 0.2735107 ] next() call None goals: [('reflect-at', 5, array([0.04828706, 0.2735107 ]), array([ 0.03630756, -0.01678574]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.011144436722510533 goals: [('bisect', 0, array([0.03375471, 0.48910751]), array([-0.00435504, -0.03976221]), None, None, None, -1, array([0.03810975, 0.52886972]), array([-0.00435504, -0.03976221]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.01633454 0.33005865] [-0.00435504 -0.03976221] -0.3611341698842485 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.0020527700218748433 goals: [('bisect', 0, array([0.01633454, 0.33005865]), array([0.00435504, 0.03976221]), None, None, None, 4, array([0.03375471, 0.48910751]), array([0.00435504, 0.03976221]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.03810975 0.52886972] [-0.00435504 -0.03976221] -0.011144436722510533 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.0020527700218748585 goals: [('bisect', 0, array([0.03810975, 0.52886972]), array([0.00435504, 0.03976221]), None, None, None, -1, array([0.03375471, 0.48910751]), array([0.00435504, 0.03976221]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.03375471 0.48910751] [-0.00435504 -0.03976221] -0.0020527700218748433 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-4, 3) ---- seed=63 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 BACKWARD SAMPLING FROM 4 [0.4072226 0.46007348] [-0.03667961 0.0159564 ] -0.10284171548913772 BACKWARD SAMPLING FROM -4 [0.586297 0.36749354] [ 0.03884142 -0.00955742] -0.3913466099390096 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05644864986759578 goals: [('bisect', 0, array([0.55394102, 0.39624789]), array([-0.03667961, 0.0159564 ]), None, None, None, 10, array([0.18714497, 0.55581185]), array([-0.03667961, 0.0159564 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.18714497 0.55581185] [-0.03667961 0.0159564 ] -0.05644864986759578 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2879815727116586 goals: [('bisect', 0, array([0.18714497, 0.55581185]), array([ 0.03667961, -0.0159564 ]), None, None, None, 10, array([0.55394102, 0.39624789]), array([ 0.03667961, -0.0159564 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.55394102 0.39624789] [-0.03667961 0.0159564 ] -0.2879815727116586 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=64 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 BACKWARD SAMPLING FROM 4 [0.39993594 0.60551572] [ 0.00067241 -0.03999435] -0.21914395901276984 BACKWARD SAMPLING FROM -4 [0.35310841 0.40922317] [0.00649753 0.03946875] -0.16534817926836115 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), None, None, None, 10, array([0.44407381, 0.96178565]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 10, array([0.44407381, 0.96178565]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.343448880085709 goals: [('bisect', 0, array([0.37909853, 0.56709817]), array([0.00649753, 0.03946875]), 2, array([0.39209358, 0.64603566]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.39209358, 0.64603566]), array([0.00649753, 0.03946875]), 3, array([0.39859111, 0.68550441]), array([0.00649753, 0.03946875]), 5, array([0.41158617, 0.76444191]), array([0.00649753, 0.03946875]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.39859111 0.68550441] [0.00649753 0.03946875] new direction: [ 0.00067241 -0.03999435] reversing there [0.00649753 0.03946875] making one step from [0.39859111 0.68550441] [0.00649753 0.03946875] --> [0.39926352 0.64551007] [ 0.00067241 -0.03999435] trying new point, [0.39926352 0.64551007] next() call -0.3443704192313505 goals: [('reflect-at', 3, array([0.39926352, 0.64551007]), array([ 0.00067241, -0.03999435]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.30755732018362913 goals: [('bisect', 3, array([0.39926352, 0.64551007]), array([ 0.00067241, -0.03999435]), None, None, None, 10, array([0.40397041, 0.36554963]), array([ 0.00067241, -0.03999435]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.40397041 0.36554963] [ 0.00067241 -0.03999435] -0.30755732018362913 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.40397041, 0.36554963]), array([-0.00067241, 0.03999435]), None, None, None, 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.13390664748382503 goals: [('bisect', 0, array([0.40397041, 0.36554963]), array([-0.00067241, 0.03999435]), 5, array([0.40060835, 0.56552137]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.3443704192313509 goals: [('bisect', 5, array([0.40060835, 0.56552137]), array([-0.00067241, 0.03999435]), 7, array([0.39926352, 0.64551007]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.39926352, 0.64551007]), array([-0.00067241, 0.03999435]), 8, array([0.39859111, 0.68550441]), array([-0.00067241, 0.03999435]), 10, array([0.39724629, 0.76549311]), array([-0.00067241, 0.03999435]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.39859111 0.68550441] [-0.00067241 0.03999435] new direction: [-0.00649753 -0.03946875] reversing there [-0.00067241 0.03999435] making one step from [0.39859111 0.68550441] [-0.00067241 0.03999435] --> [0.39209358 0.64603566] [-0.00649753 -0.03946875] trying new point, [0.39209358 0.64603566] next() call -0.3434488800857094 goals: [('reflect-at', 8, array([0.39209358, 0.64603566]), array([-0.00649753, -0.03946875]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12813489647882276 goals: [('bisect', 8, array([0.39209358, 0.64603566]), array([-0.00649753, -0.03946875]), None, None, None, 10, array([0.37909853, 0.56709817]), array([-0.00649753, -0.03946875]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.37909853 0.56709817] [0.00649753 0.03946875] -0.12813489647882234 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=65 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 BACKWARD SAMPLING FROM 4 [0.1092311 0.61062131] [-0.03020213 0.02622654] -0.1589291517496356 BACKWARD SAMPLING FROM -4 [0.35084815 0.40080902] [-0.03020213 0.02622654] -0.18453284519551352 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.23003963, 0.50571517]), array([-0.03020213, 0.02622654]), None, None, None, 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.23721446196834403 goals: [('bisect', 0, array([0.23003963, 0.50571517]), array([-0.03020213, 0.02622654]), 5, array([0.07902897, 0.63684785]), array([-0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.44810893033872173 goals: [('bisect', 5, array([0.07902897, 0.63684785]), array([-0.03020213, 0.02622654]), 7, array([0.0186247 , 0.68930092]), array([-0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.0186247 , 0.68930092]), array([-0.03020213, 0.02622654]), 8, array([0.01157743, 0.71552746]), array([0.03020213, 0.02622654]), 10, array([0.07198169, 0.76798053]), array([0.03020213, 0.02622654]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.01157743 0.71552746] [0.03020213 0.02622654] new direction: [0.03498847 0.01938573] reversing there [0.03020213 0.02622654] making one step from [0.01157743 0.71552746] [0.03020213 0.02622654] --> [0.0465659 0.73491319] [0.03498847 0.01938573] trying new point, [0.0465659 0.73491319] next() call None goals: [('reflect-at', 8, array([0.0465659 , 0.73491319]), array([0.03498847, 0.01938573]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 7... 3 steps to do at 7 -> [from 8, delta=3] targeting 5. goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 7 [0.0186247 0.68930092] [-0.03020213 0.02622654] -0.44810893033872173 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 7)] not done yet, continue expanding to 7... goals: [('expand-to', 7), ('sample-at', 7)] next() call -0.026867403984676807 goals: [('bisect', 0, array([0.0186247 , 0.68930092]), array([ 0.03020213, -0.02622654]), None, None, None, 7, array([0.23003963, 0.50571517]), array([ 0.03020213, -0.02622654]), 1), ('sample-at', 7)] bisecting ... 0 None 7 successfully went all the way in one jump! goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.23003963 0.50571517] [-0.03020213 0.02622654] -0.02686740398467679 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=66 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 BACKWARD SAMPLING FROM 4 [0.43880939 0.53837811] [ 0.01903098 -0.03518269] -0.1146878297183696 BACKWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.36268547, 0.67910888]), array([ 0.01903098, -0.03518269]), None, None, None, 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.10493653469527497 goals: [('bisect', 0, array([0.36268547, 0.67910888]), array([ 0.01903098, -0.03518269]), 5, array([0.45784037, 0.50319542]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.17935711354999778 goals: [('bisect', 5, array([0.45784037, 0.50319542]), array([ 0.01903098, -0.03518269]), 7, array([0.49590233, 0.43283003]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.2635289874278154 goals: [('bisect', 7, array([0.49590233, 0.43283003]), array([ 0.01903098, -0.03518269]), 8, array([0.51493331, 0.39764734]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.37900858427260387 goals: [('bisect', 8, array([0.51493331, 0.39764734]), array([ 0.01903098, -0.03518269]), 9, array([0.53396429, 0.36246465]), array([ 0.01903098, -0.03518269]), 10, array([0.55299527, 0.32728196]), array([ 0.01903098, -0.03518269]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.55299527 0.32728196] [ 0.01903098 -0.03518269] new direction: [-0.03590325 0.01763396] reversing there [ 0.01903098 -0.03518269] making one step from [0.55299527 0.32728196] [ 0.01903098 -0.03518269] --> [0.51709202 0.34491592] [-0.03590325 0.01763396] trying new point, [0.51709202 0.34491592] next() call -0.4343304840564407 goals: [('reflect-at', 10, array([0.51709202, 0.34491592]), array([-0.03590325, 0.01763396]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.51709202 0.34491592] [-0.03590325 0.01763396] -0.4343304840564407 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), None, None, None, 10, array([0.87612454, 0.16857633]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 5, array([0.69660828, 0.25674612]), array([ 0.03590325, -0.01763396]), 10, array([0.87612454, 0.16857633]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 2, array([0.58889852, 0.309648 ]), array([ 0.03590325, -0.01763396]), 5, array([0.69660828, 0.25674612]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.51709202, 0.34491592]), array([ 0.03590325, -0.01763396]), 1, array([0.55299527, 0.32728196]), array([ 0.03590325, -0.01763396]), 2, array([0.58889852, 0.309648 ]), array([ 0.03590325, -0.01763396]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.55299527 0.32728196] [ 0.03590325 -0.01763396] new direction: [-0.01903098 0.03518269] reversing there [ 0.03590325 -0.01763396] making one step from [0.55299527 0.32728196] [ 0.03590325 -0.01763396] --> [0.53396429 0.36246465] [-0.01903098 0.03518269] trying new point, [0.53396429 0.36246465] next() call -0.379008584272604 goals: [('reflect-at', 1, array([0.53396429, 0.36246465]), array([-0.01903098, 0.03518269]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.46677023948045687 goals: [('bisect', 1, array([0.53396429, 0.36246465]), array([-0.01903098, 0.03518269]), None, None, None, 10, array([0.36268547, 0.67910888]), array([-0.01903098, 0.03518269]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.36268547 0.67910888] [ 0.01903098 -0.03518269] -0.46677023948045726 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=67 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 BACKWARD SAMPLING FROM 4 [0.08924898 0.33300678] [0.01670024 0.03634697] -0.3525668892829215 BACKWARD SAMPLING FROM -4 [0.1925446 0.47589575] [-0.03313667 -0.02240449] -0.025799396299807646 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), None, None, None, 10, array([0.27136874, 0.16223286]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 10, array([0.27136874, 0.16223286]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.31417147356422026 goals: [('bisect', 0, array([0.05999793, 0.38627778]), array([-0.03313667, -0.02240449]), 2, array([0.0062754, 0.3414688]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4099982344835686 goals: [('bisect', 2, array([0.0062754, 0.3414688]), array([ 0.03313667, -0.02240449]), 3, array([0.03941207, 0.3190643 ]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.03941207, 0.3190643 ]), array([ 0.03313667, -0.02240449]), 4, array([0.07254874, 0.29665981]), array([ 0.03313667, -0.02240449]), 5, array([0.10568541, 0.27425532]), array([ 0.03313667, -0.02240449]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.07254874 0.29665981] [ 0.03313667 -0.02240449] new direction: [0.01670024 0.03634697] reversing there [ 0.03313667 -0.02240449] making one step from [0.07254874 0.29665981] [ 0.03313667 -0.02240449] --> [0.08924898 0.33300678] [0.01670024 0.03634697] trying new point, [0.08924898 0.33300678] next() call -0.3525668892829215 goals: [('reflect-at', 4, array([0.08924898, 0.33300678]), array([0.01670024, 0.03634697]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05057127231465654 goals: [('bisect', 4, array([0.08924898, 0.33300678]), array([0.01670024, 0.03634697]), None, None, None, 10, array([0.1894504 , 0.55108859]), array([0.01670024, 0.03634697]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.1894504 0.55108859] [0.01670024 0.03634697] -0.05057127231465654 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1894504 , 0.55108859]), array([-0.01670024, -0.03634697]), None, None, None, 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.218968162054107 goals: [('bisect', 0, array([0.1894504 , 0.55108859]), array([-0.01670024, -0.03634697]), 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 7, array([0.07254874, 0.29665981]), array([-0.01670024, -0.03634697]), 10, array([0.02244803, 0.18761891]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3525668892829218 goals: [('bisect', 5, array([0.10594921, 0.36935375]), array([-0.01670024, -0.03634697]), 6, array([0.08924898, 0.33300678]), array([-0.01670024, -0.03634697]), 7, array([0.07254874, 0.29665981]), array([-0.01670024, -0.03634697]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.07254874 0.29665981] [-0.01670024 -0.03634697] new direction: [-0.03313667 0.02240449] reversing there [-0.01670024 -0.03634697] making one step from [0.07254874 0.29665981] [-0.01670024 -0.03634697] --> [0.03941207 0.3190643 ] [-0.03313667 0.02240449] trying new point, [0.03941207 0.3190643 ] next() call -0.4099982344835688 goals: [('reflect-at', 7, array([0.03941207, 0.3190643 ]), array([-0.03313667, 0.02240449]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.16345916433290641 goals: [('bisect', 7, array([0.03941207, 0.3190643 ]), array([-0.03313667, 0.02240449]), None, None, None, 10, array([0.05999793, 0.38627778]), array([0.03313667, 0.02240449]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.05999793 0.38627778] [-0.03313667 -0.02240449] -0.16345916433290608 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-3, 0) ---- seed=68 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 BACKWARD SAMPLING FROM 3 [0.91992279 0.42837599] [-0.0176335 -0.03590348] -0.48725395469592275 BACKWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), None, None, None, 10, array([0.79648829, 0.17705165]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 10, array([0.79648829, 0.17705165]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4554553560620388 goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), 2, array([0.93755629, 0.46427947]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.48725395469592286 goals: [('bisect', 2, array([0.93755629, 0.46427947]), array([-0.0176335 , -0.03590348]), 3, array([0.91992279, 0.42837599]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.91992279, 0.42837599]), array([-0.0176335 , -0.03590348]), 4, array([0.90228929, 0.39247251]), array([-0.0176335 , -0.03590348]), 5, array([0.88465579, 0.35656904]), array([-0.0176335 , -0.03590348]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.90228929 0.39247251] [-0.0176335 -0.03590348] new direction: [-0.0084219 -0.03910335] reversing there [-0.0176335 -0.03590348] making one step from [0.90228929 0.39247251] [-0.0176335 -0.03590348] --> [0.8938674 0.35336917] [-0.0084219 -0.03910335] trying new point, [0.8938674 0.35336917] next() call None goals: [('reflect-at', 4, array([0.8938674 , 0.35336917]), array([-0.0084219 , -0.03910335]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), None, None, None, -3, array([0.97427621, 0.64379685]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 None -3 continue bisect at -2 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), -2, array([0.99190971, 0.60789338]), array([ 0.0176335 , -0.03590348]), -3, array([0.97427621, 0.64379685]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 -2 -3 continue bisect at -1 next() call None goals: [('bisect', 0, array([0.97282329, 0.53608642]), array([-0.0176335 , -0.03590348]), -1, array([0.99045679, 0.5719899 ]), array([-0.0176335 , -0.03590348]), -2, array([0.99190971, 0.60789338]), array([ 0.0176335 , -0.03590348]), -1), ('sample-at', -3)] bisecting ... 0 -1 -2 bisecting gave reflection point -1 [0.99045679 0.5719899 ] [-0.0176335 -0.03590348] new direction: [-0.03469108 0.01991304] reversing there [-0.0176335 -0.03590348] making one step from [0.99045679 0.5719899 ] [-0.0176335 -0.03590348] --> [0.95576572 0.59190294] [ 0.03469108 -0.01991304] trying new point, [0.95576572 0.59190294] next() call None goals: [('reflect-at', -1, array([0.95576572, 0.59190294]), array([ 0.03469108, -0.01991304]), -1), ('sample-at', -3)] goals: [('sample-at', -3)] reversing at 0... -3 steps to do at 0 -> [from -1, delta=-3] targeting 2. goals: [('sample-at', 2)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.91992279 0.42837599] [-0.0176335 -0.03590348] -0.48725395469592286 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.4894704551842364 goals: [('bisect', 0, array([0.91992279, 0.42837599]), array([0.0176335 , 0.03590348]), None, None, None, 3, array([0.97282329, 0.53608642]), array([0.0176335 , 0.03590348]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.97282329 0.53608642] [-0.0176335 -0.03590348] -0.4894704551842365 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=69 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 BACKWARD SAMPLING FROM 4 [0.08314008 0.33011112] [0.0398791 0.00310763] -0.3642340475299841 BACKWARD SAMPLING FROM -4 [0.23379485 0.34519503] [ 0.00209787 -0.03994495] -0.32688726566612836 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3379065727944484 goals: [('bisect', 0, array([0.07637632, 0.3176806 ]), array([-0.0398791 , 0.00310763]), None, None, None, 10, array([0.32241468, 0.3487569 ]), array([0.0398791 , 0.00310763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.32241468 0.3487569 ] [0.0398791 0.00310763] -0.3379065727944484 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4184212317690846 goals: [('bisect', 0, array([0.32241468, 0.3487569 ]), array([-0.0398791 , -0.00310763]), None, None, None, 10, array([0.07637632, 0.3176806 ]), array([ 0.0398791 , -0.00310763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.07637632 0.3176806 ] [-0.0398791 0.00310763] -0.4184212317690846 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=70 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 BACKWARD SAMPLING FROM 1 [0.89331877 0.41228611] [ 0.03378467 -0.02141486] -0.49518079847518337 BACKWARD SAMPLING FROM -4 [0.72439543 0.5193604 ] [ 0.03378467 -0.02141486] -0.2670596822248383 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), None, None, None, 10, array([0.80261921, 0.21955238]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 5, array([0.97154255, 0.32662667]), array([-0.03378467, -0.02141486]), 10, array([0.80261921, 0.21955238]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 2, array([0.92710344, 0.39087125]), array([ 0.03378467, -0.02141486]), 5, array([0.97154255, 0.32662667]), array([-0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.49518079847518337 goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), 1, array([0.89331877, 0.41228611]), array([ 0.03378467, -0.02141486]), 2, array([0.92710344, 0.39087125]), array([ 0.03378467, -0.02141486]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.92710344 0.39087125] [ 0.03378467 -0.02141486] new direction: [-0.03988025 -0.00309289] reversing there [ 0.03378467 -0.02141486] making one step from [0.92710344 0.39087125] [ 0.03378467 -0.02141486] --> [0.88722319 0.38777836] [-0.03988025 -0.00309289] trying new point, [0.88722319 0.38777836] next() call None goals: [('reflect-at', 2, array([0.88722319, 0.38777836]), array([-0.03988025, -0.00309289]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 1... 9 steps to do at 1 -> [from 2, delta=9] targeting -7. goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.28146270933833795 goals: [('bisect', 0, array([0.8595341 , 0.43370097]), array([ 0.03378467, -0.02141486]), None, None, None, -7, array([0.62304142, 0.58360498]), array([ 0.03378467, -0.02141486]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 1 [0.89331877 0.41228611] [ 0.03378467 -0.02141486] -0.49518079847518337 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 1)] not done yet, continue expanding to 1... goals: [('expand-to', 1), ('sample-at', 1)] next() call -0.42434395908116324 goals: [('bisect', 0, array([0.89331877, 0.41228611]), array([-0.03378467, 0.02141486]), None, None, None, 1, array([0.8595341 , 0.43370097]), array([-0.03378467, 0.02141486]), 1), ('sample-at', 1)] bisecting ... 0 None 1 successfully went all the way in one jump! goals: [('sample-at', 1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -7 [0.62304142 0.58360498] [ 0.03378467 -0.02141486] -0.28146270933833795 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -7)] not done yet, continue expanding to -7... goals: [('expand-to', -7), ('sample-at', -7)] next() call -0.42434395908116324 goals: [('bisect', 0, array([0.62304142, 0.58360498]), array([-0.03378467, 0.02141486]), None, None, None, -7, array([0.8595341 , 0.43370097]), array([-0.03378467, 0.02141486]), -1), ('sample-at', -7)] bisecting ... 0 None -7 successfully went all the way in one jump! goals: [('sample-at', -7)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.8595341 0.43370097] [ 0.03378467 -0.02141486] -0.42434395908116324 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=71 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 BACKWARD SAMPLING FROM 4 [0.25971764 0.3556196 ] [0.01088008 0.03849187] -0.29429788638027965 BACKWARD SAMPLING FROM -4 [0.11573234 0.53055056] [ 0.01746073 -0.03598781] -0.018363694539417472 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), None, None, None, 10, array([0.36018262, 0.02672116]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 10, array([0.36018262, 0.02672116]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.4538641787707029 goals: [('bisect', 0, array([0.18557527, 0.3865993 ]), array([ 0.01746073, -0.03598781]), 2, array([0.22049674, 0.31462368]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call None goals: [('bisect', 2, array([0.22049674, 0.31462368]), array([ 0.01746073, -0.03598781]), 3, array([0.23795748, 0.27863586]), array([ 0.01746073, -0.03598781]), 5, array([0.27287895, 0.20666023]), array([ 0.01746073, -0.03598781]), 1), ('sample-at', 10)] bisecting ... 2 3 5 bisecting gave reflection point 3 [0.23795748 0.27863586] [ 0.01746073 -0.03598781] new direction: [0.01088008 0.03849187] reversing there [ 0.01746073 -0.03598781] making one step from [0.23795748 0.27863586] [ 0.01746073 -0.03598781] --> [0.24883756 0.31712773] [0.01088008 0.03849187] trying new point, [0.24883756 0.31712773] next() call -0.44898840843073634 goals: [('reflect-at', 3, array([0.24883756, 0.31712773]), array([0.01088008, 0.03849187]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.14649318477587447 goals: [('bisect', 3, array([0.24883756, 0.31712773]), array([0.01088008, 0.03849187]), None, None, None, 10, array([0.32499811, 0.5865708 ]), array([0.01088008, 0.03849187]), 1), ('sample-at', 10)] bisecting ... 3 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.32499811 0.5865708 ] [0.01088008 0.03849187] -0.14649318477587447 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32499811, 0.5865708 ]), array([-0.01088008, -0.03849187]), None, None, None, 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.17676633722022025 goals: [('bisect', 0, array([0.32499811, 0.5865708 ]), array([-0.01088008, -0.03849187]), 5, array([0.27059772, 0.39411146]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.44898840843073634 goals: [('bisect', 5, array([0.27059772, 0.39411146]), array([-0.01088008, -0.03849187]), 7, array([0.24883756, 0.31712773]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call None goals: [('bisect', 7, array([0.24883756, 0.31712773]), array([-0.01088008, -0.03849187]), 8, array([0.23795748, 0.27863586]), array([-0.01088008, -0.03849187]), 10, array([0.21619732, 0.20165213]), array([-0.01088008, -0.03849187]), 1), ('sample-at', 10)] bisecting ... 7 8 10 bisecting gave reflection point 8 [0.23795748 0.27863586] [-0.01088008 -0.03849187] new direction: [-0.01746073 0.03598781] reversing there [-0.01088008 -0.03849187] making one step from [0.23795748 0.27863586] [-0.01088008 -0.03849187] --> [0.22049674 0.31462368] [-0.01746073 0.03598781] trying new point, [0.22049674 0.31462368] next() call -0.4538641787707029 goals: [('reflect-at', 8, array([0.22049674, 0.31462368]), array([-0.01746073, 0.03598781]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1779655671937919 goals: [('bisect', 8, array([0.22049674, 0.31462368]), array([-0.01746073, 0.03598781]), None, None, None, 10, array([0.18557527, 0.3865993 ]), array([-0.01746073, 0.03598781]), 1), ('sample-at', 10)] bisecting ... 8 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18557527 0.3865993 ] [ 0.01746073 -0.03598781] -0.17796556719379159 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -7..0 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-7, 0) ---- seed=72 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 BACKWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 BACKWARD SAMPLING FROM -4 [0.20355555 0.55695974] [-0.02420434 0.03184572] -0.06127258297454431 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), None, None, None, 10, array([0.13530517, 0.99720014]), array([ 0.02420434, -0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 5, array([0.01428348, 0.84357125]), array([0.02420434, 0.03184572]), 10, array([0.13530517, 0.99720014]), array([ 0.02420434, -0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 2, array([0.05832953, 0.74803408]), array([-0.02420434, 0.03184572]), 5, array([0.01428348, 0.84357125]), array([0.02420434, 0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), 1, array([0.08253387, 0.71618836]), array([-0.02420434, 0.03184572]), 2, array([0.05832953, 0.74803408]), array([-0.02420434, 0.03184572]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.08253387 0.71618836] [-0.02420434 0.03184572] new direction: [-0.03993916 0.0022054 ] reversing there [-0.02420434 0.03184572] making one step from [0.08253387 0.71618836] [-0.02420434 0.03184572] --> [0.04259471 0.71839376] [-0.03993916 0.0022054 ] trying new point, [0.04259471 0.71839376] next() call None goals: [('reflect-at', 1, array([0.04259471, 0.71839376]), array([-0.03993916, 0.0022054 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.1834117210951967 goals: [('bisect', 0, array([0.1067382 , 0.68434263]), array([-0.02420434, 0.03184572]), None, None, None, -9, array([0.32457724, 0.39773113]), array([-0.02420434, 0.03184572]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.32457724 0.39773113] [-0.02420434 0.03184572] -0.1834117210951967 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.4304741024618556 goals: [('bisect', 0, array([0.32457724, 0.39773113]), array([ 0.02420434, -0.03184572]), None, None, None, -9, array([0.1067382 , 0.68434263]), array([ 0.02420434, -0.03184572]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.1067382 0.68434263] [-0.02420434 0.03184572] -0.4304741024618556 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 sampling between (0, 1) ---- seed=73 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 BACKWARD SAMPLING FROM 4 [0.72214504 0.62997003] [-0.03328493 -0.02218362] -0.4718993295718914 BACKWARD SAMPLING FROM -4 [0.52994985 0.42508821] [0.02818502 0.02838318] -0.21057062182068897 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), None, None, None, 10, array([0.92454007, 0.82245273]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 10, array([0.92454007, 0.82245273]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3580765940944526 goals: [('bisect', 0, array([0.64268992, 0.53862093]), array([0.02818502, 0.02838318]), 2, array([0.69905995, 0.59538729]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.45593173307845614 goals: [('bisect', 2, array([0.69905995, 0.59538729]), array([0.02818502, 0.02838318]), 3, array([0.72724496, 0.62377047]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.72724496, 0.62377047]), array([0.02818502, 0.02838318]), 4, array([0.75542998, 0.65215365]), array([0.02818502, 0.02838318]), 5, array([0.78361499, 0.68053683]), array([0.02818502, 0.02838318]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.75542998 0.65215365] [0.02818502 0.02838318] new direction: [-0.03328493 -0.02218362] reversing there [0.02818502 0.02838318] making one step from [0.75542998 0.65215365] [0.02818502 0.02838318] --> [0.72214504 0.62997003] [-0.03328493 -0.02218362] trying new point, [0.72214504 0.62997003] next() call -0.4718993295718915 goals: [('reflect-at', 4, array([0.72214504, 0.62997003]), array([-0.03328493, -0.02218362]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.13659198800339803 goals: [('bisect', 4, array([0.72214504, 0.62997003]), array([-0.03328493, -0.02218362]), None, None, None, 10, array([0.52243544, 0.49686829]), array([-0.03328493, -0.02218362]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.52243544 0.49686829] [-0.03328493 -0.02218362] -0.13659198800339803 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.52243544, 0.49686829]), array([0.03328493, 0.02218362]), None, None, None, 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.38248798494168457 goals: [('bisect', 0, array([0.52243544, 0.49686829]), array([0.03328493, 0.02218362]), 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 7, array([0.75542998, 0.65215365]), array([0.03328493, 0.02218362]), 10, array([0.85528478, 0.71870452]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4718993295718915 goals: [('bisect', 5, array([0.68886011, 0.6077864 ]), array([0.03328493, 0.02218362]), 6, array([0.72214504, 0.62997003]), array([0.03328493, 0.02218362]), 7, array([0.75542998, 0.65215365]), array([0.03328493, 0.02218362]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.75542998 0.65215365] [0.03328493 0.02218362] new direction: [-0.02818502 -0.02838318] reversing there [0.03328493 0.02218362] making one step from [0.75542998 0.65215365] [0.03328493 0.02218362] --> [0.72724496 0.62377047] [-0.02818502 -0.02838318] trying new point, [0.72724496 0.62377047] next() call -0.4559317330784566 goals: [('reflect-at', 7, array([0.72724496, 0.62377047]), array([-0.02818502, -0.02838318]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2251698677879109 goals: [('bisect', 7, array([0.72724496, 0.62377047]), array([-0.02818502, -0.02838318]), None, None, None, 10, array([0.64268992, 0.53862093]), array([-0.02818502, -0.02838318]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64268992 0.53862093] [0.02818502 0.02838318] -0.2251698677879107 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: 0..7 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: 0..15 sampling between (0, 15) ---- seed=74 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 BACKWARD SAMPLING FROM 4 [0.908303 0.46166811] [-0.03985264 0.00343029] -0.4308738435817744 BACKWARD SAMPLING FROM -4 [0.7125903 0.50525487] [ 0.03934543 -0.00720676] -0.2542376365289063 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.38560758459709216 goals: [('bisect', 0, array([0.869972 , 0.47642782]), array([ 0.03934543, -0.00720676]), None, None, None, 10, array([0.73657373, 0.4043602 ]), array([-0.03934543, -0.00720676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.73657373 0.4043602 ] [-0.03934543 -0.00720676] -0.38560758459709216 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3853712408253484 goals: [('bisect', 0, array([0.73657373, 0.4043602 ]), array([0.03934543, 0.00720676]), None, None, None, 10, array([0.869972 , 0.47642782]), array([-0.03934543, 0.00720676]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.869972 0.47642782] [ 0.03934543 -0.00720676] -0.38537124082534857 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -14..1 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-14, 1) ---- seed=75 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 BACKWARD SAMPLING FROM 4 [0.8243863 0.61256616] [0.03617356 0.01707259] -0.49819564920674286 BACKWARD SAMPLING FROM -4 [0.53499778 0.47598547] [0.03617356 0.01707259] -0.15032003434226449 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), None, None, None, 10, array([0.95857231, 0.71500168]), array([-0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 10, array([0.95857231, 0.71500168]), array([-0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3596546025768169 goals: [('bisect', 0, array([0.67969204, 0.54427582]), array([0.03617356, 0.01707259]), 2, array([0.75203917, 0.57842099]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.42462744731562935 goals: [('bisect', 2, array([0.75203917, 0.57842099]), array([0.03617356, 0.01707259]), 3, array([0.78821274, 0.59549358]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.49819564920674275 goals: [('bisect', 3, array([0.78821274, 0.59549358]), array([0.03617356, 0.01707259]), 4, array([0.8243863 , 0.61256616]), array([0.03617356, 0.01707259]), 5, array([0.86055987, 0.62963875]), array([0.03617356, 0.01707259]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.86055987 0.62963875] [0.03617356 0.01707259] new direction: [-0.01645837 -0.03645713] reversing there [0.03617356 0.01707259] making one step from [0.86055987 0.62963875] [0.03617356 0.01707259] --> [0.84410149 0.59318162] [-0.01645837 -0.03645713] trying new point, [0.84410149 0.59318162] next() call -0.46478885376243206 goals: [('reflect-at', 5, array([0.84410149, 0.59318162]), array([-0.01645837, -0.03645713]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3894210121323491 goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([-0.01645837, -0.03645713]), None, None, None, 10, array([0.76180964, 0.41089599]), array([-0.01645837, -0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.76180964 0.41089599] [-0.01645837 -0.03645713] -0.3894210121323491 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.76180964, 0.41089599]), array([0.01645837, 0.03645713]), None, None, None, 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.46478885376243206 goals: [('bisect', 0, array([0.76180964, 0.41089599]), array([0.01645837, 0.03645713]), 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 7, array([0.87701824, 0.66609588]), array([0.01645837, 0.03645713]), 10, array([0.92639335, 0.77546725]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.84410149, 0.59318162]), array([0.01645837, 0.03645713]), 6, array([0.86055987, 0.62963875]), array([0.01645837, 0.03645713]), 7, array([0.87701824, 0.66609588]), array([0.01645837, 0.03645713]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.86055987 0.62963875] [0.01645837 0.03645713] new direction: [-0.03617356 -0.01707259] reversing there [0.01645837 0.03645713] making one step from [0.86055987 0.62963875] [0.01645837 0.03645713] --> [0.8243863 0.61256616] [-0.03617356 -0.01707259] trying new point, [0.8243863 0.61256616] next() call -0.4981956492067427 goals: [('reflect-at', 6, array([0.8243863 , 0.61256616]), array([-0.03617356, -0.01707259]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.25549498455609504 goals: [('bisect', 6, array([0.8243863 , 0.61256616]), array([-0.03617356, -0.01707259]), None, None, None, 10, array([0.67969204, 0.54427582]), array([-0.03617356, -0.01707259]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.67969204 0.54427582] [0.03617356 0.01707259] -0.25549498455609526 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -12..3 NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd NUTS step: tree depth 4, fwd sampling between (-12, 3) ---- seed=76 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 BACKWARD SAMPLING FROM 4 [0.68160346 0.52744316] [0.0063244 0.03949686] -0.24170572618743733 BACKWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.65630586, 0.36945572]), array([0.0063244 , 0.03949686]), None, None, None, 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.2926344475809864 goals: [('bisect', 0, array([0.65630586, 0.36945572]), array([0.0063244 , 0.03949686]), 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 7, array([0.70057666, 0.64593374]), array([0.0063244 , 0.03949686]), 10, array([0.71954987, 0.76442432]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.3826032159139785 goals: [('bisect', 5, array([0.68792786, 0.56694002]), array([0.0063244 , 0.03949686]), 6, array([0.69425226, 0.60643688]), array([0.0063244 , 0.03949686]), 7, array([0.70057666, 0.64593374]), array([0.0063244 , 0.03949686]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.70057666 0.64593374] [0.0063244 0.03949686] new direction: [-0.03371121 0.02153031] reversing there [0.0063244 0.03949686] making one step from [0.70057666 0.64593374] [0.0063244 0.03949686] --> [0.66686545 0.66746405] [-0.03371121 0.02153031] trying new point, [0.66686545 0.66746405] next() call None goals: [('reflect-at', 7, array([0.66686545, 0.66746405]), array([-0.03371121, 0.02153031]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.67527906 0.4879463 ] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.69425226 0.60643688] [0.0063244 0.03949686] -0.3826032159139785 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.4283913100076723 goals: [('bisect', 0, array([0.69425226, 0.60643688]), array([-0.0063244 , -0.03949686]), None, None, None, 6, array([0.65630586, 0.36945572]), array([-0.0063244 , -0.03949686]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.65630586 0.36945572] [0.0063244 0.03949686] -0.4283913100076723 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=77 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 BACKWARD SAMPLING FROM 4 [0.19450023 0.63199687] [-0.03291268 0.02273226] -0.23670484165889305 BACKWARD SAMPLING FROM -4 [0.45780164 0.45013877] [-0.03291268 0.02273226] -0.1358679463834473 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.32615094, 0.54106782]), array([-0.03291268, 0.02273226]), None, None, None, 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3123190738073511 goals: [('bisect', 0, array([0.32615094, 0.54106782]), array([-0.03291268, 0.02273226]), 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 7, array([0.0957622 , 0.70019366]), array([-0.03291268, 0.02273226]), 10, array([0.00297583, 0.76839044]), array([0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4019354437867032 goals: [('bisect', 5, array([0.16158756, 0.65472913]), array([-0.03291268, 0.02273226]), 6, array([0.12867488, 0.67746139]), array([-0.03291268, 0.02273226]), 7, array([0.0957622 , 0.70019366]), array([-0.03291268, 0.02273226]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.0957622 0.70019366] [-0.03291268 0.02273226] new direction: [-0.01742501 -0.03600513] reversing there [-0.03291268 0.02273226] making one step from [0.0957622 0.70019366] [-0.03291268 0.02273226] --> [0.07833719 0.66418853] [-0.01742501 -0.03600513] trying new point, [0.07833719 0.66418853] next() call -0.34004177980724587 goals: [('reflect-at', 7, array([0.07833719, 0.66418853]), array([-0.01742501, -0.03600513]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.039782409475446034 goals: [('bisect', 7, array([0.07833719, 0.66418853]), array([-0.01742501, -0.03600513]), None, None, None, 10, array([0.02606217, 0.55617315]), array([-0.01742501, -0.03600513]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.02606217 0.55617315] [-0.01742501 -0.03600513] -0.039782409475446034 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), None, None, None, 10, array([0.20031226, 0.91622441]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 10, array([0.20031226, 0.91622441]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.20724246552376055 goals: [('bisect', 0, array([0.02606217, 0.55617315]), array([0.01742501, 0.03600513]), 2, array([0.06091219, 0.62818341]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3400417798072463 goals: [('bisect', 2, array([0.06091219, 0.62818341]), array([0.01742501, 0.03600513]), 3, array([0.07833719, 0.66418853]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.07833719, 0.66418853]), array([0.01742501, 0.03600513]), 4, array([0.0957622 , 0.70019366]), array([0.01742501, 0.03600513]), 5, array([0.11318721, 0.73619878]), array([0.01742501, 0.03600513]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.0957622 0.70019366] [0.01742501 0.03600513] new direction: [ 0.03291268 -0.02273226] reversing there [0.01742501 0.03600513] making one step from [0.0957622 0.70019366] [0.01742501 0.03600513] --> [0.12867488 0.67746139] [ 0.03291268 -0.02273226] trying new point, [0.12867488 0.67746139] next() call -0.4019354437867037 goals: [('reflect-at', 4, array([0.12867488, 0.67746139]), array([ 0.03291268, -0.02273226]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.07426929137401193 goals: [('bisect', 4, array([0.12867488, 0.67746139]), array([ 0.03291268, -0.02273226]), None, None, None, 10, array([0.32615094, 0.54106782]), array([ 0.03291268, -0.02273226]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.32615094 0.54106782] [-0.03291268 0.02273226] -0.07426929137401193 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=78 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 BACKWARD SAMPLING FROM 4 [0.05987511 0.56296374] [ 0.02701408 -0.02949982] -0.05134792603041273 BACKWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.18718326659217294 goals: [('bisect', 0, array([0.04818123, 0.68096301]), array([-0.02701408, -0.02949982]), None, None, None, 10, array([0.22195962, 0.38596484]), array([ 0.02701408, -0.02949982]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.22195962 0.38596484] [ 0.02701408 -0.02949982] -0.18718326659217294 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.41050587019281287 goals: [('bisect', 0, array([0.22195962, 0.38596484]), array([-0.02701408, 0.02949982]), None, None, None, 10, array([0.04818123, 0.68096301]), array([0.02701408, 0.02949982]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04818123 0.68096301] [-0.02701408 -0.02949982] -0.4105058701928128 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 sampling between (-1, 0) ---- seed=79 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 BACKWARD SAMPLING FROM 4 [0.57191913 0.61132696] [0.01781275 0.03581488] -0.3184669014578434 BACKWARD SAMPLING FROM -4 [0.42941712 0.32480789] [0.01781275 0.03581488] -0.4758529786384704 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.50066813, 0.46806743]), array([0.01781275, 0.03581488]), None, None, None, 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4445258817169163 goals: [('bisect', 0, array([0.50066813, 0.46806743]), array([0.01781275, 0.03581488]), 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 7, array([0.62535738, 0.71877161]), array([0.01781275, 0.03581488]), 10, array([0.67879563, 0.82621627]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.58973188, 0.64714185]), array([0.01781275, 0.03581488]), 6, array([0.60754463, 0.68295673]), array([0.01781275, 0.03581488]), 7, array([0.62535738, 0.71877161]), array([0.01781275, 0.03581488]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.60754463 0.68295673] [0.01781275 0.03581488] new direction: [-0.03971424 -0.00477279] reversing there [0.01781275 0.03581488] making one step from [0.60754463 0.68295673] [0.01781275 0.03581488] --> [0.56783039 0.67818395] [-0.03971424 -0.00477279] trying new point, [0.56783039 0.67818395] next() call None goals: [('reflect-at', 6, array([0.56783039, 0.67818395]), array([-0.03971424, -0.00477279]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.51848088 0.50388231] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.58973188 0.64714185] [0.01781275 0.03581488] -0.4445258817169163 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.13808040243633282 goals: [('bisect', 0, array([0.58973188, 0.64714185]), array([-0.01781275, -0.03581488]), None, None, None, 5, array([0.50066813, 0.46806743]), array([-0.01781275, -0.03581488]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.50066813 0.46806743] [0.01781275 0.03581488] -0.13808040243633282 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-3, 4) ---- seed=80 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 BACKWARD SAMPLING FROM 3 [0.1516191 0.69490167] [-0.03941662 0.0068066 ] -0.4863274153461391 BACKWARD SAMPLING FROM -4 [0.42753547 0.64725549] [-0.03941662 0.0068066 ] -0.36244551853049845 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), None, None, None, 10, array([0.12429727, 0.74254784]), array([0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 10, array([0.12429727, 0.74254784]), array([0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.46049425869412336 goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), 2, array([0.19103572, 0.68809507]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4863274153461391 goals: [('bisect', 2, array([0.19103572, 0.68809507]), array([-0.03941662, 0.0068066 ]), 3, array([0.1516191 , 0.69490167]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.1516191 , 0.69490167]), array([-0.03941662, 0.0068066 ]), 4, array([0.11220248, 0.70170826]), array([-0.03941662, 0.0068066 ]), 5, array([0.07278585, 0.70851486]), array([-0.03941662, 0.0068066 ]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.11220248 0.70170826] [-0.03941662 0.0068066 ] new direction: [-0.03348855 0.02187504] reversing there [-0.03941662 0.0068066 ] making one step from [0.11220248 0.70170826] [-0.03941662 0.0068066 ] --> [0.07871393 0.7235833 ] [-0.03348855 0.02187504] trying new point, [0.07871393 0.7235833 ] next() call None goals: [('reflect-at', 4, array([0.07871393, 0.7235833 ]), array([-0.03348855, 0.02187504]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.37200718954009426 goals: [('bisect', 0, array([0.26986897, 0.67448187]), array([-0.03941662, 0.0068066 ]), None, None, None, -3, array([0.38811884, 0.65406208]), array([-0.03941662, 0.0068066 ]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.1516191 0.69490167] [-0.03941662 0.0068066 ] -0.4863274153461391 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.41696368821130175 goals: [('bisect', 0, array([0.1516191 , 0.69490167]), array([ 0.03941662, -0.0068066 ]), None, None, None, 3, array([0.26986897, 0.67448187]), array([ 0.03941662, -0.0068066 ]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.38811884 0.65406208] [-0.03941662 0.0068066 ] -0.37200718954009426 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.41696368821130175 goals: [('bisect', 0, array([0.38811884, 0.65406208]), array([ 0.03941662, -0.0068066 ]), None, None, None, -3, array([0.26986897, 0.67448187]), array([ 0.03941662, -0.0068066 ]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.26986897 0.67448187] [-0.03941662 0.0068066 ] -0.41696368821130175 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=81 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 BACKWARD SAMPLING FROM 4 [0.45306473 0.42098814] [0.02672267 0.02976405] -0.18066975294765303 BACKWARD SAMPLING FROM -4 [0.39239943 0.49651665] [-0.00924508 -0.03891694] -0.07714032966931968 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), None, None, None, 10, array([0.26296833, 0.04832056]), array([-0.00924508, 0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 5, array([0.30919372, 0.14626416]), array([-0.00924508, -0.03891694]), 10, array([0.26296833, 0.04832056]), array([-0.00924508, 0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 2, array([0.33692896, 0.26301499]), array([-0.00924508, -0.03891694]), 5, array([0.30919372, 0.14626416]), array([-0.00924508, -0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.35541912, 0.34084888]), array([-0.00924508, -0.03891694]), 1, array([0.34617404, 0.30193193]), array([-0.00924508, -0.03891694]), 2, array([0.33692896, 0.26301499]), array([-0.00924508, -0.03891694]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.34617404 0.30193193] [-0.00924508 -0.03891694] new direction: [0.02672267 0.02976405] reversing there [-0.00924508 -0.03891694] making one step from [0.34617404 0.30193193] [-0.00924508 -0.03891694] --> [0.37289671 0.33169598] [0.02672267 0.02976405] trying new point, [0.37289671 0.33169598] next() call -0.4236039997490474 goals: [('reflect-at', 1, array([0.37289671, 0.33169598]), array([0.02672267, 0.02976405]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3120636527905234 goals: [('bisect', 1, array([0.37289671, 0.33169598]), array([0.02672267, 0.02976405]), None, None, None, 10, array([0.61340077, 0.59957245]), array([0.02672267, 0.02976405]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.61340077 0.59957245] [0.02672267 0.02976405] -0.3120636527905234 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.61340077, 0.59957245]), array([-0.02672267, -0.02976405]), None, None, None, 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.14541481093575562 goals: [('bisect', 0, array([0.61340077, 0.59957245]), array([-0.02672267, -0.02976405]), 5, array([0.4797874 , 0.45075219]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2387862650871675 goals: [('bisect', 5, array([0.4797874 , 0.45075219]), array([-0.02672267, -0.02976405]), 7, array([0.42634206, 0.39122409]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3197643473542989 goals: [('bisect', 7, array([0.42634206, 0.39122409]), array([-0.02672267, -0.02976405]), 8, array([0.39961938, 0.36146004]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4236039997490474 goals: [('bisect', 8, array([0.39961938, 0.36146004]), array([-0.02672267, -0.02976405]), 9, array([0.37289671, 0.33169598]), array([-0.02672267, -0.02976405]), 10, array([0.34617404, 0.30193193]), array([-0.02672267, -0.02976405]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.34617404 0.30193193] [-0.02672267 -0.02976405] new direction: [0.00924508 0.03891694] reversing there [-0.02672267 -0.02976405] making one step from [0.34617404 0.30193193] [-0.02672267 -0.02976405] --> [0.35541912 0.34084888] [0.00924508 0.03891694] trying new point, [0.35541912 0.34084888] next() call -0.37977487528894 goals: [('reflect-at', 10, array([0.35541912, 0.34084888]), array([0.00924508, 0.03891694]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.35541912 0.34084888] [-0.00924508 -0.03891694] -0.3797748752889402 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-3, 4) ---- seed=82 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 BACKWARD SAMPLING FROM 4 [0.30917537 0.48287406] [ 0.00848742 -0.03908918] -0.051460926903102756 BACKWARD SAMPLING FROM -1 [0.26673825 0.67831994] [ 0.00848742 -0.03908918] -0.433049641425479 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.27522567, 0.63923076]), array([ 0.00848742, -0.03908918]), None, None, None, 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.08995656502013205 goals: [('bisect', 0, array([0.27522567, 0.63923076]), array([ 0.00848742, -0.03908918]), 5, array([0.31766279, 0.44378488]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.2817612222756952 goals: [('bisect', 5, array([0.31766279, 0.44378488]), array([ 0.00848742, -0.03908918]), 7, array([0.33463764, 0.36560653]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4350702414142291 goals: [('bisect', 7, array([0.33463764, 0.36560653]), array([ 0.00848742, -0.03908918]), 8, array([0.34312507, 0.32651736]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.34312507, 0.32651736]), array([ 0.00848742, -0.03908918]), 9, array([0.35161249, 0.28742818]), array([ 0.00848742, -0.03908918]), 10, array([0.36009991, 0.24833901]), array([ 0.00848742, -0.03908918]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.35161249 0.28742818] [ 0.00848742 -0.03908918] new direction: [-0.01853685 0.03544552] reversing there [ 0.00848742 -0.03908918] making one step from [0.35161249 0.28742818] [ 0.00848742 -0.03908918] --> [0.33307564 0.32287371] [-0.01853685 0.03544552] trying new point, [0.33307564 0.32287371] next() call -0.4476412362297438 goals: [('reflect-at', 9, array([0.33307564, 0.32287371]), array([-0.01853685, 0.03544552]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3003853287533051 goals: [('bisect', 9, array([0.33307564, 0.32287371]), array([-0.01853685, 0.03544552]), None, None, None, 10, array([0.31453879, 0.35831923]), array([-0.01853685, 0.03544552]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31453879 0.35831923] [-0.01853685 0.03544552] -0.3003853287533051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), None, None, None, 10, array([0.4999073 , 0.00386399]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 5, array([0.40722304, 0.18109161]), array([ 0.01853685, -0.03544552]), 10, array([0.4999073 , 0.00386399]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 2, array([0.35161249, 0.28742818]), array([ 0.01853685, -0.03544552]), 5, array([0.40722304, 0.18109161]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.4476412362297438 goals: [('bisect', 0, array([0.31453879, 0.35831923]), array([ 0.01853685, -0.03544552]), 1, array([0.33307564, 0.32287371]), array([ 0.01853685, -0.03544552]), 2, array([0.35161249, 0.28742818]), array([ 0.01853685, -0.03544552]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.35161249 0.28742818] [ 0.01853685 -0.03544552] new direction: [-0.00848742 0.03908918] reversing there [ 0.01853685 -0.03544552] making one step from [0.35161249 0.28742818] [ 0.01853685 -0.03544552] --> [0.34312507 0.32651736] [-0.00848742 0.03908918] trying new point, [0.34312507 0.32651736] next() call -0.43507024141422884 goals: [('reflect-at', 2, array([0.34312507, 0.32651736]), array([-0.00848742, 0.03908918]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2801896445066674 goals: [('bisect', 2, array([0.34312507, 0.32651736]), array([-0.00848742, 0.03908918]), None, None, None, 10, array([0.27522567, 0.63923076]), array([-0.00848742, 0.03908918]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.27522567 0.63923076] [ 0.00848742 -0.03908918] -0.2801896445066674 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-1, 2) ---- seed=83 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 BACKWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 BACKWARD SAMPLING FROM -4 [0.38697777 0.59042374] [-0.03248384 0.02334096] -0.1770815538786539 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), None, None, None, 10, array([0.06779592, 0.91719719]), array([0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 5, array([0.09462325, 0.80049239]), array([-0.03248384, 0.02334096]), 10, array([0.06779592, 0.91719719]), array([0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 2, array([0.19207476, 0.73046951]), array([-0.03248384, 0.02334096]), 5, array([0.09462325, 0.80049239]), array([-0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), 1, array([0.22455859, 0.70712854]), array([-0.03248384, 0.02334096]), 2, array([0.19207476, 0.73046951]), array([-0.03248384, 0.02334096]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.22455859 0.70712854] [-0.03248384 0.02334096] new direction: [-0.03398668 0.02109279] reversing there [-0.03248384 0.02334096] making one step from [0.22455859 0.70712854] [-0.03248384 0.02334096] --> [0.19057191 0.72822133] [-0.03398668 0.02109279] trying new point, [0.19057191 0.72822133] next() call None goals: [('reflect-at', 1, array([0.19057191, 0.72822133]), array([-0.03398668, 0.02109279]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 0... 10 steps to do at 0 -> [from 1, delta=10] targeting -9. goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.15955218049839826 goals: [('bisect', 0, array([0.25704243, 0.68378758]), array([-0.03248384, 0.02334096]), None, None, None, -9, array([0.54939694, 0.47371893]), array([-0.03248384, 0.02334096]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -9 [0.54939694 0.47371893] [-0.03248384 0.02334096] -0.15955218049839826 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -9)] not done yet, continue expanding to -9... goals: [('expand-to', -9), ('sample-at', -9)] next() call -0.4552588508048801 goals: [('bisect', 0, array([0.54939694, 0.47371893]), array([ 0.03248384, -0.02334096]), None, None, None, -9, array([0.25704243, 0.68378758]), array([ 0.03248384, -0.02334096]), -1), ('sample-at', -9)] bisecting ... 0 None -9 successfully went all the way in one jump! goals: [('sample-at', -9)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.25704243 0.68378758] [-0.03248384 0.02334096] -0.4552588508048801 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 sampling between (0, 1) ---- seed=84 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 BACKWARD SAMPLING FROM 4 [0.0588575 0.31191846] [-0.03418324 0.02077272] -0.4439154472871768 BACKWARD SAMPLING FROM -4 [0.18512274 0.4493389 ] [-0.03477044 -0.01977415] -0.049217056098525905 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), None, None, None, 10, array([0.30166336, 0.17250086]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 10, array([0.30166336, 0.17250086]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.35858253304774335 goals: [('bisect', 0, array([0.04604099, 0.37024232]), array([-0.03477044, -0.01977415]), 2, array([0.02349988, 0.33069403]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.4485888583524455 goals: [('bisect', 2, array([0.02349988, 0.33069403]), array([ 0.03477044, -0.01977415]), 3, array([0.05827031, 0.31091988]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.05827031, 0.31091988]), array([ 0.03477044, -0.01977415]), 4, array([0.09304075, 0.29114574]), array([ 0.03477044, -0.01977415]), 5, array([0.12781118, 0.27137159]), array([ 0.03477044, -0.01977415]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.09304075 0.29114574] [ 0.03477044 -0.01977415] new direction: [-0.03418324 0.02077272] reversing there [ 0.03477044 -0.01977415] making one step from [0.09304075 0.29114574] [ 0.03477044 -0.01977415] --> [0.0588575 0.31191846] [-0.03418324 0.02077272] trying new point, [0.0588575 0.31191846] next() call -0.4439154472871768 goals: [('reflect-at', 4, array([0.0588575 , 0.31191846]), array([-0.03418324, 0.02077272]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.061009567312068635 goals: [('bisect', 4, array([0.0588575 , 0.31191846]), array([-0.03418324, 0.02077272]), None, None, None, 10, array([0.14624196, 0.43655477]), array([0.03418324, 0.02077272]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.14624196 0.43655477] [0.03418324 0.02077272] -0.061009567312068635 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.14624196, 0.43655477]), array([-0.03418324, -0.02077272]), None, None, None, 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.35020744828671635 goals: [('bisect', 0, array([0.14624196, 0.43655477]), array([-0.03418324, -0.02077272]), 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 7, array([0.09304075, 0.29114574]), array([ 0.03418324, -0.02077272]), 10, array([0.19559048, 0.22882758]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4439154472871768 goals: [('bisect', 5, array([0.02467426, 0.33269117]), array([ 0.03418324, -0.02077272]), 6, array([0.0588575 , 0.31191846]), array([ 0.03418324, -0.02077272]), 7, array([0.09304075, 0.29114574]), array([ 0.03418324, -0.02077272]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.09304075 0.29114574] [ 0.03418324 -0.02077272] new direction: [-0.03477044 0.01977415] reversing there [ 0.03418324 -0.02077272] making one step from [0.09304075 0.29114574] [ 0.03418324 -0.02077272] --> [0.05827031 0.31091988] [-0.03477044 0.01977415] trying new point, [0.05827031 0.31091988] next() call -0.4485888583524455 goals: [('reflect-at', 7, array([0.05827031, 0.31091988]), array([-0.03477044, 0.01977415]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.2115230931353383 goals: [('bisect', 7, array([0.05827031, 0.31091988]), array([-0.03477044, 0.01977415]), None, None, None, 10, array([0.04604099, 0.37024232]), array([0.03477044, 0.01977415]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.04604099 0.37024232] [-0.03477044 -0.01977415] -0.2115230931353383 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -6..1 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-6, 1) ---- seed=85 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 BACKWARD SAMPLING FROM 4 [0.77064828 0.56388562] [0.03756862 0.01373314] -0.3479665415854334 BACKWARD SAMPLING FROM -4 [0.47009935 0.45402052] [0.03756862 0.01373314] -0.13692311038869834 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.62037381, 0.50895307]), array([0.03756862, 0.01373314]), None, None, None, 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4019156709890521 goals: [('bisect', 0, array([0.62037381, 0.50895307]), array([0.03756862, 0.01373314]), 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 7, array([0.88335413, 0.60508503]), array([0.03756862, 0.01373314]), 10, array([0.99605998, 0.64628445]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.4619911782824545 goals: [('bisect', 5, array([0.8082169 , 0.57761876]), array([0.03756862, 0.01373314]), 6, array([0.84578551, 0.5913519 ]), array([0.03756862, 0.01373314]), 7, array([0.88335413, 0.60508503]), array([0.03756862, 0.01373314]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.88335413 0.60508503] [0.03756862 0.01373314] new direction: [-0.01499532 -0.03708288] reversing there [0.03756862 0.01373314] making one step from [0.88335413 0.60508503] [0.03756862 0.01373314] --> [0.86835881 0.56800215] [-0.01499532 -0.03708288] trying new point, [0.86835881 0.56800215] next() call -0.43482716294154355 goals: [('reflect-at', 7, array([0.86835881, 0.56800215]), array([-0.01499532, -0.03708288]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3623496671674091 goals: [('bisect', 7, array([0.86835881, 0.56800215]), array([-0.01499532, -0.03708288]), None, None, None, 10, array([0.82337284, 0.4567535 ]), array([-0.01499532, -0.03708288]), 1), ('sample-at', 10)] bisecting ... 7 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.82337284 0.4567535 ] [-0.01499532 -0.03708288] -0.3623496671674091 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), None, None, None, 10, array([0.97332606, 0.82758234]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 10, array([0.97332606, 0.82758234]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.37606463005047236 goals: [('bisect', 0, array([0.82337284, 0.4567535 ]), array([0.01499532, 0.03708288]), 2, array([0.85336348, 0.53091927]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.43482716294154355 goals: [('bisect', 2, array([0.85336348, 0.53091927]), array([0.01499532, 0.03708288]), 3, array([0.86835881, 0.56800215]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.86835881, 0.56800215]), array([0.01499532, 0.03708288]), 4, array([0.88335413, 0.60508503]), array([0.01499532, 0.03708288]), 5, array([0.89834945, 0.64216792]), array([0.01499532, 0.03708288]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.88335413 0.60508503] [0.01499532 0.03708288] new direction: [-0.03756862 -0.01373314] reversing there [0.01499532 0.03708288] making one step from [0.88335413 0.60508503] [0.01499532 0.03708288] --> [0.84578551 0.5913519 ] [-0.03756862 -0.01373314] trying new point, [0.84578551 0.5913519 ] next() call -0.4619911782824549 goals: [('reflect-at', 4, array([0.84578551, 0.5913519 ]), array([-0.03756862, -0.01373314]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19343380286879602 goals: [('bisect', 4, array([0.84578551, 0.5913519 ]), array([-0.03756862, -0.01373314]), None, None, None, 10, array([0.62037381, 0.50895307]), array([-0.03756862, -0.01373314]), 1), ('sample-at', 10)] bisecting ... 4 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.62037381 0.50895307] [0.03756862 0.01373314] -0.19343380286879597 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-4, 3) ---- seed=86 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 BACKWARD SAMPLING FROM 4 [0.22997871 0.54410506] [ 0.00068648 -0.03999411] -0.05076080590070252 BACKWARD SAMPLING FROM -4 [0.22820267 0.50408385] [-0.00019397 0.03999953] -0.026246700683537846 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), None, None, None, 10, array([0.22548702, 0.93592274]), array([-0.00019397, -0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 5, array([0.22645689, 0.86407961]), array([-0.00019397, 0.03999953]), 10, array([0.22548702, 0.93592274]), array([-0.00019397, -0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 2, array([0.22703882, 0.74408102]), array([-0.00019397, 0.03999953]), 5, array([0.22645689, 0.86407961]), array([-0.00019397, 0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.22742677, 0.66408196]), array([-0.00019397, 0.03999953]), 1, array([0.22723279, 0.70408149]), array([-0.00019397, 0.03999953]), 2, array([0.22703882, 0.74408102]), array([-0.00019397, 0.03999953]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.22723279 0.70408149] [-0.00019397 0.03999953] new direction: [ 0.00068648 -0.03999411] reversing there [-0.00019397 0.03999953] making one step from [0.22723279 0.70408149] [-0.00019397 0.03999953] --> [0.22791927 0.66408738] [ 0.00068648 -0.03999411] trying new point, [0.22791927 0.66408738] next() call -0.362531970289674 goals: [('reflect-at', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), None, None, None, 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.026814464192513657 goals: [('bisect', 1, array([0.22791927, 0.66408738]), array([ 0.00068648, -0.03999411]), 5, array([0.23066519, 0.50411095]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.09888785040833842 goals: [('bisect', 5, array([0.23066519, 0.50411095]), array([ 0.00068648, -0.03999411]), 7, array([0.23203815, 0.42412273]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.19490757833235206 goals: [('bisect', 7, array([0.23203815, 0.42412273]), array([ 0.00068648, -0.03999411]), 8, array([0.23272463, 0.38412862]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.33091599613376643 goals: [('bisect', 8, array([0.23272463, 0.38412862]), array([ 0.00068648, -0.03999411]), 9, array([0.23341111, 0.34413451]), array([ 0.00068648, -0.03999411]), 10, array([0.23409759, 0.3041404 ]), array([ 0.00068648, -0.03999411]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.23409759 0.3041404 ] [ 0.00068648 -0.03999411] new direction: [0.03260973 0.02316475] reversing there [ 0.00068648 -0.03999411] making one step from [0.23409759 0.3041404 ] [ 0.00068648 -0.03999411] --> [0.26670732 0.32730515] [0.03260973 0.02316475] trying new point, [0.26670732 0.32730515] next() call -0.4083602779624293 goals: [('reflect-at', 10, array([0.26670732, 0.32730515]), array([0.03260973, 0.02316475]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.26670732 0.32730515] [0.03260973 0.02316475] -0.4083602779624293 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), None, None, None, 10, array([0.05938997, 0.09565768]), array([ 0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 5, array([0.10365867, 0.21148142]), array([-0.03260973, -0.02316475]), 10, array([0.05938997, 0.09565768]), array([ 0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 2, array([0.20148786, 0.28097566]), array([-0.03260973, -0.02316475]), 5, array([0.10365867, 0.21148142]), array([-0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.26670732, 0.32730515]), array([-0.03260973, -0.02316475]), 1, array([0.23409759, 0.3041404 ]), array([-0.03260973, -0.02316475]), 2, array([0.20148786, 0.28097566]), array([-0.03260973, -0.02316475]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.23409759 0.3041404 ] [-0.03260973 -0.02316475] new direction: [-0.00068648 0.03999411] reversing there [-0.03260973 -0.02316475] making one step from [0.23409759 0.3041404 ] [-0.03260973 -0.02316475] --> [0.23341111 0.34413451] [-0.00068648 0.03999411] trying new point, [0.23341111 0.34413451] next() call -0.33091599613376643 goals: [('reflect-at', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), None, None, None, 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 None 10 continue bisect at 5 next() call -0.026814464192513682 goals: [('bisect', 1, array([0.23341111, 0.34413451]), array([-0.00068648, 0.03999411]), 5, array([0.23066519, 0.50411095]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 1 5 10 continue bisect at 7 next() call -0.11469583748629265 goals: [('bisect', 5, array([0.23066519, 0.50411095]), array([-0.00068648, 0.03999411]), 7, array([0.22929223, 0.58409917]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.21861955894928337 goals: [('bisect', 7, array([0.22929223, 0.58409917]), array([-0.00068648, 0.03999411]), 8, array([0.22860575, 0.62409328]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.3625319702896749 goals: [('bisect', 8, array([0.22860575, 0.62409328]), array([-0.00068648, 0.03999411]), 9, array([0.22791927, 0.66408738]), array([-0.00068648, 0.03999411]), 10, array([0.22723279, 0.70408149]), array([-0.00068648, 0.03999411]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.22723279 0.70408149] [-0.00068648 0.03999411] new direction: [ 0.00019397 -0.03999953] reversing there [-0.00068648 0.03999411] making one step from [0.22723279 0.70408149] [-0.00068648 0.03999411] --> [0.22742677 0.66408196] [ 0.00019397 -0.03999953] trying new point, [0.22742677 0.66408196] next() call -0.36239760340404076 goals: [('reflect-at', 10, array([0.22742677, 0.66408196]), array([ 0.00019397, -0.03999953]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.22742677 0.66408196] [-0.00019397 0.03999953] -0.36239760340403976 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 sampling between (0, 3) ---- seed=87 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 BACKWARD SAMPLING FROM 4 [0.3391376 0.32791809] [ 0.03905665 -0.00863586] -0.42765944711127135 BACKWARD SAMPLING FROM -4 [0.02668439 0.39700497] [ 0.03905665 -0.00863586] -0.13295572584667534 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.18291099, 0.36246153]), array([ 0.03905665, -0.00863586]), None, None, None, 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.4797518449351289 goals: [('bisect', 0, array([0.18291099, 0.36246153]), array([ 0.03905665, -0.00863586]), 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 7, array([0.45630755, 0.30201051]), array([ 0.03905665, -0.00863586]), 10, array([0.5734775 , 0.27610293]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([ 0.03905665, -0.00863586]), 6, array([0.4172509 , 0.31064637]), array([ 0.03905665, -0.00863586]), 7, array([0.45630755, 0.30201051]), array([ 0.03905665, -0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.4172509 0.31064637] [ 0.03905665 -0.00863586] new direction: [-0.03724409 0.01459033] reversing there [ 0.03905665 -0.00863586] making one step from [0.4172509 0.31064637] [ 0.03905665 -0.00863586] --> [0.3800068 0.3252367] [-0.03724409 0.01459033] trying new point, [0.3800068 0.3252367] next() call -0.45398023973187507 goals: [('reflect-at', 6, array([0.3800068, 0.3252367]), array([-0.03724409, 0.01459033]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.19605535574242375 goals: [('bisect', 6, array([0.3800068, 0.3252367]), array([-0.03724409, 0.01459033]), None, None, None, 10, array([0.23103043, 0.383598 ]), array([-0.03724409, 0.01459033]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.23103043 0.383598 ] [-0.03724409 0.01459033] -0.19605535574242375 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), None, None, None, 10, array([0.60347136, 0.23769474]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 10, array([0.60347136, 0.23769474]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.3115996729727667 goals: [('bisect', 0, array([0.23103043, 0.383598 ]), array([ 0.03724409, -0.01459033]), 2, array([0.30551862, 0.35441735]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.37943542516122514 goals: [('bisect', 2, array([0.30551862, 0.35441735]), array([ 0.03724409, -0.01459033]), 3, array([0.34276271, 0.33982702]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.45398023973187507 goals: [('bisect', 3, array([0.34276271, 0.33982702]), array([ 0.03724409, -0.01459033]), 4, array([0.3800068, 0.3252367]), array([ 0.03724409, -0.01459033]), 5, array([0.4172509 , 0.31064637]), array([ 0.03724409, -0.01459033]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.4172509 0.31064637] [ 0.03724409 -0.01459033] new direction: [-0.03905665 0.00863586] reversing there [ 0.03724409 -0.01459033] making one step from [0.4172509 0.31064637] [ 0.03724409 -0.01459033] --> [0.37819425 0.31928223] [-0.03905665 0.00863586] trying new point, [0.37819425 0.31928223] next() call -0.4797518449351292 goals: [('reflect-at', 5, array([0.37819425, 0.31928223]), array([-0.03905665, 0.00863586]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.25318859507313635 goals: [('bisect', 5, array([0.37819425, 0.31928223]), array([-0.03905665, 0.00863586]), None, None, None, 10, array([0.18291099, 0.36246153]), array([-0.03905665, 0.00863586]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.18291099 0.36246153] [ 0.03905665 -0.00863586] -0.25318859507313624 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=88 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 BACKWARD SAMPLING FROM 3 [0.66567418 0.38852612] [ 0.00604104 -0.03954119] -0.3768913954170837 BACKWARD SAMPLING FROM -3 [0.62942792 0.62577326] [ 0.00604104 -0.03954119] -0.39582616718099384 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), None, None, None, 10, array([0.70796149, 0.11173778]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 10, array([0.70796149, 0.11173778]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.28223684347738265 goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), 2, array([0.65963314, 0.42806731]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.3768913954170836 goals: [('bisect', 2, array([0.65963314, 0.42806731]), array([ 0.00604104, -0.03954119]), 3, array([0.66567418, 0.38852612]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.66567418, 0.38852612]), array([ 0.00604104, -0.03954119]), 4, array([0.67171523, 0.34898492]), array([ 0.00604104, -0.03954119]), 5, array([0.67775627, 0.30944373]), array([ 0.00604104, -0.03954119]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.67171523 0.34898492] [ 0.00604104 -0.03954119] new direction: [-0.03138488 -0.02479897] reversing there [ 0.00604104 -0.03954119] making one step from [0.67171523 0.34898492] [ 0.00604104 -0.03954119] --> [0.64033034 0.32418595] [-0.03138488 -0.02479897] trying new point, [0.64033034 0.32418595] next() call None goals: [('reflect-at', 4, array([0.64033034, 0.32418595]), array([-0.03138488, -0.02479897]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.3958261671809942 goals: [('bisect', 0, array([0.64755105, 0.50714969]), array([ 0.00604104, -0.03954119]), None, None, None, -3, array([0.62942792, 0.62577326]), array([ 0.00604104, -0.03954119]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.66567418 0.38852612] [ 0.00604104 -0.03954119] -0.3768913954170836 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.21030015627840412 goals: [('bisect', 0, array([0.66567418, 0.38852612]), array([-0.00604104, 0.03954119]), None, None, None, 3, array([0.64755105, 0.50714969]), array([-0.00604104, 0.03954119]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.62942792 0.62577326] [ 0.00604104 -0.03954119] -0.3958261671809942 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.21030015627840412 goals: [('bisect', 0, array([0.62942792, 0.62577326]), array([-0.00604104, 0.03954119]), None, None, None, -3, array([0.64755105, 0.50714969]), array([-0.00604104, 0.03954119]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.64755105 0.50714969] [ 0.00604104 -0.03954119] -0.21030015627840412 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (0, 3) ---- seed=89 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 BACKWARD SAMPLING FROM 4 [0.20913614 0.33057099] [ 0.01413523 -0.03741918] -0.38069631886308075 BACKWARD SAMPLING FROM -4 [0.09605432 0.62992447] [ 0.01413523 -0.03741918] -0.21561781084839587 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), None, None, None, 10, array([0.29394749, 0.10605589]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 10, array([0.29394749, 0.10605589]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.12819855855898762 goals: [('bisect', 0, array([0.15259523, 0.48024773]), array([ 0.01413523, -0.03741918]), 2, array([0.18086568, 0.40540936]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.23684509426933237 goals: [('bisect', 2, array([0.18086568, 0.40540936]), array([ 0.01413523, -0.03741918]), 3, array([0.19500091, 0.36799018]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.38069631886308075 goals: [('bisect', 3, array([0.19500091, 0.36799018]), array([ 0.01413523, -0.03741918]), 4, array([0.20913614, 0.33057099]), array([ 0.01413523, -0.03741918]), 5, array([0.22327136, 0.29315181]), array([ 0.01413523, -0.03741918]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.22327136 0.29315181] [ 0.01413523 -0.03741918] new direction: [-0.03612676 0.0171714 ] reversing there [ 0.01413523 -0.03741918] making one step from [0.22327136 0.29315181] [ 0.01413523 -0.03741918] --> [0.1871446 0.31032321] [-0.03612676 0.0171714 ] trying new point, [0.1871446 0.31032321] next() call -0.46722761628857196 goals: [('reflect-at', 5, array([0.1871446 , 0.31032321]), array([-0.03612676, 0.0171714 ]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.1347530535350935 goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([-0.03612676, 0.0171714 ]), None, None, None, 10, array([0.00651078, 0.39618021]), array([-0.03612676, 0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.00651078 0.39618021] [-0.03612676 0.0171714 ] -0.1347530535350935 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.00651078, 0.39618021]), array([ 0.03612676, -0.0171714 ]), None, None, None, 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.46722761628857196 goals: [('bisect', 0, array([0.00651078, 0.39618021]), array([ 0.03612676, -0.0171714 ]), 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 7, array([0.25939812, 0.27598041]), array([ 0.03612676, -0.0171714 ]), 10, array([0.36777841, 0.22446621]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.1871446 , 0.31032321]), array([ 0.03612676, -0.0171714 ]), 6, array([0.22327136, 0.29315181]), array([ 0.03612676, -0.0171714 ]), 7, array([0.25939812, 0.27598041]), array([ 0.03612676, -0.0171714 ]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.22327136 0.29315181] [ 0.03612676 -0.0171714 ] new direction: [-0.01413523 0.03741918] reversing there [ 0.03612676 -0.0171714 ] making one step from [0.22327136 0.29315181] [ 0.03612676 -0.0171714 ] --> [0.20913614 0.33057099] [-0.01413523 0.03741918] trying new point, [0.20913614 0.33057099] next() call -0.3806963188630805 goals: [('reflect-at', 6, array([0.20913614, 0.33057099]), array([-0.01413523, 0.03741918]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.016519553788509028 goals: [('bisect', 6, array([0.20913614, 0.33057099]), array([-0.01413523, 0.03741918]), None, None, None, 10, array([0.15259523, 0.48024773]), array([-0.01413523, 0.03741918]), 1), ('sample-at', 10)] bisecting ... 6 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.15259523 0.48024773] [ 0.01413523 -0.03741918] -0.016519553788509094 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (-1, 2) ---- seed=90 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 BACKWARD SAMPLING FROM 4 [0.17606336 0.66988726] [-0.03949695 0.00632385] -0.37627016306758043 BACKWARD SAMPLING FROM -4 [0.49203895 0.61929648] [-0.03949695 0.00632385] -0.2989468009164582 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.33405116, 0.64459187]), array([-0.03949695, 0.00632385]), None, None, None, 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.3974546157438025 goals: [('bisect', 0, array([0.33405116, 0.64459187]), array([-0.03949695, 0.00632385]), 5, array([0.13656641, 0.67621111]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.4475028760344699 goals: [('bisect', 5, array([0.13656641, 0.67621111]), array([-0.03949695, 0.00632385]), 7, array([0.05757252, 0.6888588 ]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.4763666836489148 goals: [('bisect', 7, array([0.05757252, 0.6888588 ]), array([-0.03949695, 0.00632385]), 8, array([0.01807557, 0.69518265]), array([-0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.01807557, 0.69518265]), array([-0.03949695, 0.00632385]), 9, array([0.02142138, 0.70150649]), array([0.03949695, 0.00632385]), 10, array([0.06091833, 0.70783034]), array([0.03949695, 0.00632385]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.02142138 0.70150649] [0.03949695 0.00632385] new direction: [-0.02643714 0.03001795] reversing there [0.03949695 0.00632385] making one step from [0.02142138 0.70150649] [0.03949695 0.00632385] --> [0.00501576 0.73152444] [0.02643714 0.03001795] trying new point, [0.00501576 0.73152444] next() call None goals: [('reflect-at', 9, array([0.00501576, 0.73152444]), array([0.02643714, 0.03001795]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 8... 2 steps to do at 8 -> [from 9, delta=2] targeting 7. goals: [('sample-at', 7)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 8 [0.01807557 0.69518265] [-0.03949695 0.00632385] -0.4763666836489148 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 8)] not done yet, continue expanding to 8... goals: [('expand-to', 8), ('sample-at', 8)] next() call -0.31713020215676097 goals: [('bisect', 0, array([0.01807557, 0.69518265]), array([ 0.03949695, -0.00632385]), None, None, None, 8, array([0.33405116, 0.64459187]), array([ 0.03949695, -0.00632385]), 1), ('sample-at', 8)] bisecting ... 0 None 8 successfully went all the way in one jump! goals: [('sample-at', 8)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.33405116 0.64459187] [-0.03949695 0.00632385] -0.31713020215676097 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd new NUTS range: -11..4 NUTS step: tree depth 4, rwd NUTS step: tree depth 4, rwd sampling between (-11, 4) ---- seed=91 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 BACKWARD SAMPLING FROM 4 [0.04151464 0.31624266] [-0.03987224 -0.00319445] -0.42294623725634856 BACKWARD SAMPLING FROM -4 [0.36049255 0.34179827] [-0.03987224 -0.00319445] -0.37782476710495483 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.2010036 , 0.32902047]), array([-0.03987224, -0.00319445]), None, None, None, 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.43688850948485125 goals: [('bisect', 0, array([0.2010036 , 0.32902047]), array([-0.03987224, -0.00319445]), 5, array([0.0016424 , 0.31304821]), array([-0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.47030777958157655 goals: [('bisect', 5, array([0.0016424 , 0.31304821]), array([-0.03987224, -0.00319445]), 7, array([0.07810208, 0.3066593 ]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.48978477744979876 goals: [('bisect', 7, array([0.07810208, 0.3066593 ]), array([ 0.03987224, -0.00319445]), 8, array([0.11797432, 0.30346485]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call None goals: [('bisect', 8, array([0.11797432, 0.30346485]), array([ 0.03987224, -0.00319445]), 9, array([0.15784656, 0.3002704 ]), array([ 0.03987224, -0.00319445]), 10, array([0.1977188 , 0.29707595]), array([ 0.03987224, -0.00319445]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 9 [0.15784656 0.3002704 ] [ 0.03987224 -0.00319445] new direction: [0.02906527 0.02748108] reversing there [ 0.03987224 -0.00319445] making one step from [0.15784656 0.3002704 ] [ 0.03987224 -0.00319445] --> [0.18691183 0.32775148] [0.02906527 0.02748108] trying new point, [0.18691183 0.32775148] next() call -0.38833742025683327 goals: [('reflect-at', 9, array([0.18691183, 0.32775148]), array([0.02906527, 0.02748108]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.28529319268566455 goals: [('bisect', 9, array([0.18691183, 0.32775148]), array([0.02906527, 0.02748108]), None, None, None, 10, array([0.21597711, 0.35523256]), array([0.02906527, 0.02748108]), 1), ('sample-at', 10)] bisecting ... 9 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.21597711 0.35523256] [0.02906527 0.02748108] -0.28529319268566455 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), None, None, None, 10, array([0.07467563, 0.08042175]), array([ 0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 5, array([0.07065074, 0.21782716]), array([-0.02906527, -0.02748108]), 10, array([0.07467563, 0.08042175]), array([ 0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 2, array([0.15784656, 0.3002704 ]), array([-0.02906527, -0.02748108]), 5, array([0.07065074, 0.21782716]), array([-0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call -0.38833742025683327 goals: [('bisect', 0, array([0.21597711, 0.35523256]), array([-0.02906527, -0.02748108]), 1, array([0.18691183, 0.32775148]), array([-0.02906527, -0.02748108]), 2, array([0.15784656, 0.3002704 ]), array([-0.02906527, -0.02748108]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 2 [0.15784656 0.3002704 ] [-0.02906527 -0.02748108] new direction: [-0.03987224 0.00319445] reversing there [-0.02906527 -0.02748108] making one step from [0.15784656 0.3002704 ] [-0.02906527 -0.02748108] --> [0.11797432 0.30346485] [-0.03987224 0.00319445] trying new point, [0.11797432 0.30346485] next() call -0.4897847774497991 goals: [('reflect-at', 2, array([0.11797432, 0.30346485]), array([-0.03987224, 0.00319445]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.3856262338080673 goals: [('bisect', 2, array([0.11797432, 0.30346485]), array([-0.03987224, 0.00319445]), None, None, None, 10, array([0.2010036 , 0.32902047]), array([0.03987224, 0.00319445]), 1), ('sample-at', 10)] bisecting ... 2 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.2010036 0.32902047] [-0.03987224 -0.00319445] -0.38562623380806715 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=92 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 BACKWARD SAMPLING FROM 4 [0.42298615 0.31887913] [-0.0004355 -0.03999763] -0.49951826010720873 BACKWARD SAMPLING FROM -4 [0.42647012 0.63886016] [-0.0004355 -0.03999763] -0.3319651929892012 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), None, None, None, 10, array([0.42037317, 0.07889335]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 10, array([0.42037317, 0.07889335]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.21765730389482751 goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), 2, array([0.42385714, 0.39887439]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.33859005788161145 goals: [('bisect', 2, array([0.42385714, 0.39887439]), array([-0.0004355 , -0.03999763]), 3, array([0.42342164, 0.35887676]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call -0.49951826010720873 goals: [('bisect', 3, array([0.42342164, 0.35887676]), array([-0.0004355 , -0.03999763]), 4, array([0.42298615, 0.31887913]), array([-0.0004355 , -0.03999763]), 5, array([0.42255065, 0.2788815 ]), array([-0.0004355 , -0.03999763]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 5 [0.42255065 0.2788815 ] [-0.0004355 -0.03999763] new direction: [-0.03548521 0.01846077] reversing there [-0.0004355 -0.03999763] making one step from [0.42255065 0.2788815 ] [-0.0004355 -0.03999763] --> [0.38706544 0.29734227] [-0.03548521 0.01846077] trying new point, [0.38706544 0.29734227] next() call None goals: [('reflect-at', 5, array([0.38706544, 0.29734227]), array([-0.03548521, 0.01846077]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 4... 6 steps to do at 4 -> [from 5, delta=6] targeting -1. goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.09483173136735507 goals: [('bisect', 0, array([0.42472813, 0.47886965]), array([-0.0004355 , -0.03999763]), None, None, None, -1, array([0.42516363, 0.51886728]), array([-0.0004355 , -0.03999763]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 4 [0.42298615 0.31887913] [-0.0004355 -0.03999763] -0.49951826010720873 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 4)] not done yet, continue expanding to 4... goals: [('expand-to', 4), ('sample-at', 4)] next() call -0.09577814063769934 goals: [('bisect', 0, array([0.42298615, 0.31887913]), array([0.0004355 , 0.03999763]), None, None, None, 4, array([0.42472813, 0.47886965]), array([0.0004355 , 0.03999763]), 1), ('sample-at', 4)] bisecting ... 0 None 4 successfully went all the way in one jump! goals: [('sample-at', 4)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -1 [0.42516363 0.51886728] [-0.0004355 -0.03999763] -0.09483173136735507 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -1)] not done yet, continue expanding to -1... goals: [('expand-to', -1), ('sample-at', -1)] next() call -0.09577814063769935 goals: [('bisect', 0, array([0.42516363, 0.51886728]), array([0.0004355 , 0.03999763]), None, None, None, -1, array([0.42472813, 0.47886965]), array([0.0004355 , 0.03999763]), -1), ('sample-at', -1)] bisecting ... 0 None -1 successfully went all the way in one jump! goals: [('sample-at', -1)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.42472813 0.47886965] [-0.0004355 -0.03999763] -0.09577814063769932 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd new NUTS range: -4..3 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd sampling between (-4, 3) ---- seed=93 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 BACKWARD SAMPLING FROM 4 [0.515227 0.56286192] [-0.03275687 -0.02295621] -0.18212468401683823 BACKWARD SAMPLING FROM -4 [0.44675381 0.66881082] [ 0.03990013 -0.00282481] -0.4560081322130549 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), None, None, None, 10, array([0.99464435, 0.62926345]), array([-0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 5, array([0.80585499, 0.64338751]), array([ 0.03990013, -0.00282481]), 10, array([0.99464435, 0.62926345]), array([-0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 2, array([0.6861546 , 0.65186194]), array([ 0.03990013, -0.00282481]), 5, array([0.80585499, 0.64338751]), array([ 0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 1 next() call None goals: [('bisect', 0, array([0.60635434, 0.65751157]), array([ 0.03990013, -0.00282481]), 1, array([0.64625447, 0.65468676]), array([ 0.03990013, -0.00282481]), 2, array([0.6861546 , 0.65186194]), array([ 0.03990013, -0.00282481]), 1), ('sample-at', 10)] bisecting ... 0 1 2 bisecting gave reflection point 1 [0.64625447 0.65468676] [ 0.03990013 -0.00282481] new direction: [-0.03275687 -0.02295621] reversing there [ 0.03990013 -0.00282481] making one step from [0.64625447 0.65468676] [ 0.03990013 -0.00282481] --> [0.6134976 0.63173055] [-0.03275687 -0.02295621] trying new point, [0.6134976 0.63173055] next() call -0.4051013634874946 goals: [('reflect-at', 1, array([0.6134976 , 0.63173055]), array([-0.03275687, -0.02295621]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.12085928392615417 goals: [('bisect', 1, array([0.6134976 , 0.63173055]), array([-0.03275687, -0.02295621]), None, None, None, 10, array([0.31868579, 0.42512465]), array([-0.03275687, -0.02295621]), 1), ('sample-at', 10)] bisecting ... 1 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.31868579 0.42512465] [-0.03275687 -0.02295621] -0.12085928392615417 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.31868579, 0.42512465]), array([0.03275687, 0.02295621]), None, None, None, 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.1362945285525923 goals: [('bisect', 0, array([0.31868579, 0.42512465]), array([0.03275687, 0.02295621]), 5, array([0.48247013, 0.53990571]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.24220254166073774 goals: [('bisect', 5, array([0.48247013, 0.53990571]), array([0.03275687, 0.02295621]), 7, array([0.54798386, 0.58581813]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.31652810148428956 goals: [('bisect', 7, array([0.54798386, 0.58581813]), array([0.03275687, 0.02295621]), 8, array([0.58074073, 0.60877434]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.40510136348749465 goals: [('bisect', 8, array([0.58074073, 0.60877434]), array([0.03275687, 0.02295621]), 9, array([0.6134976 , 0.63173055]), array([0.03275687, 0.02295621]), 10, array([0.64625447, 0.65468676]), array([0.03275687, 0.02295621]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.64625447 0.65468676] [0.03275687 0.02295621] new direction: [-0.03990013 0.00282481] reversing there [0.03275687 0.02295621] making one step from [0.64625447 0.65468676] [0.03275687 0.02295621] --> [0.60635434 0.65751157] [-0.03990013 0.00282481] trying new point, [0.60635434 0.65751157] next() call -0.49395646957573464 goals: [('reflect-at', 10, array([0.60635434, 0.65751157]), array([-0.03990013, 0.00282481]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.60635434 0.65751157] [ 0.03990013 -0.00282481] -0.4939564695757347 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -3..4 NUTS step: tree depth 3, fwd NUTS step: tree depth 3, fwd new NUTS range: -3..12 sampling between (-3, 12) ---- seed=94 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 BACKWARD SAMPLING FROM 4 [0.86227142 0.53522328] [ 0.03572141 -0.01799947] -0.38726449528400564 BACKWARD SAMPLING FROM -2 [0.64794297 0.64322012] [ 0.03572141 -0.01799947] -0.46631508651324616 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4925337817021134 goals: [('bisect', 0, array([0.71938579, 0.60722118]), array([ 0.03572141, -0.01799947]), None, None, None, 10, array([0.92340014, 0.42722645]), array([-0.03572141, -0.01799947]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.92340014 0.42722645] [-0.03572141 -0.01799947] -0.4925337817021134 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.4024627109969381 goals: [('bisect', 0, array([0.92340014, 0.42722645]), array([0.03572141, 0.01799947]), None, None, None, 10, array([0.71938579, 0.60722118]), array([-0.03572141, 0.01799947]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.71938579 0.60722118] [ 0.03572141 -0.01799947] -0.4024627109969381 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: -1..2 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd new NUTS range: -1..6 NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd NUTS step: tree depth 3, rwd sampling between (-1, 6) ---- seed=95 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 BACKWARD SAMPLING FROM 4 [0.60734111 0.59133529] [-0.02922414 0.02731208] -0.2887083100641112 BACKWARD SAMPLING FROM -4 [0.82122514 0.40753202] [ 0.01990911 -0.03469333] -0.4440844529643073 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.72423768, 0.48208699]), array([-0.02922414, 0.02731208]), None, None, None, 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.34307459325849876 goals: [('bisect', 0, array([0.72423768, 0.48208699]), array([-0.02922414, 0.02731208]), 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 7, array([0.51966868, 0.67327152]), array([-0.02922414, 0.02731208]), 10, array([0.43199625, 0.75520775]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call -0.41694366417810785 goals: [('bisect', 5, array([0.57811696, 0.61864737]), array([-0.02922414, 0.02731208]), 6, array([0.54889282, 0.64595945]), array([-0.02922414, 0.02731208]), 7, array([0.51966868, 0.67327152]), array([-0.02922414, 0.02731208]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 7 [0.51966868 0.67327152] [-0.02922414 0.02731208] new direction: [-0.03257512 0.02321339] reversing there [-0.02922414 0.02731208] making one step from [0.51966868 0.67327152] [-0.02922414 0.02731208] --> [0.48709356 0.69648491] [-0.03257512 0.02321339] trying new point, [0.48709356 0.69648491] next() call None goals: [('reflect-at', 7, array([0.48709356, 0.69648491]), array([-0.03257512, 0.02321339]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 6... 4 steps to do at 6 -> [from 7, delta=4] targeting 3. goals: [('sample-at', 3)] target is on track, returning interpolation at 3... [0.63656525 0.56402322] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 6 [0.54889282 0.64595945] [-0.02922414 0.02731208] -0.41694366417810785 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 6)] not done yet, continue expanding to 6... goals: [('expand-to', 6), ('sample-at', 6)] next() call -0.2662710545387677 goals: [('bisect', 0, array([0.54889282, 0.64595945]), array([ 0.02922414, -0.02731208]), None, None, None, 6, array([0.72423768, 0.48208699]), array([ 0.02922414, -0.02731208]), 1), ('sample-at', 6)] bisecting ... 0 None 6 successfully went all the way in one jump! goals: [('sample-at', 6)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.72423768 0.48208699] [-0.02922414 0.02731208] -0.26627105453876776 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -2..1 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-2, 1) ---- seed=96 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 BACKWARD SAMPLING FROM 4 [0.0396262 0.47159221] [ 0.03300675 -0.02259545] -0.010872647013765053 BACKWARD SAMPLING FROM -4 [0.22442783 0.65235578] [-0.03300675 -0.02259545] -0.3153374835129045 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.36436264123928686 goals: [('bisect', 0, array([0.09240082, 0.561974 ]), array([-0.03300675, -0.02259545]), None, None, None, 10, array([0.23766673, 0.33601954]), array([ 0.03300675, -0.02259545]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 10 [0.23766673 0.33601954] [ 0.03300675 -0.02259545] -0.36436264123928686 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call -0.05227866114907242 goals: [('bisect', 0, array([0.23766673, 0.33601954]), array([-0.03300675, 0.02259545]), None, None, None, 10, array([0.09240082, 0.561974 ]), array([0.03300675, 0.02259545]), 1), ('sample-at', 10)] bisecting ... 0 None 10 successfully went all the way in one jump! goals: [('sample-at', 10)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.09240082 0.561974 ] [-0.03300675 -0.02259545] -0.05227866114907259 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd sampling between (0, 1) ---- seed=97 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 BACKWARD SAMPLING FROM 4 [0.1641606 0.49992937] [-0.01012837 0.03869646] -0.013474413804503925 BACKWARD SAMPLING FROM -1 [0.21480243 0.30644705] [-0.01012837 0.03869646] -0.4913543244490346 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.20467407, 0.34514352]), array([-0.01012837, 0.03869646]), None, None, None, 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.030512397919510853 goals: [('bisect', 0, array([0.20467407, 0.34514352]), array([-0.01012837, 0.03869646]), 5, array([0.15403223, 0.53862583]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call -0.1772023323934378 goals: [('bisect', 5, array([0.15403223, 0.53862583]), array([-0.01012837, 0.03869646]), 7, array([0.1337755 , 0.61601875]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 8 next() call -0.3068542827523578 goals: [('bisect', 7, array([0.1337755 , 0.61601875]), array([-0.01012837, 0.03869646]), 8, array([0.12364714, 0.65471522]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 7 8 10 continue bisect at 9 next() call -0.4740442218592488 goals: [('bisect', 8, array([0.12364714, 0.65471522]), array([-0.01012837, 0.03869646]), 9, array([0.11351877, 0.69341168]), array([-0.01012837, 0.03869646]), 10, array([0.1033904 , 0.73210814]), array([-0.01012837, 0.03869646]), 1), ('sample-at', 10)] bisecting ... 8 9 10 bisecting gave reflection point 10 [0.1033904 0.73210814] [-0.01012837 0.03869646] new direction: [-0.03691991 0.01539222] reversing there [-0.01012837 0.03869646] making one step from [0.1033904 0.73210814] [-0.01012837 0.03869646] --> [0.0664705 0.74750036] [-0.03691991 0.01539222] trying new point, [0.0664705 0.74750036] next() call None goals: [('reflect-at', 10, array([0.0664705 , 0.74750036]), array([-0.03691991, 0.01539222]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 9... 1 steps to do at 9 -> [from 10, delta=1] targeting 9. goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 9 [0.11351877 0.69341168] [-0.01012837 0.03869646] -0.4740442218592488 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 9)] not done yet, continue expanding to 9... goals: [('expand-to', 9), ('sample-at', 9)] next() call -0.3207023648241862 goals: [('bisect', 0, array([0.11351877, 0.69341168]), array([ 0.01012837, -0.03869646]), None, None, None, 9, array([0.20467407, 0.34514352]), array([ 0.01012837, -0.03869646]), 1), ('sample-at', 9)] bisecting ... 0 None 9 successfully went all the way in one jump! goals: [('sample-at', 9)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.20467407 0.34514352] [-0.01012837 0.03869646] -0.3207023648241864 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd sampling between (0, 1) ---- seed=98 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 BACKWARD SAMPLING FROM 4 [0.79446178 0.41977178] [ 0.01554863 -0.03685431] -0.39604184352994004 BACKWARD SAMPLING FROM -2 [0.70116998 0.64089763] [ 0.01554863 -0.03685431] -0.4939714550399919 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.73226725, 0.56718902]), array([ 0.01554863, -0.03685431]), None, None, None, 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call -0.49941240374695045 goals: [('bisect', 0, array([0.73226725, 0.56718902]), array([ 0.01554863, -0.03685431]), 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 7 next() call None goals: [('bisect', 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 7, array([0.84110768, 0.30920886]), array([ 0.01554863, -0.03685431]), 10, array([0.88775357, 0.19864593]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 5 7 10 continue bisect at 6 next() call None goals: [('bisect', 5, array([0.81001041, 0.38291747]), array([ 0.01554863, -0.03685431]), 6, array([0.82555904, 0.34606317]), array([ 0.01554863, -0.03685431]), 7, array([0.84110768, 0.30920886]), array([ 0.01554863, -0.03685431]), 1), ('sample-at', 10)] bisecting ... 5 6 7 bisecting gave reflection point 6 [0.82555904 0.34606317] [ 0.01554863 -0.03685431] new direction: [-0.03412149 -0.02087401] reversing there [ 0.01554863 -0.03685431] making one step from [0.82555904 0.34606317] [ 0.01554863 -0.03685431] --> [0.79143756 0.32518916] [-0.03412149 -0.02087401] trying new point, [0.79143756 0.32518916] next() call None goals: [('reflect-at', 6, array([0.79143756, 0.32518916]), array([-0.03412149, -0.02087401]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 5... 5 steps to do at 5 -> [from 6, delta=5] targeting 1. goals: [('sample-at', 1)] target is on track, returning interpolation at 1... [0.74781588 0.53033471] None next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 5 [0.81001041 0.38291747] [ 0.01554863 -0.03685431] -0.49941240374695045 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 5)] not done yet, continue expanding to 5... goals: [('expand-to', 5), ('sample-at', 5)] next() call -0.3245372087629051 goals: [('bisect', 0, array([0.81001041, 0.38291747]), array([-0.01554863, 0.03685431]), None, None, None, 5, array([0.73226725, 0.56718902]), array([-0.01554863, 0.03685431]), 1), ('sample-at', 5)] bisecting ... 0 None 5 successfully went all the way in one jump! goals: [('sample-at', 5)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 0)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.73226725 0.56718902] [ 0.01554863 -0.03685431] -0.3245372087629051 NUTS step: tree depth 0, fwd NUTS step: tree depth 0, fwd new NUTS range: 0..1 NUTS step: tree depth 1, fwd NUTS step: tree depth 1, fwd new NUTS range: 0..3 NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd NUTS step: tree depth 2, fwd sampling between (0, 3) ---- seed=99 ---- StepSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 BACKWARD SAMPLING FROM 3 [0.68399324 0.60750522] [0.00390489 0.03980894] -0.3783905365498532 BACKWARD SAMPLING FROM -3 [0.66056388 0.36865158] [0.00390489 0.03980894] -0.4338274302289816 BisectSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 10)] not done yet, continue expanding to 10... goals: [('expand-to', 10), ('sample-at', 10)] next() call None goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), None, None, None, 10, array([0.71132748, 0.88616781]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 None 10 continue bisect at 5 next() call None goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 10, array([0.71132748, 0.88616781]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 5 10 continue bisect at 2 next() call -0.28854490986652237 goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), 2, array([0.68008834, 0.56769628]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 0 2 5 continue bisect at 3 next() call -0.37839053654985255 goals: [('bisect', 2, array([0.68008834, 0.56769628]), array([0.00390489, 0.03980894]), 3, array([0.68399324, 0.60750522]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 2 3 5 continue bisect at 4 next() call None goals: [('bisect', 3, array([0.68399324, 0.60750522]), array([0.00390489, 0.03980894]), 4, array([0.68789813, 0.64731416]), array([0.00390489, 0.03980894]), 5, array([0.69180302, 0.68712311]), array([0.00390489, 0.03980894]), 1), ('sample-at', 10)] bisecting ... 3 4 5 bisecting gave reflection point 4 [0.68789813 0.64731416] [0.00390489 0.03980894] new direction: [-0.01907752 0.03515748] reversing there [0.00390489 0.03980894] making one step from [0.68789813 0.64731416] [0.00390489 0.03980894] --> [0.66882061 0.68247164] [-0.01907752 0.03515748] trying new point, [0.66882061 0.68247164] next() call None goals: [('reflect-at', 4, array([0.66882061, 0.68247164]), array([-0.01907752, 0.03515748]), 1), ('sample-at', 10)] goals: [('sample-at', 10)] reversing at 3... 7 steps to do at 3 -> [from 4, delta=7] targeting -3. goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.4338274302289816 goals: [('bisect', 0, array([0.67227856, 0.4880784 ]), array([0.00390489, 0.03980894]), None, None, None, -3, array([0.66056388, 0.36865158]), array([0.00390489, 0.03980894]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM 3 [0.68399324 0.60750522] [0.00390489 0.03980894] -0.37839053654985255 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', 3)] not done yet, continue expanding to 3... goals: [('expand-to', 3), ('sample-at', 3)] next() call -0.22775578725568393 goals: [('bisect', 0, array([0.68399324, 0.60750522]), array([-0.00390489, -0.03980894]), None, None, None, 3, array([0.67227856, 0.4880784 ]), array([-0.00390489, -0.03980894]), 1), ('sample-at', 3)] bisecting ... 0 None 3 successfully went all the way in one jump! goals: [('sample-at', 3)] next() call None goals: [('sample-at', 0)] next() call None BACKWARD SAMPLING FROM -3 [0.66056388 0.36865158] [0.00390489 0.03980894] -0.4338274302289816 next() call None goals: [('sample-at', 0)] next() call None next() call None goals: [('sample-at', -3)] not done yet, continue expanding to -3... goals: [('expand-to', -3), ('sample-at', -3)] next() call -0.2277557872556839 goals: [('bisect', 0, array([0.66056388, 0.36865158]), array([-0.00390489, -0.03980894]), None, None, None, -3, array([0.67227856, 0.4880784 ]), array([-0.00390489, -0.03980894]), -1), ('sample-at', -3)] bisecting ... 0 None -3 successfully went all the way in one jump! goals: [('sample-at', -3)] next() call None goals: [('sample-at', 0)] next() call None NUTSSampler ---- FORWARD SAMPLING FROM 0 [0.67227856 0.4880784 ] [0.00390489 0.03980894] -0.2277557872556839 NUTS step: tree depth 0, rwd NUTS step: tree depth 0, rwd new NUTS range: -1..0 NUTS step: tree depth 1, rwd NUTS step: tree depth 1, rwd new NUTS range: -3..0 NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd NUTS step: tree depth 2, rwd sampling between (-3, 0) | |||
Passed | tests/test_flatnuts.py::test_singlejumper | 0.02 | |
------------------------------Captured stdout call------------------------------ make reflect make stuck | |||
Passed | tests/test_flatnuts.py::test_directjumper | 0.02 | |
------------------------------Captured stdout call------------------------------ make reflect make stuck | |||
Passed | tests/test_netiterintegrate.py::test_singleblock[100] | 2.01 | |
------------------------------Captured stdout call------------------------------ ================================================================================ NLIVE=100 Standard integrator 236.2 +- 0.2 in 740 iter 0.27s Graph integrator 236.1732 +- 0.2430 (main) 236.2408 +- 0.3325 (bs) 236.2 +- 0.2 in 842 iter 0.52s Vectorized graph integrator tree size: (822, 100) 236.1728 +- 0.2432 (main) 236.1499 +- 0.3864 (bs) 236.2 +- 0.2 in 822 iter 0.34s Vectorized graph integrator with insertion order test tree size: (822, 100) 236.1728 +- 0.2432 (main) 236.2381 +- 0.3834 (bs) insertion order: inf 236.2 +- 0.2 in 822 iter 0.42s | |||
Passed | tests/test_netiterintegrate.py::test_singleblock[400] | 9.10 | |
------------------------------Captured stdout call------------------------------ ================================================================================ NLIVE=400 Standard integrator 235.9 +- 0.1 in 3070 iter 1.34s Graph integrator 235.9038 +- 0.1234 (main) 235.8853 +- 0.1403 (bs) 235.9 +- 0.1 in 3471 iter 2.89s Vectorized graph integrator tree size: (3399, 400) 235.9049 +- 0.1233 (main) 235.9990 +- 0.1520 (bs) 235.9 +- 0.1 in 3399 iter 2.19s Vectorized graph integrator with insertion order test tree size: (3399, 400) 235.9049 +- 0.1233 (main) 236.0131 +- 0.1753 (bs) insertion order: 22.0 235.9 +- 0.1 in 3399 iter 2.26s | |||
Passed | tests/test_netiterintegrate.py::test_singleblock[2000] | 24.45 | |
------------------------------Captured stdout call------------------------------ ================================================================================ NLIVE=2000 Standard integrator 235.9 +- 0.1 in 15374 iter 2.22s Graph integrator 235.8827 +- 0.0553 (main) 235.8979 +- 0.0647 (bs) 235.9 +- 0.1 in 17375 iter 9.38s Vectorized graph integrator tree size: (16988, 2000) 235.8827 +- 0.0553 (main) 235.9355 +- 0.0719 (bs) 235.9 +- 0.1 in 16988 iter 3.93s Vectorized graph integrator with insertion order test tree size: (16988, 2000) 235.8827 +- 0.0553 (main) 235.8961 +- 0.1308 (bs) insertion order: inf 235.9 +- 0.1 in 16988 iter 8.40s | |||
Passed | tests/test_netiterintegrate.py::test_visualisation | 0.00 | |
------------------------------Captured stdout call------------------------------ testing tree visualisation... - Node: None - Node: 562 - Node: 745 - Node: 476 - Node: 143 - Node: 102 - Node: 276 - Node: 309 - Node: 682 - Node: 717 - Node: 861 - Node: 482 - Node: 663 - Node: 15 - Node: 498 - Node: 625 Empty Tree ║║║\\ ║║║ \\ ║║╠╗║║ 143 ║║║O║║ 102 ║║O ║║ 276 ║║ ║\ ║║ ║ \ ║║ ║ \ ║║ ╠╦╗║ 309 ║║ ║║║╠╦╦╗ 482 ║║ ║║║║║O║ 15 ║║ ║║║║O ║ 498 O║ ║║║║ ║ 562 ║ ║║║O ║ 625 ║ ║║║ O 663 ║ ║║O 682 ║ ║O 717 + ║ 745 ║ ║ O ║ 476 O 861 | |||
Passed | tests/test_netiterintegrate.py::test_treedump | 0.04 | |
------------------------------Captured stdout call------------------------------ testing tree dumping... | |||
Passed | tests/test_ordertest.py::test_invalid_order | 0.00 | |
No log output captured. | |||
Passed | tests/test_ordertest.py::test_diff_expand | 0.00 | |
No log output captured. | |||
Passed | tests/test_ordertest.py::test_order_correctness | 0.12 | |
------------------------------Captured stdout call------------------------------ frac: 1 runlength: [] frac: 0.9 split after 551 split after 445 runlength: [551, 445] number of runs: 0 2 | |||
Passed | tests/test_regionsampling.py::test_region_sampling_scaling | 0.04 | |
------------------------------Captured stdout call------------------------------ enlargement factor: 1.6413050458476675 0.6092712640650785 sampling_method: <bound method MLFriends.sample_from_transformed_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f65304af250>> sampling_method: <bound method MLFriends.sample_from_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f65304af250>> sampling_method: <bound method MLFriends.sample_from_points of <ultranest.mlfriends.MLFriends object at 0x7f65304af250>> sampling_method: <bound method MLFriends.sample_from_wrapping_ellipsoid of <ultranest.mlfriends.MLFriends object at 0x7f65304af250>> | |||
Passed | tests/test_regionsampling.py::test_region_sampling_affine | 0.04 | |
------------------------------Captured stdout call------------------------------ enlargement factor: 1.6413050458476683 0.6092712640650781 sampling_method: <bound method MLFriends.sample_from_transformed_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f6530c10e50>> sampling_method: <bound method MLFriends.sample_from_boundingbox of <ultranest.mlfriends.MLFriends object at 0x7f6530c10e50>> sampling_method: <bound method MLFriends.sample_from_points of <ultranest.mlfriends.MLFriends object at 0x7f6530c10e50>> sampling_method: <bound method MLFriends.sample_from_wrapping_ellipsoid of <ultranest.mlfriends.MLFriends object at 0x7f6530c10e50>> | |||
Passed | tests/test_regionsampling.py::test_region_ellipsoid | 0.02 | |
------------------------------Captured stdout call------------------------------ enlargement factor: 1.641305045847665 0.6092712640650795 | |||
Passed | tests/test_regionsampling.py::test_region_mean_distances | 0.18 | |
------------------------------Captured stdout call------------------------------ circle: 604 half-circle: 317 enlargement factor: 2.0237675941072473 0.49412788450204137 (0.872214351919518, 43685.72803024098, 50086, array([[ 5.90424248e-01, -1.28168190e-01], [ 5.68326216e-01, -7.99190323e-02], [ 5.73713827e-01, -1.40974066e-01], [-1.19565575e-01, 5.61077247e-01], [-3.96422558e-01, 6.82850299e-01], [-2.59345436e-01, -6.34084337e-01], [-9.34539440e-01, -6.90742582e-01], [-4.54118206e-02, -5.78179518e-01], [-4.02749950e-01, 6.58573234e-01], [ 8.13997364e-02, 4.94366661e-01], [-3.09850782e-01, 6.14532501e-01], [-9.99417973e-02, 5.57440104e-01], [-4.37625549e-01, -6.32032570e-01], [-7.81158726e-01, -7.00564790e-01], [ 1.75458891e-01, 4.95689547e-01], [ 1.72389906e-01, 4.68867481e-01], [-8.01773651e-01, -7.15223858e-01], [ 5.21338908e-01, -2.14590400e-01], [-1.07235208e+00, -7.36808791e-01], [ 4.73338580e-01, 2.56518765e-01], [ 5.63695919e-01, -1.86477123e-01], [-8.70841117e-01, -7.11677665e-01], [-1.82362061e-01, -5.69668582e-01], [ 1.73098757e-01, -4.92037144e-01], [-1.00384656e+00, 7.21061155e-01], [ 4.43217737e-01, 2.93713871e-01], [-4.67073777e-03, -5.54412686e-01], [-6.23929429e-02, -5.55287094e-01], [-3.44813772e-01, -6.27307923e-01], [-1.08124986e+00, 7.05926589e-01], [ 3.94361999e-01, -2.85080745e-01], [ 3.09949304e-01, 4.03277027e-01], [ 4.59621597e-01, -1.96075238e-01], [-1.52726042e-01, -5.65775188e-01], [-6.08038220e-01, 6.84700627e-01], [-9.12413897e-01, -7.18619243e-01], [ 4.86777463e-02, -4.86096498e-01], [ 2.91454928e-01, 4.23042620e-01], [ 2.31918395e-01, -4.62497450e-01], [-1.02176787e+00, -7.36473700e-01], [ 3.27742484e-01, 4.07938102e-01], [-3.10999361e-01, 6.64406143e-01], [-1.06863070e-01, 5.82251954e-01], [ 1.99001281e-01, -4.81705431e-01], [ 5.28069411e-01, 3.43009964e-02], [ 5.27707974e-01, 6.99940502e-02], [-7.79644952e-01, 6.92311241e-01], [-1.28175802e-01, -5.79235117e-01], [ 4.29640240e-01, 3.44927443e-01], [ 3.80488663e-01, -3.37014162e-01], [ 2.11391114e-01, 4.82592387e-01], [ 5.45453354e-01, -4.69543644e-02], [ 5.45493267e-01, -1.72467410e-01], [-1.11318383e-01, -5.94600729e-01], [ 7.36423960e-03, 5.66951095e-01], [ 2.99291218e-01, -3.50666656e-01], [ 7.68501828e-02, -5.19709187e-01], [ 4.77348651e-02, -5.05413071e-01], [ 2.50452451e-02, 5.39406983e-01], [-3.18730924e-01, -6.52554784e-01], [-2.39256777e-01, 6.33617282e-01], [-2.88466757e-01, -6.21474875e-01], [ 4.80469484e-01, -1.58504100e-01], [-7.81309751e-01, -6.99209221e-01], [-7.99809401e-01, -7.19966299e-01], [ 5.61260056e-01, 2.07443092e-01], [ 6.00598496e-01, 1.07023267e-01], [-8.28078470e-01, 7.00202304e-01], [-7.07008910e-01, -6.91468096e-01], [ 5.79643737e-01, -7.94768507e-02], [ 2.31601268e-01, 4.38441077e-01], [-5.88732825e-01, 6.90909274e-01], [ 3.63399194e-01, 3.49554643e-01], [-3.01868015e-01, -6.04559566e-01], [-6.72179399e-01, -6.88365529e-01], [-2.20656209e-01, 6.14106558e-01], [-3.15873900e-01, -6.34460723e-01], [-2.29395363e-02, 5.55827183e-01], [ 1.22068325e-01, -4.81068091e-01], [ 1.60053053e-01, 4.54050443e-01], [ 2.34926635e-01, 4.06907034e-01], [ 6.40572426e-02, 4.96910527e-01], [-1.07581862e+00, 7.10741072e-01], [-7.79059982e-02, 5.81010585e-01], [ 3.13990457e-01, 3.58865342e-01], [-1.06545701e+00, 7.36147059e-01], [ 1.94737500e-01, 4.59040723e-01], [ 5.10198700e-02, 5.48356580e-01], [ 5.67040396e-01, -5.71229985e-02], [-5.32353607e-01, 6.64346344e-01], [ 2.29408539e-01, 4.35118178e-01], [-4.70684001e-01, -6.53176034e-01], [-2.68907819e-01, -6.02284378e-01], [ 5.09058033e-01, -2.12102299e-01], [ 2.90072345e-01, 4.08084343e-01], [-1.12205944e+00, 7.28737094e-01], [ 6.53607804e-02, -5.28177982e-01], [ 5.28723809e-01, 1.93295404e-01], [-1.04125478e+00, -7.12877859e-01], [-4.13773799e-01, 6.76765319e-01], [-3.23951768e-01, 6.66693816e-01], [ 4.51926359e-01, -2.25259849e-01], [ 3.37355863e-01, -3.34292278e-01], [-1.72688147e-01, 6.08087321e-01], [-8.42767128e-01, -6.97224524e-01], [ 5.64114235e-01, -9.35664926e-02], [-5.17747415e-01, -6.87507349e-01], [ 2.85274291e-01, -4.18731788e-01], [ 3.73648106e-01, 3.13017175e-01], [ 5.24885792e-01, -4.80149396e-02], [ 5.74123528e-01, -1.31515348e-01], [ 5.10160640e-01, -1.86260602e-01], [-2.32128947e-01, -6.21459295e-01], [ 8.53606834e-02, -4.90521609e-01], [-1.22126323e-01, 5.71042591e-01], [ 5.61162366e-01, -4.02157071e-02], [ 5.81915438e-01, -1.33557124e-01], [ 2.54251411e-01, 4.42380525e-01], [-2.96656471e-01, 6.27301543e-01], [ 6.12618000e-01, -1.54673577e-02], [ 4.68414253e-01, 3.15996267e-01], [ 1.38443846e-01, 5.06144106e-01], [ 3.38969312e-01, -3.91504214e-01], [-7.36115829e-01, 7.00008604e-01], [ 5.58683694e-01, -6.26853177e-02], [-8.75338415e-02, -5.76960767e-01], [-3.02106731e-01, 6.39277939e-01], [-7.89936457e-01, -7.15965159e-01], [ 6.24131120e-01, 6.76807148e-02], [ 4.83833063e-01, 2.09116673e-01], [-8.76175360e-01, 7.13023744e-01], [-9.50047536e-01, 7.21264422e-01], [-9.40171485e-01, 7.21434643e-01], [ 3.61128428e-01, -3.23874595e-01], [ 5.28527861e-01, -2.07977696e-01], [ 5.91031086e-01, -8.78825272e-02], [-3.31900764e-01, 6.28744257e-01], [ 5.61592717e-01, -8.70877435e-02], [ 1.01711982e-01, -4.90711675e-01], [ 5.98208937e-01, 1.30210229e-01], [ 2.31300459e-01, 4.46747873e-01], [ 5.72396956e-01, 1.45443564e-01], [ 4.82526743e-01, -2.61214652e-01], [-4.65451960e-02, -5.51682756e-01], [-8.56937404e-02, -5.61988808e-01], [ 5.92962781e-01, 9.38652273e-02], [-9.62416037e-01, -7.23512874e-01], [ 6.20222332e-01, -5.16017176e-02], [ 4.16660129e-01, 3.52897971e-01], [ 2.41583904e-02, 5.23144069e-01], [ 6.00141659e-01, -5.75933780e-02], [ 1.56927888e-01, -5.02193794e-01], [-3.93974093e-01, -6.43049126e-01], [ 2.02410228e-01, -4.55275855e-01], [-9.70814676e-04, -5.15726743e-01], [ 4.88659015e-01, 2.92225534e-01], [-1.05525804e+00, -7.30188494e-01], [ 2.52474637e-01, -4.27979784e-01], [ 5.38151632e-01, 6.75691773e-02], [ 2.42572354e-01, -4.12351242e-01], [-1.30226587e-01, 5.75922329e-01], [ 2.11651622e-01, 4.31478420e-01], [-1.08228060e-01, -5.84436143e-01], [-6.84886675e-01, -6.85042919e-01], [-2.56262799e-01, 6.37474619e-01], [ 5.67490271e-01, 1.62710894e-01], [-3.54462948e-01, 6.46586395e-01], [-1.97719948e-01, -6.04179939e-01], [ 2.62341518e-01, 3.94453328e-01], [-6.58017071e-01, 6.83796252e-01], [ 4.15531976e-01, -2.50272400e-01], [-6.10285376e-01, -6.93448002e-01], [-1.30071704e-02, 5.25061960e-01], [ 5.59574319e-01, -1.05796261e-01], [ 5.19595457e-01, 1.24528793e-01], [-8.92188768e-01, 7.05666600e-01], [-1.11557743e-01, 5.69709296e-01], [ 2.79533678e-01, -3.70884022e-01], [ 4.34984565e-01, 3.08947351e-01], [ 3.45974468e-01, 4.12969133e-01], [ 3.13933302e-01, -3.76474657e-01], [-2.75965010e-01, -6.42767643e-01], [ 5.70043451e-01, 6.56624613e-02], [ 7.57441643e-02, -5.01435276e-01], [ 5.25428777e-01, 8.08138545e-02], [-1.01292415e+00, -7.14287399e-01], [ 5.56600088e-01, -1.38665935e-01], [-1.04322227e+00, 7.31390728e-01], [ 5.20570175e-01, -2.11254458e-01], [-1.34117300e-01, 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-1.22705612e-01], [-1.10073316e+00, 7.08902191e-01], [-1.44756302e-01, 5.85217696e-01], [-3.91285306e-01, 6.54446303e-01], [-6.13796840e-01, -6.58699733e-01], [ 5.24678767e-01, 9.66140744e-02], [ 8.40114247e-02, 4.91917261e-01], [ 3.30864872e-02, 5.16473540e-01], [ 2.46226604e-01, -4.09232238e-01], [-1.33034368e-01, -5.94658196e-01], [ 6.03624607e-01, -9.70782567e-02], [-2.47891108e-01, 6.07823792e-01], [ 4.62914363e-01, 2.64549784e-01], [-5.09349525e-01, -6.44150967e-01], [ 1.13591509e-01, -4.73745674e-01], [ 1.48362665e-01, 4.98802454e-01], [-4.05371772e-01, -6.44312188e-01], [ 4.13735449e-01, -3.22718762e-01], [ 5.86936799e-01, 5.59155101e-02], [ 3.40831098e-01, -3.24550582e-01], [-2.76232847e-01, 6.39569251e-01], [ 1.53254495e-01, 4.56171994e-01], [-3.91115920e-01, 6.81134606e-01], [-9.59210936e-01, -7.00127462e-01], [ 5.72735655e-01, -9.50147825e-02], [ 2.30824521e-01, -4.46012440e-01], [ 2.28204223e-01, -4.04798095e-01], [-7.33534876e-01, 6.87691758e-01], [ 4.54868884e-01, -2.82817284e-01], [ 5.46092204e-01, -3.54687801e-03], [ 5.71604916e-01, 1.99084806e-01], [ 4.62990471e-01, 2.71594295e-01], [ 5.19813366e-01, -7.16447092e-02], [-6.74531056e-01, -6.73661254e-01], [ 4.35519314e-01, 3.27782968e-01], [ 4.59759219e-01, -2.97495711e-01], [ 5.36479128e-01, 6.97558942e-02], [ 3.20911096e-01, -3.74970703e-01], [-6.36511978e-01, 7.08221962e-01], [-3.19237142e-01, -6.38166882e-01], [ 3.08440849e-01, -3.97843176e-01], [ 2.15161217e-01, -4.45416491e-01], [ 5.23742183e-01, -6.86027422e-02], [-1.43795898e-01, 6.03843241e-01], [ 4.17881991e-01, 3.38802795e-01], [-9.05525862e-01, -6.91147062e-01], [-9.73625579e-01, 7.37176331e-01], [-1.88283171e-01, 6.24337353e-01], [ 3.17412253e-01, 3.58107852e-01], [-3.08253490e-01, 6.55257540e-01], [ 2.74791820e-01, 4.25170087e-01], [-4.85959091e-01, -6.82191636e-01], [ 4.85531428e-01, -2.17692438e-01], [-2.61347209e-01, 6.06844450e-01], [ 4.52048239e-01, -2.65805090e-01], [ 1.92686620e-01, -4.25541620e-01], [ 5.81632240e-01, 1.05684070e-01], [ 5.44123310e-01, 1.20172110e-01], [ 5.26526195e-01, 2.06299651e-01], [-2.90002911e-01, 6.16411381e-01], [-1.27839148e-01, -5.58561629e-01], [ 3.77309343e-01, 3.88445326e-01], [-6.76423775e-01, 7.04823962e-01], [ 5.12102318e-01, 1.48736261e-01], [-5.02015320e-01, -6.58331246e-01], [ 3.27664480e-01, 4.11424738e-01], [ 1.27090010e-01, -4.72192408e-01], [ 2.01735278e-02, -5.45992810e-01], [ 4.33323589e-01, -2.75800974e-01], [-2.24522422e-01, -5.94273343e-01], [-1.12824059e+00, 7.13459556e-01], [ 1.50616445e-01, -4.67437074e-01], [ 4.74098962e-01, -1.97705703e-01], [-1.38830266e-02, -5.17257962e-01], [ 6.15599276e-01, -2.81078599e-02], [-8.49426337e-01, -6.95820872e-01], [ 9.91674042e-02, 5.28045181e-01], [-7.02400738e-01, 7.13589361e-01], [ 5.30543730e-01, 8.13631383e-02], [ 5.03460184e-01, -2.13761124e-01], [-9.50434114e-01, -7.13216797e-01], [ 2.15097760e-01, -4.14738256e-01], [-6.09043167e-01, 6.74068269e-01], [ 4.26416839e-01, 3.19455107e-01], [ 1.42980694e-01, 5.07039208e-01], [ 2.53103622e-01, 4.31004531e-01], [-7.51466786e-01, -6.98367551e-01], [ 6.06775012e-01, -5.69107304e-02], [-3.31556017e-01, 6.48084055e-01], [-7.20021723e-01, -7.05147717e-01], [ 3.42373787e-01, -3.13355433e-01], [ 5.41800018e-01, -1.43625112e-01], [ 5.92055711e-01, -1.06163740e-02], [ 5.41007418e-01, -1.62003709e-01], [ 6.11496879e-01, -9.55651797e-02], [-8.98704729e-02, -5.93749811e-01], [-5.27060656e-01, -6.66801199e-01], [-1.12398671e-01, -5.82338575e-01], [ 2.39603269e-01, 4.03478432e-01], [ 3.36486746e-01, 4.12896778e-01]])) | |||
Passed | tests/test_run.py::test_run | 3.95 | |
------------------------------Captured stdout call------------------------------ Creating directory for new run logs/test/run223 [ultranest.integrator.NestedSampler] Num live points [400] [ultranest.integrator.NestedSampler] Resuming... [ultranest.integrator.NestedSampler] Starting sampling ... Mono-modal Volume: ~exp(-4.03) Expected Volume: exp(-5.99) Hinz: -10.0| -4.9 *************************** +5.0 | +10.0 Kunz: -10.0| -5.0 *************************** +5.0 | +10.0 Z=-1e+02+0.6 | Like=-1e+02..0.6 | it/evals=0/500 eff=0.0000% Z=-7e+01+0.4 | Like=-6e+01..0.6 | it/evals=50/500 eff=10.0000% Z=-5e+01+0.3 | Like=-5e+01..0.6 | it/evals=100/625 eff=16.0000% Z=-4e+01+0.2 | Like=-4e+01..0.6 | it/evals=150/625 eff=24.0000% Z=-4e+01+0.06 | Like=-3e+01..0.6 | it/evals=200/742 eff=26.9542% Z=-3e+01+-0.07 | Like=-3e+01..0.6 | it/evals=250/742 eff=33.6927% Mono-modal Volume: ~exp(-5.27) Expected Volume: exp(-6.66) Hinz: -10.0| -3.3 ********************** +4.5 | +10.0 Kunz: -10.0| -3.2 ********************* +4.4 | +10.0 Z=-3e+01+-0.2 | Like=-3e+01..0.6 | it/evals=300/842 eff=35.6295% Z=-3e+01+-0.3 | Like=-2e+01..0.6 | it/evals=350/913 eff=38.3352% Z=-2e+01+-0.4 | Like=-2e+01..0.6 | it/evals=400/971 eff=41.1946% Z=-2e+01+-0.6 | Like=-2e+01..0.6 | it/evals=450/1025 eff=43.9024% Z=-2e+01+-0.7 | Like=-1e+01..0.6 | it/evals=500/1123 eff=44.5236% Z=-2e+01+-0.8 | Like=-1e+01..0.6 | it/evals=550/1167 eff=47.1294% Mono-modal Volume: ~exp(-5.27) Expected Volume: exp(-7.47) Hinz: -10.0| -1.9 ************** +3.2 | +10.0 Kunz: -10.0| -1.9 ************** +3.1 | +10.0 Z=-2e+01+-0.9 | Like=-1e+01..0.6 | it/evals=600/1263 eff=47.5059% Z=-1e+01+-1 | Like=-1e+01..0.6 | it/evals=650/1311 eff=49.5805% Z=-1e+01+-1 | Like=-9..0.6 | it/evals=700/1397 eff=50.1074% Z=-1e+01+-1 | Like=-8..0.6 | it/evals=750/1491 eff=50.3018% Z=-1e+01+-1 | Like=-7..0.6 | it/evals=800/1582 eff=50.5689% Z=-1e+01+-2 | Like=-6..0.6 | it/evals=850/1652 eff=51.4528% Mono-modal Volume: ~exp(-6.45) Expected Volume: exp(-8.12) Hinz: -10.0| -1.3 ********** +2.4 | +10.0 Kunz: -10.0| -1.2 ********** +2.4 | +10.0 Z=-9+-2 | Like=-5..0.6 | it/evals=900/1727 eff=52.1135% Z=-8+-2 | Like=-4..0.6 | it/evals=950/1780 eff=53.3708% Z=-8+-2 | Like=-4..0.6 | it/evals=1000/1852 eff=53.9957% Z=-7+-2 | Like=-3..0.6 | it/evals=1050/1931 eff=54.3760% Z=-7+-2 | Like=-2..0.6 | it/evals=1100/2001 eff=54.9725% Mono-modal Volume: ~exp(-7.45) Expected Volume: exp(-8.84) Hinz: -10.0| -0.6 ******** +1.9 | +10.0 Kunz: -10.0| -0.5 ******* +1.8 | +10.0 Z=-6+-2 | Like=-2..0.6 | it/evals=1150/2079 eff=55.3151% Z=-6+-2 | Like=-2..0.6 | it/evals=1200/2143 eff=55.9963% Z=-5+-3 | Like=-1..0.6 | it/evals=1250/2205 eff=56.6893% Z=-5+-3 | Like=-1..0.6 | it/evals=1300/2278 eff=57.0676% Z=-5+-3 | Like=-1..0.6 | it/evals=1350/2351 eff=57.4224% Z=-5+-3 | Like=-0.9..0.6 | it/evals=1400/2413 eff=58.0191% Mono-modal Volume: ~exp(-7.84) Expected Volume: exp(-9.59) Hinz: -10.0| -0.2 ****** +1.5 | +10.0 Kunz: -10.0| -0.2 ***** +1.4 | +10.0 Z=-5+-3 | Like=-0.7..0.6 | it/evals=1450/2495 eff=58.1162% Z=-4+-3 | Like=-0.6..0.6 | it/evals=1500/2645 eff=56.7108% Z=-4+-3 | Like=-0.4..0.6 | it/evals=1550/2645 eff=58.6011% Z=-4+-3 | Like=-0.3..0.6 | it/evals=1600/2763 eff=57.9081% Z=-4+-4 | Like=-0.2..0.6 | it/evals=1650/2852 eff=57.8541% Mono-modal Volume: ~exp(-8.81) Expected Volume: exp(-10.22) Hinz: +0.0e+00|******* +1.3e+00 | +1.0e+01 Kunz: +0.0e+00|******* +1.2e+00 | +1.0e+01 Z=-4+-4 | Like=-0.1..0.6 | it/evals=1700/2930 eff=58.0205% Z=-4+-4 | Like=-0.02..0.6 | it/evals=1750/2955 eff=59.2217% Z=-4+-4 | Like=0.03..0.6 | it/evals=1800/3027 eff=59.4648% Z=-4+-4 | Like=0.09..0.6 | it/evals=1850/3088 eff=59.9093% Z=-4+-4 | Like=0.1..0.6 | it/evals=1900/3165 eff=60.0316% Z=-4+-4 | Like=0.2..0.6 | it/evals=1950/3242 eff=60.1481% Z=-4+-4 | Like=0.3..0.6 | it/evals=2000/3316 eff=60.3136% Mono-modal Volume: ~exp(-9.68) Expected Volume: exp(-11.02) Hinz: +0.0| ***** +1.1 | +10.0 Kunz: +0.0| ***** +1.0 | +10.0 Z=-4+-5 | Like=0.3..0.6 | it/evals=2050/3467 eff=59.1289% Z=-4+-5 | Like=0.3..0.6 | it/evals=2100/3467 eff=60.5711% Z=-4+-5 | Like=0.4..0.6 | it/evals=2150/3571 eff=60.2072% Z=-3+-5 | Like=0.4..0.6 | it/evals=2200/3661 eff=60.0929% Mono-modal Volume: ~exp(-10.20) Expected Volume: exp(-11.58) Hinz: +0.0| +0.3 *********************************** | +1.0 Kunz: +0.0| +0.3 ********************************* | +1.0 Z=-3+-5 | Like=0.4..0.6 | it/evals=2250/3739 eff=60.1765% Z=-3+-5 | Like=0.4..0.6 | it/evals=2300/3769 eff=61.0241% Z=-3+-5 | Like=0.5..0.6 | it/evals=2350/3845 eff=61.1183% Z=-3+-5 | Like=0.5..0.6 | it/evals=2400/3918 eff=61.2557% Z=-3+-6 | Like=0.5..0.6 | it/evals=2450/3978 eff=61.5887% Z=-3+-6 | Like=0.5..0.6 | it/evals=2500/4060 eff=61.5764% Mono-modal Volume: ~exp(-10.83) Expected Volume: exp(-12.35) Hinz: +0.0| +0.4 ************************ | +1.0 Kunz: +0.0| +0.4 *********************** | +1.0 Z=-3+-6 | Like=0.5..0.6 | it/evals=2550/4269 eff=59.7330% Z=-3+-6 | Like=0.5..0.6 | it/evals=2600/4269 eff=60.9042% Z=-3+-6 | Like=0.5..0.6 | it/evals=2650/4385 eff=60.4333% Z=-3+-6 | Like=0.5..0.6 | it/evals=2700/4385 eff=61.5735% Z=-3+-6 | Like=0.5..0.6 | it/evals=2750/4489 eff=61.2609% Mono-modal Volume: ~exp(-11.27) Expected Volume: exp(-12.98) Hinz: +0.0| +0.5 ****************** +0.8 | +1.0 Kunz: +0.0| +0.5 ***************** +0.8 | +1.0 Z=-3+-6 | Like=0.6..0.6 | it/evals=2800/4574 eff=61.2156% Z=-3+-7 | Like=0.6..0.6 | it/evals=2850/4582 eff=62.1999% Z=-3+-7 | Like=0.6..0.6 | it/evals=2900/4653 eff=62.3254% Z=-3+-7 | Like=0.6..0.6 | it/evals=2950/4732 eff=62.3415% Z=-3+-7 | Like=0.6..0.6 | it/evals=3000/4802 eff=62.4740% Z=-3+-7 | Like=0.6..0.6 | it/evals=3050/4887 eff=62.4105% Z=-3+-7 | Like=0.6..0.6 | it/evals=3100/4966 eff=62.4245% Mono-modal Volume: ~exp(-12.44) Expected Volume: exp(-13.76) Hinz: +0.0| +0.5 ************ +0.7 | +1.0 Kunz: +0.0| +0.5 *********** +0.7 | +1.0 Z=-3+-7 | Like=0.6..0.6 | it/evals=3150/5106 eff=61.6921% Z=-3+-7 | Like=0.6..0.6 | it/evals=3200/5218 eff=61.3262% Z=-3+-8 | Like=0.6..0.6 | it/evals=3250/5218 eff=62.2844% Z=-3+-8 | Like=0.6..0.6 | it/evals=3300/5317 eff=62.0651% Mono-modal Volume: ~exp(-12.94) Expected Volume: exp(-14.32) Hinz: +0.0| +0.6 ********* +0.7 | +1.0 Kunz: +0.0| +0.6 ********* +0.7 | +1.0 Z=-3+-8 | Like=0.6..0.6 | it/evals=3350/5409 eff=61.9338% Z=-3+-8 | Like=0.6..0.6 | it/evals=3400/5429 eff=62.6266% Z=-3+-8 | Like=0.6..0.6 | it/evals=3450/5498 eff=62.7501% Z=-3+-8 | Like=0.6..0.6 | it/evals=3500/5564 eff=62.9044% Z=-3+-8 | Like=0.6..0.6 | it/evals=3550/5637 eff=62.9768% Z=-3+-8 | Like=0.6..0.6 | it/evals=3600/5702 eff=63.1357% Z=-3+-9 | Like=0.6..0.6 | it/evals=3650/5799 eff=62.9419% Mono-modal Volume: ~exp(-13.21) Expected Volume: exp(-15.14) Hinz: +0.0| +0.6 ******* +0.7 | +1.0 Kunz: +0.0| +0.6 ******* +0.7 | +1.0 Z=-3+-9 | Like=0.6..0.6 | it/evals=3700/5941 eff=62.2791% Z=-3+-9 | Like=0.6..0.6 | it/evals=3750/5941 eff=63.1207% Z=-3+-9 | Like=0.6..0.6 | it/evals=3800/6056 eff=62.7477% Z=-3+-9 | Like=0.6..0.6 | it/evals=3850/6167 eff=62.4291% Mono-modal Volume: ~exp(-14.12) Expected Volume: exp(-15.71) Hinz: +0.0| +0.6 ***** +0.7 | +1.0 Kunz: +0.0| +0.6 ***** +0.7 | +1.0 Z=-3+-9 | Like=0.6..0.6 | it/evals=3900/6259 eff=62.3103% Z=-3+-9 | Like=0.6..0.6 | it/evals=3950/6387 eff=61.8444% Z=-3+-9 | Like=0.6..0.6 | it/evals=4000/6387 eff=62.6272% Z=-3+-1e+01 | Like=0.6..0.6 | it/evals=4050/6496 eff=62.3461% Z=-3+-1e+01 | Like=0.6..0.6 | it/evals=4100/6496 eff=63.1158% Z=-3+-1e+01 | Like=0.6..0.6 | it/evals=4150/6586 eff=63.0125% Mono-modal Volume: ~exp(-14.95) Expected Volume: exp(-16.39) Hinz: +0.0| +0.6 **** +0.7 | +1.0 Kunz: +0.0| +0.6 *** +0.7 | +1.0 Z=-3+-1e+01 | Like=0.6..0.6 | it/evals=4200/6670 eff=62.9685% Z=-3+-1e+01 | Like=0.6..0.6 | it/evals=4250/6798 eff=62.5184% Z=-3+-1e+01 | Like=0.6..0.6 | it/evals=4300/6798 eff=63.2539% niter: 4321 ncall: 6913 nsamples: 4721 logz: -3.296 +/- 0.085 h: 2.900 -------------------------------Captured log call-------------------------------- [32mINFO [0m ultranest.integrator.NestedSampler:integrator.py:474 Num live points [400] [32mINFO [0m ultranest.integrator.NestedSampler:integrator.py:530 Resuming... [32mINFO [0m ultranest.integrator.NestedSampler:integrator.py:621 Starting sampling ... | |||
Passed | tests/test_run.py::test_reactive_run | 4.02 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.28) * Expected Volume: exp(0.00) Quality: ok Hinz: -5.0|*****************************************************| +5.0 Kunz: -5.0|*****************************************************| +5.0 Z=-inf(0.00%) | Like=-110.42..0.28 [-110.4238..0.2570] | it/evals=0/401 eff=0.0000% N=400 Z=-67.0(0.00%) | Like=-62.58..0.43 [-110.4238..0.2570] | it/evals=50/452 eff=96.1538% N=400 Mono-modal Volume: ~exp(-4.42) * Expected Volume: exp(-0.23) Quality: ok Hinz: -5.0| ***************************************************| +5.0 Kunz: -5.0| * *************************************************| +5.0 Z=-57.4(0.00%) | Like=-52.63..0.43 [-110.4238..0.2570] | it/evals=90/494 eff=95.7447% N=400 Z=-54.9(0.00%) | Like=-50.20..0.43 [-110.4238..0.2570] | it/evals=100/505 eff=95.2381% N=400 Z=-46.9(0.00%) | Like=-42.21..0.43 [-110.4238..0.2570] | it/evals=150/567 eff=89.8204% N=400 Mono-modal Volume: ~exp(-4.60) * Expected Volume: exp(-0.45) Quality: ok Hinz: -5.0| ***********************************************| +5.0 Kunz: -5.0| ***********************************************| +5.0 Z=-42.2(0.00%) | Like=-37.96..0.43 [-110.4238..0.2570] | it/evals=180/613 eff=84.5070% N=400 Z=-40.4(0.00%) | Like=-36.05..0.43 [-110.4238..0.2570] | it/evals=200/634 eff=85.4701% N=400 Z=-36.2(0.00%) | Like=-31.84..0.43 [-110.4238..0.2570] | it/evals=250/700 eff=83.3333% N=400 Mono-modal Volume: ~exp(-4.98) * Expected Volume: exp(-0.67) Quality: ok Hinz: -5.0| ****************************************** | +5.0 Kunz: -5.0| ****************************************** | +5.0 Z=-34.3(0.00%) | Like=-29.94..0.43 [-110.4238..0.2570] | it/evals=270/735 eff=80.5970% N=400 Z=-31.7(0.00%) | Like=-27.71..0.43 [-110.4238..0.2570] | it/evals=300/770 eff=81.0811% N=400 Z=-28.9(0.00%) | Like=-24.89..0.43 [-110.4238..0.2570] | it/evals=350/834 eff=80.6452% N=400 Mono-modal Volume: ~exp(-4.98) Expected Volume: exp(-0.90) Quality: ok Hinz: -5.0| *************************************** | +5.0 Kunz: -5.0| -2.8 ************************************** | +5.0 Z=-25.4(0.00%) | Like=-20.82..0.49 [-110.4238..0.2570] | it/evals=400/907 eff=78.8955% N=400 Mono-modal Volume: ~exp(-5.43) * Expected Volume: exp(-1.12) Quality: ok Hinz: -5.0| -2.5 ********************************** | +5.0 Kunz: -5.0| -2.5 ********************************** | +5.0 Z=-22.6(0.00%) | Like=-18.55..0.49 [-110.4238..0.2570] | it/evals=450/976 eff=78.1250% N=400 Z=-20.5(0.00%) | Like=-16.26..0.49 [-110.4238..0.2570] | it/evals=500/1043 eff=77.7605% N=400 Mono-modal Volume: ~exp(-5.80) * Expected Volume: exp(-1.35) Quality: ok Hinz: -5.0| -2.3 ******************************* | +5.0 Kunz: -5.0| -2.1 ****************************** | +5.0 Z=-18.7(0.00%) | Like=-14.60..0.51 [-110.4238..0.2570] | it/evals=540/1105 eff=76.5957% N=400 Z=-18.3(0.00%) | Like=-14.26..0.55 [-110.4238..0.2570] | it/evals=550/1118 eff=76.6017% N=400 Z=-16.6(0.00%) | Like=-12.62..0.55 [-110.4238..0.2570] | it/evals=600/1179 eff=77.0218% N=400 Mono-modal Volume: ~exp(-6.11) * Expected Volume: exp(-1.57) Quality: ok Hinz: -5.0| -2.0 **************************** | +5.0 Kunz: -5.0| -1.9 **************************** | +5.0 Z=-15.7(0.00%) | Like=-11.69..0.55 [-110.4238..0.2570] | it/evals=630/1225 eff=76.3636% N=400 Z=-15.2(0.00%) | Like=-11.26..0.55 [-110.4238..0.2570] | it/evals=650/1250 eff=76.4706% N=400 Z=-13.8(0.00%) | Like=-9.78..0.55 [-110.4238..0.2570] | it/evals=700/1314 eff=76.5864% N=400 Mono-modal Volume: ~exp(-6.11) Expected Volume: exp(-1.80) Quality: ok Hinz: -5.0| -1.7 ************************** +2.9 | +5.0 Kunz: -5.0| -1.6 ************************ +2.9 | +5.0 Z=-12.7(0.01%) | Like=-8.72..0.55 [-110.4238..0.2570] | it/evals=750/1378 eff=76.6871% N=400 Z=-11.8(0.03%) | Like=-7.66..0.55 [-110.4238..0.2570] | it/evals=800/1448 eff=76.3359% N=400 Mono-modal Volume: ~exp(-6.11) Expected Volume: exp(-2.02) Quality: ok Hinz: -5.0| -1.4 *********************** +2.6 | +5.0 Kunz: -5.0| -1.4 ********************* +2.5 | +5.0 Z=-10.7(0.07%) | Like=-6.56..0.55 [-110.4238..0.2570] | it/evals=850/1516 eff=76.1649% N=400 Mono-modal Volume: ~exp(-6.54) * Expected Volume: exp(-2.25) Quality: ok Hinz: -5.0| -1.2 ******************** +2.5 | +5.0 Kunz: -5.0| -1.1 ******************** +2.5 | +5.0 Z=-9.8(0.18%) | Like=-5.80..0.56 [-110.4238..0.2570] | it/evals=900/1588 eff=75.7576% N=400 Z=-9.1(0.37%) | Like=-4.92..0.57 [-110.4238..0.2570] | it/evals=950/1654 eff=75.7576% N=400 Mono-modal Volume: ~exp(-6.86) * Expected Volume: exp(-2.47) Quality: ok Hinz: -5.0| -1.0 ****************** +2.3 | +5.0 Kunz: -5.0| -0.9 ****************** +2.2 | +5.0 Z=-8.5(0.69%) | Like=-4.29..0.57 [-110.4238..0.2570] | it/evals=990/1707 eff=75.7460% N=400 Z=-8.4(0.80%) | Like=-4.17..0.57 [-110.4238..0.2570] | it/evals=1000/1719 eff=75.8150% N=400 Z=-7.8(1.42%) | Like=-3.65..0.59 [-110.4238..0.2570] | it/evals=1050/1787 eff=75.7030% N=400 Mono-modal Volume: ~exp(-7.25) * Expected Volume: exp(-2.70) Quality: ok Hinz: -5.0| -0.8 **************** +2.1 | +5.0 Kunz: -5.0| -0.8 **************** +2.0 | +5.0 Z=-7.4(1.95%) | Like=-3.36..0.59 [-110.4238..0.2570] | it/evals=1080/1835 eff=75.2613% N=400 Z=-7.3(2.35%) | Like=-3.20..0.59 [-110.4238..0.2570] | it/evals=1100/1859 eff=75.3941% N=400 Z=-6.8(3.59%) | Like=-2.70..0.59 [-110.4238..0.2570] | it/evals=1150/1926 eff=75.3604% N=400 Mono-modal Volume: ~exp(-7.32) * Expected Volume: exp(-2.92) Quality: ok Hinz: -5.0| -0.7 **************** +2.0 | +5.0 Kunz: -5.0| -0.7 ************** +1.9 | +5.0 Z=-6.7(4.17%) | Like=-2.58..0.59 [-110.4238..0.2570] | it/evals=1170/1958 eff=75.0963% N=400 Z=-6.4(5.26%) | Like=-2.40..0.59 [-110.4238..0.2570] | it/evals=1200/1996 eff=75.1880% N=400 Z=-6.1(7.29%) | Like=-2.06..0.59 [-110.4238..0.2570] | it/evals=1250/2050 eff=75.7576% N=400 Mono-modal Volume: ~exp(-7.62) * Expected Volume: exp(-3.15) Quality: ok Hinz: -5.0| -0.6 ************** +1.8 | +5.0 Kunz: -5.0| -0.5 ************* +1.7 | +5.0 Z=-6.0(7.81%) | Like=-2.00..0.59 [-110.4238..0.2570] | it/evals=1260/2061 eff=75.8579% N=400 Z=-5.8(9.88%) | Like=-1.73..0.59 [-110.4238..0.2570] | it/evals=1300/2108 eff=76.1124% N=400 Mono-modal Volume: ~exp(-7.62) Expected Volume: exp(-3.37) Quality: ok Hinz: -5.0| -0.4 ************ +1.7 | +5.0 Kunz: -5.0| -0.4 ************ +1.7 | +5.0 Z=-5.5(12.75%) | Like=-1.48..0.59 [-110.4238..0.2570] | it/evals=1350/2169 eff=76.3143% N=400 Z=-5.3(16.19%) | Like=-1.26..0.59 [-110.4238..0.2570] | it/evals=1400/2237 eff=76.2112% N=400 Mono-modal Volume: ~exp(-8.00) * Expected Volume: exp(-3.60) Quality: ok Hinz: -5.0| -0.4 ************ +1.6 | +5.0 Kunz: -5.0| -0.3 ********** +1.6 | +5.0 Z=-5.1(19.40%) | Like=-1.09..0.59 [-110.4238..0.2570] | it/evals=1440/2295 eff=75.9894% N=400 Z=-5.1(20.14%) | Like=-1.04..0.59 [-110.4238..0.2570] | it/evals=1450/2306 eff=76.0756% N=400 Z=-4.9(23.91%) | Like=-0.91..0.59 [-110.4238..0.2570] | it/evals=1500/2374 eff=75.9878% N=400 Mono-modal Volume: ~exp(-8.00) Expected Volume: exp(-3.82) Quality: ok Hinz: -5.0| -0.2 ********** +1.5 | +5.0 Kunz: -5.0| -0.2 ********** +1.5 | +5.0 Z=-4.8(28.28%) | Like=-0.70..0.59 [-110.4238..0.2570] | it/evals=1550/2436 eff=76.1297% N=400 Z=-4.6(32.78%) | Like=-0.54..0.59 [-110.4238..0.2570] | it/evals=1600/2513 eff=75.7217% N=400 Mono-modal Volume: ~exp(-8.11) * Expected Volume: exp(-4.05) Quality: ok Hinz: -5.0| -0.1 ********** +1.4 | +5.0 Kunz: -5.0| -0.1 ********* +1.4 | +5.0 Z=-4.6(34.48%) | Like=-0.49..0.59 [-110.4238..0.2570] | it/evals=1620/2546 eff=75.4893% N=400 Z=-4.5(37.16%) | Like=-0.40..0.59 [-110.4238..0.2570] | it/evals=1650/2581 eff=75.6534% N=400 Z=-4.4(41.71%) | Like=-0.30..0.59 [-110.4238..0.2570] | it/evals=1700/2654 eff=75.4215% N=400 Mono-modal Volume: ~exp(-8.53) * Expected Volume: exp(-4.27) Quality: ok Hinz: -5.0e+00| -5.7e-02 ******** +1.3e+00 | +5.0e+00 Kunz: -5.0e+00| -4.2e-02 ******** +1.3e+00 | +5.0e+00 Z=-4.4(42.67%) | Like=-0.29..0.59 [-110.4238..0.2570] | it/evals=1710/2670 eff=75.3304% N=400 Z=-4.3(46.38%) | Like=-0.20..0.59 [-110.4238..0.2570] | it/evals=1750/2723 eff=75.3336% N=400 Mono-modal Volume: ~exp(-9.00) * Expected Volume: exp(-4.50) Quality: ok Hinz: +0.0e+00|************** +1.2e+00 | +5.0e+00 Kunz: +0.0e+00|************** +1.2e+00 | +5.0e+00 Z=-4.2(50.51%) | Like=-0.09..0.59 [-110.4238..0.2570] | it/evals=1800/2788 eff=75.3769% N=400 Z=-4.1(54.67%) | Like=-0.02..0.59 [-110.4238..0.2570] | it/evals=1850/2846 eff=75.6337% N=400 Mono-modal Volume: ~exp(-9.00) Expected Volume: exp(-4.73) Quality: ok Hinz: +0.0e+00|************* +1.2e+00 | +5.0e+00 Kunz: +0.0| ************ +1.2 | +5.0 Z=-4.0(58.61%) | Like=0.06..0.59 [-110.4238..0.2570] | it/evals=1900/2909 eff=75.7274% N=400 Z=-4.0(62.35%) | Like=0.14..0.59 [-110.4238..0.2570] | it/evals=1950/2986 eff=75.4060% N=400 Mono-modal Volume: ~exp(-9.22) * Expected Volume: exp(-4.95) Quality: ok Hinz: +0.0| *********** +1.1 | +5.0 Kunz: +0.0| *********** +1.1 | +5.0 Z=-4.0(64.48%) | Like=0.17..0.59 [-110.4238..0.2570] | it/evals=1980/3032 eff=75.2280% N=400 Z=-3.9(65.91%) | Like=0.20..0.59 [-110.4238..0.2570] | it/evals=2000/3058 eff=75.2445% N=400 Z=-3.9(69.23%) | Like=0.25..0.59 [-110.4238..0.2570] | it/evals=2050/3130 eff=75.0916% N=400 Mono-modal Volume: ~exp(-9.22) Expected Volume: exp(-5.18) Quality: ok Hinz: +0.0| ********** +1.1 | +5.0 Kunz: +0.0| ********** +1.0 | +5.0 Z=-3.8(72.35%) | Like=0.30..0.59 [0.3022..0.3037]*| it/evals=2100/3198 eff=75.0536% N=400 Z=-3.8(75.22%) | Like=0.34..0.59 [0.3430..0.3442]*| it/evals=2150/3266 eff=75.0174% N=400 Mono-modal Volume: ~exp(-9.28) * Expected Volume: exp(-5.40) Quality: ok Hinz: +0.0| ********* +1.0 | +5.0 Kunz: +0.0| +0.3 **************************************| +1.0 Z=-3.8(75.76%) | Like=0.35..0.59 [0.3487..0.3489]*| it/evals=2160/3281 eff=74.9740% N=400 Z=-3.8(77.80%) | Like=0.37..0.59 [0.3745..0.3752]*| it/evals=2200/3327 eff=75.1623% N=400 Mono-modal Volume: ~exp(-9.98) * Expected Volume: exp(-5.63) Quality: ok Hinz: +0.0| +0.3 ************************************* | +1.0 Kunz: +0.0| +0.3 *********************************** | +1.0 Z=-3.7(80.20%) | Like=0.40..0.59 [0.3974..0.3977]*| it/evals=2250/3400 eff=75.0000% N=400 Z=-3.7(82.32%) | Like=0.42..0.59 [0.4190..0.4195]*| it/evals=2300/3462 eff=75.1143% N=400 Mono-modal Volume: ~exp(-10.17) * Expected Volume: exp(-5.85) Quality: ok Hinz: +0.0| +0.3 ********************************* | +1.0 Kunz: +0.0| +0.4 ******************************* | +1.0 Z=-3.7(83.88%) | Like=0.43..0.59 [0.4339..0.4339]*| it/evals=2340/3515 eff=75.1204% N=400 Z=-3.7(84.26%) | Like=0.44..0.59 [0.4383..0.4383]*| it/evals=2350/3529 eff=75.1039% N=400 Z=-3.7(85.99%) | Like=0.45..0.59 [0.4536..0.4538]*| it/evals=2400/3594 eff=75.1409% N=400 Mono-modal Volume: ~exp(-10.48) * Expected Volume: exp(-6.08) Quality: ok Hinz: +0.0| +0.4 ****************************** | +1.0 Kunz: +0.0| +0.4 ***************************** | +1.0 Z=-3.7(86.93%) | Like=0.46..0.59 [0.4626..0.4627]*| it/evals=2430/3634 eff=75.1391% N=400 Z=-3.6(87.52%) | Like=0.47..0.59 [0.4695..0.4695]*| it/evals=2450/3658 eff=75.1995% N=400 Z=-3.6(88.90%) | Like=0.49..0.59 [0.4854..0.4862]*| it/evals=2500/3731 eff=75.0525% N=400 Mono-modal Volume: ~exp(-10.68) * Expected Volume: exp(-6.30) Quality: ok Hinz: +0.0| +0.4 *************************** | +1.0 Kunz: +0.0| +0.4 ************************* | +1.0 Z=-3.6(89.42%) | Like=0.49..0.59 [0.4901..0.4901]*| it/evals=2520/3759 eff=75.0223% N=400 Z=-3.6(90.14%) | Like=0.50..0.59 [0.4964..0.4965]*| it/evals=2550/3792 eff=75.1769% N=400 Z=-3.6(91.25%) | Like=0.51..0.59 [0.5081..0.5085]*| it/evals=2600/3852 eff=75.3187% N=400 Mono-modal Volume: ~exp(-10.69) * Expected Volume: exp(-6.53) Quality: ok Hinz: +0.0| +0.4 ************************ | +1.0 Kunz: +0.0| +0.4 *********************** | +1.0 Z=-3.6(91.46%) | Like=0.51..0.59 [0.5109..0.5110]*| it/evals=2610/3865 eff=75.3247% N=400 Z=-3.6(92.24%) | Like=0.52..0.59 [0.5188..0.5189]*| it/evals=2650/3919 eff=75.3055% N=400 Mono-modal Volume: ~exp(-11.24) * Expected Volume: exp(-6.75) Quality: ok Hinz: +0.0| +0.4 ********************* | +1.0 Kunz: +0.0| +0.5 ********************* | +1.0 Z=-3.6(93.12%) | Like=0.53..0.59 [0.5284..0.5285]*| it/evals=2700/3994 eff=75.1252% N=400 Z=-3.6(93.91%) | Like=0.54..0.59 [0.5365..0.5367]*| it/evals=2750/4066 eff=75.0136% N=400 Mono-modal Volume: ~exp(-11.24) Expected Volume: exp(-6.98) Quality: ok Hinz: +0.0| +0.5 ******************* +0.8 | +1.0 Kunz: +0.0| +0.5 ****************** +0.8 | +1.0 Z=-3.6(94.61%) | Like=0.54..0.59 [0.5416..0.5417]*| it/evals=2800/4137 eff=74.9264% N=400 Z=-3.6(95.23%) | Like=0.55..0.59 [0.5472..0.5473]*| it/evals=2850/4211 eff=74.7835% N=400 Mono-modal Volume: ~exp(-11.33) * Expected Volume: exp(-7.20) Quality: ok Hinz: +0.0| +0.5 ****************** +0.8 | +1.0 Kunz: +0.0| +0.5 ***************** +0.8 | +1.0 Z=-3.6(95.56%) | Like=0.55..0.59 [0.5497..0.5498]*| it/evals=2880/4259 eff=74.6307% N=400 Z=-3.6(95.78%) | Like=0.55..0.59 [0.5517..0.5518]*| it/evals=2900/4283 eff=74.6845% N=400 Z=-3.6(96.26%) | Like=0.56..0.59 [0.5568..0.5568]*| it/evals=2950/4349 eff=74.7025% N=400 Mono-modal Volume: ~exp(-12.05) * Expected Volume: exp(-7.43) Quality: ok Hinz: +0.0| +0.5 *************** +0.8 | +1.0 Kunz: +0.0| +0.5 *************** +0.8 | +1.0 Z=-3.5(96.44%) | Like=0.56..0.59 [0.5591..0.5592]*| it/evals=2970/4377 eff=74.6794% N=400 Z=-3.5(96.70%) | Like=0.56..0.59 [0.5616..0.5618]*| it/evals=3000/4417 eff=74.6826% N=400 Z=-3.5(97.08%) | Like=0.57..0.59 [0.5651..0.5652]*| it/evals=3050/4483 eff=74.7000% N=400 Mono-modal Volume: ~exp(-12.05) Expected Volume: exp(-7.65) Quality: ok Hinz: +0.0| +0.5 *************** +0.8 | +1.0 Kunz: +0.0| +0.5 ************* +0.8 | +1.0 Z=-3.5(97.42%) | Like=0.57..0.59 [0.5679..0.5679]*| it/evals=3100/4552 eff=74.6628% N=400 Mono-modal Volume: ~exp(-12.28) * Expected Volume: exp(-7.88) Quality: ok Hinz: +0.0| +0.5 ************* +0.7 | +1.0 Kunz: +0.0| +0.5 ************ +0.7 | +1.0 Z=-3.5(97.72%) | Like=0.57..0.59 [0.5706..0.5707]*| it/evals=3150/4629 eff=74.4857% N=400 Z=-3.5(97.98%) | Like=0.57..0.59 [0.5730..0.5730]*| it/evals=3200/4692 eff=74.5573% N=400 Mono-modal Volume: ~exp(-12.40) * Expected Volume: exp(-8.10) Quality: ok Hinz: +0.0| +0.5 *********** +0.7 | +1.0 Kunz: +0.0| +0.5 *********** +0.7 | +1.0 Z=-3.5(98.17%) | Like=0.57..0.59 [0.5749..0.5749]*| it/evals=3240/4743 eff=74.6028% N=400 Z=-3.5(98.22%) | Like=0.58..0.59 [0.5752..0.5752]*| it/evals=3250/4757 eff=74.5926% N=400 Z=-3.5(98.43%) | Like=0.58..0.59 [0.5772..0.5772]*| it/evals=3300/4822 eff=74.6269% N=400 Mono-modal Volume: ~exp(-12.82) * Expected Volume: exp(-8.33) Quality: ok Hinz: +0.0| +0.5 *********** +0.7 | +1.0 Kunz: +0.0| +0.5 ********** +0.7 | +1.0 Z=-3.5(98.54%) | Like=0.58..0.59 [0.5788..0.5788]*| it/evals=3330/4858 eff=74.6972% N=400 Z=-3.5(98.61%) | Like=0.58..0.59 [0.5793..0.5793]*| it/evals=3350/4882 eff=74.7434% N=400 Z=-3.5(98.77%) | Like=0.58..0.59 [0.5811..0.5811]*| it/evals=3400/4940 eff=74.8899% N=400 Mono-modal Volume: ~exp(-12.99) * Expected Volume: exp(-8.55) Quality: ok Hinz: +0.0| +0.6 ********* +0.7 | +1.0 Kunz: +0.0| +0.6 ********* +0.7 | +1.0 Z=-3.5(98.83%) | Like=0.58..0.59 [0.5817..0.5817]*| it/evals=3420/4973 eff=74.7868% N=400 Z=-3.5(98.92%) | Like=0.58..0.59 [0.5824..0.5824]*| it/evals=3450/5012 eff=74.8049% N=400 [ultranest] Explored until L=0.6 [ultranest] Likelihood function evaluations: 5053 [ultranest] logZ = -3.495 +- 0.06646 [ultranest] Effective samples strategy satisfied (ESS = 1629.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.15, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.01 total:0.07 required:<0.50 [ultranest] done iterating. ncalls: 5055 nunique: 5055 {'niter': 3883, 'logz': -3.5129797392816973, 'logzerr': 0.15019082031188902, 'logz_bs': -3.4946153773041653, 'logz_single': -3.5129797392816973, 'logzerr_tail': 0.00993867560773154, 'logzerr_bs': 0.14986162028058558, 'ess': 1629.9116528926754, 'H': 3.093626125867617, 'Herr': 0.053276582247596176, 'posterior': {'mean': [0.6528641810663335, 0.6264357937278213], 'stdev': [0.5380843565640637, 0.5207584836042055], 'median': [0.6513496553807032, 0.634660513750779], 'errlo': [0.11736651751957705, 0.08940050480431339], 'errup': [1.193722161567365, 1.137157590020708], 'information_gain_bits': [0.6859949672653227, 0.7756177953890441]}, 'weighted_samples': {'upoints': array([[0.01988013, 0.02621099], [0.01833264, 0.066725 ], [0.08504421, 0.03905478], ..., [0.56409333, 0.5633068 ], [0.56303122, 0.5635434 ], [0.56347491, 0.56317946]]), 'points': array([[-4.80119866, -4.73789013], [-4.81667357, -4.33275002], [-4.14955789, -4.60945217], ..., [ 0.64093333, 0.63306805], [ 0.63031216, 0.63543397], [ 0.63474906, 0.63179457]]), 'weights': array([9.26018546e-50, 2.47035294e-46, 4.83768179e-43, ..., 2.50932121e-05, 2.50942808e-05, 2.50947339e-05]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -14.69896455, -14.69896455, -14.69896455]), 'bootstrapped_weights': array([[1.40582785e-49, 1.35668842e-49, 0.00000000e+00, ..., 1.36553936e-49, 1.51693786e-49, 1.46025903e-49], [0.00000000e+00, 3.61422607e-46, 4.17988021e-46, ..., 3.63785987e-46, 0.00000000e+00, 3.88958952e-46], [0.00000000e+00, 7.06788512e-43, 8.17277585e-43, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], ..., [0.00000000e+00, 4.11559930e-05, 4.44503916e-05, ..., 0.00000000e+00, 0.00000000e+00, 3.81059410e-05], [4.47343654e-05, 4.11577458e-05, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 4.44530874e-05, ..., 0.00000000e+00, 4.46347506e-05, 0.00000000e+00]]), 'logl': array([-110.42379603, -102.5323187 , -94.94998881, ..., 0.59307162, 0.59311421, 0.59313227])}, 'samples': array([[ 1.29700997, 0.39691822], [-0.25159545, 1.1739252 ], [ 0.49331732, -0.01375432], ..., [ 1.50143774, 0.56239362], [ 0.97385436, 1.10514422], [ 0.65458513, 0.52712821]]), 'maximum_likelihood': {'logl': 0.5931322698047243, 'point': [0.6347490626876349, 0.6317945702385996], 'point_untransformed': [0.5634749062687635, 0.56317945702386]}, 'ncall': 5053, 'paramnames': ['Hinz', 'Kunz'], 'logzerr_single': 0.08794353480881378, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=401, logz=-inf, remainder_fraction=100.0000%, Lmin=-110.42, Lmax=0.28 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=452, logz=-66.99, remainder_fraction=100.0000%, Lmin=-62.58, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=494, logz=-57.38, remainder_fraction=100.0000%, Lmin=-52.63, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=505, logz=-54.91, remainder_fraction=100.0000%, Lmin=-50.20, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=567, logz=-46.91, remainder_fraction=100.0000%, Lmin=-42.21, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=613, logz=-42.21, remainder_fraction=100.0000%, Lmin=-37.96, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=634, logz=-40.41, remainder_fraction=100.0000%, Lmin=-36.05, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=700, logz=-36.16, remainder_fraction=100.0000%, Lmin=-31.84, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=735, logz=-34.25, remainder_fraction=100.0000%, Lmin=-29.94, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=770, logz=-31.69, remainder_fraction=100.0000%, Lmin=-27.71, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=834, logz=-28.93, remainder_fraction=100.0000%, Lmin=-24.89, Lmax=0.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=907, logz=-25.35, remainder_fraction=100.0000%, Lmin=-20.82, Lmax=0.49 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=976, logz=-22.62, remainder_fraction=100.0000%, Lmin=-18.55, Lmax=0.49 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=1043, logz=-20.49, remainder_fraction=100.0000%, Lmin=-16.26, Lmax=0.49 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=1105, logz=-18.69, remainder_fraction=100.0000%, Lmin=-14.60, Lmax=0.51 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=1118, logz=-18.33, remainder_fraction=100.0000%, Lmin=-14.26, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=1179, logz=-16.64, remainder_fraction=99.9998%, Lmin=-12.62, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=1225, logz=-15.74, remainder_fraction=99.9995%, Lmin=-11.69, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=1250, logz=-15.21, remainder_fraction=99.9991%, Lmin=-11.26, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=1314, logz=-13.84, remainder_fraction=99.9968%, Lmin=-9.78, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=1378, logz=-12.73, remainder_fraction=99.9903%, Lmin=-8.72, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=1448, logz=-11.76, remainder_fraction=99.9742%, Lmin=-7.66, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=1516, logz=-10.71, remainder_fraction=99.9267%, Lmin=-6.56, Lmax=0.55 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1588, logz=-9.83, remainder_fraction=99.8233%, Lmin=-5.80, Lmax=0.56 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=1654, logz=-9.11, remainder_fraction=99.6334%, Lmin=-4.92, Lmax=0.57 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=1707, logz=-8.49, remainder_fraction=99.3057%, Lmin=-4.29, Lmax=0.57 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=1719, logz=-8.36, remainder_fraction=99.1963%, Lmin=-4.17, Lmax=0.57 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=1787, logz=-7.76, remainder_fraction=98.5780%, Lmin=-3.65, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=1835, logz=-7.44, remainder_fraction=98.0469%, Lmin=-3.36, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=1859, logz=-7.26, remainder_fraction=97.6487%, Lmin=-3.20, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=1926, logz=-6.82, remainder_fraction=96.4136%, Lmin=-2.70, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=1958, logz=-6.65, remainder_fraction=95.8254%, Lmin=-2.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=1996, logz=-6.43, remainder_fraction=94.7437%, Lmin=-2.40, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=2050, logz=-6.10, remainder_fraction=92.7134%, Lmin=-2.06, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=2061, logz=-6.04, remainder_fraction=92.1904%, Lmin=-2.00, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=2108, logz=-5.80, remainder_fraction=90.1182%, Lmin=-1.73, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=2169, logz=-5.54, remainder_fraction=87.2523%, Lmin=-1.48, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=2237, logz=-5.31, remainder_fraction=83.8089%, Lmin=-1.26, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=2295, logz=-5.14, remainder_fraction=80.6009%, Lmin=-1.09, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=2306, logz=-5.11, remainder_fraction=79.8571%, Lmin=-1.04, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=2374, logz=-4.93, remainder_fraction=76.0914%, Lmin=-0.91, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=2436, logz=-4.77, remainder_fraction=71.7238%, Lmin=-0.70, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=2513, logz=-4.62, remainder_fraction=67.2236%, Lmin=-0.54, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=2546, logz=-4.57, remainder_fraction=65.5165%, Lmin=-0.49, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=2581, logz=-4.50, remainder_fraction=62.8444%, Lmin=-0.40, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=2654, logz=-4.38, remainder_fraction=58.2874%, Lmin=-0.30, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=2670, logz=-4.36, remainder_fraction=57.3338%, Lmin=-0.29, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=2723, logz=-4.28, remainder_fraction=53.6176%, Lmin=-0.20, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=2788, logz=-4.20, remainder_fraction=49.4894%, Lmin=-0.09, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=2846, logz=-4.12, remainder_fraction=45.3322%, Lmin=-0.02, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=2909, logz=-4.05, remainder_fraction=41.3899%, Lmin=0.06, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=2986, logz=-3.99, remainder_fraction=37.6453%, Lmin=0.14, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=3032, logz=-3.95, remainder_fraction=35.5167%, Lmin=0.17, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=3058, logz=-3.93, remainder_fraction=34.0860%, Lmin=0.20, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=3130, logz=-3.88, remainder_fraction=30.7692%, Lmin=0.25, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=3198, logz=-3.84, remainder_fraction=27.6476%, Lmin=0.30, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=3266, logz=-3.80, remainder_fraction=24.7819%, Lmin=0.34, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=3281, logz=-3.79, remainder_fraction=24.2430%, Lmin=0.35, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=3327, logz=-3.76, remainder_fraction=22.1990%, Lmin=0.37, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=3400, logz=-3.73, remainder_fraction=19.8044%, Lmin=0.40, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=3462, logz=-3.71, remainder_fraction=17.6802%, Lmin=0.42, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2340, ncalls=3515, logz=-3.69, remainder_fraction=16.1212%, Lmin=0.43, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=3529, logz=-3.68, remainder_fraction=15.7410%, Lmin=0.44, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3594, logz=-3.66, remainder_fraction=14.0103%, Lmin=0.45, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3634, logz=-3.65, remainder_fraction=13.0726%, Lmin=0.46, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3658, logz=-3.65, remainder_fraction=12.4782%, Lmin=0.47, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3731, logz=-3.63, remainder_fraction=11.0953%, Lmin=0.49, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=3759, logz=-3.62, remainder_fraction=10.5813%, Lmin=0.49, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3792, logz=-3.62, remainder_fraction=9.8607%, Lmin=0.50, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3852, logz=-3.60, remainder_fraction=8.7482%, Lmin=0.51, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3865, logz=-3.60, remainder_fraction=8.5412%, Lmin=0.51, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3919, logz=-3.59, remainder_fraction=7.7618%, Lmin=0.52, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3994, logz=-3.58, remainder_fraction=6.8783%, Lmin=0.53, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=4066, logz=-3.58, remainder_fraction=6.0943%, Lmin=0.54, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=4137, logz=-3.57, remainder_fraction=5.3940%, Lmin=0.54, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=4211, logz=-3.56, remainder_fraction=4.7748%, Lmin=0.55, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2880, ncalls=4259, logz=-3.56, remainder_fraction=4.4363%, Lmin=0.55, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2900, ncalls=4283, logz=-3.56, remainder_fraction=4.2245%, Lmin=0.55, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2950, ncalls=4349, logz=-3.55, remainder_fraction=3.7367%, Lmin=0.56, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2970, ncalls=4377, logz=-3.55, remainder_fraction=3.5573%, Lmin=0.56, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3000, ncalls=4417, logz=-3.55, remainder_fraction=3.3040%, Lmin=0.56, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3050, ncalls=4483, logz=-3.54, remainder_fraction=2.9209%, Lmin=0.57, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3100, ncalls=4552, logz=-3.54, remainder_fraction=2.5820%, Lmin=0.57, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3150, ncalls=4629, logz=-3.54, remainder_fraction=2.2817%, Lmin=0.57, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3200, ncalls=4692, logz=-3.53, remainder_fraction=2.0165%, Lmin=0.57, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3240, ncalls=4743, logz=-3.53, remainder_fraction=1.8265%, Lmin=0.57, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3250, ncalls=4757, logz=-3.53, remainder_fraction=1.7818%, Lmin=0.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3300, ncalls=4822, logz=-3.53, remainder_fraction=1.5739%, Lmin=0.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3330, ncalls=4858, logz=-3.53, remainder_fraction=1.4610%, Lmin=0.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3350, ncalls=4882, logz=-3.53, remainder_fraction=1.3902%, Lmin=0.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3400, ncalls=4940, logz=-3.53, remainder_fraction=1.2278%, Lmin=0.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3420, ncalls=4973, logz=-3.52, remainder_fraction=1.1682%, Lmin=0.58, Lmax=0.59 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3450, ncalls=5012, logz=-3.52, remainder_fraction=1.0842%, Lmin=0.58, Lmax=0.59 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=0.6 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 5053 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -3.495 +- 0.06646 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1629.9, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.15, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.07 tail:0.01 total:0.07 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:2647 Making corner plot ... [35mDEBUG [0m ultranest:integrator.py:2693 Making run plot ... [35mDEBUG [0m ultranest:integrator.py:2669 Making trace plot ... | |||
Passed | tests/test_run.py::test_return_summary | 4.15 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.13) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-2791.49..9.91 [-2791.4854..9.5619] | it/evals=0/401 eff=0.0000% N=400 Z=-2148.7(0.00%) | Like=-2139.23..9.91 [-2791.4854..9.5619] | it/evals=40/444 eff=90.9091% N=400 Z=-1718.8(0.00%) | Like=-1711.95..9.91 [-2791.4854..9.5619] | it/evals=80/484 eff=95.2381% N=400 Mono-modal Volume: ~exp(-4.66) * Expected Volume: exp(-0.23) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| **********************************************| +1.0 Z=-1595.1(0.00%) | Like=-1586.09..9.91 [-2791.4854..9.5619] | it/evals=90/494 eff=95.7447% N=400 Z=-1255.6(0.00%) | Like=-1247.82..9.91 [-2791.4854..9.5619] | it/evals=120/527 eff=94.4882% N=400 Z=-937.5(0.00%) | Like=-924.32..9.91 [-2791.4854..9.5619] | it/evals=160/570 eff=94.1176% N=400 Mono-modal Volume: ~exp(-4.67) * Expected Volume: exp(-0.45) Quality: ok a: +0.0000|********************************************************| +1.0000 b: +0.0| +0.3 *************************************| +1.0 Z=-805.6(0.00%) | Like=-795.31..9.91 [-2791.4854..9.5619] | it/evals=180/591 eff=94.2408% N=400 Z=-693.5(0.00%) | Like=-683.46..9.91 [-2791.4854..9.5619] | it/evals=200/613 eff=93.8967% N=400 Z=-482.5(0.00%) | Like=-467.19..9.91 [-2791.4854..9.5619] | it/evals=240/655 eff=94.1176% N=400 Mono-modal Volume: ~exp(-5.05) * Expected Volume: exp(-0.67) Quality: ok a: +0.000|************** *****************************************| +1.000 b: +0.0| +0.5 ******************************| +1.0 Z=-382.3(0.00%) | Like=-370.95..9.94 [-2791.4854..9.5619] | it/evals=270/693 eff=92.1502% N=400 Z=-346.7(0.00%) | Like=-332.57..9.94 [-2791.4854..9.5619] | it/evals=280/704 eff=92.1053% N=400 Z=-278.4(0.00%) | Like=-269.56..9.94 [-2791.4854..9.5619] | it/evals=320/747 eff=92.2190% N=400 Mono-modal Volume: ~exp(-5.05) Expected Volume: exp(-0.90) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| +0.5 ************************* | +1.0 Z=-238.2(0.00%) | Like=-231.02..9.94 [-2791.4854..9.5619] | it/evals=360/791 eff=92.0716% N=400 Z=-190.7(0.00%) | Like=-183.25..10.10 [-2791.4854..9.5619] | it/evals=400/841 eff=90.7029% N=400 Z=-166.2(0.00%) | Like=-157.82..10.13 [-2791.4854..9.5619] | it/evals=440/893 eff=89.2495% N=400 Mono-modal Volume: ~exp(-5.27) * Expected Volume: exp(-1.12) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| +0.6 ********************* | +1.0 Z=-161.1(0.00%) | Like=-152.40..10.13 [-2791.4854..9.5619] | it/evals=450/908 eff=88.5827% N=400 Z=-132.3(0.00%) | Like=-125.63..10.13 [-2791.4854..9.5619] | it/evals=480/945 eff=88.0734% N=400 Z=-109.2(0.00%) | Like=-102.31..10.13 [-2791.4854..9.5619] | it/evals=520/990 eff=88.1356% N=400 Mono-modal Volume: ~exp(-5.42) * Expected Volume: exp(-1.35) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| +0.6 ***************** | +1.0 Z=-101.2(0.00%) | Like=-94.53..10.13 [-2791.4854..9.5619] | it/evals=540/1016 eff=87.6623% N=400 Z=-88.8(0.00%) | Like=-81.41..10.13 [-2791.4854..9.5619] | it/evals=560/1040 eff=87.5000% N=400 Z=-73.6(0.00%) | Like=-66.76..10.13 [-2791.4854..9.5619] | it/evals=600/1091 eff=86.8307% N=400 Mono-modal Volume: ~exp(-5.42) Expected Volume: exp(-1.57) Quality: ok a: +0.000|******* ************************************************| +1.000 b: +0.0| +0.6 ************** | +1.0 Z=-60.9(0.00%) | Like=-54.71..10.13 [-2791.4854..9.5619] | it/evals=640/1145 eff=85.9060% N=400 Z=-48.5(0.00%) | Like=-41.38..10.13 [-2791.4854..9.5619] | it/evals=680/1209 eff=84.0544% N=400 Mono-modal Volume: ~exp(-5.93) * Expected Volume: exp(-1.80) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| +0.7 ************ | +1.0 Z=-39.5(0.00%) | Like=-32.99..10.13 [-2791.4854..9.5619] | it/evals=720/1258 eff=83.9161% N=400 Z=-31.3(0.00%) | Like=-24.77..10.13 [-2791.4854..9.5619] | it/evals=760/1302 eff=84.2572% N=400 Z=-25.4(0.00%) | Like=-19.27..10.13 [-2791.4854..9.5619] | it/evals=800/1352 eff=84.0336% N=400 Mono-modal Volume: ~exp(-6.05) * Expected Volume: exp(-2.02) Quality: ok a: +0.000|************** *****************************************| +1.000 b: +0.0| +0.7 ********** | +1.0 Z=-24.0(0.00%) | Like=-18.08..10.13 [-2791.4854..9.5619] | it/evals=810/1362 eff=84.1996% N=400 Z=-20.8(0.00%) | Like=-15.18..10.13 [-2791.4854..9.5619] | it/evals=840/1395 eff=84.4221% N=400 Z=-17.3(0.00%) | Like=-11.39..10.13 [-2791.4854..9.5619] | it/evals=880/1448 eff=83.9695% N=400 Mono-modal Volume: ~exp(-6.60) * Expected Volume: exp(-2.25) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| +0.7 ******** +0.8 | +1.0 Z=-15.4(0.00%) | Like=-9.69..10.13 [-2791.4854..9.5619] | it/evals=900/1472 eff=83.9552% N=400 Z=-13.9(0.00%) | Like=-8.12..10.13 [-2791.4854..9.5619] | it/evals=920/1495 eff=84.0183% N=400 Z=-11.1(0.00%) | Like=-5.68..10.13 [-2791.4854..9.5619] | it/evals=960/1546 eff=83.7696% N=400 Mono-modal Volume: ~exp(-6.60) Expected Volume: exp(-2.47) Quality: ok a: +0.000|********************************************************| +1.000 b: +0.0| +0.7 ****** +0.8 | +1.0 Z=-9.4(0.00%) | Like=-4.23..10.13 [-2791.4854..9.5619] | it/evals=1000/1605 eff=82.9876% N=400 Z=-7.9(0.00%) | Like=-2.57..10.13 [-2791.4854..9.5619] | it/evals=1040/1655 eff=82.8685% N=400 Mono-modal Volume: ~exp(-6.74) * Expected Volume: exp(-2.70) Quality: ok a: +0.00| ************************************************* **** | +1.00 b: +0.0| +0.7 ****** +0.8 | +1.0 Z=-6.6(0.00%) | Like=-1.57..10.13 [-2791.4854..9.5619] | it/evals=1080/1707 eff=82.6320% N=400 Z=-5.5(0.00%) | Like=-0.16..10.13 [-2791.4854..9.5619] | it/evals=1120/1755 eff=82.6568% N=400 Z=-4.4(0.01%) | Like=0.78..10.13 [-2791.4854..9.5619] | it/evals=1160/1816 eff=81.9209% N=400 Mono-modal Volume: ~exp(-7.03) * Expected Volume: exp(-2.92) Quality: ok a: +0.00| ********************************************** * | +1.00 b: +0.0| +0.7 ****** +0.8 | +1.0 Z=-4.1(0.01%) | Like=0.95..10.13 [-2791.4854..9.5619] | it/evals=1170/1831 eff=81.7610% N=400 Z=-3.5(0.02%) | Like=1.60..10.13 [-2791.4854..9.5619] | it/evals=1200/1867 eff=81.7996% N=400 Z=-2.6(0.04%) | Like=2.56..10.13 [-2791.4854..9.5619] | it/evals=1240/1918 eff=81.6864% N=400 Mono-modal Volume: ~exp(-7.24) * Expected Volume: exp(-3.15) Quality: ok a: +0.0| ******************************************* | +1.0 b: +0.0| +0.7 ****** +0.8 | +1.0 Z=-2.2(0.06%) | Like=2.93..10.13 [-2791.4854..9.5619] | it/evals=1260/1944 eff=81.6062% N=400 Z=-1.9(0.09%) | Like=3.40..10.13 [-2791.4854..9.5619] | it/evals=1280/1967 eff=81.6847% N=400 Z=-1.2(0.19%) | Like=3.87..10.13 [-2791.4854..9.5619] | it/evals=1320/2014 eff=81.7844% N=400 Mono-modal Volume: ~exp(-7.73) * Expected Volume: exp(-3.37) Quality: ok a: +0.0| ************************************** | +1.0 b: +0.0| +0.7 **** +0.8 | +1.0 Z=-0.8(0.30%) | Like=4.39..10.13 [-2791.4854..9.5619] | it/evals=1350/2055 eff=81.5710% N=400 Z=-0.6(0.34%) | Like=4.52..10.13 [-2791.4854..9.5619] | it/evals=1360/2070 eff=81.4371% N=400 Z=-0.0(0.62%) | Like=5.18..10.13 [-2791.4854..9.5619] | it/evals=1400/2121 eff=81.3481% N=400 Mono-modal Volume: ~exp(-7.84) * Expected Volume: exp(-3.60) Quality: ok a: +0.0| +0.2 ********************************** +0.8 | +1.0 b: +0.0| +0.7 **** +0.8 | +1.0 Z=0.5(1.02%) | Like=5.65..10.13 [-2791.4854..9.5619] | it/evals=1440/2178 eff=80.9899% N=400 Z=0.9(1.55%) | Like=6.00..10.13 [-2791.4854..9.5619] | it/evals=1480/2235 eff=80.6540% N=400 Z=1.3(2.32%) | Like=6.52..10.13 [-2791.4854..9.5619] | it/evals=1520/2287 eff=80.5511% N=400 Mono-modal Volume: ~exp(-8.39) * Expected Volume: exp(-3.82) Quality: ok a: +0.0| +0.2 ****************************** +0.8 | +1.0 b: +0.0| +0.7 **** +0.8 | +1.0 Z=1.4(2.56%) | Like=6.63..10.13 [-2791.4854..9.5619] | it/evals=1530/2302 eff=80.4416% N=400 Z=1.7(3.43%) | Like=6.93..10.13 [-2791.4854..9.5619] | it/evals=1560/2341 eff=80.3709% N=400 Z=2.0(4.83%) | Like=7.19..10.13 [-2791.4854..9.5619] | it/evals=1600/2397 eff=80.1202% N=400 Mono-modal Volume: ~exp(-8.58) * Expected Volume: exp(-4.05) Quality: ok a: +0.0| +0.3 *************************** +0.7 | +1.0 b: +0.0| +0.7 **** +0.8 | +1.0 Z=2.2(5.66%) | Like=7.35..10.13 [-2791.4854..9.5619] | it/evals=1620/2424 eff=80.0395% N=400 Z=2.3(6.58%) | Like=7.49..10.13 [-2791.4854..9.5619] | it/evals=1640/2452 eff=79.9220% N=400 Z=2.6(8.55%) | Like=7.74..10.13 [-2791.4854..9.5619] | it/evals=1680/2496 eff=80.1527% N=400 Mono-modal Volume: ~exp(-8.89) * Expected Volume: exp(-4.27) Quality: ok a: +0.0| +0.3 *********************** +0.7 | +1.0 b: +0.0| +0.7 **** +0.8 | +1.0 Z=2.8(10.30%) | Like=7.99..10.13 [-2791.4854..9.5619] | it/evals=1710/2536 eff=80.0562% N=400 Z=2.9(10.95%) | Like=8.05..10.13 [-2791.4854..9.5619] | it/evals=1720/2549 eff=80.0372% N=400 Z=3.1(13.77%) | Like=8.24..10.13 [-2791.4854..9.5619] | it/evals=1760/2603 eff=79.8911% N=400 Mono-modal Volume: ~exp(-8.89) * Expected Volume: exp(-4.50) Quality: ok a: +0.0| +0.3 ********************** +0.7 | +1.0 b: +0.0| +0.7 *** +0.8 | +1.0 Z=3.3(16.62%) | Like=8.37..10.13 [-2791.4854..9.5619] | it/evals=1800/2664 eff=79.5053% N=400 Z=3.5(19.73%) | Like=8.54..10.13 [-2791.4854..9.5619] | it/evals=1840/2716 eff=79.4473% N=400 Z=3.6(23.13%) | Like=8.76..10.13 [-2791.4854..9.5619] | it/evals=1880/2769 eff=79.3584% N=400 Mono-modal Volume: ~exp(-8.89) Expected Volume: exp(-4.73) Quality: ok a: +0.0| +0.3 ******************* +0.7 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=3.8(26.83%) | Like=8.88..10.13 [-2791.4854..9.5619] | it/evals=1920/2822 eff=79.2733% N=400 Z=3.9(30.57%) | Like=8.99..10.14 [-2791.4854..9.5619] | it/evals=1960/2874 eff=79.2239% N=400 Mono-modal Volume: ~exp(-9.50) * Expected Volume: exp(-4.95) Quality: ok a: +0.0| +0.4 ****************** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=3.9(32.62%) | Like=9.05..10.14 [-2791.4854..9.5619] | it/evals=1980/2905 eff=79.0419% N=400 Z=4.0(34.45%) | Like=9.09..10.14 [-2791.4854..9.5619] | it/evals=2000/2932 eff=78.9889% N=400 Z=4.1(38.31%) | Like=9.19..10.14 [-2791.4854..9.5619] | it/evals=2040/2989 eff=78.7949% N=400 Mono-modal Volume: ~exp(-9.94) * Expected Volume: exp(-5.18) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.2(41.18%) | Like=9.26..10.14 [-2791.4854..9.5619] | it/evals=2070/3029 eff=78.7372% N=400 Z=4.2(42.03%) | Like=9.28..10.14 [-2791.4854..9.5619] | it/evals=2080/3039 eff=78.8177% N=400 Z=4.3(45.67%) | Like=9.36..10.14 [-2791.4854..9.5619] | it/evals=2120/3087 eff=78.8984% N=400 Mono-modal Volume: ~exp(-9.94) Expected Volume: exp(-5.40) Quality: ok a: +0.0| +0.4 ************** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.4(49.26%) | Like=9.41..10.14 [-2791.4854..9.5619] | it/evals=2160/3140 eff=78.8321% N=400 Z=4.4(52.72%) | Like=9.48..10.14 [-2791.4854..9.5619] | it/evals=2200/3199 eff=78.5995% N=400 Z=4.5(55.93%) | Like=9.55..10.14 [-2791.4854..9.5619] | it/evals=2240/3257 eff=78.4039% N=400 Mono-modal Volume: ~exp(-10.07) * Expected Volume: exp(-5.63) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.5(56.73%) | Like=9.56..10.14 [-2791.4854..9.5619] | it/evals=2250/3269 eff=78.4245% N=400 Z=4.5(59.08%) | Like=9.60..10.14 [9.6014..9.6025]*| it/evals=2280/3306 eff=78.4584% N=400 Z=4.6(62.08%) | Like=9.64..10.14 [9.6440..9.6457]*| it/evals=2320/3357 eff=78.4579% N=400 Mono-modal Volume: ~exp(-10.07) Expected Volume: exp(-5.85) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.6(64.77%) | Like=9.69..10.14 [9.6937..9.6975]*| it/evals=2360/3413 eff=78.3272% N=400 Z=4.7(67.48%) | Like=9.74..10.14 [9.7388..9.7394]*| it/evals=2400/3469 eff=78.2014% N=400 Mono-modal Volume: ~exp(-10.68) * Expected Volume: exp(-6.08) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.7(69.37%) | Like=9.76..10.14 [9.7644..9.7649]*| it/evals=2430/3506 eff=78.2357% N=400 Z=4.7(70.00%) | Like=9.77..10.14 [9.7735..9.7744]*| it/evals=2440/3517 eff=78.2804% N=400 Z=4.8(72.40%) | Like=9.81..10.14 [9.8146..9.8156]*| it/evals=2480/3565 eff=78.3570% N=400 Mono-modal Volume: ~exp(-10.71) * Expected Volume: exp(-6.30) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.8(74.67%) | Like=9.85..10.14 [9.8495..9.8504]*| it/evals=2520/3621 eff=78.2366% N=400 Z=4.8(76.81%) | Like=9.88..10.14 [9.8769..9.8787]*| it/evals=2560/3672 eff=78.2396% N=400 Z=4.8(78.77%) | Like=9.90..10.14 [9.9031..9.9033]*| it/evals=2600/3730 eff=78.0781% N=400 Mono-modal Volume: ~exp(-10.71) Expected Volume: exp(-6.53) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.9(80.58%) | Like=9.92..10.14 [9.9235..9.9239]*| it/evals=2640/3782 eff=78.0603% N=400 Z=4.9(82.27%) | Like=9.94..10.14 [9.9440..9.9447]*| it/evals=2680/3839 eff=77.9296% N=400 Mono-modal Volume: ~exp(-11.00) * Expected Volume: exp(-6.75) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.9(83.06%) | Like=9.96..10.14 [9.9557..9.9562]*| it/evals=2700/3873 eff=77.7426% N=400 Z=4.9(83.81%) | Like=9.96..10.14 [9.9629..9.9630]*| it/evals=2720/3903 eff=77.6477% N=400 Z=4.9(85.24%) | Like=9.98..10.14 [9.9776..9.9781]*| it/evals=2760/3959 eff=77.5499% N=400 Mono-modal Volume: ~exp(-11.00) Expected Volume: exp(-6.98) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.0| +0.7 ** +0.8 | +1.0 Z=4.9(86.54%) | Like=9.99..10.14 [9.9912..9.9913]*| it/evals=2800/4022 eff=77.3054% N=400 Z=4.9(87.74%) | Like=10.01..10.14 [10.0059..10.0059]*| it/evals=2840/4076 eff=77.2579% N=400 Mono-modal Volume: ~exp(-11.41) * Expected Volume: exp(-7.20) Quality: ok a: +0.00| +0.45 ****** +0.55 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(88.84%) | Like=10.02..10.14 [10.0179..10.0190]*| it/evals=2880/4132 eff=77.1704% N=400 Z=5.0(89.84%) | Like=10.03..10.14 [10.0310..10.0311]*| it/evals=2920/4182 eff=77.2078% N=400 Z=5.0(90.76%) | Like=10.04..10.14 [10.0409..10.0410]*| it/evals=2960/4248 eff=76.9231% N=400 Mono-modal Volume: ~exp(-11.65) * Expected Volume: exp(-7.43) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(90.98%) | Like=10.04..10.14 [10.0439..10.0441]*| it/evals=2970/4262 eff=76.9032% N=400 Z=5.0(91.60%) | Like=10.05..10.14 [10.0503..10.0504]*| it/evals=3000/4294 eff=77.0416% N=400 Z=5.0(92.37%) | Like=10.06..10.14 [10.0592..10.0594]*| it/evals=3040/4342 eff=77.1182% N=400 Mono-modal Volume: ~exp(-11.87) * Expected Volume: exp(-7.65) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(92.73%) | Like=10.06..10.14 [10.0639..10.0648]*| it/evals=3060/4371 eff=77.0587% N=400 Z=5.0(93.07%) | Like=10.07..10.14 [10.0667..10.0671]*| it/evals=3080/4392 eff=77.1543% N=400 Z=5.0(93.70%) | Like=10.07..10.14 [10.0750..10.0752]*| it/evals=3120/4450 eff=77.0370% N=400 Mono-modal Volume: ~exp(-11.87) Expected Volume: exp(-7.88) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(94.29%) | Like=10.08..10.14 [10.0794..10.0795]*| it/evals=3160/4506 eff=76.9605% N=400 Z=5.0(94.82%) | Like=10.08..10.14 [10.0845..10.0850]*| it/evals=3200/4567 eff=76.7939% N=400 Mono-modal Volume: ~exp(-12.44) * Expected Volume: exp(-8.10) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(95.30%) | Like=10.09..10.14 [10.0903..10.0903]*| it/evals=3240/4620 eff=76.7773% N=400 Z=5.0(95.73%) | Like=10.09..10.14 [10.0949..10.0950]*| it/evals=3280/4670 eff=76.8150% N=400 Z=5.0(96.13%) | Like=10.10..10.14 [10.0986..10.0986]*| it/evals=3320/4722 eff=76.8163% N=400 Mono-modal Volume: ~exp(-12.58) * Expected Volume: exp(-8.33) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(96.22%) | Like=10.10..10.14 [10.0998..10.0998]*| it/evals=3330/4734 eff=76.8343% N=400 Z=5.0(96.49%) | Like=10.10..10.14 [10.1035..10.1035]*| it/evals=3360/4773 eff=76.8351% N=400 Z=5.0(96.82%) | Like=10.11..10.14 [10.1063..10.1063]*| it/evals=3400/4829 eff=76.7668% N=400 Mono-modal Volume: ~exp(-12.62) * Expected Volume: exp(-8.55) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(96.97%) | Like=10.11..10.14 [10.1083..10.1086]*| it/evals=3420/4854 eff=76.7849% N=400 Z=5.0(97.12%) | Like=10.11..10.14 [10.1098..10.1098]*| it/evals=3440/4882 eff=76.7515% N=400 Z=5.0(97.39%) | Like=10.11..10.14 [10.1137..10.1137]*| it/evals=3480/4935 eff=76.7365% N=400 Mono-modal Volume: ~exp(-13.47) * Expected Volume: exp(-8.78) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.0(97.57%) | Like=10.12..10.14 [10.1162..10.1163]*| it/evals=3510/4975 eff=76.7213% N=400 Z=5.0(97.63%) | Like=10.12..10.14 [10.1168..10.1169]*| it/evals=3520/4986 eff=76.7553% N=400 Z=5.1(97.86%) | Like=10.12..10.14 [10.1187..10.1187]*| it/evals=3560/5042 eff=76.6911% N=400 Mono-modal Volume: ~exp(-13.47) Expected Volume: exp(-9.00) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.1(98.06%) | Like=10.12..10.14 [10.1202..10.1202]*| it/evals=3600/5089 eff=76.7754% N=400 Z=5.1(98.24%) | Like=10.12..10.14 [10.1222..10.1222]*| it/evals=3640/5135 eff=76.8743% N=400 Z=5.1(98.41%) | Like=10.12..10.14 [10.1240..10.1241]*| it/evals=3680/5190 eff=76.8267% N=400 Mono-modal Volume: ~exp(-13.47) Expected Volume: exp(-9.23) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.1(98.56%) | Like=10.13..10.14 [10.1257..10.1258]*| it/evals=3720/5236 eff=76.9231% N=400 Z=5.1(98.69%) | Like=10.13..10.14 [10.1270..10.1270]*| it/evals=3760/5292 eff=76.8602% N=400 Mono-modal Volume: ~exp(-13.87) * Expected Volume: exp(-9.45) Quality: ok a: +0.00| +0.48 ** +0.51 | +1.00 b: +0.0| +0.7 ** +0.8 | +1.0 Z=5.1(98.76%) | Like=10.13..10.14 [10.1275..10.1275]*| it/evals=3780/5321 eff=76.8137% N=400 Z=5.1(98.82%) | Like=10.13..10.14 [10.1282..10.1282]*| it/evals=3800/5344 eff=76.8608% N=400 Z=5.1(98.93%) | Like=10.13..10.14 [10.1289..10.1289]*| it/evals=3840/5393 eff=76.9077% N=400 [ultranest] Explored until L=1e+01 [ultranest] Likelihood function evaluations: 5428 [ultranest] logZ = 5.061 +- 0.07247 [ultranest] Effective samples strategy satisfied (ESS = 1575.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.12, need <0.5) [ultranest] logZ error budget: single: 0.10 bs:0.07 tail:0.01 total:0.07 required:<0.50 [ultranest] done iterating. {'niter': 4268, 'logz': 5.072093035741405, 'logzerr': 0.11837805530088492, 'logz_bs': 5.061458886075594, 'logz_single': 5.072093035741405, 'logzerr_tail': 0.00993124211471308, 'logzerr_bs': 0.11796073247855965, 'ess': 1575.0183105741953, 'H': 4.087188734808281, 'Herr': 0.07102138967494825, 'posterior': {'mean': [0.4965835316598401, 0.7501064450977161], 'stdev': [0.10099859711226661, 0.009707628694915751], 'median': [0.4965325603087882, 0.7501706380816336], 'errlo': [0.3933488492704615, 0.7402816223772167], 'errup': [0.6003420410903435, 0.7595352995047611], 'information_gain_bits': [-1.9107352984160901, 3.4609791719968843]}, 'weighted_samples': {'upoints': array([[0.30187078, 0.00171363], [0.95493601, 0.00581425], [0.95117894, 0.00830578], ..., [0.5012239 , 0.75000996], [0.49895706, 0.75005148], [0.5002795 , 0.74996783]]), 'points': array([[0.30187078, 0.00171363], [0.95493601, 0.00581425], [0.95117894, 0.00830578], ..., [0.5012239 , 0.75000996], [0.49895706, 0.75005148], [0.5002795 , 0.74996783]]), 'weights': array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 2.50690497e-05, 2.50692442e-05, 2.50707122e-05]), 'logw': array([ -5.99271429, -5.99521429, -5.99771429, ..., -15.66146455, -15.66146455, -15.66146455]), 'bootstrapped_weights': array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ..., 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], ..., [0.00000000e+00, 4.63842793e-05, 0.00000000e+00, ..., 0.00000000e+00, 3.64154106e-05, 0.00000000e+00], [4.09096217e-05, 4.63846390e-05, 3.83904198e-05, ..., 0.00000000e+00, 3.64156930e-05, 4.63917802e-05], [0.00000000e+00, 4.63873552e-05, 0.00000000e+00, ..., 3.57156848e-05, 3.64178254e-05, 4.63944967e-05]]), 'logl': array([-2791.48544009, -2769.27072051, -2750.58996186, ..., 10.13968103, 10.13968879, 10.13974734])}, 'samples': array([[0.59530049, 0.75647723], [0.40771282, 0.74505146], [0.56408907, 0.73633409], ..., [0.35210306, 0.73840614], [0.54574849, 0.75235101], [0.74549798, 0.74616706]]), 'maximum_likelihood': {'logl': 10.139747343213443, 'point': [0.5002795024048327, 0.749967825934594], 'point_untransformed': [0.5002795024048327, 0.749967825934594]}, 'ncall': 5428, 'paramnames': ['a', 'b'], 'logzerr_single': 0.10108398407769997, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=False, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=401, logz=-inf, remainder_fraction=100.0000%, Lmin=-2791.49, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=444, logz=-2148.71, remainder_fraction=100.0000%, Lmin=-2139.23, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=484, logz=-1718.80, remainder_fraction=100.0000%, Lmin=-1711.95, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=494, logz=-1595.06, remainder_fraction=100.0000%, Lmin=-1586.09, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=527, logz=-1255.58, remainder_fraction=100.0000%, Lmin=-1247.82, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=570, logz=-937.45, remainder_fraction=100.0000%, Lmin=-924.32, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=591, logz=-805.57, remainder_fraction=100.0000%, Lmin=-795.31, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=613, logz=-693.47, remainder_fraction=100.0000%, Lmin=-683.46, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=655, logz=-482.53, remainder_fraction=100.0000%, Lmin=-467.19, Lmax=9.91 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=693, logz=-382.26, remainder_fraction=100.0000%, Lmin=-370.95, Lmax=9.94 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=704, logz=-346.71, remainder_fraction=100.0000%, Lmin=-332.57, Lmax=9.94 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=747, logz=-278.35, remainder_fraction=100.0000%, Lmin=-269.56, Lmax=9.94 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=791, logz=-238.21, remainder_fraction=100.0000%, Lmin=-231.02, Lmax=9.94 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=841, logz=-190.70, remainder_fraction=100.0000%, Lmin=-183.25, Lmax=10.10 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=440, ncalls=893, logz=-166.20, remainder_fraction=100.0000%, Lmin=-157.82, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=908, logz=-161.05, remainder_fraction=100.0000%, Lmin=-152.40, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=480, ncalls=945, logz=-132.33, remainder_fraction=100.0000%, Lmin=-125.63, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=520, ncalls=990, logz=-109.17, remainder_fraction=100.0000%, Lmin=-102.31, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=1016, logz=-101.16, remainder_fraction=100.0000%, Lmin=-94.53, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=560, ncalls=1040, logz=-88.79, remainder_fraction=100.0000%, Lmin=-81.41, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=1091, logz=-73.64, remainder_fraction=100.0000%, Lmin=-66.76, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=640, ncalls=1145, logz=-60.89, remainder_fraction=100.0000%, Lmin=-54.71, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=680, ncalls=1209, logz=-48.48, remainder_fraction=100.0000%, Lmin=-41.38, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=1258, logz=-39.46, remainder_fraction=100.0000%, Lmin=-32.99, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=760, ncalls=1302, logz=-31.31, remainder_fraction=100.0000%, Lmin=-24.77, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=1352, logz=-25.37, remainder_fraction=100.0000%, Lmin=-19.27, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=1362, logz=-24.04, remainder_fraction=100.0000%, Lmin=-18.08, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=840, ncalls=1395, logz=-20.84, remainder_fraction=100.0000%, Lmin=-15.18, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=880, ncalls=1448, logz=-17.26, remainder_fraction=100.0000%, Lmin=-11.39, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1472, logz=-15.42, remainder_fraction=100.0000%, Lmin=-9.69, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=920, ncalls=1495, logz=-13.86, remainder_fraction=100.0000%, Lmin=-8.12, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=960, ncalls=1546, logz=-11.13, remainder_fraction=100.0000%, Lmin=-5.68, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=1605, logz=-9.44, remainder_fraction=100.0000%, Lmin=-4.23, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1040, ncalls=1655, logz=-7.89, remainder_fraction=99.9998%, Lmin=-2.57, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=1707, logz=-6.63, remainder_fraction=99.9992%, Lmin=-1.57, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1120, ncalls=1755, logz=-5.47, remainder_fraction=99.9975%, Lmin=-0.16, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1160, ncalls=1816, logz=-4.36, remainder_fraction=99.9923%, Lmin=0.78, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=1831, logz=-4.13, remainder_fraction=99.9901%, Lmin=0.95, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=1867, logz=-3.51, remainder_fraction=99.9818%, Lmin=1.60, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1240, ncalls=1918, logz=-2.62, remainder_fraction=99.9559%, Lmin=2.56, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=1944, logz=-2.25, remainder_fraction=99.9370%, Lmin=2.93, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1280, ncalls=1967, logz=-1.86, remainder_fraction=99.9052%, Lmin=3.40, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1320, ncalls=2014, logz=-1.19, remainder_fraction=99.8123%, Lmin=3.87, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=2055, logz=-0.75, remainder_fraction=99.6992%, Lmin=4.39, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1360, ncalls=2070, logz=-0.61, remainder_fraction=99.6558%, Lmin=4.52, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=2121, logz=-0.03, remainder_fraction=99.3759%, Lmin=5.18, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=2178, logz=0.48, remainder_fraction=98.9788%, Lmin=5.65, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1480, ncalls=2235, logz=0.92, remainder_fraction=98.4515%, Lmin=6.00, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1520, ncalls=2287, logz=1.31, remainder_fraction=97.6848%, Lmin=6.52, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=2302, logz=1.41, remainder_fraction=97.4410%, Lmin=6.63, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1560, ncalls=2341, logz=1.70, remainder_fraction=96.5694%, Lmin=6.93, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=2397, logz=2.04, remainder_fraction=95.1683%, Lmin=7.19, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=2424, logz=2.20, remainder_fraction=94.3378%, Lmin=7.35, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1640, ncalls=2452, logz=2.35, remainder_fraction=93.4167%, Lmin=7.49, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1680, ncalls=2496, logz=2.61, remainder_fraction=91.4495%, Lmin=7.74, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=2536, logz=2.80, remainder_fraction=89.7018%, Lmin=7.99, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1720, ncalls=2549, logz=2.86, remainder_fraction=89.0544%, Lmin=8.05, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1760, ncalls=2603, logz=3.09, remainder_fraction=86.2314%, Lmin=8.24, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=2664, logz=3.29, remainder_fraction=83.3784%, Lmin=8.37, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1840, ncalls=2716, logz=3.45, remainder_fraction=80.2670%, Lmin=8.54, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1880, ncalls=2769, logz=3.61, remainder_fraction=76.8715%, Lmin=8.76, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1920, ncalls=2822, logz=3.76, remainder_fraction=73.1725%, Lmin=8.88, Lmax=10.13 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1960, ncalls=2874, logz=3.89, remainder_fraction=69.4333%, Lmin=8.99, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=2905, logz=3.95, remainder_fraction=67.3788%, Lmin=9.05, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=2932, logz=4.00, remainder_fraction=65.5475%, Lmin=9.09, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2040, ncalls=2989, logz=4.11, remainder_fraction=61.6933%, Lmin=9.19, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=3029, logz=4.18, remainder_fraction=58.8200%, Lmin=9.26, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2080, ncalls=3039, logz=4.20, remainder_fraction=57.9748%, Lmin=9.28, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2120, ncalls=3087, logz=4.28, remainder_fraction=54.3326%, Lmin=9.36, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=3140, logz=4.36, remainder_fraction=50.7397%, Lmin=9.41, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=3199, logz=4.43, remainder_fraction=47.2817%, Lmin=9.48, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2240, ncalls=3257, logz=4.49, remainder_fraction=44.0670%, Lmin=9.55, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=3269, logz=4.50, remainder_fraction=43.2654%, Lmin=9.56, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2280, ncalls=3306, logz=4.54, remainder_fraction=40.9178%, Lmin=9.60, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2320, ncalls=3357, logz=4.59, remainder_fraction=37.9169%, Lmin=9.64, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2360, ncalls=3413, logz=4.64, remainder_fraction=35.2308%, Lmin=9.69, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3469, logz=4.68, remainder_fraction=32.5208%, Lmin=9.74, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3506, logz=4.71, remainder_fraction=30.6264%, Lmin=9.76, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2440, ncalls=3517, logz=4.72, remainder_fraction=30.0048%, Lmin=9.77, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2480, ncalls=3565, logz=4.75, remainder_fraction=27.5976%, Lmin=9.81, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=3621, logz=4.78, remainder_fraction=25.3267%, Lmin=9.85, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2560, ncalls=3672, logz=4.81, remainder_fraction=23.1873%, Lmin=9.88, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3730, logz=4.83, remainder_fraction=21.2264%, Lmin=9.90, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2640, ncalls=3782, logz=4.86, remainder_fraction=19.4241%, Lmin=9.92, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2680, ncalls=3839, logz=4.88, remainder_fraction=17.7319%, Lmin=9.94, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3873, logz=4.89, remainder_fraction=16.9423%, Lmin=9.96, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2720, ncalls=3903, logz=4.90, remainder_fraction=16.1929%, Lmin=9.96, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2760, ncalls=3959, logz=4.91, remainder_fraction=14.7616%, Lmin=9.98, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=4022, logz=4.93, remainder_fraction=13.4614%, Lmin=9.99, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2840, ncalls=4076, logz=4.94, remainder_fraction=12.2623%, Lmin=10.01, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2880, ncalls=4132, logz=4.95, remainder_fraction=11.1635%, Lmin=10.02, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2920, ncalls=4182, logz=4.96, remainder_fraction=10.1587%, Lmin=10.03, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2960, ncalls=4248, logz=4.98, remainder_fraction=9.2395%, Lmin=10.04, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2970, ncalls=4262, logz=4.98, remainder_fraction=9.0228%, Lmin=10.04, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3000, ncalls=4294, logz=4.98, remainder_fraction=8.4032%, Lmin=10.05, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3040, ncalls=4342, logz=4.99, remainder_fraction=7.6324%, Lmin=10.06, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3060, ncalls=4371, logz=5.00, remainder_fraction=7.2717%, Lmin=10.06, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3080, ncalls=4392, logz=5.00, remainder_fraction=6.9310%, Lmin=10.07, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3120, ncalls=4450, logz=5.01, remainder_fraction=6.2960%, Lmin=10.07, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3160, ncalls=4506, logz=5.01, remainder_fraction=5.7136%, Lmin=10.08, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3200, ncalls=4567, logz=5.02, remainder_fraction=5.1837%, Lmin=10.08, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3240, ncalls=4620, logz=5.02, remainder_fraction=4.7045%, Lmin=10.09, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3280, ncalls=4670, logz=5.03, remainder_fraction=4.2659%, Lmin=10.09, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3320, ncalls=4722, logz=5.03, remainder_fraction=3.8691%, Lmin=10.10, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3330, ncalls=4734, logz=5.03, remainder_fraction=3.7762%, Lmin=10.10, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3360, ncalls=4773, logz=5.04, remainder_fraction=3.5082%, Lmin=10.10, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3400, ncalls=4829, logz=5.04, remainder_fraction=3.1796%, Lmin=10.11, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3420, ncalls=4854, logz=5.04, remainder_fraction=3.0273%, Lmin=10.11, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3440, ncalls=4882, logz=5.04, remainder_fraction=2.8825%, Lmin=10.11, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3480, ncalls=4935, logz=5.05, remainder_fraction=2.6119%, Lmin=10.11, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3510, ncalls=4975, logz=5.05, remainder_fraction=2.4253%, Lmin=10.12, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3520, ncalls=4986, logz=5.05, remainder_fraction=2.3662%, Lmin=10.12, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3560, ncalls=5042, logz=5.05, remainder_fraction=2.1437%, Lmin=10.12, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3600, ncalls=5089, logz=5.05, remainder_fraction=1.9415%, Lmin=10.12, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3640, ncalls=5135, logz=5.05, remainder_fraction=1.7580%, Lmin=10.12, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3680, ncalls=5190, logz=5.06, remainder_fraction=1.5922%, Lmin=10.12, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3720, ncalls=5236, logz=5.06, remainder_fraction=1.4417%, Lmin=10.13, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3760, ncalls=5292, logz=5.06, remainder_fraction=1.3052%, Lmin=10.13, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3780, ncalls=5321, logz=5.06, remainder_fraction=1.2420%, Lmin=10.13, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3800, ncalls=5344, logz=5.06, remainder_fraction=1.1818%, Lmin=10.13, Lmax=10.14 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3840, ncalls=5393, logz=5.06, remainder_fraction=1.0700%, Lmin=10.13, Lmax=10.14 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=1e+01 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 5428 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = 5.061 +- 0.07247 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1575.0, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.06 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.12, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.10 bs:0.07 tail:0.01 total:0.07 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_run_resume[2.0] | 5.89 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.32) * Expected Volume: exp(0.00) Quality: ok a: +0.0000|********************************************************| +1.0000 Z=-inf(0.00%) | Like=-1245.39..3.65 [-1245.3896..3.5736] | it/evals=0/500 eff=0.0000% N=400 Z=-990.5(0.00%) | Like=-981.54..3.68 [-1245.3896..3.5736] | it/evals=50/500 eff=50.0000% N=400 Mono-modal Volume: ~exp(-4.32) Expected Volume: exp(-0.23) Quality: ok a: +0.00| ************************************************ | +1.00 Z=-823.2(0.00%) | Like=-812.27..3.68 [-1245.3896..3.5736] | it/evals=100/609 eff=47.8469% N=400 Z=-626.4(0.00%) | Like=-615.76..3.68 [-1245.3896..3.5736] | it/evals=150/609 eff=71.7703% N=400 Mono-modal Volume: ~exp(-4.59) * Expected Volume: exp(-0.45) Quality: ok a: +0.0| ************************************** | +1.0 Z=-543.9(0.00%) | Like=-534.44..3.69 [-1245.3896..3.5736] | it/evals=180/609 eff=86.1244% N=400 Z=-498.6(0.00%) | Like=-492.04..3.69 [-1245.3896..3.5736] | it/evals=200/695 eff=67.7966% N=400 Z=-387.0(0.00%) | Like=-379.22..3.69 [-1245.3896..3.5736] | it/evals=250/695 eff=84.7458% N=400 Mono-modal Volume: ~exp(-4.90) * Expected Volume: exp(-0.67) Quality: ok a: +0.0| +0.2 ****************************** +0.8 | +1.0 Z=-354.3(0.00%) | Like=-345.17..3.69 [-1245.3896..3.5736] | it/evals=270/763 eff=74.3802% N=400 Z=-309.4(0.00%) | Like=-302.94..3.69 [-1245.3896..3.5736] | it/evals=300/763 eff=82.6446% N=400 Z=-233.6(0.00%) | Like=-224.53..3.69 [-1245.3896..3.5736] | it/evals=350/824 eff=82.5472% N=400 Have 3 modes Volume: ~exp(-5.25) * Expected Volume: exp(-0.90) Quality: ok a: +0.0| +0.3 222222222222222231111111 +0.7 | +1.0 Z=-219.5(0.00%) | Like=-213.07..3.69 [-1245.3896..3.5736] | it/evals=360/824 eff=84.9057% N=400 Z=-182.5(0.00%) | Like=-175.31..3.69 [-1245.3896..3.5736] | it/evals=400/874 eff=84.3882% N=400 Have 3 modes Volume: ~exp(-5.25) Expected Volume: exp(-1.12) Quality: ok a: +0.0| +0.3 22222222222222311111 +0.7 | +1.0 Z=-139.5(0.00%) | Like=-133.48..3.69 [-1245.3896..3.5736] | it/evals=450/920 eff=86.5385% N=400 Z=-113.4(0.00%) | Like=-106.86..3.69 [-1245.3896..3.5736] | it/evals=500/963 eff=88.8099% N=400 Mono-modal Volume: ~exp(-5.35) * Expected Volume: exp(-1.35) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 Z=-92.5(0.00%) | Like=-86.35..3.69 [-1245.3896..3.5736] | it/evals=540/1034 eff=85.1735% N=400 Z=-89.9(0.00%) | Like=-84.15..3.69 [-1245.3896..3.5736] | it/evals=550/1034 eff=86.7508% N=400 Z=-69.0(0.00%) | Like=-61.63..3.69 [-1245.3896..3.5736] | it/evals=600/1070 eff=89.5522% N=400 Mono-modal Volume: ~exp(-5.70) * Expected Volume: exp(-1.57) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-58.9(0.00%) | Like=-52.62..3.69 [-1245.3896..3.5736] | it/evals=630/1103 eff=89.6159% N=400 Z=-51.8(0.00%) | Like=-45.46..3.69 [-1245.3896..3.5736] | it/evals=650/1131 eff=88.9193% N=400 Z=-38.8(0.00%) | Like=-32.28..3.69 [-1245.3896..3.5736] | it/evals=700/1180 eff=89.7436% N=400 Mono-modal Volume: ~exp(-5.75) * Expected Volume: exp(-1.80) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 Z=-34.9(0.00%) | Like=-28.85..3.69 [-1245.3896..3.5736] | it/evals=720/1200 eff=90.0000% N=400 Z=-29.7(0.00%) | Like=-23.75..3.69 [-1245.3896..3.5736] | it/evals=750/1224 eff=91.0194% N=400 Z=-23.0(0.00%) | Like=-17.00..3.69 [-1245.3896..3.5736] | it/evals=800/1269 eff=92.0598% N=400 Mono-modal Volume: ~exp(-5.96) * Expected Volume: exp(-2.02) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-21.6(0.00%) | Like=-15.56..3.69 [-1245.3896..3.5736] | it/evals=810/1289 eff=91.1136% N=400 Z=-18.0(0.00%) | Like=-12.45..3.69 [-1245.3896..3.5736] | it/evals=850/1338 eff=90.6183% N=400 Mono-modal Volume: ~exp(-6.48) * Expected Volume: exp(-2.25) Quality: ok a: +0.0| +0.4 ****** +0.6 | +1.0 Z=-14.8(0.00%) | Like=-9.46..3.69 [-1245.3896..3.5736] | it/evals=900/1373 eff=92.4974% N=400 Z=-12.0(0.00%) | Like=-6.45..3.69 [-1245.3896..3.5736] | it/evals=950/1435 eff=91.7874% N=400 Mono-modal Volume: ~exp(-6.67) * Expected Volume: exp(-2.47) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-9.9(0.00%) | Like=-4.24..3.69 [-1245.3896..3.5736] | it/evals=990/1467 eff=92.7835% N=400 Z=-9.4(0.01%) | Like=-3.97..3.69 [-1245.3896..3.5736] | it/evals=1000/1480 eff=92.5926% N=400 Z=-7.2(0.06%) | Like=-1.88..3.69 [-1245.3896..3.5736] | it/evals=1050/1543 eff=91.8635% N=400 Mono-modal Volume: ~exp(-7.04) * Expected Volume: exp(-2.70) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.3(0.17%) | Like=-1.16..3.69 [-1245.3896..3.5736] | it/evals=1080/1573 eff=92.0716% N=400 Z=-5.8(0.30%) | Like=-0.73..3.69 [-1245.3896..3.5736] | it/evals=1100/1597 eff=91.8964% N=400 Z=-4.8(0.82%) | Like=0.10..3.69 [-1245.3896..3.5736] | it/evals=1150/1643 eff=92.5181% N=400 Mono-modal Volume: ~exp(-7.04) Expected Volume: exp(-2.92) Quality: ok a: +0.00| +0.47 **** +0.52 | +1.00 Z=-3.9(1.95%) | Like=0.91..3.69 [-1245.3896..3.5736] | it/evals=1200/1699 eff=92.3788% N=400 Z=-3.2(3.96%) | Like=1.61..3.69 [-1245.3896..3.5736] | it/evals=1250/1746 eff=92.8678% N=400 Mono-modal Volume: ~exp(-7.08) * Expected Volume: exp(-3.15) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.0(4.52%) | Like=1.74..3.69 [-1245.3896..3.5736] | it/evals=1260/1756 eff=92.9204% N=400 Z=-2.6(7.06%) | Like=2.03..3.69 [-1245.3896..3.5736] | it/evals=1300/1799 eff=92.9235% N=400 Mono-modal Volume: ~exp(-7.46) * Expected Volume: exp(-3.37) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 Z=-2.2(11.02%) | Like=2.35..3.69 [-1245.3896..3.5736] | it/evals=1350/1849 eff=93.1677% N=400 Z=-1.8(15.65%) | Like=2.62..3.69 [-1245.3896..3.5736] | it/evals=1400/1903 eff=93.1470% N=400 Mono-modal Volume: ~exp(-7.95) * Expected Volume: exp(-3.60) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(19.84%) | Like=2.84..3.69 [-1245.3896..3.5736] | it/evals=1440/2029 eff=88.3978% N=400 Z=-1.5(20.87%) | Like=2.87..3.69 [-1245.3896..3.5736] | it/evals=1450/2029 eff=89.0117% N=400 Z=-1.3(26.62%) | Like=3.04..3.69 [-1245.3896..3.5736] | it/evals=1500/2029 eff=92.0810% N=400 Mono-modal Volume: ~exp(-7.95) Expected Volume: exp(-3.82) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.1(32.62%) | Like=3.17..3.69 [-1245.3896..3.5736] | it/evals=1550/2147 eff=88.7235% N=400 Z=-0.9(38.53%) | Like=3.28..3.69 [-1245.3896..3.5736] | it/evals=1600/2147 eff=91.5856% N=400 Mono-modal Volume: ~exp(-8.10) * Expected Volume: exp(-4.05) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.9(40.81%) | Like=3.32..3.69 [-1245.3896..3.5736] | it/evals=1620/2248 eff=87.6623% N=400 Z=-0.8(44.20%) | Like=3.38..3.69 [-1245.3896..3.5736] | it/evals=1650/2248 eff=89.2857% N=400 Z=-0.7(49.70%) | Like=3.45..3.69 [-1245.3896..3.5736] | it/evals=1700/2249 eff=91.9416% N=400 Mono-modal Volume: ~exp(-8.55) * Expected Volume: exp(-4.27) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(50.75%) | Like=3.46..3.69 [-1245.3896..3.5736] | it/evals=1710/2261 eff=91.8861% N=400 Z=-0.6(54.87%) | Like=3.51..3.69 [-1245.3896..3.5736] | it/evals=1750/2389 eff=87.9839% N=400 Mono-modal Volume: ~exp(-8.89) * Expected Volume: exp(-4.50) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(59.70%) | Like=3.55..3.69 [-1245.3896..3.5736] | it/evals=1800/2389 eff=90.4977% N=400 Z=-0.4(64.08%) | Like=3.58..3.69 [3.5769..3.5771]*| it/evals=1850/2430 eff=91.1330% N=400 Mono-modal Volume: ~exp(-8.99) * Expected Volume: exp(-4.73) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.3(67.27%) | Like=3.59..3.69 [3.5925..3.5925]*| it/evals=1890/2477 eff=90.9966% N=400 Z=-0.3(68.04%) | Like=3.60..3.69 [3.5972..3.5972]*| it/evals=1900/2477 eff=91.4781% N=400 Z=-0.3(71.62%) | Like=3.61..3.69 [3.6147..3.6154]*| it/evals=1950/2537 eff=91.2494% N=400 Mono-modal Volume: ~exp(-9.13) * Expected Volume: exp(-4.95) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(73.59%) | Like=3.63..3.69 [3.6260..3.6263]*| it/evals=1980/2563 eff=91.5395% N=400 Z=-0.2(74.83%) | Like=3.63..3.69 [3.6314..3.6315]*| it/evals=2000/2686 eff=87.4891% N=400 Z=-0.2(77.69%) | Like=3.64..3.69 [3.6419..3.6426]*| it/evals=2050/2686 eff=89.6763% N=400 Mono-modal Volume: ~exp(-9.41) * Expected Volume: exp(-5.18) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.2(78.75%) | Like=3.65..3.69 [3.6458..3.6458]*| it/evals=2070/2686 eff=90.5512% N=400 Z=-0.2(80.25%) | Like=3.65..3.69 [3.6504..3.6504]*| it/evals=2100/2693 eff=91.5831% N=400 Z=-0.1(82.53%) | Like=3.66..3.69 [3.6602..3.6602]*| it/evals=2150/2804 eff=89.4343% N=400 Mono-modal Volume: ~exp(-9.55) * Expected Volume: exp(-5.40) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(82.95%) | Like=3.66..3.69 [3.6619..3.6622]*| it/evals=2160/2804 eff=89.8502% N=400 Z=-0.1(84.55%) | Like=3.67..3.69 [3.6668..3.6669]*| it/evals=2200/2815 eff=91.0973% N=400 Mono-modal Volume: ~exp(-9.69) * Expected Volume: exp(-5.63) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(86.35%) | Like=3.67..3.69 [3.6696..3.6697]*| it/evals=2250/2988 eff=86.9397% N=400 Z=-0.1(87.94%) | Like=3.67..3.69 [3.6730..3.6731]*| it/evals=2300/2988 eff=88.8717% N=400 Mono-modal Volume: ~exp(-9.99) * Expected Volume: exp(-5.85) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.08%) | Like=3.68..3.69 [3.6751..3.6752]*| it/evals=2340/2988 eff=90.4173% N=400 Z=-0.1(89.34%) | Like=3.68..3.69 [3.6758..3.6758]*| it/evals=2350/2988 eff=90.8037% N=400 Z=-0.1(90.59%) | Like=3.68..3.69 [3.6780..3.6780]*| it/evals=2400/3107 eff=88.6590% N=400 Mono-modal Volume: ~exp(-10.24) * Expected Volume: exp(-6.08) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(91.27%) | Like=3.68..3.69 [3.6792..3.6793]*| it/evals=2430/3107 eff=89.7673% N=400 Z=-0.0(91.69%) | Like=3.68..3.69 [3.6799..3.6799]*| it/evals=2450/3107 eff=90.5061% N=400 Z=-0.0(92.66%) | Like=3.68..3.69 [3.6814..3.6814]*| it/evals=2500/3226 eff=88.4643% N=400 Mono-modal Volume: ~exp(-10.24) Expected Volume: exp(-6.30) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(93.52%) | Like=3.68..3.69 [3.6826..3.6826]*| it/evals=2550/3226 eff=90.2335% N=400 Z=-0.0(94.28%) | Like=3.68..3.69 [3.6833..3.6834]*| it/evals=2600/3310 eff=89.3471% N=400 Mono-modal Volume: ~exp(-10.67) * Expected Volume: exp(-6.53) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.42%) | Like=3.68..3.69 [3.6835..3.6835]*| it/evals=2610/3310 eff=89.6907% N=400 Z=-0.0(94.95%) | Like=3.68..3.69 [3.6840..3.6840]*| it/evals=2650/3419 eff=87.7774% N=400 Have 2 modes Volume: ~exp(-10.76) * Expected Volume: exp(-6.75) Quality: ok a: +0.000| +0.499 11 +0.501 | +1.000 Z=0.0(95.54%) | Like=3.68..3.69 [3.6845..3.6845]*| it/evals=2700/3419 eff=89.4336% N=400 Z=0.0(96.07%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=2750/3539 eff=87.6075% N=400 Have 2 modes Volume: ~exp(-10.76) Expected Volume: exp(-6.98) Quality: ok a: +0.0000| +0.4996 11 +0.5004 | +1.0000 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3539 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.05055 +- 0.06921 [ultranest] Effective samples strategy satisfied (ESS = 1268.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.13, need <2.0) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<2.00 [ultranest] done iterating. logZ = 0.047 +- 0.123 single instance: logZ = 0.047 +- 0.089 bootstrapped : logZ = 0.051 +- 0.119 tail : logZ = +- 0.035 insert order U test : converged: True correlation: inf iterations a 0.500 +- 0.010 [ultranest] Resuming from 3430 stored points Mono-modal Volume: ~exp(-4.18) * Expected Volume: exp(0.00) Quality: ok a: +0.0000|********************************************************| +1.0000 Z=-inf(0.00%) | Like=-1245.39..3.65 [-1245.3896..3.5736] | it/evals=0/3539 eff=inf% N=400 Z=-990.5(0.00%) | Like=-981.54..3.68 [-1245.3896..3.5736] | it/evals=50/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-4.26) * Expected Volume: exp(-0.23) Quality: ok a: +0.00| ************************************************ | +1.00 Z=-861.8(0.00%) | Like=-854.74..3.68 [-1245.3896..3.5736] | it/evals=90/3539 eff=inf% N=400 Z=-823.2(0.00%) | Like=-812.27..3.68 [-1245.3896..3.5736] | it/evals=100/3539 eff=inf% N=400 Z=-626.4(0.00%) | Like=-615.76..3.68 [-1245.3896..3.5736] | it/evals=150/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-4.30) * Expected Volume: exp(-0.45) Quality: ok a: +0.0| ************************************** | +1.0 Z=-543.9(0.00%) | Like=-534.44..3.69 [-1245.3896..3.5736] | it/evals=180/3539 eff=inf% N=400 Z=-498.6(0.00%) | Like=-492.04..3.69 [-1245.3896..3.5736] | it/evals=200/3539 eff=inf% N=400 Z=-387.0(0.00%) | Like=-379.22..3.69 [-1245.3896..3.5736] | it/evals=250/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-4.49) * Expected Volume: exp(-0.67) Quality: ok a: +0.0| +0.2 ****************************** +0.8 | +1.0 Z=-354.3(0.00%) | Like=-345.17..3.69 [-1245.3896..3.5736] | it/evals=270/3539 eff=inf% N=400 Z=-309.4(0.00%) | Like=-302.94..3.69 [-1245.3896..3.5736] | it/evals=300/3539 eff=inf% N=400 Z=-233.6(0.00%) | Like=-224.53..3.69 [-1245.3896..3.5736] | it/evals=350/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-4.78) * Expected Volume: exp(-0.90) Quality: ok a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-219.5(0.00%) | Like=-213.07..3.69 [-1245.3896..3.5736] | it/evals=360/3539 eff=inf% N=400 Z=-182.5(0.00%) | Like=-175.31..3.69 [-1245.3896..3.5736] | it/evals=400/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-5.06) * Expected Volume: exp(-1.12) Quality: ok a: +0.0| +0.3 ******************** +0.7 | +1.0 Z=-139.5(0.00%) | Like=-133.48..3.69 [-1245.3896..3.5736] | it/evals=450/3539 eff=inf% N=400 Z=-113.4(0.00%) | Like=-106.86..3.69 [-1245.3896..3.5736] | it/evals=500/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-5.39) * Expected Volume: exp(-1.35) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 Z=-92.5(0.00%) | Like=-86.35..3.69 [-1245.3896..3.5736] | it/evals=540/3539 eff=inf% N=400 Z=-89.9(0.00%) | Like=-84.15..3.69 [-1245.3896..3.5736] | it/evals=550/3539 eff=inf% N=400 Z=-69.0(0.00%) | Like=-61.63..3.69 [-1245.3896..3.5736] | it/evals=600/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-5.41) * Expected Volume: exp(-1.57) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-58.9(0.00%) | Like=-52.62..3.69 [-1245.3896..3.5736] | it/evals=630/3539 eff=inf% N=400 Z=-51.8(0.00%) | Like=-45.46..3.69 [-1245.3896..3.5736] | it/evals=650/3539 eff=inf% N=400 Z=-38.8(0.00%) | Like=-32.28..3.69 [-1245.3896..3.5736] | it/evals=700/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-5.70) * Expected Volume: exp(-1.80) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 Z=-34.9(0.00%) | Like=-28.85..3.69 [-1245.3896..3.5736] | it/evals=720/3539 eff=inf% N=400 Z=-29.7(0.00%) | Like=-23.75..3.69 [-1245.3896..3.5736] | it/evals=750/3539 eff=inf% N=400 Z=-23.0(0.00%) | Like=-17.00..3.69 [-1245.3896..3.5736] | it/evals=800/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-6.20) * Expected Volume: exp(-2.02) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-21.6(0.00%) | Like=-15.56..3.69 [-1245.3896..3.5736] | it/evals=810/3539 eff=inf% N=400 Z=-18.0(0.00%) | Like=-12.45..3.69 [-1245.3896..3.5736] | it/evals=850/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-6.20) Expected Volume: exp(-2.25) Quality: ok a: +0.0| +0.4 ****** +0.6 | +1.0 Z=-14.8(0.00%) | Like=-9.46..3.69 [-1245.3896..3.5736] | it/evals=900/3539 eff=inf% N=400 Z=-12.0(0.00%) | Like=-6.45..3.69 [-1245.3896..3.5736] | it/evals=950/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-6.81) * Expected Volume: exp(-2.47) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-9.9(0.00%) | Like=-4.24..3.69 [-1245.3896..3.5736] | it/evals=990/3539 eff=inf% N=400 Z=-9.4(0.01%) | Like=-3.97..3.69 [-1245.3896..3.5736] | it/evals=1000/3539 eff=inf% N=400 Z=-7.2(0.06%) | Like=-1.88..3.69 [-1245.3896..3.5736] | it/evals=1050/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-7.23) * Expected Volume: exp(-2.70) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.3(0.17%) | Like=-1.16..3.69 [-1245.3896..3.5736] | it/evals=1080/3539 eff=inf% N=400 Z=-5.8(0.30%) | Like=-0.73..3.69 [-1245.3896..3.5736] | it/evals=1100/3539 eff=inf% N=400 Z=-4.8(0.82%) | Like=0.10..3.69 [-1245.3896..3.5736] | it/evals=1150/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-7.23) Expected Volume: exp(-2.92) Quality: ok a: +0.00| +0.47 **** +0.52 | +1.00 Z=-3.9(1.95%) | Like=0.91..3.69 [-1245.3896..3.5736] | it/evals=1200/3539 eff=inf% N=400 Z=-3.2(3.96%) | Like=1.61..3.69 [-1245.3896..3.5736] | it/evals=1250/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-7.26) * Expected Volume: exp(-3.15) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.0(4.52%) | Like=1.74..3.69 [-1245.3896..3.5736] | it/evals=1260/3539 eff=inf% N=400 Z=-2.6(7.06%) | Like=2.03..3.69 [-1245.3896..3.5736] | it/evals=1300/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-7.60) * Expected Volume: exp(-3.37) Quality: ok a: +0.00| +0.48 ** +0.52 | +1.00 Z=-2.2(11.02%) | Like=2.35..3.69 [-1245.3896..3.5736] | it/evals=1350/3539 eff=inf% N=400 Z=-1.8(15.65%) | Like=2.62..3.69 [-1245.3896..3.5736] | it/evals=1400/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-7.70) * Expected Volume: exp(-3.60) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(19.84%) | Like=2.84..3.69 [-1245.3896..3.5736] | it/evals=1440/3539 eff=inf% N=400 Z=-1.5(20.87%) | Like=2.87..3.69 [-1245.3896..3.5736] | it/evals=1450/3539 eff=inf% N=400 Z=-1.3(26.62%) | Like=3.04..3.69 [-1245.3896..3.5736] | it/evals=1500/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-7.94) * Expected Volume: exp(-3.82) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.2(30.24%) | Like=3.15..3.69 [-1245.3896..3.5736] | it/evals=1530/3539 eff=inf% N=400 Z=-1.1(32.62%) | Like=3.17..3.69 [-1245.3896..3.5736] | it/evals=1550/3539 eff=inf% N=400 Z=-0.9(38.53%) | Like=3.28..3.69 [-1245.3896..3.5736] | it/evals=1600/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-8.19) * Expected Volume: exp(-4.05) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.9(40.81%) | Like=3.32..3.69 [-1245.3896..3.5736] | it/evals=1620/3539 eff=inf% N=400 Z=-0.8(44.20%) | Like=3.38..3.69 [-1245.3896..3.5736] | it/evals=1650/3539 eff=inf% N=400 Z=-0.7(49.70%) | Like=3.45..3.69 [-1245.3896..3.5736] | it/evals=1700/3539 eff=inf% N=400 Have 2 modes Volume: ~exp(-8.21) * Expected Volume: exp(-4.27) Quality: ok a: +0.00| +0.49 21 +0.51 | +1.00 Z=-0.6(50.75%) | Like=3.46..3.69 [-1245.3896..3.5736] | it/evals=1710/3539 eff=inf% N=400 Z=-0.6(54.87%) | Like=3.51..3.69 [-1245.3896..3.5736] | it/evals=1750/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-8.65) * Expected Volume: exp(-4.50) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(59.70%) | Like=3.55..3.69 [-1245.3896..3.5736] | it/evals=1800/3539 eff=inf% N=400 Z=-0.4(64.08%) | Like=3.58..3.69 [3.5769..3.5771]*| it/evals=1850/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-8.95) * Expected Volume: exp(-4.73) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.3(67.27%) | Like=3.59..3.69 [3.5925..3.5925]*| it/evals=1890/3539 eff=inf% N=400 Z=-0.3(68.04%) | Like=3.60..3.69 [3.5972..3.5972]*| it/evals=1900/3539 eff=inf% N=400 Z=-0.3(71.62%) | Like=3.61..3.69 [3.6147..3.6154]*| it/evals=1950/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-9.15) * Expected Volume: exp(-4.95) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(73.59%) | Like=3.63..3.69 [3.6260..3.6263]*| it/evals=1980/3539 eff=inf% N=400 Z=-0.2(74.83%) | Like=3.63..3.69 [3.6314..3.6315]*| it/evals=2000/3539 eff=inf% N=400 Z=-0.2(77.69%) | Like=3.64..3.69 [3.6419..3.6426]*| it/evals=2050/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-9.31) * Expected Volume: exp(-5.18) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.2(78.75%) | Like=3.65..3.69 [3.6458..3.6458]*| it/evals=2070/3539 eff=inf% N=400 Z=-0.2(80.25%) | Like=3.65..3.69 [3.6504..3.6504]*| it/evals=2100/3539 eff=inf% N=400 Z=-0.1(82.53%) | Like=3.66..3.69 [3.6602..3.6602]*| it/evals=2150/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-9.46) * Expected Volume: exp(-5.40) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(82.95%) | Like=3.66..3.69 [3.6619..3.6622]*| it/evals=2160/3539 eff=inf% N=400 Z=-0.1(84.55%) | Like=3.67..3.69 [3.6668..3.6669]*| it/evals=2200/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-9.75) * Expected Volume: exp(-5.63) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(86.35%) | Like=3.67..3.69 [3.6696..3.6697]*| it/evals=2250/3539 eff=inf% N=400 Z=-0.1(87.94%) | Like=3.67..3.69 [3.6730..3.6731]*| it/evals=2300/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-9.99) * Expected Volume: exp(-5.85) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.08%) | Like=3.68..3.69 [3.6751..3.6752]*| it/evals=2340/3539 eff=inf% N=400 Z=-0.1(89.34%) | Like=3.68..3.69 [3.6758..3.6758]*| it/evals=2350/3539 eff=inf% N=400 Z=-0.1(90.59%) | Like=3.68..3.69 [3.6780..3.6780]*| it/evals=2400/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-10.24) * Expected Volume: exp(-6.08) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(91.27%) | Like=3.68..3.69 [3.6792..3.6793]*| it/evals=2430/3539 eff=inf% N=400 Z=-0.0(91.69%) | Like=3.68..3.69 [3.6799..3.6799]*| it/evals=2450/3539 eff=inf% N=400 Z=-0.0(92.66%) | Like=3.68..3.69 [3.6814..3.6814]*| it/evals=2500/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-10.51) * Expected Volume: exp(-6.30) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(93.02%) | Like=3.68..3.69 [3.6818..3.6818]*| it/evals=2520/3539 eff=inf% N=400 Z=-0.0(93.52%) | Like=3.68..3.69 [3.6826..3.6826]*| it/evals=2550/3539 eff=inf% N=400 Z=-0.0(94.28%) | Like=3.68..3.69 [3.6833..3.6834]*| it/evals=2600/3539 eff=inf% N=400 Mono-modal Volume: ~exp(-10.61) * Expected Volume: exp(-6.53) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.42%) | Like=3.68..3.69 [3.6835..3.6835]*| it/evals=2610/3539 eff=inf% N=400 Z=-0.0(94.95%) | Like=3.68..3.69 [3.6840..3.6840]*| it/evals=2650/3539 eff=inf% N=400 Have 2 modes Volume: ~exp(-11.06) * Expected Volume: exp(-6.75) Quality: ok a: +0.000| +0.499 11 +0.501 | +1.000 Z=0.0(95.54%) | Like=3.68..3.69 [3.6845..3.6845]*| it/evals=2700/3539 eff=inf% N=400 Z=0.0(96.07%) | Like=3.68..3.69 [3.6849..3.6849]*| it/evals=2750/3539 eff=inf% N=400 Have 2 modes Volume: ~exp(-11.14) * Expected Volume: exp(-6.98) Quality: ok a: +0.0000| +0.4996 11 +0.5004 | +1.0000 Z=0.0(96.44%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2790/3539 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3539 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.05879 +- 0.07442 [ultranest] Effective samples strategy satisfied (ESS = 1268.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.19, need <2.0) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<2.00 [ultranest] done iterating. logZ = 0.047 +- 0.191 single instance: logZ = 0.047 +- 0.089 bootstrapped : logZ = 0.059 +- 0.188 tail : logZ = +- 0.035 insert order U test : converged: True correlation: inf iterations a 0.500 +- 0.010 ran with dlogz: 2.0 first run gave: {'niter': 3195, 'logz': 0.046807674137349264, 'logzerr': 0.12344757562182432, 'logz_bs': 0.050546910112277486, 'logz_single': 0.046807674137349264, 'logzerr_tail': 0.03453638602818779, 'logzerr_bs': 0.11851810818190622, 'ess': 1268.1554531233794, 'H': 3.142281088841729, 'Herr': 0.06475125278208514, 'posterior': {'mean': [0.49996283843753414], 'stdev': [0.010129246874575209], 'median': [0.5000811924518125], 'errlo': [0.489645507298889], 'errup': [0.5099411526316042], 'information_gain_bits': [3.4799024194769563]}, 'maximum_likelihood': {'logl': 3.6862316499885406, 'point': [0.5000007476467405], 'point_untransformed': [0.5000007476467405]}, 'ncall': 3539, 'paramnames': ['a'], 'logzerr_single': 0.08863240221332333, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} second run gave: {'niter': 3195, 'logz': 0.046807674137349264, 'logzerr': 0.19105780872483483, 'logz_bs': 0.05878735013968942, 'logz_single': 0.046807674137349264, 'logzerr_tail': 0.03453638602818779, 'logzerr_bs': 0.1879104156635485, 'ess': 1268.1554531233794, 'H': 3.142281088841729, 'Herr': 0.06742326429379818, 'posterior': {'mean': [0.5000371524446212], 'stdev': [0.010156820812511607], 'median': [0.5001422333528115], 'errlo': [0.48966827010855574], 'errup': [0.510033048414859], 'information_gain_bits': [3.4799024194769563]}, 'maximum_likelihood': {'logl': 3.6862316499885406, 'point': [0.5000007476467405], 'point_untransformed': [0.5000007476467405]}, 'ncall': 3539, 'paramnames': ['a'], 'logzerr_single': 0.08863240221332333, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmp5lzcv4au, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=2.0, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=500, logz=-inf, remainder_fraction=100.0000%, Lmin=-1245.39, Lmax=3.65 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=500, logz=-990.55, remainder_fraction=100.0000%, Lmin=-981.54, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=609, logz=-823.22, remainder_fraction=100.0000%, Lmin=-812.27, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=609, logz=-626.43, remainder_fraction=100.0000%, Lmin=-615.76, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=609, logz=-543.89, remainder_fraction=100.0000%, Lmin=-534.44, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=695, logz=-498.58, remainder_fraction=100.0000%, Lmin=-492.04, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=695, logz=-387.01, remainder_fraction=100.0000%, Lmin=-379.22, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=763, logz=-354.34, remainder_fraction=100.0000%, Lmin=-345.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=763, logz=-309.38, remainder_fraction=100.0000%, Lmin=-302.94, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=824, logz=-233.62, remainder_fraction=100.0000%, Lmin=-224.53, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=824, logz=-219.55, remainder_fraction=100.0000%, Lmin=-213.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=874, logz=-182.54, remainder_fraction=100.0000%, Lmin=-175.31, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=920, logz=-139.53, remainder_fraction=100.0000%, Lmin=-133.48, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=963, logz=-113.40, remainder_fraction=100.0000%, Lmin=-106.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=1034, logz=-92.54, remainder_fraction=100.0000%, Lmin=-86.35, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=1034, logz=-89.87, remainder_fraction=100.0000%, Lmin=-84.15, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=1070, logz=-68.97, remainder_fraction=100.0000%, Lmin=-61.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=1103, logz=-58.86, remainder_fraction=100.0000%, Lmin=-52.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=1131, logz=-51.80, remainder_fraction=100.0000%, Lmin=-45.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=1180, logz=-38.80, remainder_fraction=100.0000%, Lmin=-32.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=1200, logz=-34.86, remainder_fraction=100.0000%, Lmin=-28.85, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=1224, logz=-29.71, remainder_fraction=100.0000%, Lmin=-23.75, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=1269, logz=-23.03, remainder_fraction=100.0000%, Lmin=-17.00, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=1289, logz=-21.60, remainder_fraction=100.0000%, Lmin=-15.56, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=1338, logz=-18.05, remainder_fraction=100.0000%, Lmin=-12.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1373, logz=-14.79, remainder_fraction=100.0000%, Lmin=-9.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=1435, logz=-11.95, remainder_fraction=99.9994%, Lmin=-6.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=1467, logz=-9.94, remainder_fraction=99.9955%, Lmin=-4.24, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=1480, logz=-9.43, remainder_fraction=99.9925%, Lmin=-3.97, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=1543, logz=-7.24, remainder_fraction=99.9353%, Lmin=-1.88, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=1573, logz=-6.28, remainder_fraction=99.8264%, Lmin=-1.16, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=1597, logz=-5.76, remainder_fraction=99.7047%, Lmin=-0.73, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=1643, logz=-4.75, remainder_fraction=99.1777%, Lmin=0.10, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=1699, logz=-3.89, remainder_fraction=98.0488%, Lmin=0.91, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=1746, logz=-3.18, remainder_fraction=96.0403%, Lmin=1.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=1756, logz=-3.05, remainder_fraction=95.4754%, Lmin=1.74, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=1799, logz=-2.61, remainder_fraction=92.9450%, Lmin=2.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=1849, logz=-2.16, remainder_fraction=88.9774%, Lmin=2.35, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=1903, logz=-1.81, remainder_fraction=84.3489%, Lmin=2.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=2029, logz=-1.58, remainder_fraction=80.1644%, Lmin=2.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=2029, logz=-1.52, remainder_fraction=79.1283%, Lmin=2.87, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=2029, logz=-1.28, remainder_fraction=73.3770%, Lmin=3.04, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=2147, logz=-1.07, remainder_fraction=67.3789%, Lmin=3.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=2147, logz=-0.91, remainder_fraction=61.4709%, Lmin=3.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=2248, logz=-0.85, remainder_fraction=59.1887%, Lmin=3.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=2248, logz=-0.77, remainder_fraction=55.7962%, Lmin=3.38, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=2249, logz=-0.65, remainder_fraction=50.2963%, Lmin=3.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=2261, logz=-0.63, remainder_fraction=49.2455%, Lmin=3.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=2389, logz=-0.55, remainder_fraction=45.1338%, Lmin=3.51, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=2389, logz=-0.47, remainder_fraction=40.2952%, Lmin=3.55, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=2430, logz=-0.40, remainder_fraction=35.9242%, Lmin=3.58, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=2477, logz=-0.35, remainder_fraction=32.7271%, Lmin=3.59, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=2477, logz=-0.34, remainder_fraction=31.9636%, Lmin=3.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=2537, logz=-0.29, remainder_fraction=28.3772%, Lmin=3.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=2563, logz=-0.26, remainder_fraction=26.4131%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=2686, logz=-0.24, remainder_fraction=25.1732%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=2686, logz=-0.21, remainder_fraction=22.3082%, Lmin=3.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=2686, logz=-0.19, remainder_fraction=21.2492%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=2693, logz=-0.17, remainder_fraction=19.7502%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=2804, logz=-0.15, remainder_fraction=17.4742%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=2804, logz=-0.14, remainder_fraction=17.0491%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=2815, logz=-0.12, remainder_fraction=15.4465%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=2988, logz=-0.10, remainder_fraction=13.6520%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=2988, logz=-0.08, remainder_fraction=12.0622%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2340, ncalls=2988, logz=-0.07, remainder_fraction=10.9236%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=2988, logz=-0.07, remainder_fraction=10.6558%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3107, logz=-0.05, remainder_fraction=9.4110%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3107, logz=-0.04, remainder_fraction=8.7344%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3107, logz=-0.04, remainder_fraction=8.3103%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3226, logz=-0.03, remainder_fraction=7.3374%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3226, logz=-0.02, remainder_fraction=6.4777%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3310, logz=-0.01, remainder_fraction=5.7182%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3310, logz=-0.01, remainder_fraction=5.5773%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3419, logz=-0.00, remainder_fraction=5.0474%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3419, logz=0.00, remainder_fraction=4.4550%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=3539, logz=0.01, remainder_fraction=3.9320%, Lmin=3.68, Lmax=3.69 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=4 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 3539 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = 0.05055 +- 0.06921 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1268.2, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.06 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.13, need <2.0) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<2.00 [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmp5lzcv4au, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [35mDEBUG [0m ultranest:integrator.py:1126 Testing resume consistency: [3.68477536 3.68615729 0. 0.49987805 0.49987805]: u=[0.49987805] -> p=[0.49987805] -> L=3.6861572944866396 [32mINFO [0m ultranest:integrator.py:2164 Resuming from 3430 stored points [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=2.0, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=3539, logz=-inf, remainder_fraction=100.0000%, Lmin=-1245.39, Lmax=3.65 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=3539, logz=-990.55, remainder_fraction=100.0000%, Lmin=-981.54, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=3539, logz=-861.82, remainder_fraction=100.0000%, Lmin=-854.74, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=3539, logz=-823.22, remainder_fraction=100.0000%, Lmin=-812.27, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=3539, logz=-626.43, remainder_fraction=100.0000%, Lmin=-615.76, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=3539, logz=-543.89, remainder_fraction=100.0000%, Lmin=-534.44, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=3539, logz=-498.58, remainder_fraction=100.0000%, Lmin=-492.04, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=3539, logz=-387.01, remainder_fraction=100.0000%, Lmin=-379.22, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=3539, logz=-354.34, remainder_fraction=100.0000%, Lmin=-345.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=3539, logz=-309.38, remainder_fraction=100.0000%, Lmin=-302.94, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=3539, logz=-233.62, remainder_fraction=100.0000%, Lmin=-224.53, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=3539, logz=-219.55, remainder_fraction=100.0000%, Lmin=-213.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=3539, logz=-182.54, remainder_fraction=100.0000%, Lmin=-175.31, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=3539, logz=-139.53, remainder_fraction=100.0000%, Lmin=-133.48, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=3539, logz=-113.40, remainder_fraction=100.0000%, Lmin=-106.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=3539, logz=-92.54, remainder_fraction=100.0000%, Lmin=-86.35, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=3539, logz=-89.87, remainder_fraction=100.0000%, Lmin=-84.15, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=3539, logz=-68.97, remainder_fraction=100.0000%, Lmin=-61.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=3539, logz=-58.86, remainder_fraction=100.0000%, Lmin=-52.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=3539, logz=-51.80, remainder_fraction=100.0000%, Lmin=-45.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=3539, logz=-38.80, remainder_fraction=100.0000%, Lmin=-32.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=3539, logz=-34.86, remainder_fraction=100.0000%, Lmin=-28.85, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=3539, logz=-29.71, remainder_fraction=100.0000%, Lmin=-23.75, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=3539, logz=-23.03, remainder_fraction=100.0000%, Lmin=-17.00, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=3539, logz=-21.60, remainder_fraction=100.0000%, Lmin=-15.56, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=3539, logz=-18.05, remainder_fraction=100.0000%, Lmin=-12.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=3539, logz=-14.79, remainder_fraction=100.0000%, Lmin=-9.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=3539, logz=-11.95, remainder_fraction=99.9994%, Lmin=-6.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=3539, logz=-9.94, remainder_fraction=99.9955%, Lmin=-4.24, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=3539, logz=-9.43, remainder_fraction=99.9925%, Lmin=-3.97, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=3539, logz=-7.24, remainder_fraction=99.9353%, Lmin=-1.88, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=3539, logz=-6.28, remainder_fraction=99.8264%, Lmin=-1.16, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=3539, logz=-5.76, remainder_fraction=99.7047%, Lmin=-0.73, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=3539, logz=-4.75, remainder_fraction=99.1777%, Lmin=0.10, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=3539, logz=-3.89, remainder_fraction=98.0488%, Lmin=0.91, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=3539, logz=-3.18, remainder_fraction=96.0403%, Lmin=1.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=3539, logz=-3.05, remainder_fraction=95.4754%, Lmin=1.74, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=3539, logz=-2.61, remainder_fraction=92.9450%, Lmin=2.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=3539, logz=-2.16, remainder_fraction=88.9774%, Lmin=2.35, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=3539, logz=-1.81, remainder_fraction=84.3489%, Lmin=2.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=3539, logz=-1.58, remainder_fraction=80.1644%, Lmin=2.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=3539, logz=-1.52, remainder_fraction=79.1283%, Lmin=2.87, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=3539, logz=-1.28, remainder_fraction=73.3770%, Lmin=3.04, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=3539, logz=-1.15, remainder_fraction=69.7628%, Lmin=3.15, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=3539, logz=-1.07, remainder_fraction=67.3789%, Lmin=3.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=3539, logz=-0.91, remainder_fraction=61.4709%, Lmin=3.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=3539, logz=-0.85, remainder_fraction=59.1887%, Lmin=3.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=3539, logz=-0.77, remainder_fraction=55.7962%, Lmin=3.38, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=3539, logz=-0.65, remainder_fraction=50.2963%, Lmin=3.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=3539, logz=-0.63, remainder_fraction=49.2455%, Lmin=3.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=3539, logz=-0.55, remainder_fraction=45.1338%, Lmin=3.51, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=3539, logz=-0.47, remainder_fraction=40.2952%, Lmin=3.55, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=3539, logz=-0.40, remainder_fraction=35.9242%, Lmin=3.58, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=3539, logz=-0.35, remainder_fraction=32.7271%, Lmin=3.59, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=3539, logz=-0.34, remainder_fraction=31.9636%, Lmin=3.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=3539, logz=-0.29, remainder_fraction=28.3772%, Lmin=3.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=3539, logz=-0.26, remainder_fraction=26.4131%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=3539, logz=-0.24, remainder_fraction=25.1732%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=3539, logz=-0.21, remainder_fraction=22.3082%, Lmin=3.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=3539, logz=-0.19, remainder_fraction=21.2492%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=3539, logz=-0.17, remainder_fraction=19.7502%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=3539, logz=-0.15, remainder_fraction=17.4742%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=3539, logz=-0.14, remainder_fraction=17.0491%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=3539, logz=-0.12, remainder_fraction=15.4465%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=3539, logz=-0.10, remainder_fraction=13.6520%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=3539, logz=-0.08, remainder_fraction=12.0622%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2340, ncalls=3539, logz=-0.07, remainder_fraction=10.9236%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=3539, logz=-0.07, remainder_fraction=10.6558%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3539, logz=-0.05, remainder_fraction=9.4110%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3539, logz=-0.04, remainder_fraction=8.7344%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3539, logz=-0.04, remainder_fraction=8.3103%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3539, logz=-0.03, remainder_fraction=7.3374%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=3539, logz=-0.03, remainder_fraction=6.9807%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3539, logz=-0.02, remainder_fraction=6.4777%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3539, logz=-0.01, remainder_fraction=5.7182%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3539, logz=-0.01, remainder_fraction=5.5773%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3539, logz=-0.00, remainder_fraction=5.0474%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3539, logz=0.00, remainder_fraction=4.4550%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=3539, logz=0.01, remainder_fraction=3.9320%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=3539, logz=0.01, remainder_fraction=3.5581%, Lmin=3.69, Lmax=3.69 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=4 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 3539 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = 0.05879 +- 0.07442 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1268.2, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.05 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.19, need <2.0) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<2.00 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_run_resume[0.5] | 5.91 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.31) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1229.24..3.69 [-1229.2436..3.6851] | it/evals=0/500 eff=0.0000% N=400 Z=-947.8(0.00%) | Like=-936.03..3.69 [-1229.2436..3.6851] | it/evals=50/500 eff=50.0000% N=400 Mono-modal Volume: ~exp(-4.31) Expected Volume: exp(-0.23) Quality: ok a: +0.0| ******************************************** | +1.0 Z=-744.3(0.00%) | Like=-735.03..3.69 [-1229.2436..3.6851] | it/evals=100/605 eff=48.7805% N=400 Z=-558.9(0.00%) | Like=-549.10..3.69 [-1229.2436..3.6851] | it/evals=150/605 eff=73.1707% N=400 Mono-modal Volume: ~exp(-4.60) * Expected Volume: exp(-0.45) Quality: ok a: +0.0| ************************************ +0.8 | +1.0 Z=-478.3(0.00%) | Like=-471.91..3.69 [-1229.2436..3.6851] | it/evals=180/690 eff=62.0690% N=400 Z=-443.0(0.00%) | Like=-432.23..3.69 [-1229.2436..3.6851] | it/evals=200/690 eff=68.9655% N=400 Z=-352.3(0.00%) | Like=-345.84..3.69 [-1229.2436..3.6851] | it/evals=250/690 eff=86.2069% N=400 Mono-modal Volume: ~exp(-4.82) * Expected Volume: exp(-0.67) Quality: ok a: +0.0| +0.3 ***************************** +0.8 | +1.0 Z=-317.4(0.00%) | Like=-311.29..3.69 [-1229.2436..3.6851] | it/evals=270/763 eff=74.3802% N=400 Z=-282.4(0.00%) | Like=-275.50..3.69 [-1229.2436..3.6851] | it/evals=300/763 eff=82.6446% N=400 Z=-224.6(0.00%) | Like=-217.57..3.69 [-1229.2436..3.6851] | it/evals=350/816 eff=84.1346% N=400 Mono-modal Volume: ~exp(-5.11) * Expected Volume: exp(-0.90) Quality: ok a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-215.6(0.00%) | Like=-209.54..3.69 [-1229.2436..3.6851] | it/evals=360/816 eff=86.5385% N=400 Z=-176.4(0.00%) | Like=-170.36..3.69 [-1229.2436..3.6851] | it/evals=400/872 eff=84.7458% N=400 Mono-modal Volume: ~exp(-5.21) * Expected Volume: exp(-1.12) Quality: ok a: +0.0| +0.3 ******************** +0.7 | +1.0 Z=-142.4(0.00%) | Like=-136.03..3.69 [-1229.2436..3.6851] | it/evals=450/927 eff=85.3890% N=400 Z=-111.1(0.00%) | Like=-104.21..3.69 [-1229.2436..3.6851] | it/evals=500/971 eff=87.5657% N=400 Mono-modal Volume: ~exp(-5.44) * Expected Volume: exp(-1.35) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 Z=-90.3(0.00%) | Like=-84.61..3.69 [-1229.2436..3.6851] | it/evals=540/1038 eff=84.6395% N=400 Z=-87.9(0.00%) | Like=-81.32..3.69 [-1229.2436..3.6851] | it/evals=550/1038 eff=86.2069% N=400 Z=-67.7(0.00%) | Like=-60.73..3.69 [-1229.2436..3.6851] | it/evals=600/1100 eff=85.7143% N=400 Mono-modal Volume: ~exp(-5.81) * Expected Volume: exp(-1.57) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-58.7(0.00%) | Like=-51.96..3.69 [-1229.2436..3.6851] | it/evals=630/1129 eff=86.4198% N=400 Z=-53.1(0.00%) | Like=-46.93..3.69 [-1229.2436..3.6851] | it/evals=650/1129 eff=89.1632% N=400 Z=-41.7(0.00%) | Like=-35.84..3.69 [-1229.2436..3.6851] | it/evals=700/1195 eff=88.0503% N=400 Have 2 modes Volume: ~exp(-5.96) * Expected Volume: exp(-1.80) Quality: ok a: +0.0| +0.4 1111222222 +0.6 | +1.0 Z=-39.5(0.00%) | Like=-34.07..3.69 [-1229.2436..3.6851] | it/evals=720/1218 eff=88.0196% N=400 Z=-36.7(0.00%) | Like=-30.50..3.69 [-1229.2436..3.6851] | it/evals=750/1242 eff=89.0736% N=400 Z=-28.6(0.00%) | Like=-22.50..3.69 [-1229.2436..3.6851] | it/evals=800/1301 eff=88.7902% N=400 Mono-modal Volume: ~exp(-6.09) * Expected Volume: exp(-2.02) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-27.0(0.00%) | Like=-20.71..3.69 [-1229.2436..3.6851] | it/evals=810/1301 eff=89.9001% N=400 Z=-22.1(0.00%) | Like=-16.17..3.69 [-1229.2436..3.6851] | it/evals=850/1335 eff=90.9091% N=400 Mono-modal Volume: ~exp(-6.20) * Expected Volume: exp(-2.25) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-18.1(0.00%) | Like=-12.33..3.69 [-1229.2436..3.6851] | it/evals=900/1393 eff=90.6344% N=400 Z=-14.6(0.00%) | Like=-8.98..3.69 [-1229.2436..3.6851] | it/evals=950/1444 eff=90.9962% N=400 Mono-modal Volume: ~exp(-6.28) * Expected Volume: exp(-2.47) Quality: ok a: +0.00| +0.45 ****** +0.55 | +1.00 Z=-12.4(0.00%) | Like=-6.92..3.69 [-1229.2436..3.6851] | it/evals=990/1481 eff=91.5819% N=400 Z=-12.0(0.00%) | Like=-6.52..3.69 [-1229.2436..3.6851] | it/evals=1000/1499 eff=90.9918% N=400 Z=-9.9(0.01%) | Like=-4.54..3.69 [-1229.2436..3.6851] | it/evals=1050/1548 eff=91.4634% N=400 Mono-modal Volume: ~exp(-6.28) Expected Volume: exp(-2.70) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-8.2(0.03%) | Like=-2.86..3.69 [-1229.2436..3.6851] | it/evals=1100/1597 eff=91.8964% N=400 Z=-6.7(0.14%) | Like=-1.41..3.69 [-1229.2436..3.6851] | it/evals=1150/1656 eff=91.5605% N=400 Mono-modal Volume: ~exp(-7.06) * Expected Volume: exp(-2.92) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.2(0.23%) | Like=-1.07..3.69 [-1229.2436..3.6851] | it/evals=1170/1675 eff=91.7647% N=400 Z=-5.6(0.44%) | Like=-0.49..3.69 [-1229.2436..3.6851] | it/evals=1200/1707 eff=91.8133% N=400 Z=-4.7(1.03%) | Like=0.33..3.69 [-1229.2436..3.6851] | it/evals=1250/1760 eff=91.9118% N=400 Mono-modal Volume: ~exp(-7.06) Expected Volume: exp(-3.15) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-3.9(2.27%) | Like=1.22..3.69 [-1229.2436..3.6851] | it/evals=1300/1807 eff=92.3952% N=400 Mono-modal Volume: ~exp(-7.44) * Expected Volume: exp(-3.37) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.2(4.72%) | Like=1.83..3.69 [-1229.2436..3.6851] | it/evals=1350/1864 eff=92.2131% N=400 Z=-2.6(8.34%) | Like=2.32..3.69 [-1229.2436..3.6851] | it/evals=1400/1911 eff=92.6539% N=400 Mono-modal Volume: ~exp(-7.50) * Expected Volume: exp(-3.60) Quality: ok a: +0.00| +0.49 ** +0.52 | +1.00 Z=-2.2(11.98%) | Like=2.54..3.69 [-1229.2436..3.6851] | it/evals=1440/1951 eff=92.8433% N=400 Z=-2.2(13.02%) | Like=2.59..3.69 [-1229.2436..3.6851] | it/evals=1450/1965 eff=92.6518% N=400 Z=-1.8(18.33%) | Like=2.85..3.69 [-1229.2436..3.6851] | it/evals=1500/2098 eff=88.3392% N=400 Mono-modal Volume: ~exp(-8.08) * Expected Volume: exp(-3.82) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(21.85%) | Like=2.98..3.69 [-1229.2436..3.6851] | it/evals=1530/2098 eff=90.1060% N=400 Z=-1.5(24.24%) | Like=3.05..3.69 [-1229.2436..3.6851] | it/evals=1550/2098 eff=91.2839% N=400 Z=-1.3(30.41%) | Like=3.18..3.69 [-1229.2436..3.6851] | it/evals=1600/2222 eff=87.8156% N=400 Mono-modal Volume: ~exp(-8.08) Expected Volume: exp(-4.05) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.1(36.62%) | Like=3.28..3.69 [-1229.2436..3.6851] | it/evals=1650/2222 eff=90.5598% N=400 Z=-1.0(42.59%) | Like=3.37..3.69 [-1229.2436..3.6851] | it/evals=1700/2312 eff=88.9121% N=400 Mono-modal Volume: ~exp(-8.15) * Expected Volume: exp(-4.27) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.9(43.73%) | Like=3.38..3.69 [-1229.2436..3.6851] | it/evals=1710/2312 eff=89.4351% N=400 Z=-0.8(48.21%) | Like=3.42..3.69 [-1229.2436..3.6851] | it/evals=1750/2312 eff=91.5272% N=400 Mono-modal Volume: ~exp(-8.62) * Expected Volume: exp(-4.50) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.7(53.41%) | Like=3.47..3.69 [-1229.2436..3.6851] | it/evals=1800/2430 eff=88.6700% N=400 Z=-0.7(58.28%) | Like=3.52..3.69 [-1229.2436..3.6851] | it/evals=1850/2430 eff=91.1330% N=400 Mono-modal Volume: ~exp(-8.64) * Expected Volume: exp(-4.73) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(61.89%) | Like=3.55..3.69 [-1229.2436..3.6851] | it/evals=1890/2541 eff=88.2765% N=400 Z=-0.6(62.77%) | Like=3.56..3.69 [-1229.2436..3.6851] | it/evals=1900/2541 eff=88.7436% N=400 Z=-0.5(66.87%) | Like=3.58..3.69 [-1229.2436..3.6851] | it/evals=1950/2541 eff=91.0789% N=400 Mono-modal Volume: ~exp(-8.88) * Expected Volume: exp(-4.95) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.5(69.12%) | Like=3.60..3.69 [-1229.2436..3.6851] | it/evals=1980/2654 eff=87.8438% N=400 Z=-0.5(70.54%) | Like=3.61..3.69 [-1229.2436..3.6851] | it/evals=2000/2654 eff=88.7311% N=400 Z=-0.4(73.85%) | Like=3.62..3.69 [-1229.2436..3.6851] | it/evals=2050/2654 eff=90.9494% N=400 Mono-modal Volume: ~exp(-9.30) * Expected Volume: exp(-5.18) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.4(75.08%) | Like=3.63..3.69 [-1229.2436..3.6851] | it/evals=2070/2667 eff=91.3101% N=400 Z=-0.4(76.82%) | Like=3.64..3.69 [-1229.2436..3.6851] | it/evals=2100/2702 eff=91.2250% N=400 Z=-0.3(79.47%) | Like=3.65..3.69 [-1229.2436..3.6851] | it/evals=2150/2753 eff=91.3727% N=400 Mono-modal Volume: ~exp(-9.30) Expected Volume: exp(-5.40) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(81.83%) | Like=3.66..3.69 [-1229.2436..3.6851] | it/evals=2200/2801 eff=91.6285% N=400 Mono-modal Volume: ~exp(-9.91) * Expected Volume: exp(-5.63) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.3(83.94%) | Like=3.66..3.69 [-1229.2436..3.6851] | it/evals=2250/2861 eff=91.4262% N=400 Z=-0.3(85.80%) | Like=3.67..3.69 [-1229.2436..3.6851] | it/evals=2300/2987 eff=88.9061% N=400 Mono-modal Volume: ~exp(-9.91) Expected Volume: exp(-5.85) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.3(87.45%) | Like=3.67..3.69 [-1229.2436..3.6851] | it/evals=2350/2987 eff=90.8388% N=400 Z=-0.2(88.92%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2400/3085 eff=89.3855% N=400 Have 2 modes Volume: ~exp(-10.14) * Expected Volume: exp(-6.08) Quality: ok a: +0.000| +0.499 11 +0.501 | +1.000 Z=-0.2(89.71%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2430/3085 eff=90.5028% N=400 Z=-0.2(90.21%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2450/3085 eff=91.2477% N=400 Z=-0.2(91.36%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2500/3142 eff=91.1743% N=400 Have 2 modes Volume: ~exp(-10.14) Expected Volume: exp(-6.30) Quality: ok a: +0.000| +0.499 11 +0.501 | +1.000 Z=-0.2(92.37%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2550/3187 eff=91.4962% N=400 Z=-0.2(93.26%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2600/3244 eff=91.4205% N=400 Mono-modal Volume: ~exp(-10.36) * Expected Volume: exp(-6.53) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(93.43%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2610/3253 eff=91.4826% N=400 Z=-0.2(94.05%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2650/3293 eff=91.6004% N=400 Mono-modal Volume: ~exp(-10.78) * Expected Volume: exp(-6.75) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(94.75%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2700/3347 eff=91.6186% N=400 Z=-0.2(95.37%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2750/3475 eff=89.4309% N=400 Mono-modal Volume: ~exp(-10.83) * Expected Volume: exp(-6.98) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(95.81%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2790/3475 eff=90.7317% N=400 Z=-0.2(95.91%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2800/3475 eff=91.0569% N=400 Z=-0.2(96.39%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2850/3595 eff=89.2019% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3595 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -0.1062 +- 0.07211 [ultranest] Effective samples strategy satisfied (ESS = 1233.8, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.15, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<0.50 [ultranest] done iterating. logZ = -0.118 +- 0.151 single instance: logZ = -0.118 +- 0.091 bootstrapped : logZ = -0.106 +- 0.148 tail : logZ = +- 0.034 insert order U test : converged: True correlation: inf iterations a 0.5000 +- 0.0099 [ultranest] Resuming from 3491 stored points Mono-modal Volume: ~exp(-4.25) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1229.24..3.69 [-1229.2436..3.6851] | it/evals=0/3595 eff=inf% N=400 Z=-947.8(0.00%) | Like=-936.03..3.69 [-1229.2436..3.6851] | it/evals=50/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-4.54) * Expected Volume: exp(-0.23) Quality: ok a: +0.0| ******************************************** | +1.0 Z=-794.7(0.00%) | Like=-767.63..3.69 [-1229.2436..3.6851] | it/evals=90/3595 eff=inf% N=400 Z=-744.3(0.00%) | Like=-735.03..3.69 [-1229.2436..3.6851] | it/evals=100/3595 eff=inf% N=400 Z=-558.9(0.00%) | Like=-549.10..3.69 [-1229.2436..3.6851] | it/evals=150/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-4.54) Expected Volume: exp(-0.45) Quality: ok a: +0.0| ************************************ +0.8 | +1.0 Z=-443.0(0.00%) | Like=-432.23..3.69 [-1229.2436..3.6851] | it/evals=200/3595 eff=inf% N=400 Z=-352.3(0.00%) | Like=-345.84..3.69 [-1229.2436..3.6851] | it/evals=250/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-4.78) * Expected Volume: exp(-0.67) Quality: ok a: +0.0| +0.3 ***************************** +0.8 | +1.0 Z=-317.4(0.00%) | Like=-311.29..3.69 [-1229.2436..3.6851] | it/evals=270/3595 eff=inf% N=400 Z=-282.4(0.00%) | Like=-275.50..3.69 [-1229.2436..3.6851] | it/evals=300/3595 eff=inf% N=400 Z=-224.6(0.00%) | Like=-217.57..3.69 [-1229.2436..3.6851] | it/evals=350/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-4.91) * Expected Volume: exp(-0.90) Quality: ok a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-215.6(0.00%) | Like=-209.54..3.69 [-1229.2436..3.6851] | it/evals=360/3595 eff=inf% N=400 Z=-176.4(0.00%) | Like=-170.36..3.69 [-1229.2436..3.6851] | it/evals=400/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-5.23) * Expected Volume: exp(-1.12) Quality: ok a: +0.0| +0.3 ******************** +0.7 | +1.0 Z=-142.4(0.00%) | Like=-136.03..3.69 [-1229.2436..3.6851] | it/evals=450/3595 eff=inf% N=400 Z=-111.1(0.00%) | Like=-104.21..3.69 [-1229.2436..3.6851] | it/evals=500/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-5.45) * Expected Volume: exp(-1.35) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 Z=-90.3(0.00%) | Like=-84.61..3.69 [-1229.2436..3.6851] | it/evals=540/3595 eff=inf% N=400 Z=-87.9(0.00%) | Like=-81.32..3.69 [-1229.2436..3.6851] | it/evals=550/3595 eff=inf% N=400 Z=-67.7(0.00%) | Like=-60.73..3.69 [-1229.2436..3.6851] | it/evals=600/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-5.69) * Expected Volume: exp(-1.57) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-58.7(0.00%) | Like=-51.96..3.69 [-1229.2436..3.6851] | it/evals=630/3595 eff=inf% N=400 Z=-53.1(0.00%) | Like=-46.93..3.69 [-1229.2436..3.6851] | it/evals=650/3595 eff=inf% N=400 Z=-41.7(0.00%) | Like=-35.84..3.69 [-1229.2436..3.6851] | it/evals=700/3595 eff=inf% N=400 Have 2 modes Volume: ~exp(-5.81) * Expected Volume: exp(-1.80) Quality: ok a: +0.0| +0.4 1111222222 +0.6 | +1.0 Z=-39.5(0.00%) | Like=-34.07..3.69 [-1229.2436..3.6851] | it/evals=720/3595 eff=inf% N=400 Z=-36.7(0.00%) | Like=-30.50..3.69 [-1229.2436..3.6851] | it/evals=750/3595 eff=inf% N=400 Z=-28.6(0.00%) | Like=-22.50..3.69 [-1229.2436..3.6851] | it/evals=800/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-5.97) * Expected Volume: exp(-2.02) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-27.0(0.00%) | Like=-20.71..3.69 [-1229.2436..3.6851] | it/evals=810/3595 eff=inf% N=400 Z=-22.1(0.00%) | Like=-16.17..3.69 [-1229.2436..3.6851] | it/evals=850/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-6.34) * Expected Volume: exp(-2.25) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-18.1(0.00%) | Like=-12.33..3.69 [-1229.2436..3.6851] | it/evals=900/3595 eff=inf% N=400 Z=-14.6(0.00%) | Like=-8.98..3.69 [-1229.2436..3.6851] | it/evals=950/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-6.49) * Expected Volume: exp(-2.47) Quality: ok a: +0.00| +0.45 ****** +0.55 | +1.00 Z=-12.4(0.00%) | Like=-6.92..3.69 [-1229.2436..3.6851] | it/evals=990/3595 eff=inf% N=400 Z=-12.0(0.00%) | Like=-6.52..3.69 [-1229.2436..3.6851] | it/evals=1000/3595 eff=inf% N=400 Z=-9.9(0.01%) | Like=-4.54..3.69 [-1229.2436..3.6851] | it/evals=1050/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-6.49) Expected Volume: exp(-2.70) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-8.2(0.03%) | Like=-2.86..3.69 [-1229.2436..3.6851] | it/evals=1100/3595 eff=inf% N=400 Z=-6.7(0.14%) | Like=-1.41..3.69 [-1229.2436..3.6851] | it/evals=1150/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-6.89) * Expected Volume: exp(-2.92) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.2(0.23%) | Like=-1.07..3.69 [-1229.2436..3.6851] | it/evals=1170/3595 eff=inf% N=400 Z=-5.6(0.44%) | Like=-0.49..3.69 [-1229.2436..3.6851] | it/evals=1200/3595 eff=inf% N=400 Z=-4.7(1.03%) | Like=0.33..3.69 [-1229.2436..3.6851] | it/evals=1250/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-7.27) * Expected Volume: exp(-3.15) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 Z=-4.5(1.21%) | Like=0.51..3.69 [-1229.2436..3.6851] | it/evals=1260/3595 eff=inf% N=400 Z=-3.9(2.27%) | Like=1.22..3.69 [-1229.2436..3.6851] | it/evals=1300/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-7.32) * Expected Volume: exp(-3.37) Quality: ok a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.2(4.72%) | Like=1.83..3.69 [-1229.2436..3.6851] | it/evals=1350/3595 eff=inf% N=400 Z=-2.6(8.34%) | Like=2.32..3.69 [-1229.2436..3.6851] | it/evals=1400/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-7.84) * Expected Volume: exp(-3.60) Quality: ok a: +0.00| +0.49 ** +0.52 | +1.00 Z=-2.2(11.98%) | Like=2.54..3.69 [-1229.2436..3.6851] | it/evals=1440/3595 eff=inf% N=400 Z=-2.2(13.02%) | Like=2.59..3.69 [-1229.2436..3.6851] | it/evals=1450/3595 eff=inf% N=400 Z=-1.8(18.33%) | Like=2.85..3.69 [-1229.2436..3.6851] | it/evals=1500/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-8.12) * Expected Volume: exp(-3.82) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(21.85%) | Like=2.98..3.69 [-1229.2436..3.6851] | it/evals=1530/3595 eff=inf% N=400 Z=-1.5(24.24%) | Like=3.05..3.69 [-1229.2436..3.6851] | it/evals=1550/3595 eff=inf% N=400 Z=-1.3(30.41%) | Like=3.18..3.69 [-1229.2436..3.6851] | it/evals=1600/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-8.15) * Expected Volume: exp(-4.05) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.2(32.94%) | Like=3.23..3.69 [-1229.2436..3.6851] | it/evals=1620/3595 eff=inf% N=400 Z=-1.1(36.62%) | Like=3.28..3.69 [-1229.2436..3.6851] | it/evals=1650/3595 eff=inf% N=400 Z=-1.0(42.59%) | Like=3.37..3.69 [-1229.2436..3.6851] | it/evals=1700/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-8.40) * Expected Volume: exp(-4.27) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.9(43.73%) | Like=3.38..3.69 [-1229.2436..3.6851] | it/evals=1710/3595 eff=inf% N=400 Z=-0.8(48.21%) | Like=3.42..3.69 [-1229.2436..3.6851] | it/evals=1750/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-8.53) * Expected Volume: exp(-4.50) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.7(53.41%) | Like=3.47..3.69 [-1229.2436..3.6851] | it/evals=1800/3595 eff=inf% N=400 Z=-0.7(58.28%) | Like=3.52..3.69 [-1229.2436..3.6851] | it/evals=1850/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-8.87) * Expected Volume: exp(-4.73) Quality: ok a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(61.89%) | Like=3.55..3.69 [-1229.2436..3.6851] | it/evals=1890/3595 eff=inf% N=400 Z=-0.6(62.77%) | Like=3.56..3.69 [-1229.2436..3.6851] | it/evals=1900/3595 eff=inf% N=400 Z=-0.5(66.87%) | Like=3.58..3.69 [-1229.2436..3.6851] | it/evals=1950/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-8.87) Expected Volume: exp(-4.95) Quality: ok a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.5(70.54%) | Like=3.61..3.69 [-1229.2436..3.6851] | it/evals=2000/3595 eff=inf% N=400 Z=-0.4(73.85%) | Like=3.62..3.69 [-1229.2436..3.6851] | it/evals=2050/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-9.05) * Expected Volume: exp(-5.18) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.4(75.08%) | Like=3.63..3.69 [-1229.2436..3.6851] | it/evals=2070/3595 eff=inf% N=400 Z=-0.4(76.82%) | Like=3.64..3.69 [-1229.2436..3.6851] | it/evals=2100/3595 eff=inf% N=400 Z=-0.3(79.47%) | Like=3.65..3.69 [-1229.2436..3.6851] | it/evals=2150/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-9.40) * Expected Volume: exp(-5.40) Quality: ok a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(79.97%) | Like=3.65..3.69 [-1229.2436..3.6851] | it/evals=2160/3595 eff=inf% N=400 Z=-0.3(81.83%) | Like=3.66..3.69 [-1229.2436..3.6851] | it/evals=2200/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-9.85) * Expected Volume: exp(-5.63) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.3(83.94%) | Like=3.66..3.69 [-1229.2436..3.6851] | it/evals=2250/3595 eff=inf% N=400 Z=-0.3(85.80%) | Like=3.67..3.69 [-1229.2436..3.6851] | it/evals=2300/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-9.85) Expected Volume: exp(-5.85) Quality: ok a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.3(87.45%) | Like=3.67..3.69 [-1229.2436..3.6851] | it/evals=2350/3595 eff=inf% N=400 Z=-0.2(88.92%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2400/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-10.02) * Expected Volume: exp(-6.08) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(89.71%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2430/3595 eff=inf% N=400 Z=-0.2(90.21%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2450/3595 eff=inf% N=400 Z=-0.2(91.36%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2500/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-10.20) * Expected Volume: exp(-6.30) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(91.78%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2520/3595 eff=inf% N=400 Z=-0.2(92.37%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2550/3595 eff=inf% N=400 Z=-0.2(93.26%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2600/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-10.30) * Expected Volume: exp(-6.53) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(93.43%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2610/3595 eff=inf% N=400 Z=-0.2(94.05%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2650/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-10.88) * Expected Volume: exp(-6.75) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(94.75%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2700/3595 eff=inf% N=400 Z=-0.2(95.37%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2750/3595 eff=inf% N=400 Mono-modal Volume: ~exp(-10.93) * Expected Volume: exp(-6.98) Quality: ok a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.2(95.81%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2790/3595 eff=inf% N=400 Z=-0.2(95.91%) | Like=3.68..3.69 [-1229.2436..3.6851] | it/evals=2800/3595 eff=inf% N=400 Z=-0.2(96.39%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2850/3595 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3595 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = -0.1173 +- 0.05407 [ultranest] Effective samples strategy satisfied (ESS = 1233.8, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) [ultranest] logZ error budget: single: 0.09 bs:0.05 tail:0.03 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -0.118 +- 0.104 single instance: logZ = -0.118 +- 0.091 bootstrapped : logZ = -0.117 +- 0.099 tail : logZ = +- 0.034 insert order U test : converged: True correlation: inf iterations a 0.4999 +- 0.0099 ran with dlogz: 0.5 first run gave: {'niter': 3271, 'logz': -0.11762175119953859, 'logzerr': 0.15147335897640027, 'logz_bs': -0.10621452602822, 'logz_single': -0.11762175119953859, 'logzerr_tail': 0.03367928356141833, 'logzerr_bs': 0.14768169940240733, 'ess': 1233.7908506225695, 'H': 3.3348180858376155, 'Herr': 0.06257186887859931, 'posterior': {'mean': [0.5000034011002668], 'stdev': [0.009868169921797974], 'median': [0.4998242933092234], 'errlo': [0.4902342202924638], 'errup': [0.5099131078174356], 'information_gain_bits': [3.463963810367678]}, 'maximum_likelihood': {'logl': 3.6862316522715544, 'point': [0.5000003199576626], 'point_untransformed': [0.5000003199576626]}, 'ncall': 3595, 'paramnames': ['a'], 'logzerr_single': 0.09130742146503776, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} second run gave: {'niter': 3271, 'logz': -0.11762175119953859, 'logzerr': 0.10430897833677111, 'logz_bs': -0.11733934882363599, 'logz_single': -0.11762175119953859, 'logzerr_tail': 0.03367928356141833, 'logzerr_bs': 0.09872217998226417, 'ess': 1233.7908506225695, 'H': 3.3348180858376155, 'Herr': 0.048702912024589685, 'posterior': {'mean': [0.4999254732710433], 'stdev': [0.009861666989975225], 'median': [0.49980712153989776], 'errlo': [0.4902131577281437], 'errup': [0.5097521082671864], 'information_gain_bits': [3.463963810367678]}, 'maximum_likelihood': {'logl': 3.6862316522715544, 'point': [0.5000003199576626], 'point_untransformed': [0.5000003199576626]}, 'ncall': 3595, 'paramnames': ['a'], 'logzerr_single': 0.09130742146503776, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpnne0sg6f, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=500, logz=-inf, remainder_fraction=100.0000%, Lmin=-1229.24, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=500, logz=-947.80, remainder_fraction=100.0000%, Lmin=-936.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=605, logz=-744.35, remainder_fraction=100.0000%, Lmin=-735.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=605, logz=-558.93, remainder_fraction=100.0000%, Lmin=-549.10, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=690, logz=-478.32, remainder_fraction=100.0000%, Lmin=-471.91, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=690, logz=-442.95, remainder_fraction=100.0000%, Lmin=-432.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=690, logz=-352.29, remainder_fraction=100.0000%, Lmin=-345.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=763, logz=-317.39, remainder_fraction=100.0000%, Lmin=-311.29, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=763, logz=-282.39, remainder_fraction=100.0000%, Lmin=-275.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=816, logz=-224.65, remainder_fraction=100.0000%, Lmin=-217.57, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=816, logz=-215.62, remainder_fraction=100.0000%, Lmin=-209.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=872, logz=-176.39, remainder_fraction=100.0000%, Lmin=-170.36, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=927, logz=-142.39, remainder_fraction=100.0000%, Lmin=-136.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=971, logz=-111.10, remainder_fraction=100.0000%, Lmin=-104.21, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=1038, logz=-90.30, remainder_fraction=100.0000%, Lmin=-84.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=1038, logz=-87.89, remainder_fraction=100.0000%, Lmin=-81.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=1100, logz=-67.73, remainder_fraction=100.0000%, Lmin=-60.73, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=1129, logz=-58.71, remainder_fraction=100.0000%, Lmin=-51.96, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=1129, logz=-53.11, remainder_fraction=100.0000%, Lmin=-46.93, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=1195, logz=-41.73, remainder_fraction=100.0000%, Lmin=-35.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=1218, logz=-39.49, remainder_fraction=100.0000%, Lmin=-34.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=1242, logz=-36.71, remainder_fraction=100.0000%, Lmin=-30.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=1301, logz=-28.59, remainder_fraction=100.0000%, Lmin=-22.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=1301, logz=-26.98, remainder_fraction=100.0000%, Lmin=-20.71, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=1335, logz=-22.06, remainder_fraction=100.0000%, Lmin=-16.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1393, logz=-18.07, remainder_fraction=100.0000%, Lmin=-12.33, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=1444, logz=-14.61, remainder_fraction=99.9999%, Lmin=-8.98, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=1481, logz=-12.44, remainder_fraction=99.9996%, Lmin=-6.92, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=1499, logz=-11.98, remainder_fraction=99.9993%, Lmin=-6.52, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=1548, logz=-9.90, remainder_fraction=99.9943%, Lmin=-4.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=1597, logz=-8.20, remainder_fraction=99.9692%, Lmin=-2.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=1656, logz=-6.66, remainder_fraction=99.8560%, Lmin=-1.41, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=1675, logz=-6.18, remainder_fraction=99.7670%, Lmin=-1.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=1707, logz=-5.56, remainder_fraction=99.5641%, Lmin=-0.49, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=1760, logz=-4.71, remainder_fraction=98.9746%, Lmin=0.33, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=1807, logz=-3.90, remainder_fraction=97.7307%, Lmin=1.22, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=1864, logz=-3.16, remainder_fraction=95.2752%, Lmin=1.83, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=1911, logz=-2.60, remainder_fraction=91.6644%, Lmin=2.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=1951, logz=-2.24, remainder_fraction=88.0170%, Lmin=2.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=1965, logz=-2.16, remainder_fraction=86.9760%, Lmin=2.59, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=2098, logz=-1.81, remainder_fraction=81.6668%, Lmin=2.85, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=2098, logz=-1.63, remainder_fraction=78.1472%, Lmin=2.98, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=2098, logz=-1.53, remainder_fraction=75.7564%, Lmin=3.05, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=2222, logz=-1.30, remainder_fraction=69.5858%, Lmin=3.18, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=2222, logz=-1.12, remainder_fraction=63.3836%, Lmin=3.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=2312, logz=-0.97, remainder_fraction=57.4148%, Lmin=3.37, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=2312, logz=-0.94, remainder_fraction=56.2675%, Lmin=3.38, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=2312, logz=-0.85, remainder_fraction=51.7929%, Lmin=3.42, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=2430, logz=-0.74, remainder_fraction=46.5893%, Lmin=3.47, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=2430, logz=-0.66, remainder_fraction=41.7151%, Lmin=3.52, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=2541, logz=-0.60, remainder_fraction=38.1094%, Lmin=3.55, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=2541, logz=-0.58, remainder_fraction=37.2343%, Lmin=3.56, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=2541, logz=-0.52, remainder_fraction=33.1317%, Lmin=3.58, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=2654, logz=-0.49, remainder_fraction=30.8838%, Lmin=3.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=2654, logz=-0.47, remainder_fraction=29.4601%, Lmin=3.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=2654, logz=-0.42, remainder_fraction=26.1457%, Lmin=3.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=2667, logz=-0.40, remainder_fraction=24.9168%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=2702, logz=-0.38, remainder_fraction=23.1781%, Lmin=3.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=2753, logz=-0.35, remainder_fraction=20.5306%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=2801, logz=-0.32, remainder_fraction=18.1657%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=2861, logz=-0.29, remainder_fraction=16.0618%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=2987, logz=-0.27, remainder_fraction=14.1983%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=2987, logz=-0.25, remainder_fraction=12.5457%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3085, logz=-0.24, remainder_fraction=11.0819%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3085, logz=-0.23, remainder_fraction=10.2864%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3085, logz=-0.22, remainder_fraction=9.7875%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3142, logz=-0.21, remainder_fraction=8.6428%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3187, logz=-0.20, remainder_fraction=7.6313%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3244, logz=-0.19, remainder_fraction=6.7373%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3253, logz=-0.19, remainder_fraction=6.5714%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3293, logz=-0.18, remainder_fraction=5.9476%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3347, logz=-0.17, remainder_fraction=5.2501%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=3475, logz=-0.17, remainder_fraction=4.6339%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=3475, logz=-0.16, remainder_fraction=4.1935%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=3475, logz=-0.16, remainder_fraction=4.0900%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=3595, logz=-0.15, remainder_fraction=3.6098%, Lmin=3.69, Lmax=3.69 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=4 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 3595 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -0.1062 +- 0.07211 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1233.8, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.15, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.08 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpnne0sg6f, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [35mDEBUG [0m ultranest:integrator.py:1126 Testing resume consistency: [3.68491226 3.68512565 0. 0.50047032 0.50047032]: u=[0.50047032] -> p=[0.50047032] -> L=3.685125649678668 [32mINFO [0m ultranest:integrator.py:2164 Resuming from 3491 stored points [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=3595, logz=-inf, remainder_fraction=100.0000%, Lmin=-1229.24, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=3595, logz=-947.80, remainder_fraction=100.0000%, Lmin=-936.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=3595, logz=-794.67, remainder_fraction=100.0000%, Lmin=-767.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=3595, logz=-744.35, remainder_fraction=100.0000%, Lmin=-735.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=3595, logz=-558.93, remainder_fraction=100.0000%, Lmin=-549.10, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=3595, logz=-442.95, remainder_fraction=100.0000%, Lmin=-432.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=3595, logz=-352.29, remainder_fraction=100.0000%, Lmin=-345.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=3595, logz=-317.39, remainder_fraction=100.0000%, Lmin=-311.29, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=3595, logz=-282.39, remainder_fraction=100.0000%, Lmin=-275.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=3595, logz=-224.65, remainder_fraction=100.0000%, Lmin=-217.57, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=3595, logz=-215.62, remainder_fraction=100.0000%, Lmin=-209.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=3595, logz=-176.39, remainder_fraction=100.0000%, Lmin=-170.36, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=3595, logz=-142.39, remainder_fraction=100.0000%, Lmin=-136.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=3595, logz=-111.10, remainder_fraction=100.0000%, Lmin=-104.21, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=3595, logz=-90.30, remainder_fraction=100.0000%, Lmin=-84.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=3595, logz=-87.89, remainder_fraction=100.0000%, Lmin=-81.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=3595, logz=-67.73, remainder_fraction=100.0000%, Lmin=-60.73, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=3595, logz=-58.71, remainder_fraction=100.0000%, Lmin=-51.96, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=3595, logz=-53.11, remainder_fraction=100.0000%, Lmin=-46.93, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=3595, logz=-41.73, remainder_fraction=100.0000%, Lmin=-35.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=3595, logz=-39.49, remainder_fraction=100.0000%, Lmin=-34.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=3595, logz=-36.71, remainder_fraction=100.0000%, Lmin=-30.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=3595, logz=-28.59, remainder_fraction=100.0000%, Lmin=-22.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=3595, logz=-26.98, remainder_fraction=100.0000%, Lmin=-20.71, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=3595, logz=-22.06, remainder_fraction=100.0000%, Lmin=-16.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=3595, logz=-18.07, remainder_fraction=100.0000%, Lmin=-12.33, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=3595, logz=-14.61, remainder_fraction=99.9999%, Lmin=-8.98, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=3595, logz=-12.44, remainder_fraction=99.9996%, Lmin=-6.92, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=3595, logz=-11.98, remainder_fraction=99.9993%, Lmin=-6.52, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=3595, logz=-9.90, remainder_fraction=99.9943%, Lmin=-4.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=3595, logz=-8.20, remainder_fraction=99.9692%, Lmin=-2.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=3595, logz=-6.66, remainder_fraction=99.8560%, Lmin=-1.41, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=3595, logz=-6.18, remainder_fraction=99.7670%, Lmin=-1.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=3595, logz=-5.56, remainder_fraction=99.5641%, Lmin=-0.49, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=3595, logz=-4.71, remainder_fraction=98.9746%, Lmin=0.33, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=3595, logz=-4.54, remainder_fraction=98.7881%, Lmin=0.51, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=3595, logz=-3.90, remainder_fraction=97.7307%, Lmin=1.22, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=3595, logz=-3.16, remainder_fraction=95.2752%, Lmin=1.83, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=3595, logz=-2.60, remainder_fraction=91.6644%, Lmin=2.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=3595, logz=-2.24, remainder_fraction=88.0170%, Lmin=2.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=3595, logz=-2.16, remainder_fraction=86.9760%, Lmin=2.59, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=3595, logz=-1.81, remainder_fraction=81.6668%, Lmin=2.85, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=3595, logz=-1.63, remainder_fraction=78.1472%, Lmin=2.98, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=3595, logz=-1.53, remainder_fraction=75.7564%, Lmin=3.05, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=3595, logz=-1.30, remainder_fraction=69.5858%, Lmin=3.18, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=3595, logz=-1.23, remainder_fraction=67.0561%, Lmin=3.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=3595, logz=-1.12, remainder_fraction=63.3836%, Lmin=3.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=3595, logz=-0.97, remainder_fraction=57.4148%, Lmin=3.37, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=3595, logz=-0.94, remainder_fraction=56.2675%, Lmin=3.38, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=3595, logz=-0.85, remainder_fraction=51.7929%, Lmin=3.42, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=3595, logz=-0.74, remainder_fraction=46.5893%, Lmin=3.47, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=3595, logz=-0.66, remainder_fraction=41.7151%, Lmin=3.52, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=3595, logz=-0.60, remainder_fraction=38.1094%, Lmin=3.55, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=3595, logz=-0.58, remainder_fraction=37.2343%, Lmin=3.56, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=3595, logz=-0.52, remainder_fraction=33.1317%, Lmin=3.58, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=3595, logz=-0.47, remainder_fraction=29.4601%, Lmin=3.61, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=3595, logz=-0.42, remainder_fraction=26.1457%, Lmin=3.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=3595, logz=-0.40, remainder_fraction=24.9168%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=3595, logz=-0.38, remainder_fraction=23.1781%, Lmin=3.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=3595, logz=-0.35, remainder_fraction=20.5306%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=3595, logz=-0.34, remainder_fraction=20.0329%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=3595, logz=-0.32, remainder_fraction=18.1657%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=3595, logz=-0.29, remainder_fraction=16.0618%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=3595, logz=-0.27, remainder_fraction=14.1983%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=3595, logz=-0.25, remainder_fraction=12.5457%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3595, logz=-0.24, remainder_fraction=11.0819%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3595, logz=-0.23, remainder_fraction=10.2864%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3595, logz=-0.22, remainder_fraction=9.7875%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3595, logz=-0.21, remainder_fraction=8.6428%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=3595, logz=-0.20, remainder_fraction=8.2231%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3595, logz=-0.20, remainder_fraction=7.6313%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3595, logz=-0.19, remainder_fraction=6.7373%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3595, logz=-0.19, remainder_fraction=6.5714%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3595, logz=-0.18, remainder_fraction=5.9476%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3595, logz=-0.17, remainder_fraction=5.2501%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=3595, logz=-0.17, remainder_fraction=4.6339%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=3595, logz=-0.16, remainder_fraction=4.1935%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=3595, logz=-0.16, remainder_fraction=4.0900%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=3595, logz=-0.15, remainder_fraction=3.6098%, Lmin=3.69, Lmax=3.69 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=4 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 3595 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -0.1173 +- 0.05407 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1233.8, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.10, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.05 tail:0.03 total:0.06 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_run_resume[0.1] | 5.90 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.23) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1226.65..3.68 [-1226.6504..3.5637] | it/evals=0/500 eff=0.0000% N=400 Z=-951.8(0.00%) | Like=-945.36..3.68 [-1226.6504..3.5637] | it/evals=50/500 eff=50.0000% N=400 Mono-modal Volume: ~exp(-4.40) * Expected Volume: exp(-0.23) Quality: correlation length: 11 (-) a: +0.0| ********************************************** | +1.0 Z=-786.4(0.00%) | Like=-779.24..3.68 [-1226.6504..3.5637] | it/evals=90/594 eff=46.3918% N=400 Z=-746.9(0.00%) | Like=-740.63..3.68 [-1226.6504..3.5637] | it/evals=100/594 eff=51.5464% N=400 Z=-574.4(0.00%) | Like=-567.24..3.68 [-1226.6504..3.5637] | it/evals=150/594 eff=77.3196% N=400 Have 2 modes Volume: ~exp(-4.52) * Expected Volume: exp(-0.45) Quality: correlation length: 11 (-) a: +0.0| 222222111111111111111111111111111111 +0.8 | +1.0 Z=-512.4(0.00%) | Like=-505.23..3.69 [-1226.6504..3.5637] | it/evals=180/681 eff=64.0569% N=400 Z=-476.3(0.00%) | Like=-468.28..3.69 [-1226.6504..3.5637] | it/evals=200/681 eff=71.1744% N=400 Z=-378.1(0.00%) | Like=-371.23..3.69 [-1226.6504..3.5637] | it/evals=250/758 eff=69.8324% N=400 Mono-modal Volume: ~exp(-4.57) * Expected Volume: exp(-0.67) Quality: correlation length: 11 (-) a: +0.0| +0.2 ****************************** +0.8 | +1.0 Z=-335.7(0.00%) | Like=-328.94..3.69 [-1226.6504..3.5637] | it/evals=270/758 eff=75.4190% N=400 Z=-298.0(0.00%) | Like=-291.53..3.69 [-1226.6504..3.5637] | it/evals=300/758 eff=83.7989% N=400 Z=-218.0(0.00%) | Like=-211.22..3.69 [-1226.6504..3.5637] | it/evals=350/816 eff=84.1346% N=400 Mono-modal Volume: ~exp(-4.60) * Expected Volume: exp(-0.90) Quality: correlation length: 11 (-) a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-207.9(0.00%) | Like=-199.20..3.69 [-1226.6504..3.5637] | it/evals=360/816 eff=86.5385% N=400 Z=-172.6(0.00%) | Like=-165.97..3.69 [-1226.6504..3.5637] | it/evals=400/872 eff=84.7458% N=400 Mono-modal Volume: ~exp(-5.49) * Expected Volume: exp(-1.12) Quality: correlation length: 11 (-) a: +0.0| +0.3 ******************** +0.7 | +1.0 Z=-133.1(0.00%) | Like=-126.45..3.69 [-1226.6504..3.5637] | it/evals=450/919 eff=86.7052% N=400 Z=-100.9(0.00%) | Like=-93.64..3.69 [-1226.6504..3.5637] | it/evals=500/997 eff=83.7521% N=400 Mono-modal Volume: ~exp(-5.49) Expected Volume: exp(-1.35) Quality: correlation length: 11 (-) a: +0.0| +0.4 ************** +0.6 | +1.0 Z=-71.4(0.00%) | Like=-64.75..3.69 [-1226.6504..3.5637] | it/evals=550/1031 eff=87.1632% N=400 Z=-57.4(0.00%) | Like=-50.86..3.69 [-1226.6504..3.5637] | it/evals=600/1084 eff=87.7193% N=400 Mono-modal Volume: ~exp(-5.89) * Expected Volume: exp(-1.57) Quality: correlation length: 11 (-) a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-49.9(0.00%) | Like=-44.17..3.69 [-1226.6504..3.5637] | it/evals=630/1125 eff=86.8966% N=400 Z=-45.1(0.00%) | Like=-38.91..3.69 [-1226.6504..3.5637] | it/evals=650/1146 eff=87.1314% N=400 Z=-34.8(0.00%) | Like=-28.81..3.69 [-1226.6504..3.5637] | it/evals=700/1203 eff=87.1731% N=400 Mono-modal Volume: ~exp(-6.01) * Expected Volume: exp(-1.80) Quality: correlation length: 11 (-) a: +0.0| +0.4 ********** +0.6 | +1.0 Z=-31.2(0.00%) | Like=-25.42..3.69 [-1226.6504..3.5637] | it/evals=720/1222 eff=87.5912% N=400 Z=-26.5(0.00%) | Like=-20.62..3.69 [-1226.6504..3.5637] | it/evals=750/1245 eff=88.7574% N=400 Z=-21.1(0.00%) | Like=-15.53..3.69 [-1226.6504..3.5637] | it/evals=800/1305 eff=88.3978% N=400 Mono-modal Volume: ~exp(-6.45) * Expected Volume: exp(-2.02) Quality: correlation length: 11 (-) a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-20.4(0.00%) | Like=-15.11..3.69 [-1226.6504..3.5637] | it/evals=810/1324 eff=87.6623% N=400 Z=-17.4(0.00%) | Like=-11.54..3.69 [-1226.6504..3.5637] | it/evals=850/1359 eff=88.6340% N=400 Mono-modal Volume: ~exp(-6.45) Expected Volume: exp(-2.25) Quality: correlation length: 11 (-) a: +0.00| +0.45 ****** +0.55 | +1.00 Z=-13.8(0.00%) | Like=-8.50..3.69 [-1226.6504..3.5637] | it/evals=900/1405 eff=89.5522% N=400 Z=-11.1(0.00%) | Like=-5.75..3.69 [-1226.6504..3.5637] | it/evals=950/1459 eff=89.7073% N=400 Mono-modal Volume: ~exp(-6.69) * Expected Volume: exp(-2.47) Quality: correlation length: 11 (-) a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-9.6(0.01%) | Like=-4.31..3.69 [-1226.6504..3.5637] | it/evals=990/1506 eff=89.5118% N=400 Z=-9.1(0.01%) | Like=-3.86..3.69 [-1226.6504..3.5637] | it/evals=1000/1506 eff=90.4159% N=400 Z=-7.4(0.06%) | Like=-2.39..3.69 [-1226.6504..3.5637] | it/evals=1050/1557 eff=90.7519% N=400 Mono-modal Volume: ~exp(-6.80) * Expected Volume: exp(-2.70) Quality: correlation length: 11 (-) a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.7(0.12%) | Like=-1.64..3.69 [-1226.6504..3.5637] | it/evals=1080/1586 eff=91.0624% N=400 Z=-6.2(0.20%) | Like=-1.12..3.69 [-1226.6504..3.5637] | it/evals=1100/1604 eff=91.3621% N=400 Z=-5.1(0.61%) | Like=-0.05..3.69 [-1226.6504..3.5637] | it/evals=1150/1658 eff=91.4149% N=400 Mono-modal Volume: ~exp(-6.93) * Expected Volume: exp(-2.92) Quality: correlation length: 11 (-) a: +0.00| +0.48 **** +0.52 | +1.00 Z=-4.6(0.95%) | Like=0.59..3.69 [-1226.6504..3.5637] | it/evals=1170/1683 eff=91.1925% N=400 Z=-4.0(1.81%) | Like=1.07..3.69 [-1226.6504..3.5637] | it/evals=1200/1714 eff=91.3242% N=400 Z=-3.2(3.98%) | Like=1.66..3.69 [-1226.6504..3.5637] | it/evals=1250/1762 eff=91.7768% N=400 Mono-modal Volume: ~exp(-7.48) * Expected Volume: exp(-3.15) Quality: correlation length: 11 (-) a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.0(4.53%) | Like=1.76..3.69 [-1226.6504..3.5637] | it/evals=1260/1771 eff=91.9037% N=400 Z=-2.6(7.13%) | Like=2.07..3.69 [-1226.6504..3.5637] | it/evals=1300/1816 eff=91.8079% N=400 Have 2 modes Volume: ~exp(-7.52) * Expected Volume: exp(-3.37) Quality: correlation length: 11 (-) a: +0.00| +0.48 12 +0.52 | +1.00 Z=-2.1(11.11%) | Like=2.32..3.69 [-1226.6504..3.5637] | it/evals=1350/1874 eff=91.5875% N=400 Z=-1.8(15.53%) | Like=2.60..3.69 [-1226.6504..3.5637] | it/evals=1400/1926 eff=91.7431% N=400 Mono-modal Volume: ~exp(-7.53) * Expected Volume: exp(-3.60) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(19.56%) | Like=2.80..3.69 [-1226.6504..3.5637] | it/evals=1440/1963 eff=92.1305% N=400 Z=-1.5(20.70%) | Like=2.84..3.69 [-1226.6504..3.5637] | it/evals=1450/1974 eff=92.1220% N=400 Z=-1.3(26.39%) | Like=3.03..3.69 [-1226.6504..3.5637] | it/evals=1500/2025 eff=92.3077% N=400 Mono-modal Volume: ~exp(-7.81) * Expected Volume: exp(-3.82) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.2(29.96%) | Like=3.15..3.69 [-1226.6504..3.5637] | it/evals=1530/2136 eff=88.1336% N=400 Z=-1.1(32.31%) | Like=3.20..3.69 [-1226.6504..3.5637] | it/evals=1550/2136 eff=89.2857% N=400 Z=-0.9(38.37%) | Like=3.32..3.69 [-1226.6504..3.5637] | it/evals=1600/2137 eff=92.1128% N=400 Mono-modal Volume: ~exp(-8.36) * Expected Volume: exp(-4.05) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.8(40.72%) | Like=3.34..3.69 [-1226.6504..3.5637] | it/evals=1620/2157 eff=92.2026% N=400 Z=-0.8(44.19%) | Like=3.40..3.69 [-1226.6504..3.5637] | it/evals=1650/2190 eff=92.1788% N=400 Z=-0.6(49.76%) | Like=3.46..3.69 [-1226.6504..3.5637] | it/evals=1700/2247 eff=92.0411% N=400 Have 2 modes Volume: ~exp(-8.73) * Expected Volume: exp(-4.27) Quality: correlation length: 11 (-) a: +0.00| +0.49 12 +0.51 | +1.00 Z=-0.6(50.83%) | Like=3.47..3.69 [-1226.6504..3.5637] | it/evals=1710/2253 eff=92.2828% N=400 Z=-0.5(54.98%) | Like=3.51..3.69 [-1226.6504..3.5637] | it/evals=1750/2389 eff=87.9839% N=400 Mono-modal Volume: ~exp(-8.73) * Expected Volume: exp(-4.50) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(59.78%) | Like=3.55..3.69 [-1226.6504..3.5637] | it/evals=1800/2389 eff=90.4977% N=400 Z=-0.4(64.17%) | Like=3.58..3.69 [3.5798..3.5798]*| it/evals=1850/2426 eff=91.3129% N=400 Mono-modal Volume: ~exp(-9.03) * Expected Volume: exp(-4.73) Quality: correlation length: 11 (-) a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.3(67.38%) | Like=3.60..3.69 [3.5969..3.5973]*| it/evals=1890/2460 eff=91.7476% N=400 Z=-0.3(68.15%) | Like=3.60..3.69 [3.6018..3.6018]*| it/evals=1900/2472 eff=91.6988% N=400 Z=-0.3(71.72%) | Like=3.62..3.69 [3.6196..3.6198]*| it/evals=1950/2523 eff=91.8512% N=400 Have 2 modes Volume: ~exp(-9.27) * Expected Volume: exp(-4.95) Quality: correlation length: 11 (-) a: +0.000| +0.497 21 +0.503 | +1.000 Z=-0.3(73.68%) | Like=3.63..3.69 [3.6266..3.6270]*| it/evals=1980/2553 eff=91.9647% N=400 Z=-0.2(74.92%) | Like=3.63..3.69 [3.6319..3.6319]*| it/evals=2000/2575 eff=91.9540% N=400 Z=-0.2(77.78%) | Like=3.64..3.69 [3.6423..3.6427]*| it/evals=2050/2633 eff=91.8047% N=400 Have 3 modes Volume: ~exp(-9.34) * Expected Volume: exp(-5.18) Quality: correlation length: 11 (-) a: +0.000| +0.497 11 +0.503 | +1.000 Z=-0.2(78.83%) | Like=3.65..3.69 [3.6467..3.6468]*| it/evals=2070/2651 eff=91.9591% N=400 Z=-0.2(80.33%) | Like=3.65..3.69 [3.6506..3.6508]*| it/evals=2100/2678 eff=92.1861% N=400 Z=-0.1(82.59%) | Like=3.66..3.69 [3.6585..3.6586]*| it/evals=2150/2739 eff=91.9196% N=400 Mono-modal Volume: ~exp(-9.68) * Expected Volume: exp(-5.40) Quality: correlation length: 11 (-) a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(83.02%) | Like=3.66..3.69 [3.6594..3.6597]*| it/evals=2160/2739 eff=92.3472% N=400 Z=-0.1(84.61%) | Like=3.66..3.69 [3.6643..3.6645]*| it/evals=2200/2780 eff=92.4370% N=400 Mono-modal Volume: ~exp(-9.86) * Expected Volume: exp(-5.63) Quality: correlation length: 11 (-) a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(86.40%) | Like=3.67..3.69 [3.6689..3.6689]*| it/evals=2250/2953 eff=88.1316% N=400 Z=-0.1(87.98%) | Like=3.67..3.69 [3.6723..3.6723]*| it/evals=2300/2953 eff=90.0901% N=400 Mono-modal Volume: ~exp(-9.86) Expected Volume: exp(-5.85) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.38%) | Like=3.68..3.69 [3.6755..3.6756]*| it/evals=2350/2953 eff=92.0486% N=400 Z=-0.0(90.62%) | Like=3.68..3.69 [3.6776..3.6776]*| it/evals=2400/3046 eff=90.7029% N=400 Mono-modal Volume: ~exp(-10.15) * Expected Volume: exp(-6.08) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(91.29%) | Like=3.68..3.69 [3.6791..3.6791]*| it/evals=2430/3046 eff=91.8367% N=400 Z=-0.0(91.72%) | Like=3.68..3.69 [3.6797..3.6798]*| it/evals=2450/3058 eff=92.1746% N=400 Z=-0.0(92.69%) | Like=3.68..3.69 [3.6815..3.6815]*| it/evals=2500/3113 eff=92.1489% N=400 Mono-modal Volume: ~exp(-10.34) * Expected Volume: exp(-6.30) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(93.04%) | Like=3.68..3.69 [3.6819..3.6819]*| it/evals=2520/3139 eff=92.0044% N=400 Z=-0.0(93.54%) | Like=3.68..3.69 [3.6825..3.6825]*| it/evals=2550/3167 eff=92.1576% N=400 Z=-0.0(94.30%) | Like=3.68..3.69 [3.6834..3.6834]*| it/evals=2600/3221 eff=92.1659% N=400 Mono-modal Volume: ~exp(-10.45) * Expected Volume: exp(-6.53) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.44%) | Like=3.68..3.69 [3.6835..3.6835]*| it/evals=2610/3221 eff=92.5204% N=400 Z=-0.0(94.97%) | Like=3.68..3.69 [3.6839..3.6840]*| it/evals=2650/3340 eff=90.1361% N=400 Mono-modal Volume: ~exp(-10.66) * Expected Volume: exp(-6.75) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=0.0(95.56%) | Like=3.68..3.69 [3.6844..3.6844]*| it/evals=2700/3340 eff=91.8367% N=400 Z=0.0(96.08%) | Like=3.68..3.69 [3.6848..3.6848]*| it/evals=2750/3469 eff=89.6057% N=400 Mono-modal Volume: ~exp(-11.05) * Expected Volume: exp(-6.98) Quality: correlation length: 11 (-) a: +0.0000| +0.4995 ** +0.5005 | +1.0000 Z=0.0(96.45%) | Like=3.69..3.69 [3.6851..3.6851]*| it/evals=2790/3469 eff=90.9091% N=400 Z=0.0(96.54%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2800/3469 eff=91.2349% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3469 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.06064 +- 0.06607 [ultranest] Effective samples strategy satisfied (ESS = 1263.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.05 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.14, need <0.1) [ultranest] logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.07 required:<0.10 [ultranest] done iterating. logZ = 0.050 +- 0.126 single instance: logZ = 0.050 +- 0.089 bootstrapped : logZ = 0.061 +- 0.121 tail : logZ = +- 0.033 insert order U test : converged: False correlation: 11.0 iterations a 0.500 +- 0.010 [ultranest] Resuming from 3368 stored points Mono-modal Volume: ~exp(-4.11) * Expected Volume: exp(0.00) Quality: ok a: +0.000|********************************************************| +1.000 Z=-inf(0.00%) | Like=-1226.65..3.68 [-1226.6504..3.5637] | it/evals=0/3469 eff=inf% N=400 Z=-951.8(0.00%) | Like=-945.36..3.68 [-1226.6504..3.5637] | it/evals=50/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-4.51) * Expected Volume: exp(-0.23) Quality: correlation length: 11 (-) a: +0.0| ********************************************** | +1.0 Z=-786.4(0.00%) | Like=-779.24..3.68 [-1226.6504..3.5637] | it/evals=90/3469 eff=inf% N=400 Z=-746.9(0.00%) | Like=-740.63..3.68 [-1226.6504..3.5637] | it/evals=100/3469 eff=inf% N=400 Z=-574.4(0.00%) | Like=-567.24..3.68 [-1226.6504..3.5637] | it/evals=150/3469 eff=inf% N=400 Have 2 modes Volume: ~exp(-4.54) * Expected Volume: exp(-0.45) Quality: correlation length: 11 (-) a: +0.0| 222222111111111111111111111111111111 +0.8 | +1.0 Z=-512.4(0.00%) | Like=-505.23..3.69 [-1226.6504..3.5637] | it/evals=180/3469 eff=inf% N=400 Z=-476.3(0.00%) | Like=-468.28..3.69 [-1226.6504..3.5637] | it/evals=200/3469 eff=inf% N=400 Z=-378.1(0.00%) | Like=-371.23..3.69 [-1226.6504..3.5637] | it/evals=250/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-4.72) * Expected Volume: exp(-0.67) Quality: correlation length: 11 (-) a: +0.0| +0.2 ****************************** +0.8 | +1.0 Z=-335.7(0.00%) | Like=-328.94..3.69 [-1226.6504..3.5637] | it/evals=270/3469 eff=inf% N=400 Z=-298.0(0.00%) | Like=-291.53..3.69 [-1226.6504..3.5637] | it/evals=300/3469 eff=inf% N=400 Z=-218.0(0.00%) | Like=-211.22..3.69 [-1226.6504..3.5637] | it/evals=350/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-4.93) * Expected Volume: exp(-0.90) Quality: correlation length: 11 (-) a: +0.0| +0.3 ************************ +0.7 | +1.0 Z=-207.9(0.00%) | Like=-199.20..3.69 [-1226.6504..3.5637] | it/evals=360/3469 eff=inf% N=400 Z=-172.6(0.00%) | Like=-165.97..3.69 [-1226.6504..3.5637] | it/evals=400/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-5.52) * Expected Volume: exp(-1.12) Quality: correlation length: 11 (-) a: +0.0| +0.3 ******************** +0.7 | +1.0 Z=-133.1(0.00%) | Like=-126.45..3.69 [-1226.6504..3.5637] | it/evals=450/3469 eff=inf% N=400 Z=-100.9(0.00%) | Like=-93.64..3.69 [-1226.6504..3.5637] | it/evals=500/3469 eff=inf% N=400 Have 2 modes Volume: ~exp(-5.69) * Expected Volume: exp(-1.35) Quality: correlation length: 11 (-) a: +0.0| +0.4 21111111111111 +0.6 | +1.0 Z=-77.2(0.00%) | Like=-70.26..3.69 [-1226.6504..3.5637] | it/evals=540/3469 eff=inf% N=400 Z=-71.4(0.00%) | Like=-64.75..3.69 [-1226.6504..3.5637] | it/evals=550/3469 eff=inf% N=400 Z=-57.4(0.00%) | Like=-50.86..3.69 [-1226.6504..3.5637] | it/evals=600/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-5.84) * Expected Volume: exp(-1.57) Quality: correlation length: 11 (-) a: +0.0| +0.4 ************ +0.6 | +1.0 Z=-49.9(0.00%) | Like=-44.17..3.69 [-1226.6504..3.5637] | it/evals=630/3469 eff=inf% N=400 Z=-45.1(0.00%) | Like=-38.91..3.69 [-1226.6504..3.5637] | it/evals=650/3469 eff=inf% N=400 Z=-34.8(0.00%) | Like=-28.81..3.69 [-1226.6504..3.5637] | it/evals=700/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-6.01) * Expected Volume: exp(-1.80) Quality: correlation length: 11 (-) a: +0.0| +0.4 ********** +0.6 | +1.0 Z=-31.2(0.00%) | Like=-25.42..3.69 [-1226.6504..3.5637] | it/evals=720/3469 eff=inf% N=400 Z=-26.5(0.00%) | Like=-20.62..3.69 [-1226.6504..3.5637] | it/evals=750/3469 eff=inf% N=400 Z=-21.1(0.00%) | Like=-15.53..3.69 [-1226.6504..3.5637] | it/evals=800/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-6.23) * Expected Volume: exp(-2.02) Quality: correlation length: 11 (-) a: +0.0| +0.4 ******** +0.6 | +1.0 Z=-20.4(0.00%) | Like=-15.11..3.69 [-1226.6504..3.5637] | it/evals=810/3469 eff=inf% N=400 Z=-17.4(0.00%) | Like=-11.54..3.69 [-1226.6504..3.5637] | it/evals=850/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-6.58) * Expected Volume: exp(-2.25) Quality: correlation length: 11 (-) a: +0.00| +0.45 ****** +0.55 | +1.00 Z=-13.8(0.00%) | Like=-8.50..3.69 [-1226.6504..3.5637] | it/evals=900/3469 eff=inf% N=400 Z=-11.1(0.00%) | Like=-5.75..3.69 [-1226.6504..3.5637] | it/evals=950/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-6.58) Expected Volume: exp(-2.47) Quality: correlation length: 11 (-) a: +0.00| +0.46 ****** +0.54 | +1.00 Z=-9.1(0.01%) | Like=-3.86..3.69 [-1226.6504..3.5637] | it/evals=1000/3469 eff=inf% N=400 Z=-7.4(0.06%) | Like=-2.39..3.69 [-1226.6504..3.5637] | it/evals=1050/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-6.65) * Expected Volume: exp(-2.70) Quality: correlation length: 11 (-) a: +0.00| +0.47 **** +0.53 | +1.00 Z=-6.7(0.12%) | Like=-1.64..3.69 [-1226.6504..3.5637] | it/evals=1080/3469 eff=inf% N=400 Z=-6.2(0.20%) | Like=-1.12..3.69 [-1226.6504..3.5637] | it/evals=1100/3469 eff=inf% N=400 Z=-5.1(0.61%) | Like=-0.05..3.69 [-1226.6504..3.5637] | it/evals=1150/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-7.18) * Expected Volume: exp(-2.92) Quality: correlation length: 11 (-) a: +0.00| +0.48 **** +0.52 | +1.00 Z=-4.6(0.95%) | Like=0.59..3.69 [-1226.6504..3.5637] | it/evals=1170/3469 eff=inf% N=400 Z=-4.0(1.81%) | Like=1.07..3.69 [-1226.6504..3.5637] | it/evals=1200/3469 eff=inf% N=400 Z=-3.2(3.98%) | Like=1.66..3.69 [-1226.6504..3.5637] | it/evals=1250/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-7.26) * Expected Volume: exp(-3.15) Quality: correlation length: 11 (-) a: +0.00| +0.48 **** +0.52 | +1.00 Z=-3.0(4.53%) | Like=1.76..3.69 [-1226.6504..3.5637] | it/evals=1260/3469 eff=inf% N=400 Z=-2.6(7.13%) | Like=2.07..3.69 [-1226.6504..3.5637] | it/evals=1300/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-7.53) * Expected Volume: exp(-3.37) Quality: correlation length: 11 (-) a: +0.00| +0.48 ** +0.52 | +1.00 Z=-2.1(11.11%) | Like=2.32..3.69 [-1226.6504..3.5637] | it/evals=1350/3469 eff=inf% N=400 Z=-1.8(15.53%) | Like=2.60..3.69 [-1226.6504..3.5637] | it/evals=1400/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-7.92) * Expected Volume: exp(-3.60) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.6(19.56%) | Like=2.80..3.69 [-1226.6504..3.5637] | it/evals=1440/3469 eff=inf% N=400 Z=-1.5(20.70%) | Like=2.84..3.69 [-1226.6504..3.5637] | it/evals=1450/3469 eff=inf% N=400 Z=-1.3(26.39%) | Like=3.03..3.69 [-1226.6504..3.5637] | it/evals=1500/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-8.15) * Expected Volume: exp(-3.82) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-1.2(29.96%) | Like=3.15..3.69 [-1226.6504..3.5637] | it/evals=1530/3469 eff=inf% N=400 Z=-1.1(32.31%) | Like=3.20..3.69 [-1226.6504..3.5637] | it/evals=1550/3469 eff=inf% N=400 Z=-0.9(38.37%) | Like=3.32..3.69 [-1226.6504..3.5637] | it/evals=1600/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-8.15) Expected Volume: exp(-4.05) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.8(44.19%) | Like=3.40..3.69 [-1226.6504..3.5637] | it/evals=1650/3469 eff=inf% N=400 Z=-0.6(49.76%) | Like=3.46..3.69 [-1226.6504..3.5637] | it/evals=1700/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-8.63) * Expected Volume: exp(-4.27) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.6(50.83%) | Like=3.47..3.69 [-1226.6504..3.5637] | it/evals=1710/3469 eff=inf% N=400 Z=-0.5(54.98%) | Like=3.51..3.69 [-1226.6504..3.5637] | it/evals=1750/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-8.93) * Expected Volume: exp(-4.50) Quality: correlation length: 11 (-) a: +0.00| +0.49 ** +0.51 | +1.00 Z=-0.5(59.78%) | Like=3.55..3.69 [-1226.6504..3.5637] | it/evals=1800/3469 eff=inf% N=400 Z=-0.4(64.17%) | Like=3.58..3.69 [3.5798..3.5798]*| it/evals=1850/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-8.93) Expected Volume: exp(-4.73) Quality: correlation length: 11 (-) a: +0.000| +0.496 ** +0.504 | +1.000 Z=-0.3(68.15%) | Like=3.60..3.69 [3.6018..3.6018]*| it/evals=1900/3469 eff=inf% N=400 Z=-0.3(71.72%) | Like=3.62..3.69 [3.6196..3.6198]*| it/evals=1950/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-9.34) * Expected Volume: exp(-4.95) Quality: correlation length: 11 (-) a: +0.000| +0.497 ** +0.503 | +1.000 Z=-0.3(73.68%) | Like=3.63..3.69 [3.6266..3.6270]*| it/evals=1980/3469 eff=inf% N=400 Z=-0.2(74.92%) | Like=3.63..3.69 [3.6319..3.6319]*| it/evals=2000/3469 eff=inf% N=400 Z=-0.2(77.78%) | Like=3.64..3.69 [3.6423..3.6427]*| it/evals=2050/3469 eff=inf% N=400 Have 2 modes Volume: ~exp(-9.39) * Expected Volume: exp(-5.18) Quality: correlation length: 11 (-) a: +0.000| +0.497 11 +0.503 | +1.000 Z=-0.2(78.83%) | Like=3.65..3.69 [3.6467..3.6468]*| it/evals=2070/3469 eff=inf% N=400 Z=-0.2(80.33%) | Like=3.65..3.69 [3.6506..3.6508]*| it/evals=2100/3469 eff=inf% N=400 Z=-0.1(82.59%) | Like=3.66..3.69 [3.6585..3.6586]*| it/evals=2150/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-9.39) * Expected Volume: exp(-5.40) Quality: correlation length: 11 (-) a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(83.02%) | Like=3.66..3.69 [3.6594..3.6597]*| it/evals=2160/3469 eff=inf% N=400 Z=-0.1(84.61%) | Like=3.66..3.69 [3.6643..3.6645]*| it/evals=2200/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-9.81) * Expected Volume: exp(-5.63) Quality: correlation length: 11 (-) a: +0.000| +0.498 ** +0.502 | +1.000 Z=-0.1(86.40%) | Like=3.67..3.69 [3.6689..3.6689]*| it/evals=2250/3469 eff=inf% N=400 Z=-0.1(87.98%) | Like=3.67..3.69 [3.6723..3.6723]*| it/evals=2300/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-9.91) * Expected Volume: exp(-5.85) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.1(89.11%) | Like=3.68..3.69 [3.6750..3.6751]*| it/evals=2340/3469 eff=inf% N=400 Z=-0.1(89.38%) | Like=3.68..3.69 [3.6755..3.6756]*| it/evals=2350/3469 eff=inf% N=400 Z=-0.0(90.62%) | Like=3.68..3.69 [3.6776..3.6776]*| it/evals=2400/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-9.93) * Expected Volume: exp(-6.08) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(91.29%) | Like=3.68..3.69 [3.6791..3.6791]*| it/evals=2430/3469 eff=inf% N=400 Z=-0.0(91.72%) | Like=3.68..3.69 [3.6797..3.6798]*| it/evals=2450/3469 eff=inf% N=400 Z=-0.0(92.69%) | Like=3.68..3.69 [3.6815..3.6815]*| it/evals=2500/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-10.29) * Expected Volume: exp(-6.30) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(93.04%) | Like=3.68..3.69 [3.6819..3.6819]*| it/evals=2520/3469 eff=inf% N=400 Z=-0.0(93.54%) | Like=3.68..3.69 [3.6825..3.6825]*| it/evals=2550/3469 eff=inf% N=400 Z=-0.0(94.30%) | Like=3.68..3.69 [3.6834..3.6834]*| it/evals=2600/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-10.74) * Expected Volume: exp(-6.53) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=-0.0(94.44%) | Like=3.68..3.69 [3.6835..3.6835]*| it/evals=2610/3469 eff=inf% N=400 Z=-0.0(94.97%) | Like=3.68..3.69 [3.6839..3.6840]*| it/evals=2650/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-10.83) * Expected Volume: exp(-6.75) Quality: correlation length: 11 (-) a: +0.000| +0.499 ** +0.501 | +1.000 Z=0.0(95.56%) | Like=3.68..3.69 [3.6844..3.6844]*| it/evals=2700/3469 eff=inf% N=400 Z=0.0(96.08%) | Like=3.68..3.69 [3.6848..3.6848]*| it/evals=2750/3469 eff=inf% N=400 Mono-modal Volume: ~exp(-11.06) * Expected Volume: exp(-6.98) Quality: correlation length: 11 (-) a: +0.0000| +0.4995 ** +0.5005 | +1.0000 Z=0.0(96.45%) | Like=3.69..3.69 [3.6851..3.6851]*| it/evals=2790/3469 eff=inf% N=400 Z=0.0(96.54%) | Like=3.69..3.69 [3.6852..3.6852]*| it/evals=2800/3469 eff=inf% N=400 [ultranest] Explored until L=4 [ultranest] Likelihood function evaluations: 3469 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] logZ = 0.05168 +- 0.07736 [ultranest] Effective samples strategy satisfied (ESS = 1263.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.16, need <0.1) [ultranest] logZ error budget: single: 0.09 bs:0.08 tail:0.03 total:0.08 required:<0.10 [ultranest] done iterating. logZ = 0.050 +- 0.144 single instance: logZ = 0.050 +- 0.089 bootstrapped : logZ = 0.052 +- 0.140 tail : logZ = +- 0.033 insert order U test : converged: False correlation: 11.0 iterations a 0.500 +- 0.010 ran with dlogz: 0.1 first run gave: {'niter': 3210, 'logz': 0.05007425375795922, 'logzerr': 0.1259031303829853, 'logz_bs': 0.060637411510027196, 'logz_single': 0.05007425375795922, 'logzerr_tail': 0.033179507400614386, 'logzerr_bs': 0.12145253611550307, 'ess': 1263.8576481794294, 'H': 3.1468886719437146, 'Herr': 0.06589050463297975, 'posterior': {'mean': [0.5000779609737973], 'stdev': [0.010066292415746223], 'median': [0.4998407988189507], 'errlo': [0.4900202529404075], 'errup': [0.5098428871484062], 'information_gain_bits': [3.468884837016907]}, 'maximum_likelihood': {'logl': 3.6862316478600636, 'point': [0.4999990076941093], 'point_untransformed': [0.4999990076941093]}, 'ncall': 3469, 'paramnames': ['a'], 'logzerr_single': 0.08869736005011246, 'insertion_order_MWW_test': {'independent_iterations': 11.0, 'converged': False}} second run gave: {'niter': 3210, 'logz': 0.05007425375795922, 'logzerr': 0.14421262852260344, 'logz_bs': 0.05168271140077616, 'logz_single': 0.05007425375795922, 'logzerr_tail': 0.033179507400614386, 'logzerr_bs': 0.14034387237799517, 'ess': 1263.8576481794294, 'H': 3.1468886719437146, 'Herr': 0.07335937065668022, 'posterior': {'mean': [0.5000876069232556], 'stdev': [0.01005314026385506], 'median': [0.49998679950449504], 'errlo': [0.49001118680948863], 'errup': [0.5098186563050526], 'information_gain_bits': [3.468884837016907]}, 'maximum_likelihood': {'logl': 3.6862316478600636, 'point': [0.4999990076941093], 'point_untransformed': [0.4999990076941093]}, 'ncall': 3469, 'paramnames': ['a'], 'logzerr_single': 0.08869736005011246, 'insertion_order_MWW_test': {'independent_iterations': 11.0, 'converged': False}} -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpo0asn8ok, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=500, logz=-inf, remainder_fraction=100.0000%, Lmin=-1226.65, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=500, logz=-951.81, remainder_fraction=100.0000%, Lmin=-945.36, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=594, logz=-786.35, remainder_fraction=100.0000%, Lmin=-779.24, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=594, logz=-746.93, remainder_fraction=100.0000%, Lmin=-740.63, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=594, logz=-574.45, remainder_fraction=100.0000%, Lmin=-567.24, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=681, logz=-512.36, remainder_fraction=100.0000%, Lmin=-505.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=681, logz=-476.28, remainder_fraction=100.0000%, Lmin=-468.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=758, logz=-378.12, remainder_fraction=100.0000%, Lmin=-371.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=758, logz=-335.69, remainder_fraction=100.0000%, Lmin=-328.94, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=758, logz=-298.02, remainder_fraction=100.0000%, Lmin=-291.53, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=816, logz=-218.03, remainder_fraction=100.0000%, Lmin=-211.22, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=816, logz=-207.94, remainder_fraction=100.0000%, Lmin=-199.20, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=872, logz=-172.63, remainder_fraction=100.0000%, Lmin=-165.97, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=919, logz=-133.06, remainder_fraction=100.0000%, Lmin=-126.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=997, logz=-100.95, remainder_fraction=100.0000%, Lmin=-93.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=1031, logz=-71.39, remainder_fraction=100.0000%, Lmin=-64.75, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=1084, logz=-57.38, remainder_fraction=100.0000%, Lmin=-50.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=1125, logz=-49.91, remainder_fraction=100.0000%, Lmin=-44.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=1146, logz=-45.08, remainder_fraction=100.0000%, Lmin=-38.91, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=1203, logz=-34.81, remainder_fraction=100.0000%, Lmin=-28.81, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=1222, logz=-31.23, remainder_fraction=100.0000%, Lmin=-25.42, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=1245, logz=-26.49, remainder_fraction=100.0000%, Lmin=-20.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=1305, logz=-21.13, remainder_fraction=100.0000%, Lmin=-15.53, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=1324, logz=-20.42, remainder_fraction=100.0000%, Lmin=-15.11, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=1359, logz=-17.37, remainder_fraction=100.0000%, Lmin=-11.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1405, logz=-13.85, remainder_fraction=99.9999%, Lmin=-8.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=1459, logz=-11.13, remainder_fraction=99.9986%, Lmin=-5.75, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=1506, logz=-9.56, remainder_fraction=99.9931%, Lmin=-4.31, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=1506, logz=-9.15, remainder_fraction=99.9895%, Lmin=-3.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=1557, logz=-7.41, remainder_fraction=99.9409%, Lmin=-2.39, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=1586, logz=-6.66, remainder_fraction=99.8754%, Lmin=-1.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=1604, logz=-6.16, remainder_fraction=99.7957%, Lmin=-1.12, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=1658, logz=-5.06, remainder_fraction=99.3933%, Lmin=-0.05, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=1683, logz=-4.61, remainder_fraction=99.0470%, Lmin=0.59, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=1714, logz=-3.97, remainder_fraction=98.1900%, Lmin=1.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=1762, logz=-3.18, remainder_fraction=96.0219%, Lmin=1.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=1771, logz=-3.05, remainder_fraction=95.4735%, Lmin=1.76, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=1816, logz=-2.58, remainder_fraction=92.8655%, Lmin=2.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=1874, logz=-2.15, remainder_fraction=88.8874%, Lmin=2.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=1926, logz=-1.81, remainder_fraction=84.4746%, Lmin=2.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=1963, logz=-1.58, remainder_fraction=80.4444%, Lmin=2.80, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=1974, logz=-1.53, remainder_fraction=79.3015%, Lmin=2.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=2025, logz=-1.28, remainder_fraction=73.6095%, Lmin=3.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=2136, logz=-1.16, remainder_fraction=70.0390%, Lmin=3.15, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=2136, logz=-1.08, remainder_fraction=67.6861%, Lmin=3.20, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=2137, logz=-0.91, remainder_fraction=61.6345%, Lmin=3.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=2157, logz=-0.85, remainder_fraction=59.2757%, Lmin=3.34, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=2190, logz=-0.77, remainder_fraction=55.8108%, Lmin=3.40, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=2247, logz=-0.65, remainder_fraction=50.2425%, Lmin=3.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=2253, logz=-0.63, remainder_fraction=49.1701%, Lmin=3.47, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=2389, logz=-0.55, remainder_fraction=45.0224%, Lmin=3.51, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=2389, logz=-0.46, remainder_fraction=40.2243%, Lmin=3.55, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=2426, logz=-0.39, remainder_fraction=35.8345%, Lmin=3.58, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=2460, logz=-0.34, remainder_fraction=32.6174%, Lmin=3.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=2472, logz=-0.33, remainder_fraction=31.8523%, Lmin=3.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=2523, logz=-0.28, remainder_fraction=28.2819%, Lmin=3.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=2553, logz=-0.26, remainder_fraction=26.3218%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=2575, logz=-0.24, remainder_fraction=25.0831%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=2633, logz=-0.20, remainder_fraction=22.2240%, Lmin=3.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3]), array([345, 1, 54])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=2651, logz=-0.19, remainder_fraction=21.1658%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=2678, logz=-0.17, remainder_fraction=19.6743%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=2739, logz=-0.14, remainder_fraction=17.4060%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=2739, logz=-0.14, remainder_fraction=16.9845%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=2780, logz=-0.12, remainder_fraction=15.3931%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=2953, logz=-0.10, remainder_fraction=13.6042%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=2953, logz=-0.08, remainder_fraction=12.0199%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=2953, logz=-0.06, remainder_fraction=10.6188%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3046, logz=-0.05, remainder_fraction=9.3790%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3046, logz=-0.04, remainder_fraction=8.7051%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3058, logz=-0.04, remainder_fraction=8.2827%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3113, logz=-0.03, remainder_fraction=7.3129%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=3139, logz=-0.02, remainder_fraction=6.9574%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3167, logz=-0.02, remainder_fraction=6.4561%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3221, logz=-0.01, remainder_fraction=5.6989%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3221, logz=-0.01, remainder_fraction=5.5585%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3340, logz=-0.00, remainder_fraction=5.0305%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3340, logz=0.00, remainder_fraction=4.4402%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=3469, logz=0.01, remainder_fraction=3.9190%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=3469, logz=0.01, remainder_fraction=3.5464%, Lmin=3.69, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=3469, logz=0.01, remainder_fraction=3.4589%, Lmin=3.69, Lmax=3.69 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=4 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 3469 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = 0.06064 +- 0.06607 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1263.9, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.05 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.14, need <0.1) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.07 tail:0.03 total:0.07 required:<0.10 [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpo0asn8ok, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [35mDEBUG [0m ultranest:integrator.py:1126 Testing resume consistency: [3.68450361 3.68579645 0. 0.49970498 0.49970498]: u=[0.49970498] -> p=[0.49970498] -> L=3.6857964549601805 [32mINFO [0m ultranest:integrator.py:2164 Resuming from 3368 stored points [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.1, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=3469, logz=-inf, remainder_fraction=100.0000%, Lmin=-1226.65, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=3469, logz=-951.81, remainder_fraction=100.0000%, Lmin=-945.36, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=3469, logz=-786.35, remainder_fraction=100.0000%, Lmin=-779.24, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=3469, logz=-746.93, remainder_fraction=100.0000%, Lmin=-740.63, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=3469, logz=-574.45, remainder_fraction=100.0000%, Lmin=-567.24, Lmax=3.68 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=3469, logz=-512.36, remainder_fraction=100.0000%, Lmin=-505.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=3469, logz=-476.28, remainder_fraction=100.0000%, Lmin=-468.28, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=3469, logz=-378.12, remainder_fraction=100.0000%, Lmin=-371.23, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=3469, logz=-335.69, remainder_fraction=100.0000%, Lmin=-328.94, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=3469, logz=-298.02, remainder_fraction=100.0000%, Lmin=-291.53, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=3469, logz=-218.03, remainder_fraction=100.0000%, Lmin=-211.22, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=3469, logz=-207.94, remainder_fraction=100.0000%, Lmin=-199.20, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=3469, logz=-172.63, remainder_fraction=100.0000%, Lmin=-165.97, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=3469, logz=-133.06, remainder_fraction=100.0000%, Lmin=-126.45, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=3469, logz=-100.95, remainder_fraction=100.0000%, Lmin=-93.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=3469, logz=-77.23, remainder_fraction=100.0000%, Lmin=-70.26, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=3469, logz=-71.39, remainder_fraction=100.0000%, Lmin=-64.75, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=3469, logz=-57.38, remainder_fraction=100.0000%, Lmin=-50.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=3469, logz=-49.91, remainder_fraction=100.0000%, Lmin=-44.17, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=3469, logz=-45.08, remainder_fraction=100.0000%, Lmin=-38.91, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=3469, logz=-34.81, remainder_fraction=100.0000%, Lmin=-28.81, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=3469, logz=-31.23, remainder_fraction=100.0000%, Lmin=-25.42, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=3469, logz=-26.49, remainder_fraction=100.0000%, Lmin=-20.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=3469, logz=-21.13, remainder_fraction=100.0000%, Lmin=-15.53, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=3469, logz=-20.42, remainder_fraction=100.0000%, Lmin=-15.11, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=3469, logz=-17.37, remainder_fraction=100.0000%, Lmin=-11.54, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=3469, logz=-13.85, remainder_fraction=99.9999%, Lmin=-8.50, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=3469, logz=-11.13, remainder_fraction=99.9986%, Lmin=-5.75, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=3469, logz=-9.15, remainder_fraction=99.9895%, Lmin=-3.86, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=3469, logz=-7.41, remainder_fraction=99.9409%, Lmin=-2.39, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=3469, logz=-6.66, remainder_fraction=99.8754%, Lmin=-1.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=3469, logz=-6.16, remainder_fraction=99.7957%, Lmin=-1.12, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=3469, logz=-5.06, remainder_fraction=99.3933%, Lmin=-0.05, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=3469, logz=-4.61, remainder_fraction=99.0470%, Lmin=0.59, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=3469, logz=-3.97, remainder_fraction=98.1900%, Lmin=1.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=3469, logz=-3.18, remainder_fraction=96.0219%, Lmin=1.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=3469, logz=-3.05, remainder_fraction=95.4735%, Lmin=1.76, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=3469, logz=-2.58, remainder_fraction=92.8655%, Lmin=2.07, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=3469, logz=-2.15, remainder_fraction=88.8874%, Lmin=2.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=3469, logz=-1.81, remainder_fraction=84.4746%, Lmin=2.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=3469, logz=-1.58, remainder_fraction=80.4444%, Lmin=2.80, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=3469, logz=-1.53, remainder_fraction=79.3015%, Lmin=2.84, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=3469, logz=-1.28, remainder_fraction=73.6095%, Lmin=3.03, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=3469, logz=-1.16, remainder_fraction=70.0390%, Lmin=3.15, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=3469, logz=-1.08, remainder_fraction=67.6861%, Lmin=3.20, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=3469, logz=-0.91, remainder_fraction=61.6345%, Lmin=3.32, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=3469, logz=-0.77, remainder_fraction=55.8108%, Lmin=3.40, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=3469, logz=-0.65, remainder_fraction=50.2425%, Lmin=3.46, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=3469, logz=-0.63, remainder_fraction=49.1701%, Lmin=3.47, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=3469, logz=-0.55, remainder_fraction=45.0224%, Lmin=3.51, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=3469, logz=-0.46, remainder_fraction=40.2243%, Lmin=3.55, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=3469, logz=-0.39, remainder_fraction=35.8345%, Lmin=3.58, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=3469, logz=-0.33, remainder_fraction=31.8523%, Lmin=3.60, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=3469, logz=-0.28, remainder_fraction=28.2819%, Lmin=3.62, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=3469, logz=-0.26, remainder_fraction=26.3218%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=3469, logz=-0.24, remainder_fraction=25.0831%, Lmin=3.63, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=3469, logz=-0.20, remainder_fraction=22.2240%, Lmin=3.64, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=3469, logz=-0.19, remainder_fraction=21.1658%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=3469, logz=-0.17, remainder_fraction=19.6743%, Lmin=3.65, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=3469, logz=-0.14, remainder_fraction=17.4060%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=3469, logz=-0.14, remainder_fraction=16.9845%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=3469, logz=-0.12, remainder_fraction=15.3931%, Lmin=3.66, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=3469, logz=-0.10, remainder_fraction=13.6042%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=3469, logz=-0.08, remainder_fraction=12.0199%, Lmin=3.67, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2340, ncalls=3469, logz=-0.07, remainder_fraction=10.8855%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=3469, logz=-0.06, remainder_fraction=10.6188%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=3469, logz=-0.05, remainder_fraction=9.3790%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=3469, logz=-0.04, remainder_fraction=8.7051%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=3469, logz=-0.04, remainder_fraction=8.2827%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=3469, logz=-0.03, remainder_fraction=7.3129%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=3469, logz=-0.02, remainder_fraction=6.9574%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=3469, logz=-0.02, remainder_fraction=6.4561%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=3469, logz=-0.01, remainder_fraction=5.6989%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=3469, logz=-0.01, remainder_fraction=5.5585%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=3469, logz=-0.00, remainder_fraction=5.0305%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=3469, logz=0.00, remainder_fraction=4.4402%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=3469, logz=0.01, remainder_fraction=3.9190%, Lmin=3.68, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=3469, logz=0.01, remainder_fraction=3.5464%, Lmin=3.69, Lmax=3.69 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=3469, logz=0.01, remainder_fraction=3.4589%, Lmin=3.69, Lmax=3.69 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=4 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 3469 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = 0.05168 +- 0.07736 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1263.9, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.16, need <0.1) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.09 bs:0.08 tail:0.03 total:0.08 required:<0.10 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_reactive_run_resume_eggbox[hdf5] | 1.14 | |
------------------------------Captured stdout call------------------------------ ====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..225.3019] | it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..225.3019] | it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..225.3019] | it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..225.3019] | it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..225.3019] | it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..225.3019] | it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..225.3019] | it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [1.1994..225.3019] | it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [1.1994..225.3019] | it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [1.1994..225.3019] | it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [1.1994..225.3019] | it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [1.1994..225.3019] | it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=43.4(0.00%) | Like=49.11..241.87 [1.1994..225.3019] | it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [1.1994..225.3019] | it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [1.1994..225.3019] | it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [1.1994..225.3019] | it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [1.1994..225.3019] | it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [1.1994..225.3019] | it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [1.1994..225.3019] | it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [1.1994..225.3019] | it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a 18.98 +- 0.35 b 6.3 +- 1.1 pointstore: (300, 7) 626 626 0 ====== Running Eggbox problem [2] ===== [ultranest] Resuming from 300 stored points Mono-modal Volume: ~exp(-3.06) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..225.3019] | it/evals=0/626 eff=inf% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..225.3019] | it/evals=10/626 eff=inf% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..225.3019] | it/evals=20/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..225.3019] | it/evals=30/626 eff=inf% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..225.3019] | it/evals=40/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..225.3019] | it/evals=50/626 eff=inf% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..225.3019] | it/evals=60/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [1.1994..225.3019] | it/evals=70/626 eff=inf% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [1.1994..225.3019] | it/evals=80/626 eff=inf% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [1.1994..225.3019] | it/evals=90/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.06) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [1.1994..225.3019] | it/evals=100/626 eff=inf% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [1.1994..225.3019] | it/evals=110/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) * Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=41.4(0.00%) | Like=46.04..241.87 [1.1994..225.3019] | it/evals=115/626 eff=inf% N=100 Z=43.4(0.00%) | Like=49.11..241.87 [1.1994..225.3019] | it/evals=120/626 eff=inf% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [1.1994..225.3019] | it/evals=130/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [1.1994..225.3019] | it/evals=140/626 eff=inf% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [1.1994..225.3019] | it/evals=150/626 eff=inf% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [1.1994..225.3019] | it/evals=160/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [1.1994..225.3019] | it/evals=170/626 eff=inf% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [1.1994..225.3019] | it/evals=180/626 eff=inf% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [1.1994..225.3019] | it/evals=190/626 eff=inf% N=100 Z=102.1(0.00%) | Like=108.02..241.87 [1.1994..225.3019] | it/evals=200/635 eff=2222.2222% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.07) Quality: ok a: +0.0| ** ******* ****** ****** ******* ****| +31.4 b: +0.0|**** ******* *** ** ******* ****** ***| +31.4 Z=107.6(0.00%) | Like=113.25..241.87 [1.1994..225.3019] | it/evals=210/686 eff=350.0000% N=100 Z=115.9(0.00%) | Like=122.26..241.87 [1.1994..225.3019] | it/evals=220/773 eff=149.6599% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.30) Quality: ok a: +0.0|*** ***** ******* ****** ****** ***| +31.4 b: +0.0|*** ****** ** ** ****** ****** ***| +31.4 Z=122.3(0.00%) | Like=129.85..241.87 [1.1994..225.3019] | it/evals=230/847 eff=104.0724% N=100 Z=129.8(0.00%) | Like=136.55..241.87 [1.1994..225.3019] | it/evals=240/970 eff=69.7674% N=100 Z=137.3(0.00%) | Like=144.23..241.87 [1.1994..225.3019] | it/evals=250/1051 eff=58.8235% N=100 Mono-modal Volume: ~exp(-3.27) Expected Volume: exp(-2.53) Quality: ok a: +3.1e-05|*** ***** ***** ***** ***** ***| +3.1e+01 b: +0.0|*** ****** ** ** ***** ****** ***| +31.4 Z=142.6(0.00%) | Like=149.88..241.87 [1.1994..225.3019] | it/evals=260/1113 eff=53.3881% N=100 Z=150.6(0.00%) | Like=158.76..242.08 [1.1994..225.3019] | it/evals=270/1240 eff=43.9739% N=100 Have 17 modes Volume: ~exp(-3.30) * Expected Volume: exp(-2.76) Quality: ok a: +3.1e-05|66 HAFAH 3343 522D5 11191 G77| +3.1e+01 b: +3.1e-05|66E 2H22C 94 44 55A75 31131 DDF| +3.1e+01 Z=155.4(0.00%) | Like=161.77..242.08 [1.1994..225.3019] | it/evals=276/1298 eff=41.0714% N=100 Z=157.4(0.00%) | Like=165.84..242.08 [1.1994..225.3019] | it/evals=280/1339 eff=39.2707% N=100 Z=163.4(0.00%) | Like=169.78..242.08 [1.1994..225.3019] | it/evals=290/1390 eff=37.9581% N=100 Have 11 modes Volume: ~exp(-3.97) * Expected Volume: exp(-2.99) Quality: ok a: +3.1e-05|61 1AB31 33432 22221 1112 87| +3.1e+01 b: +3.1e-05|61 12228 94221 173A1 31131 3B| +3.1e+01 Z=169.2(0.00%) | Like=176.32..242.08 [1.1994..225.3019] | it/evals=299/1456 eff=36.0241% N=100 Z=169.7(0.00%) | Like=176.48..242.08 [1.1994..225.3019] | it/evals=300/1464 eff=35.7995% N=100 Z=177.0(0.00%) | Like=183.98..242.08 [1.1994..225.3019] | it/evals=310/1544 eff=33.7691% N=100 Z=182.0(0.00%) | Like=189.03..242.08 [1.1994..225.3019] | it/evals=320/1653 eff=31.1587% N=100 Have 11 modes Volume: ~exp(-4.06) * Expected Volume: exp(-3.22) Quality: ok a: +3.1e-05|61 1A111 33432 22221 8112 87| +3.1e+01 b: +3.1e-05|61 12288 9421 173A3 1133 3B| +3.1e+01 Z=182.7(0.00%) | Like=189.52..242.08 [1.1994..225.3019] | it/evals=322/1678 eff=30.6084% N=100 Z=185.5(0.00%) | Like=192.14..242.08 [1.1994..225.3019] | it/evals=330/1823 eff=27.5689% N=100 Z=187.8(0.00%) | Like=194.77..242.08 [1.1994..225.3019] | it/evals=340/1954 eff=25.6024% N=100 Have 9 modes Volume: ~exp(-4.40) * Expected Volume: exp(-3.45) Quality: ok a: +3.1e-05|69 1311 3432 22221 1112 27| +3.1e+01 b: +3.1e-05|82 1221 42 17233 1139 9| +3.1e+01 Z=189.3(0.00%) | Like=196.24..242.08 [1.1994..225.3019] | it/evals=345/2018 eff=24.7845% N=100 Z=190.7(0.00%) | Like=197.56..242.08 [1.1994..225.3019] | it/evals=350/2076 eff=24.1379% N=100 Z=193.4(0.00%) | Like=201.00..242.08 [1.1994..225.3019] | it/evals=360/2164 eff=23.4070% N=100 Have 9 modes Volume: ~exp(-4.40) Expected Volume: exp(-3.68) Quality: ok a: +3.1e-05|69 9391 343 222 1112 27| +3.1e+01 b: +3.1e-05|82 221 420 7233 1133 9| +3.1e+01 Z=197.1(0.00%) | Like=204.14..242.08 [1.1994..225.3019] | it/evals=370/2261 eff=22.6300% N=100 Z=200.0(0.00%) | Like=206.82..242.86 [1.1994..225.3019] | it/evals=380/2354 eff=21.9907% N=100 Z=203.2(0.00%) | Like=210.59..242.86 [1.1994..225.3019] | it/evals=390/2534 eff=20.4403% N=100 Have 9 modes Volume: ~exp(-4.40) Expected Volume: exp(-3.91) Quality: ok a: +3.1e-05|69 9391 343 222 1111 27| +3.1e+01 b: +3.1e-05|82 221 430 723 113 09| +3.1e+01 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 2692 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.433 +- 0.793 single instance: logZ = 235.433 +- 0.246 bootstrapped : logZ = 235.293 +- 0.385 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a 18.3 +- 7.5 b 18 +- 11 pointstore: (500, 7) 2066 2692 626 sampler results: ******************** {'niter': 500, 'logz': 235.43269744807787, 'logzerr': 0.7927566606506654, 'logz_bs': 235.29290858222754, 'logz_single': 235.43269744807787, 'logzerr_tail': 0.6931471805598903, 'logzerr_bs': 0.38472081967040594, 'ess': 5.274154691031552, 'H': 6.033256737351138, 'Herr': 0.22556685337143384, 'posterior': {'mean': [18.307180915024208, 17.648001295331124], 'stdev': [7.461548357996892, 10.76980339796849], 'median': [18.865082871338988, 18.948817848540145], 'errlo': [12.522158632337275, 0.18220504961510647], 'errup': [25.226194363774848, 25.103965082907077], 'information_gain_bits': [2.585369753894852, 2.5350418776355]}, 'maximum_likelihood': {'logl': 242.85917012872116, 'point': [12.522158632337275, 25.103965082907077], 'point_untransformed': [0.398592688903465, 0.7990840268302006]}, 'ncall': 2692, 'paramnames': ['a', 'b'], 'logzerr_single': 0.24562688650372005, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} reader results: ******************** {'niter': 500, 'logz': 235.43269744807787, 'logzerr': 0.7656270015727977, 'logz_bs': 235.75786154760183, 'logz_single': 235.43269744807787, 'logzerr_tail': 0.6931471805598903, 'logzerr_bs': 0.32516409952395975, 'ess': 5.274154691031552, 'H': 6.033256737351138, 'Herr': 0.22000811918063334, 'posterior': {'mean': [18.307180915024208, 17.648001295331113], 'stdev': [7.461548357996893, 10.769803397968483], 'median': [18.865082871338988, 18.948817848540145], 'errlo': [12.522158632337275, 0.18220504961510647], 'errup': [25.226194363774848, 25.103965082907077], 'information_gain_bits': [2.585369753894852, 2.5350418776355]}, 'maximum_likelihood': {'logl': 242.85917012872116, 'point': [12.522158632337275, 25.103965082907077], 'point_untransformed': [0.398592688903465, 0.7990840268302006]}, 'insertion_order_MWW_test': {'independent_iterations': inf, 'converged': True}} niter () logz () skipping logzerr () skipping logz_bs () logz_single () skipping logzerr_tail () skipping logzerr_bs () ess () H () skipping Herr () weighted_samples :: upoints (500, 2) weighted_samples :: points (500, 2) weighted_samples :: weights (500,) weighted_samples :: logw (500,) weighted_samples :: logl (500,) maximum_likelihood :: logl () maximum_likelihood :: point (2,) maximum_likelihood :: point_untransformed (2,) insertion_order_MWW_test: {'independent_iterations': inf, 'converged': True} {'independent_iterations': inf, 'converged': True} -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpa_4ie_dv, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 100 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=101, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=111, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=123, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=137, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=149, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=162, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=175, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=188, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=206, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=223, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=244, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=284, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=309, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=341, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=377, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=396, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=441, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=502, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=553, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=584, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=2e+02 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 626 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmpa_4ie_dv, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [35mDEBUG [0m ultranest:integrator.py:1126 Testing resume consistency: [107.94292989 191.2912043 0. 0.57032947 0.98250479 17.91742875 30.86629839]: u=[0.57032947 0.98250479] -> p=[17.91742875 30.86629839] -> L=191.29120430116933 [32mINFO [0m ultranest:integrator.py:2164 Resuming from 300 stored points [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=626, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=626, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=626, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=626, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=626, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=626, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=626, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=626, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=626, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=626, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=626, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=626, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=115, ncalls=626, logz=41.41, remainder_fraction=100.0000%, Lmin=46.04, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=626, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=626, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=626, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=626, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=626, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=626, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=626, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=626, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=635, logz=102.10, remainder_fraction=100.0000%, Lmin=108.02, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=210, ncalls=686, logz=107.58, remainder_fraction=100.0000%, Lmin=113.25, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=220, ncalls=773, logz=115.88, remainder_fraction=100.0000%, Lmin=122.26, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), array([13, 18, 18, 14, 9, 15, 4, 6, 2, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=230, ncalls=847, logz=122.33, remainder_fraction=100.0000%, Lmin=129.85, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=970, logz=129.76, remainder_fraction=100.0000%, Lmin=136.55, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=1051, logz=137.33, remainder_fraction=100.0000%, Lmin=144.23, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]), array([ 8, 13, 5, 6, 8, 3, 8, 5, 8, 6, 9, 5, 5, 4, 6, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=260, ncalls=1113, logz=142.65, remainder_fraction=100.0000%, Lmin=149.88, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=1240, logz=150.61, remainder_fraction=100.0000%, Lmin=158.76, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17]), array([ 7, 14, 8, 5, 8, 4, 6, 5, 8, 10, 3, 5, 4, 5, 2, 1, 5])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=276, ncalls=1298, logz=155.38, remainder_fraction=100.0000%, Lmin=161.77, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=1339, logz=157.41, remainder_fraction=100.0000%, Lmin=165.84, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=290, ncalls=1390, logz=163.43, remainder_fraction=100.0000%, Lmin=169.78, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), array([25, 33, 23, 1, 1, 1, 1, 8, 1, 1, 5])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=299, ncalls=1456, logz=169.15, remainder_fraction=100.0000%, Lmin=176.32, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=1464, logz=169.65, remainder_fraction=100.0000%, Lmin=176.48, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=310, ncalls=1544, logz=177.02, remainder_fraction=100.0000%, Lmin=183.98, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=1653, logz=182.02, remainder_fraction=100.0000%, Lmin=189.03, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), array([26, 35, 22, 1, 1, 1, 1, 7, 1, 1, 4])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=322, ncalls=1678, logz=182.71, remainder_fraction=100.0000%, Lmin=189.52, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=330, ncalls=1823, logz=185.51, remainder_fraction=100.0000%, Lmin=192.14, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=340, ncalls=1954, logz=187.85, remainder_fraction=100.0000%, Lmin=194.77, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([27, 34, 24, 1, 1, 1, 1, 5, 6])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=345, ncalls=2018, logz=189.30, remainder_fraction=100.0000%, Lmin=196.24, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=2076, logz=190.69, remainder_fraction=100.0000%, Lmin=197.56, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=2164, logz=193.38, remainder_fraction=100.0000%, Lmin=201.00, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([29, 28, 28, 1, 1, 1, 1, 6, 5])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=370, ncalls=2261, logz=197.14, remainder_fraction=100.0000%, Lmin=204.14, Lmax=242.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=380, ncalls=2354, logz=200.04, remainder_fraction=100.0000%, Lmin=206.82, Lmax=242.86 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=390, ncalls=2534, logz=203.21, remainder_fraction=100.0000%, Lmin=210.59, Lmax=242.86 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5, 6, 7, 8, 9]), array([35, 23, 27, 1, 1, 1, 1, 6, 5])) [32mINFO [0m ultranest:integrator.py:2450 Explored until L=2e+02 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 2692 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_reactive_run_resume_eggbox[tsv] | 1.18 | |
------------------------------Captured stdout call------------------------------ ====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..225.3019] | it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..225.3019] | it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..225.3019] | it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..225.3019] | it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..225.3019] | it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..225.3019] | it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..225.3019] | it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [1.1994..225.3019] | it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [1.1994..225.3019] | it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [1.1994..225.3019] | it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [1.1994..225.3019] | it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [1.1994..225.3019] | it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=43.4(0.00%) | Like=49.11..241.87 [1.1994..225.3019] | it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [1.1994..225.3019] | it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [1.1994..225.3019] | it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [1.1994..225.3019] | it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [1.1994..225.3019] | it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [1.1994..225.3019] | it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [1.1994..225.3019] | it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [1.1994..225.3019] | it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a 18.98 +- 0.35 b 6.3 +- 1.1 626 626 0 ====== Running Eggbox problem [2] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.23) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|* **** ************** ************ ****** *** **********| +3.1e+01 b: +3.1e-05|**** ****** ** ***** ********** **** *** **** **********| +3.1e+01 Z=-inf(0.00%) | Like=1.05..221.09 [1.0467..181.1505] | it/evals=0/101 eff=0.0000% N=100 Z=0.1(0.00%) | Like=3.95..221.09 [1.0467..181.1505] | it/evals=10/111 eff=90.9091% N=100 Z=3.5(0.00%) | Like=6.71..221.09 [1.0467..181.1505] | it/evals=20/122 eff=90.9091% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.23) Quality: ok a: +3.1e-05|* ****************** *********** ***** * ********* **| +3.1e+01 b: +3.1e-05|**** ********* ****** ******* *** *** **** * ********| +3.1e+01 Z=6.4(0.00%) | Like=10.30..228.18 [1.0467..181.1505] | it/evals=30/133 eff=90.9091% N=100 Z=10.4(0.00%) | Like=14.59..228.18 [1.0467..181.1505] | it/evals=40/145 eff=88.8889% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.46) Quality: ok a: +3.1e-05|* *********** ****************** ***** ****** *******| +3.1e+01 b: +3.1e-05|**** **** **** ***** * ******* * ** *** **** *** ******| +3.1e+01 Z=14.8(0.00%) | Like=19.71..228.18 [1.0467..181.1505] | it/evals=50/156 eff=89.2857% N=100 Z=22.2(0.00%) | Like=26.91..228.18 [1.0467..181.1505] | it/evals=60/174 eff=81.0811% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.69) Quality: ok a: +3.1e-05|* ** ******* ****************** ************* ** ***| +3.1e+01 b: +3.1e-05|**** **** **** ***** ** ******* * *********** *** ******| +3.1e+01 Z=26.6(0.00%) | Like=31.35..228.18 [1.0467..181.1505] | it/evals=70/189 eff=78.6517% N=100 Z=29.7(0.00%) | Like=34.32..228.18 [1.0467..181.1505] | it/evals=80/213 eff=70.7965% N=100 Z=33.3(0.00%) | Like=38.77..228.18 [1.0467..181.1505] | it/evals=90/240 eff=64.2857% N=100 Mono-modal Volume: ~exp(-3.26) * Expected Volume: exp(-0.92) Quality: ok a: +3.1e-05|* * ******* * **************** ************* * * ***| +3.1e+01 b: +3.1e-05|**** ******** ***** * ******* * *********** *** *****| +3.1e+01 Z=34.5(0.00%) | Like=39.28..228.18 [1.0467..181.1505] | it/evals=92/246 eff=63.0137% N=100 Z=37.8(0.00%) | Like=42.61..228.18 [1.0467..181.1505] | it/evals=100/273 eff=57.8035% N=100 Z=42.8(0.00%) | Like=47.95..228.18 [1.0467..181.1505] | it/evals=110/297 eff=55.8376% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.15) Quality: ok a: +3.1e-05|** * ********* ********** **** *** ********** * ***| +3.1e+01 b: +3.1e-05|**** ******** * *********** ** * ***** ***** *** * ***| +3.1e+01 Z=48.9(0.00%) | Like=54.86..228.18 [1.0467..181.1505] | it/evals=120/326 eff=53.0973% N=100 Z=55.4(0.00%) | Like=61.66..228.18 [1.0467..181.1505] | it/evals=130/368 eff=48.5075% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.38) Quality: ok a: +3.1e-05|** * ********* ******** ***** *** ********* * ***| +3.1e+01 b: +3.1e-05|**** ******* * ********* ** * *** ***** *** *****| +3.1e+01 Z=60.1(0.00%) | Like=68.52..228.18 [1.0467..181.1505] | it/evals=140/402 eff=46.3576% N=100 Z=67.2(0.00%) | Like=72.18..228.18 [1.0467..181.1505] | it/evals=150/452 eff=42.6136% N=100 Z=71.3(0.00%) | Like=76.78..238.35 [1.0467..181.1505] | it/evals=160/496 eff=40.4040% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.61) Quality: ok a: +3.1e-05|** ******* ******* **** *** ********* ***| +3.1e+01 b: +3.1e-05|**** ******* * * ****** **** **** ********* ***| +3.1e+01 Z=77.7(0.00%) | Like=85.32..238.35 [1.0467..181.1505] | it/evals=170/544 eff=38.2883% N=100 Z=83.6(0.00%) | Like=91.87..238.35 [1.0467..181.1505] | it/evals=180/573 eff=38.0550% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.84) Quality: ok a: +3.1e-05|*** ****** ******* ******** ******** ****| +3.1e+01 b: +3.1e-05|**** ******* ******* ********* ******** ***| +3.1e+01 Z=92.1(0.00%) | Like=98.48..238.35 [1.0467..181.1505] | it/evals=190/595 eff=38.3838% N=100 Z=101.4(0.00%) | Like=108.11..240.89 [1.0467..181.1505] | it/evals=200/674 eff=34.8432% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.07) Quality: correlation length: 198 (+) a: +0.0|*** ****** ******* **** ** ******* ****| +31.4 b: +3.1e-05|*** ****** ******* ******* ******** ***| +3.1e+01 Z=108.2(0.00%) | Like=114.20..240.89 [1.0467..181.1505] | it/evals=210/722 eff=33.7621% N=100 Z=114.0(0.00%) | Like=121.27..240.89 [1.0467..181.1505] | it/evals=220/778 eff=32.4484% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.30) Quality: correlation length: 198 (+) a: +0.0|*** ****** ****** *** ** ******* ***| +31.4 b: +3.1e-05|*** ***** ***** ******* ****** ** | +3.1e+01 Z=122.3(0.00%) | Like=128.65..240.89 [1.0467..181.1505] | it/evals=230/849 eff=30.7076% N=100 Z=128.0(0.00%) | Like=134.37..240.89 [1.0467..181.1505] | it/evals=240/950 eff=28.2353% N=100 Z=132.5(0.00%) | Like=139.29..242.00 [1.0467..181.1505] | it/evals=250/1034 eff=26.7666% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.53) Quality: correlation length: 198 (+) a: +0.0|*** ***** ****** *** ** ****** ***| +31.4 b: +3.1e-05|*** ***** ****** ******* ****** ** | +3.1e+01 Z=140.8(0.00%) | Like=147.11..242.37 [1.0467..181.1505] | it/evals=260/1135 eff=25.1208% N=100 Z=148.1(0.00%) | Like=155.97..242.37 [1.0467..181.1505] | it/evals=270/1279 eff=22.9008% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.76) Quality: correlation length: 198 (+) a: +0.0|*** **** ****** *** * ***** **| +31.4 b: +3.1e-05|*** ***** ***** ***** ****** * *| +3.1e+01 Z=155.6(0.00%) | Like=163.08..242.37 [1.0467..181.1505] | it/evals=280/1411 eff=21.3577% N=100 Z=161.0(0.00%) | Like=168.19..242.37 [1.0467..181.1505] | it/evals=290/1566 eff=19.7817% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.99) Quality: correlation length: 198 (+) a: +3.1e-05|** **** ***** ***** ***** **| +3.1e+01 b: +3.1e-05|** ***** ***** ***** ***** *| +3.1e+01 Z=166.0(0.00%) | Like=173.84..242.37 [1.0467..181.1505] | it/evals=300/1700 eff=18.7500% N=100 Z=171.7(0.00%) | Like=179.38..242.37 [1.0467..181.1505] | it/evals=310/1793 eff=18.3107% N=100 Z=177.1(0.00%) | Like=184.35..242.37 [181.4171..239.2774] | it/evals=320/1938 eff=17.4102% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.22) Quality: correlation length: 103 (+) a: +3.1e-05|** **** **** ***** **** **| +3.1e+01 b: +3.1e-05|** ***** ***** **** **** *| +3.1e+01 Z=182.5(0.00%) | Like=189.50..242.37 [181.4171..239.2774] | it/evals=330/2226 eff=15.5221% N=100 Z=186.2(0.00%) | Like=193.29..242.37 [181.4171..239.2774] | it/evals=340/2654 eff=13.3125% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.45) Quality: correlation length: 103 (+) a: +3.1e-05|** **** **** **** **** **| +3.1e+01 b: +3.1e-05|** **** **** **** *** *| +3.1e+01 Z=191.2(0.00%) | Like=198.42..242.37 [181.4171..239.2774] | it/evals=350/3009 eff=12.0316% N=100 Z=197.3(0.00%) | Like=205.11..242.37 [181.4171..239.2774] | it/evals=360/3318 eff=11.1871% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.68) Quality: correlation length: 103 (+) a: +3.1e-05|** **** **** *** **** **| +3.1e+01 b: +3.1e-05|** **** *** *** *** *| +3.1e+01 Z=200.0(0.00%) | Like=206.86..242.37 [181.4171..239.2774] | it/evals=370/3667 eff=10.3729% N=100 Z=203.2(0.00%) | Like=210.98..242.51 [181.4171..239.2774] | it/evals=380/4187 eff=9.2978% N=100 Z=206.3(0.00%) | Like=213.44..242.60 [181.4171..239.2774] | it/evals=390/4799 eff=8.2996% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.91) Quality: correlation length: 103 (+) a: +3.1e-05|** **** *** *** *** *| +3.1e+01 b: +3.1e-05|** **** *** *** *** *| +3.1e+01 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 5287 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 236.030 +- 0.815 single instance: logZ = 236.030 +- 0.247 bootstrapped : logZ = 236.020 +- 0.429 tail : logZ = +- 0.693 insert order U test : converged: False correlation: 103.0 iterations a 16.9 +- 7.9 b 14 +- 11 5287 5287 0 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmp8q_8heny, backend=tsv, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 100 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=101, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=111, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=123, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=137, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=149, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=162, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=175, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=188, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=206, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=223, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=244, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=284, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=309, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=341, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=377, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=396, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=441, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=502, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=553, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=584, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=2e+02 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 626 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmp8q_8heny, backend=tsv, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 100 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=101, logz=-inf, remainder_fraction=100.0000%, Lmin=1.05, Lmax=221.09 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=111, logz=0.06, remainder_fraction=100.0000%, Lmin=3.95, Lmax=221.09 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=122, logz=3.55, remainder_fraction=100.0000%, Lmin=6.71, Lmax=221.09 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=133, logz=6.36, remainder_fraction=100.0000%, Lmin=10.30, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=145, logz=10.43, remainder_fraction=100.0000%, Lmin=14.59, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=156, logz=14.85, remainder_fraction=100.0000%, Lmin=19.71, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=174, logz=22.21, remainder_fraction=100.0000%, Lmin=26.91, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=189, logz=26.59, remainder_fraction=100.0000%, Lmin=31.35, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=213, logz=29.74, remainder_fraction=100.0000%, Lmin=34.32, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=240, logz=33.34, remainder_fraction=100.0000%, Lmin=38.77, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=92, ncalls=246, logz=34.49, remainder_fraction=100.0000%, Lmin=39.28, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=273, logz=37.85, remainder_fraction=100.0000%, Lmin=42.61, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=297, logz=42.78, remainder_fraction=100.0000%, Lmin=47.95, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=326, logz=48.91, remainder_fraction=100.0000%, Lmin=54.86, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=368, logz=55.41, remainder_fraction=100.0000%, Lmin=61.66, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=402, logz=60.12, remainder_fraction=100.0000%, Lmin=68.52, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=452, logz=67.24, remainder_fraction=100.0000%, Lmin=72.18, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=496, logz=71.34, remainder_fraction=100.0000%, Lmin=76.78, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=544, logz=77.69, remainder_fraction=100.0000%, Lmin=85.32, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=573, logz=83.64, remainder_fraction=100.0000%, Lmin=91.87, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=595, logz=92.13, remainder_fraction=100.0000%, Lmin=98.48, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=674, logz=101.38, remainder_fraction=100.0000%, Lmin=108.11, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=210, ncalls=722, logz=108.20, remainder_fraction=100.0000%, Lmin=114.20, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=220, ncalls=778, logz=114.04, remainder_fraction=100.0000%, Lmin=121.27, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=230, ncalls=849, logz=122.34, remainder_fraction=100.0000%, Lmin=128.65, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=950, logz=128.02, remainder_fraction=100.0000%, Lmin=134.37, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=1034, logz=132.48, remainder_fraction=100.0000%, Lmin=139.29, Lmax=242.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=260, ncalls=1135, logz=140.81, remainder_fraction=100.0000%, Lmin=147.11, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=1279, logz=148.11, remainder_fraction=100.0000%, Lmin=155.97, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=1411, logz=155.63, remainder_fraction=100.0000%, Lmin=163.08, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=290, ncalls=1566, logz=161.05, remainder_fraction=100.0000%, Lmin=168.19, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=1700, logz=166.03, remainder_fraction=100.0000%, Lmin=173.84, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=310, ncalls=1793, logz=171.65, remainder_fraction=100.0000%, Lmin=179.38, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=1938, logz=177.14, remainder_fraction=100.0000%, Lmin=184.35, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=330, ncalls=2226, logz=182.54, remainder_fraction=100.0000%, Lmin=189.50, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=340, ncalls=2654, logz=186.24, remainder_fraction=100.0000%, Lmin=193.29, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=3009, logz=191.15, remainder_fraction=100.0000%, Lmin=198.42, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=3318, logz=197.32, remainder_fraction=100.0000%, Lmin=205.11, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=370, ncalls=3667, logz=200.02, remainder_fraction=100.0000%, Lmin=206.86, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=380, ncalls=4187, logz=203.15, remainder_fraction=100.0000%, Lmin=210.98, Lmax=242.51 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=390, ncalls=4799, logz=206.25, remainder_fraction=100.0000%, Lmin=213.44, Lmax=242.60 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=2e+02 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 5287 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_reactive_run_resume_eggbox[csv] | 1.11 | |
------------------------------Captured stdout call------------------------------ ====== Running Eggbox problem [1] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.50) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|******************* ** * * ******* *** ** ** ********| +3.1e+01 b: +0.0|**** ***** * ***** *** * * ****** ** *********** *******| +31.4 Z=-inf(0.00%) | Like=1.20..233.34 [1.1994..225.3019] | it/evals=0/101 eff=0.0000% N=100 Z=-0.3(0.00%) | Like=2.82..233.34 [1.1994..225.3019] | it/evals=10/111 eff=90.9091% N=100 Z=1.8(0.00%) | Like=5.72..241.87 [1.1994..225.3019] | it/evals=20/123 eff=86.9565% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.23) Quality: ok a: +0.0|********************* ** ********* *** ** ** ****** *| +31.4 b: +0.0| *** **** ** **** *** * * ****** ************* *******| +31.4 Z=5.8(0.00%) | Like=9.88..241.87 [1.1994..225.3019] | it/evals=30/137 eff=81.0811% N=100 Z=10.9(0.00%) | Like=15.15..241.87 [1.1994..225.3019] | it/evals=40/149 eff=81.6327% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.46) Quality: ok a: +0.0|************** ****** ** **** ***** *** *** ** ****** *| +31.4 b: +0.0|**** ***** ** **** *** * * *** ** ********** ** ********| +31.4 Z=14.8(0.00%) | Like=19.62..241.87 [1.1994..225.3019] | it/evals=50/162 eff=80.6452% N=100 Z=21.2(0.00%) | Like=25.71..241.87 [1.1994..225.3019] | it/evals=60/175 eff=80.0000% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.69) Quality: ok a: +0.0|******** ***** ******** ********** ** **** * ********| +31.4 b: +0.0|********** ** **** ***** *** ** ********** ** ********| +31.4 Z=25.5(0.00%) | Like=29.64..241.87 [1.1994..225.3019] | it/evals=70/188 eff=79.5455% N=100 Z=28.4(0.00%) | Like=32.87..241.87 [1.1994..225.3019] | it/evals=80/206 eff=75.4717% N=100 Z=31.0(0.00%) | Like=35.17..241.87 [1.1994..225.3019] | it/evals=90/223 eff=73.1707% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-0.92) Quality: ok a: +0.0|******** ***** ** ***** **** ******* ** ****** ********| +31.4 b: +0.0|********** ******* *** ** ************ **** ***** *****| +31.4 Z=34.9(0.00%) | Like=39.71..241.87 [1.1994..225.3019] | it/evals=100/244 eff=69.4444% N=100 Z=39.4(0.00%) | Like=45.13..241.87 [1.1994..225.3019] | it/evals=110/284 eff=59.7826% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.15) Quality: ok a: +0.0| **** ** ***** * ****** *** * ***** ** ********** *****| +31.4 b: +0.0|***** **** **** * **** **** ********* **** ***** *****| +31.4 Z=43.4(0.00%) | Like=49.11..241.87 [1.1994..225.3019] | it/evals=120/309 eff=57.4163% N=100 Z=48.4(0.00%) | Like=54.54..241.87 [1.1994..225.3019] | it/evals=130/341 eff=53.9419% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.38) Quality: ok a: +0.0| *** * ******* ****** ** ******* * ********* ****| +31.4 b: +0.0|***** *** **** ******** ********* ********** ***| +31.4 Z=54.8(0.00%) | Like=60.32..241.87 [1.1994..225.3019] | it/evals=140/377 eff=50.5415% N=100 Z=63.7(0.00%) | Like=69.11..241.87 [1.1994..225.3019] | it/evals=150/396 eff=50.6757% N=100 Z=71.7(0.00%) | Like=77.89..241.87 [1.1994..225.3019] | it/evals=160/441 eff=46.9208% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.61) Quality: ok a: +0.0| *** * ****** ******* ********* ********* ****| +31.4 b: +0.0|**** ******** ******** ******* * ******* ***| +31.4 Z=77.8(0.00%) | Like=87.30..241.87 [1.1994..225.3019] | it/evals=170/502 eff=42.2886% N=100 Z=88.7(0.00%) | Like=94.79..241.87 [1.1994..225.3019] | it/evals=180/553 eff=39.7351% N=100 Mono-modal Volume: ~exp(-3.50) Expected Volume: exp(-1.84) Quality: ok a: +0.0| ** * ****** ***** ******** ******** ****| +31.4 b: +0.0|*** ******** ******* ******* ****** ***| +31.4 Z=94.6(0.00%) | Like=100.05..241.87 [1.1994..225.3019] | it/evals=190/584 eff=39.2562% N=100 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 626 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 235.268 +- 1.038 single instance: logZ = 235.268 +- 0.231 bootstrapped : logZ = 231.619 +- 0.772 tail : logZ = +- 0.693 insert order U test : converged: True correlation: inf iterations a 18.98 +- 0.35 b 6.3 +- 1.1 626 626 0 ====== Running Eggbox problem [2] ===== [ultranest] Sampling 100 live points from prior ... Mono-modal Volume: ~exp(-3.23) * Expected Volume: exp(0.00) Quality: ok a: +3.1e-05|* **** ************** ************ ****** *** **********| +3.1e+01 b: +3.1e-05|**** ****** ** ***** ********** **** *** **** **********| +3.1e+01 Z=-inf(0.00%) | Like=1.05..221.09 [1.0467..181.1505] | it/evals=0/101 eff=0.0000% N=100 Z=0.1(0.00%) | Like=3.95..221.09 [1.0467..181.1505] | it/evals=10/111 eff=90.9091% N=100 Z=3.5(0.00%) | Like=6.71..221.09 [1.0467..181.1505] | it/evals=20/122 eff=90.9091% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.23) Quality: ok a: +3.1e-05|* ****************** *********** ***** * ********* **| +3.1e+01 b: +3.1e-05|**** ********* ****** ******* *** *** **** * ********| +3.1e+01 Z=6.4(0.00%) | Like=10.30..228.18 [1.0467..181.1505] | it/evals=30/133 eff=90.9091% N=100 Z=10.4(0.00%) | Like=14.59..228.18 [1.0467..181.1505] | it/evals=40/145 eff=88.8889% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.46) Quality: ok a: +3.1e-05|* *********** ****************** ***** ****** *******| +3.1e+01 b: +3.1e-05|**** **** **** ***** * ******* * ** *** **** *** ******| +3.1e+01 Z=14.8(0.00%) | Like=19.71..228.18 [1.0467..181.1505] | it/evals=50/156 eff=89.2857% N=100 Z=22.2(0.00%) | Like=26.91..228.18 [1.0467..181.1505] | it/evals=60/174 eff=81.0811% N=100 Mono-modal Volume: ~exp(-3.23) Expected Volume: exp(-0.69) Quality: ok a: +3.1e-05|* ** ******* ****************** ************* ** ***| +3.1e+01 b: +3.1e-05|**** **** **** ***** ** ******* * *********** *** ******| +3.1e+01 Z=26.6(0.00%) | Like=31.35..228.18 [1.0467..181.1505] | it/evals=70/189 eff=78.6517% N=100 Z=29.7(0.00%) | Like=34.32..228.18 [1.0467..181.1505] | it/evals=80/213 eff=70.7965% N=100 Z=33.3(0.00%) | Like=38.77..228.18 [1.0467..181.1505] | it/evals=90/240 eff=64.2857% N=100 Mono-modal Volume: ~exp(-3.26) * Expected Volume: exp(-0.92) Quality: ok a: +3.1e-05|* * ******* * **************** ************* * * ***| +3.1e+01 b: +3.1e-05|**** ******** ***** * ******* * *********** *** *****| +3.1e+01 Z=34.5(0.00%) | Like=39.28..228.18 [1.0467..181.1505] | it/evals=92/246 eff=63.0137% N=100 Z=37.8(0.00%) | Like=42.61..228.18 [1.0467..181.1505] | it/evals=100/273 eff=57.8035% N=100 Z=42.8(0.00%) | Like=47.95..228.18 [1.0467..181.1505] | it/evals=110/297 eff=55.8376% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.15) Quality: ok a: +3.1e-05|** * ********* ********** **** *** ********** * ***| +3.1e+01 b: +3.1e-05|**** ******** * *********** ** * ***** ***** *** * ***| +3.1e+01 Z=48.9(0.00%) | Like=54.86..228.18 [1.0467..181.1505] | it/evals=120/326 eff=53.0973% N=100 Z=55.4(0.00%) | Like=61.66..228.18 [1.0467..181.1505] | it/evals=130/368 eff=48.5075% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.38) Quality: ok a: +3.1e-05|** * ********* ******** ***** *** ********* * ***| +3.1e+01 b: +3.1e-05|**** ******* * ********* ** * *** ***** *** *****| +3.1e+01 Z=60.1(0.00%) | Like=68.52..228.18 [1.0467..181.1505] | it/evals=140/402 eff=46.3576% N=100 Z=67.2(0.00%) | Like=72.18..228.18 [1.0467..181.1505] | it/evals=150/452 eff=42.6136% N=100 Z=71.3(0.00%) | Like=76.78..238.35 [1.0467..181.1505] | it/evals=160/496 eff=40.4040% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.61) Quality: ok a: +3.1e-05|** ******* ******* **** *** ********* ***| +3.1e+01 b: +3.1e-05|**** ******* * * ****** **** **** ********* ***| +3.1e+01 Z=77.7(0.00%) | Like=85.32..238.35 [1.0467..181.1505] | it/evals=170/544 eff=38.2883% N=100 Z=83.6(0.00%) | Like=91.87..238.35 [1.0467..181.1505] | it/evals=180/573 eff=38.0550% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-1.84) Quality: ok a: +3.1e-05|*** ****** ******* ******** ******** ****| +3.1e+01 b: +3.1e-05|**** ******* ******* ********* ******** ***| +3.1e+01 Z=92.1(0.00%) | Like=98.48..238.35 [1.0467..181.1505] | it/evals=190/595 eff=38.3838% N=100 Z=101.4(0.00%) | Like=108.11..240.89 [1.0467..181.1505] | it/evals=200/674 eff=34.8432% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.07) Quality: correlation length: 198 (+) a: +0.0|*** ****** ******* **** ** ******* ****| +31.4 b: +3.1e-05|*** ****** ******* ******* ******** ***| +3.1e+01 Z=108.2(0.00%) | Like=114.20..240.89 [1.0467..181.1505] | it/evals=210/722 eff=33.7621% N=100 Z=114.0(0.00%) | Like=121.27..240.89 [1.0467..181.1505] | it/evals=220/778 eff=32.4484% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.30) Quality: correlation length: 198 (+) a: +0.0|*** ****** ****** *** ** ******* ***| +31.4 b: +3.1e-05|*** ***** ***** ******* ****** ** | +3.1e+01 Z=122.3(0.00%) | Like=128.65..240.89 [1.0467..181.1505] | it/evals=230/849 eff=30.7076% N=100 Z=128.0(0.00%) | Like=134.37..240.89 [1.0467..181.1505] | it/evals=240/950 eff=28.2353% N=100 Z=132.5(0.00%) | Like=139.29..242.00 [1.0467..181.1505] | it/evals=250/1034 eff=26.7666% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.53) Quality: correlation length: 198 (+) a: +0.0|*** ***** ****** *** ** ****** ***| +31.4 b: +3.1e-05|*** ***** ****** ******* ****** ** | +3.1e+01 Z=140.8(0.00%) | Like=147.11..242.37 [1.0467..181.1505] | it/evals=260/1135 eff=25.1208% N=100 Z=148.1(0.00%) | Like=155.97..242.37 [1.0467..181.1505] | it/evals=270/1279 eff=22.9008% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.76) Quality: correlation length: 198 (+) a: +0.0|*** **** ****** *** * ***** **| +31.4 b: +3.1e-05|*** ***** ***** ***** ****** * *| +3.1e+01 Z=155.6(0.00%) | Like=163.08..242.37 [1.0467..181.1505] | it/evals=280/1411 eff=21.3577% N=100 Z=161.0(0.00%) | Like=168.19..242.37 [1.0467..181.1505] | it/evals=290/1566 eff=19.7817% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-2.99) Quality: correlation length: 198 (+) a: +3.1e-05|** **** ***** ***** ***** **| +3.1e+01 b: +3.1e-05|** ***** ***** ***** ***** *| +3.1e+01 Z=166.0(0.00%) | Like=173.84..242.37 [1.0467..181.1505] | it/evals=300/1700 eff=18.7500% N=100 Z=171.7(0.00%) | Like=179.38..242.37 [1.0467..181.1505] | it/evals=310/1793 eff=18.3107% N=100 Z=177.1(0.00%) | Like=184.35..242.37 [181.4171..239.2774] | it/evals=320/1938 eff=17.4102% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.22) Quality: correlation length: 103 (+) a: +3.1e-05|** **** **** ***** **** **| +3.1e+01 b: +3.1e-05|** ***** ***** **** **** *| +3.1e+01 Z=182.5(0.00%) | Like=189.50..242.37 [181.4171..239.2774] | it/evals=330/2226 eff=15.5221% N=100 Z=186.2(0.00%) | Like=193.29..242.37 [181.4171..239.2774] | it/evals=340/2654 eff=13.3125% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.45) Quality: correlation length: 103 (+) a: +3.1e-05|** **** **** **** **** **| +3.1e+01 b: +3.1e-05|** **** **** **** *** *| +3.1e+01 Z=191.2(0.00%) | Like=198.42..242.37 [181.4171..239.2774] | it/evals=350/3009 eff=12.0316% N=100 Z=197.3(0.00%) | Like=205.11..242.37 [181.4171..239.2774] | it/evals=360/3318 eff=11.1871% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.68) Quality: correlation length: 103 (+) a: +3.1e-05|** **** **** *** **** **| +3.1e+01 b: +3.1e-05|** **** *** *** *** *| +3.1e+01 Z=200.0(0.00%) | Like=206.86..242.37 [181.4171..239.2774] | it/evals=370/3667 eff=10.3729% N=100 Z=203.2(0.00%) | Like=210.98..242.51 [181.4171..239.2774] | it/evals=380/4187 eff=9.2978% N=100 Z=206.3(0.00%) | Like=213.44..242.60 [181.4171..239.2774] | it/evals=390/4799 eff=8.2996% N=100 Mono-modal Volume: ~exp(-3.26) Expected Volume: exp(-3.91) Quality: correlation length: 103 (+) a: +3.1e-05|** **** *** *** *** *| +3.1e+01 b: +3.1e-05|** **** *** *** *** *| +3.1e+01 [ultranest] Explored until L=2e+02 [ultranest] Likelihood function evaluations: 5287 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = 236.030 +- 0.815 single instance: logZ = 236.030 +- 0.247 bootstrapped : logZ = 236.020 +- 0.429 tail : logZ = +- 0.693 insert order U test : converged: False correlation: 103.0 iterations a 16.9 +- 7.9 b 14 +- 11 5287 5287 0 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmptxdkldb5, backend=csv, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 100 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=200, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=101, logz=-inf, remainder_fraction=100.0000%, Lmin=1.20, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=111, logz=-0.29, remainder_fraction=100.0000%, Lmin=2.82, Lmax=233.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=123, logz=1.84, remainder_fraction=100.0000%, Lmin=5.72, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=137, logz=5.81, remainder_fraction=100.0000%, Lmin=9.88, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=149, logz=10.87, remainder_fraction=100.0000%, Lmin=15.15, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=162, logz=14.85, remainder_fraction=100.0000%, Lmin=19.62, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=175, logz=21.16, remainder_fraction=100.0000%, Lmin=25.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=188, logz=25.45, remainder_fraction=100.0000%, Lmin=29.64, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=206, logz=28.39, remainder_fraction=100.0000%, Lmin=32.87, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=223, logz=31.00, remainder_fraction=100.0000%, Lmin=35.17, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=244, logz=34.92, remainder_fraction=100.0000%, Lmin=39.71, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=284, logz=39.44, remainder_fraction=100.0000%, Lmin=45.13, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=309, logz=43.44, remainder_fraction=100.0000%, Lmin=49.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=341, logz=48.37, remainder_fraction=100.0000%, Lmin=54.54, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2, 3, 4, 5]), array([60, 22, 14, 3, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=377, logz=54.83, remainder_fraction=100.0000%, Lmin=60.32, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=396, logz=63.66, remainder_fraction=100.0000%, Lmin=69.11, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=441, logz=71.73, remainder_fraction=100.0000%, Lmin=77.89, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=502, logz=77.78, remainder_fraction=100.0000%, Lmin=87.30, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=553, logz=88.69, remainder_fraction=100.0000%, Lmin=94.79, Lmax=241.87 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=584, logz=94.65, remainder_fraction=100.0000%, Lmin=100.05, Lmax=241.87 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=2e+02 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 626 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=/tmp/tmptxdkldb5, backend=csv, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 100 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=400, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=101, logz=-inf, remainder_fraction=100.0000%, Lmin=1.05, Lmax=221.09 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=111, logz=0.06, remainder_fraction=100.0000%, Lmin=3.95, Lmax=221.09 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=122, logz=3.55, remainder_fraction=100.0000%, Lmin=6.71, Lmax=221.09 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=133, logz=6.36, remainder_fraction=100.0000%, Lmin=10.30, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=145, logz=10.43, remainder_fraction=100.0000%, Lmin=14.59, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=156, logz=14.85, remainder_fraction=100.0000%, Lmin=19.71, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=174, logz=22.21, remainder_fraction=100.0000%, Lmin=26.91, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=189, logz=26.59, remainder_fraction=100.0000%, Lmin=31.35, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=213, logz=29.74, remainder_fraction=100.0000%, Lmin=34.32, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=240, logz=33.34, remainder_fraction=100.0000%, Lmin=38.77, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=92, ncalls=246, logz=34.49, remainder_fraction=100.0000%, Lmin=39.28, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=273, logz=37.85, remainder_fraction=100.0000%, Lmin=42.61, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=297, logz=42.78, remainder_fraction=100.0000%, Lmin=47.95, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=326, logz=48.91, remainder_fraction=100.0000%, Lmin=54.86, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=368, logz=55.41, remainder_fraction=100.0000%, Lmin=61.66, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=402, logz=60.12, remainder_fraction=100.0000%, Lmin=68.52, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=452, logz=67.24, remainder_fraction=100.0000%, Lmin=72.18, Lmax=228.18 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=496, logz=71.34, remainder_fraction=100.0000%, Lmin=76.78, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=544, logz=77.69, remainder_fraction=100.0000%, Lmin=85.32, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=573, logz=83.64, remainder_fraction=100.0000%, Lmin=91.87, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=595, logz=92.13, remainder_fraction=100.0000%, Lmin=98.48, Lmax=238.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=674, logz=101.38, remainder_fraction=100.0000%, Lmin=108.11, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=210, ncalls=722, logz=108.20, remainder_fraction=100.0000%, Lmin=114.20, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=220, ncalls=778, logz=114.04, remainder_fraction=100.0000%, Lmin=121.27, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=230, ncalls=849, logz=122.34, remainder_fraction=100.0000%, Lmin=128.65, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=950, logz=128.02, remainder_fraction=100.0000%, Lmin=134.37, Lmax=240.89 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=1034, logz=132.48, remainder_fraction=100.0000%, Lmin=139.29, Lmax=242.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=260, ncalls=1135, logz=140.81, remainder_fraction=100.0000%, Lmin=147.11, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=1279, logz=148.11, remainder_fraction=100.0000%, Lmin=155.97, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=1411, logz=155.63, remainder_fraction=100.0000%, Lmin=163.08, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=290, ncalls=1566, logz=161.05, remainder_fraction=100.0000%, Lmin=168.19, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=1700, logz=166.03, remainder_fraction=100.0000%, Lmin=173.84, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=310, ncalls=1793, logz=171.65, remainder_fraction=100.0000%, Lmin=179.38, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=1938, logz=177.14, remainder_fraction=100.0000%, Lmin=184.35, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=330, ncalls=2226, logz=182.54, remainder_fraction=100.0000%, Lmin=189.50, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=340, ncalls=2654, logz=186.24, remainder_fraction=100.0000%, Lmin=193.29, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=3009, logz=191.15, remainder_fraction=100.0000%, Lmin=198.42, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=3318, logz=197.32, remainder_fraction=100.0000%, Lmin=205.11, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=370, ncalls=3667, logz=200.02, remainder_fraction=100.0000%, Lmin=206.86, Lmax=242.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=380, ncalls=4187, logz=203.15, remainder_fraction=100.0000%, Lmin=210.98, Lmax=242.51 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=390, ncalls=4799, logz=206.25, remainder_fraction=100.0000%, Lmin=213.44, Lmax=242.60 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=2e+02 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 5287 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_reactive_run_warmstart_gauss | 4.61 | |
------------------------------Captured stdout call------------------------------ ====== Running Gauss problem [1] ===== [ultranest] Sampling 100 live points from prior ... Z=-inf(0.00%) | Like=-5e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=0/101 eff=0.0000% N=100 Z=-4e+13(0.00%) | Like=-4.1e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=10/112 eff=83.3333% N=100 Z=-3e+13(0.00%) | Like=-3.3e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=20/122 eff=90.9091% N=100 Z=-3e+13(0.00%) | Like=-3e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=30/132 eff=93.7500% N=100 Z=-3e+13(0.00%) | Like=-2.6e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=40/143 eff=93.0233% N=100 Z=-2e+13(0.00%) | Like=-2.2e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=46/151 eff=90.1961% N=100 Z=-2e+13(0.00%) | Like=-2.1e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=50/155 eff=90.9091% N=100 Z=-2e+13(0.00%) | Like=-1.7e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=60/165 eff=92.3077% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=69/174 eff=93.2432% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=70/176 eff=92.1053% N=100 Z=-1e+13(0.00%) | Like=-1.3e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=80/186 eff=93.0233% N=100 Z=-1e+13(0.00%) | Like=-9.6e+12..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=90/197 eff=92.7835% N=100 Z=-8e+12(0.00%) | Like=-8.1e+12..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=100/208 eff=92.5926% N=100 Z=-7e+12(0.00%) | Like=-7e+12..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=110/220 eff=91.6667% N=100 Z=-7e+12(0.00%) | Like=-6.8e+12..-2.1e+09 [-4.998e+13..-4.434e+10] | it/evals=115/225 eff=92.0000% N=100 Z=-6e+12(0.00%) | Like=-6.2e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=120/230 eff=92.3077% N=100 Z=-5e+12(0.00%) | Like=-5e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=130/243 eff=90.9091% N=100 Z=-5e+12(0.00%) | Like=-4.5e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=140/257 eff=89.1720% N=100 Z=-3e+12(0.00%) | Like=-3.4e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=150/268 eff=89.2857% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=160/278 eff=89.8876% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=161/279 eff=89.9441% N=100 Z=-2e+12(0.00%) | Like=-2.1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=170/289 eff=89.9471% N=100 Z=-2e+12(0.00%) | Like=-1.8e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=180/299 eff=90.4523% N=100 Z=-1e+12(0.00%) | Like=-1.5e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=190/309 eff=90.9091% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=200/319 eff=91.3242% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=207/326 eff=91.5929% N=100 Z=-1e+12(0.00%) | Like=-1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=210/329 eff=91.7031% N=100 Z=-9e+11(0.00%) | Like=-8.4e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=220/342 eff=90.9091% N=100 Z=-7e+11(0.00%) | Like=-7.1e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=230/352 eff=91.2698% N=100 Z=-6e+11(0.00%) | Like=-5.8e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=240/364 eff=90.9091% N=100 Z=-5e+11(0.00%) | Like=-5e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=250/376 eff=90.5797% N=100 Z=-5e+11(0.00%) | Like=-4.6e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=253/379 eff=90.6810% N=100 Z=-4e+11(0.00%) | Like=-4.2e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=260/387 eff=90.5923% N=100 Z=-3e+11(0.00%) | Like=-3.3e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=270/401 eff=89.7010% N=100 Z=-3e+11(0.00%) | Like=-3e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=276/408 eff=89.6104% N=100 Z=-3e+11(0.00%) | Like=-2.7e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=280/412 eff=89.7436% N=100 Z=-2e+11(0.00%) | Like=-2.2e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=290/422 eff=90.0621% N=100 Z=-2e+11(0.00%) | Like=-1.9e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=299/431 eff=90.3323% N=100 Z=-2e+11(0.00%) | Like=-1.8e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=300/432 eff=90.3614% N=100 Z=-1e+11(0.00%) | Like=-1.3e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=310/446 eff=89.5954% N=100 Z=-1e+11(0.00%) | Like=-1.1e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=320/458 eff=89.3855% N=100 Z=-1e+11(0.00%) | Like=-1e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=322/460 eff=89.4444% N=100 Z=-9e+10(0.00%) | Like=-8.4e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=330/468 eff=89.6739% N=100 Z=-8e+10(0.00%) | Like=-7.8e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=340/478 eff=89.9471% N=100 Z=-7e+10(0.00%) | Like=-6.5e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=350/488 eff=90.2062% N=100 Z=-5e+10(0.00%) | Like=-5.2e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=360/498 eff=90.4523% N=100 Z=-4e+10(0.00%) | Like=-4.5e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=368/506 eff=90.6404% N=100 Z=-4e+10(0.00%) | Like=-4.4e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=370/508 eff=90.6863% N=100 Z=-4e+10(0.00%) | Like=-3.8e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=380/518 eff=90.9091% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=390/528 eff=91.1215% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=391/529 eff=91.1422% N=100 Z=-3e+10(0.00%) | Like=-2.5e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=400/539 eff=91.1162% N=100 Z=-2e+10(0.00%) | Like=-2.2e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=410/549 eff=91.3140% N=100 Z=-2e+10(0.00%) | Like=-2e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=414/553 eff=91.3907% N=100 Z=-2e+10(0.00%) | Like=-1.7e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=420/559 eff=91.5033% N=100 Z=-1e+10(0.00%) | Like=-1.3e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=430/569 eff=91.6844% N=100 Z=-1e+10(0.00%) | Like=-1.1e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=440/581 eff=91.4761% N=100 Z=-9e+09(0.00%) | Like=-8.8e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=450/591 eff=91.6497% N=100 Z=-7e+09(0.00%) | Like=-7.3e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=460/603 eff=91.4513% N=100 Z=-6e+09(0.00%) | Like=-5.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=470/615 eff=91.2621% N=100 Z=-5e+09(0.00%) | Like=-4.5e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=480/625 eff=91.4286% N=100 Z=-4e+09(0.00%) | Like=-4.3e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=483/628 eff=91.4773% N=100 Z=-4e+09(0.00%) | Like=-3.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=490/635 eff=91.5888% N=100 Z=-3e+09(0.00%) | Like=-3.1e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=500/648 eff=91.2409% N=100 Z=-3e+09(0.00%) | Like=-2.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=506/656 eff=91.0072% N=100 Z=-2e+09(0.00%) | Like=-2.5e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=510/660 eff=91.0714% N=100 Z=-2e+09(0.00%) | Like=-2e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=520/671 eff=91.0683% N=100 Z=-2e+09(0.00%) | Like=-1.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=529/682 eff=90.8935% N=100 Z=-2e+09(0.00%) | Like=-1.6e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=530/685 eff=90.5983% N=100 Z=-1e+09(0.00%) | Like=-1.3e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=540/697 eff=90.4523% N=100 Z=-8e+08(0.00%) | Like=-8.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=550/710 eff=90.1639% N=100 Z=-8e+08(0.00%) | Like=-8.2e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=552/712 eff=90.1961% N=100 Z=-8e+08(0.00%) | Like=-7.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=560/721 eff=90.1771% N=100 Z=-6e+08(0.00%) | Like=-5.9e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=570/731 eff=90.3328% N=100 Z=-5e+08(0.00%) | Like=-5.2e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=580/741 eff=90.4836% N=100 Z=-4e+08(0.00%) | Like=-3.8e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=590/755 eff=90.0763% N=100 Z=-3e+08(0.00%) | Like=-3.1e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=598/763 eff=90.1961% N=100 Z=-3e+08(0.00%) | Like=-2.8e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=600/765 eff=90.2256% N=100 Z=-2e+08(0.00%) | Like=-2.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=610/775 eff=90.3704% N=100 Z=-2e+08(0.00%) | Like=-2.2e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=620/786 eff=90.3790% N=100 Z=-2e+08(0.00%) | Like=-1.8e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=630/796 eff=90.5172% N=100 Z=-1e+08(0.00%) | Like=-1.5e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=640/806 eff=90.6516% N=100 Z=-1e+08(0.00%) | Like=-1.4e+08..-6e+03 [-4.392e+10..-1.275e+07] | it/evals=644/810 eff=90.7042% N=100 Z=-1e+08(0.00%) | Like=-1.3e+08..-6e+03 [-4.392e+10..-1.275e+07] | it/evals=650/816 eff=90.7821% N=100 Z=-1e+08(0.00%) | Like=-1.1e+08..-6e+03 [-4.392e+10..-1.275e+07] | it/evals=660/827 eff=90.7840% N=100 Z=-99584971.5(0.00%) | Like=-99056746.97..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=667/835 eff=90.7483% N=100 Z=-95148616.1(0.00%) | Like=-93692477.41..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=670/838 eff=90.7859% N=100 Z=-78681625.8(0.00%) | Like=-76849640.99..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=680/849 eff=90.7877% N=100 Z=-67129640.5(0.00%) | Like=-66446442.40..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=690/860 eff=90.7895% N=100 Z=-52437072.4(0.00%) | Like=-52098992.93..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=700/872 eff=90.6736% N=100 Z=-42467034.5(0.00%) | Like=-40947576.24..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=710/883 eff=90.6769% N=100 Z=-40875016.2(0.00%) | Like=-40682265.05..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=713/886 eff=90.7125% N=100 Z=-34273953.3(0.00%) | Like=-34009302.56..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=720/893 eff=90.7945% N=100 Z=-28150952.9(0.00%) | Like=-27577294.66..-6022.96 [-4.392e+10..-1.275e+07] | it/evals=730/904 eff=90.7960% N=100 Z=-24903284.6(0.00%) | Like=-24585788.12..-26.00 [-4.392e+10..-1.275e+07] | it/evals=740/917 eff=90.5753% N=100 Z=-18109608.4(0.00%) | Like=-17736757.48..-26.00 [-4.392e+10..-1.275e+07] | it/evals=750/927 eff=90.6892% N=100 Z=-15169525.4(0.00%) | Like=-14227274.47..-26.00 [-4.392e+10..-1.275e+07] | it/evals=760/937 eff=90.8005% N=100 Z=-11387981.3(0.00%) | Like=-11171106.07..-26.00 [-12498016.5796..-6022.9623] | it/evals=770/949 eff=90.6949% N=100 Z=-9540359.8(0.00%) | Like=-9254160.55..-26.00 [-12498016.5796..-6022.9623] | it/evals=780/959 eff=90.8033% N=100 Z=-9246880.2(0.00%) | Like=-9220004.55..-26.00 [-12498016.5796..-6022.9623] | it/evals=782/961 eff=90.8246% N=100 Z=-8202857.7(0.00%) | Like=-7968261.52..-26.00 [-12498016.5796..-6022.9623] | it/evals=790/969 eff=90.9091% N=100 Z=-6151494.4(0.00%) | Like=-6110210.34..-26.00 [-12498016.5796..-6022.9623] | it/evals=800/980 eff=90.9091% N=100 Z=-5595023.2(0.00%) | Like=-5544084.40..-26.00 [-12498016.5796..-6022.9623] | it/evals=805/986 eff=90.8578% N=100 Z=-5168753.7(0.00%) | Like=-5104017.56..-26.00 [-12498016.5796..-6022.9623] | it/evals=810/991 eff=90.9091% N=100 Z=-4348450.3(0.00%) | Like=-4124983.59..-26.00 [-12498016.5796..-6022.9623] | it/evals=820/1001 eff=91.0100% N=100 Z=-3288211.8(0.00%) | Like=-3052967.15..-26.00 [-12498016.5796..-6022.9623] | it/evals=828/1010 eff=90.9890% N=100 Z=-2816901.9(0.00%) | Like=-2813964.84..-26.00 [-12498016.5796..-6022.9623] | it/evals=830/1012 eff=91.0088% N=100 Z=-2391242.8(0.00%) | Like=-2352037.02..-26.00 [-12498016.5796..-6022.9623] | it/evals=840/1022 eff=91.1063% N=100 Z=-1694476.5(0.00%) | Like=-1688714.15..-26.00 [-12498016.5796..-6022.9623] | it/evals=850/1033 eff=91.1040% N=100 Z=-1688727.3(0.00%) | Like=-1641589.55..-26.00 [-12498016.5796..-6022.9623] | it/evals=851/1034 eff=91.1135% N=100 Z=-1391311.1(0.00%) | Like=-1378714.97..-26.00 [-12498016.5796..-6022.9623] | it/evals=860/1044 eff=91.1017% N=100 Z=-1016207.0(0.00%) | Like=-1005805.90..-26.00 [-12498016.5796..-6022.9623] | it/evals=870/1056 eff=91.0042% N=100 Z=-921148.4(0.00%) | Like=-899817.07..-26.00 [-12498016.5796..-6022.9623] | it/evals=874/1061 eff=90.9469% N=100 Z=-823593.3(0.00%) | Like=-820443.05..-26.00 [-12498016.5796..-6022.9623] | it/evals=880/1067 eff=91.0031% N=100 Z=-718128.1(0.00%) | Like=-716385.20..-26.00 [-12498016.5796..-6022.9623] | it/evals=890/1078 eff=91.0020% N=100 Z=-596455.2(0.00%) | Like=-575764.61..-26.00 [-12498016.5796..-6022.9623] | it/evals=900/1090 eff=90.9091% N=100 Z=-491331.9(0.00%) | Like=-490644.03..-26.00 [-12498016.5796..-6022.9623] | it/evals=910/1101 eff=90.9091% N=100 Z=-403815.9(0.00%) | Like=-396540.01..-26.00 [-12498016.5796..-6022.9623] | it/evals=920/1112 eff=90.9091% N=100 Z=-335464.4(0.00%) | Like=-335428.11..-4.83 [-12498016.5796..-6022.9623] | it/evals=930/1122 eff=90.9980% N=100 Z=-281288.1(0.00%) | Like=-269279.55..-4.83 [-12498016.5796..-6022.9623] | it/evals=940/1133 eff=90.9971% N=100 Z=-267112.8(0.00%) | Like=-259247.40..-4.83 [-12498016.5796..-6022.9623] | it/evals=943/1137 eff=90.9354% N=100 Z=-232361.2(0.00%) | Like=-227851.27..-4.83 [-12498016.5796..-6022.9623] | it/evals=950/1144 eff=90.9962% N=100 Z=-195082.6(0.00%) | Like=-192338.76..-4.83 [-12498016.5796..-6022.9623] | it/evals=960/1154 eff=91.0816% N=100 Z=-158846.7(0.00%) | Like=-156838.84..-4.83 [-12498016.5796..-6022.9623] | it/evals=970/1165 eff=91.0798% N=100 Z=-123015.8(0.00%) | Like=-122093.92..-4.83 [-12498016.5796..-6022.9623] | it/evals=980/1176 eff=91.0781% N=100 Z=-98769.3(0.00%) | Like=-94308.81..-4.83 [-12498016.5796..-6022.9623] | it/evals=989/1186 eff=91.0681% N=100 Z=-94323.3(0.00%) | Like=-93705.11..-4.83 [-12498016.5796..-6022.9623] | it/evals=990/1187 eff=91.0764% N=100 Z=-75793.0(0.00%) | Like=-75159.71..-4.83 [-12498016.5796..-6022.9623] | it/evals=1000/1198 eff=91.0747% N=100 Z=-69193.8(0.00%) | Like=-69178.34..-4.43 [-12498016.5796..-6022.9623] | it/evals=1010/1209 eff=91.0730% N=100 Z=-68151.1(0.00%) | Like=-67031.91..-4.43 [-12498016.5796..-6022.9623] | it/evals=1012/1212 eff=91.0072% N=100 Z=-59478.1(0.00%) | Like=-56316.63..-4.43 [-12498016.5796..-6022.9623] | it/evals=1020/1221 eff=90.9902% N=100 Z=-49166.7(0.00%) | Like=-46314.73..-4.43 [-12498016.5796..-6022.9623] | it/evals=1030/1232 eff=90.9894% N=100 Z=-42809.3(0.00%) | Like=-40722.23..-4.43 [-12498016.5796..-6022.9623] | it/evals=1035/1238 eff=90.9490% N=100 Z=-38197.5(0.00%) | Like=-36533.18..-4.43 [-12498016.5796..-6022.9623] | it/evals=1040/1243 eff=90.9886% N=100 Z=-33560.9(0.00%) | Like=-32411.75..-4.43 [-12498016.5796..-6022.9623] | it/evals=1050/1253 eff=91.0668% N=100 Z=-28364.5(0.00%) | Like=-28235.71..-4.43 [-12498016.5796..-6022.9623] | it/evals=1060/1263 eff=91.1436% N=100 Z=-23735.6(0.00%) | Like=-21704.04..-4.43 [-12498016.5796..-6022.9623] | it/evals=1070/1273 eff=91.2191% N=100 Z=-17722.4(0.00%) | Like=-17494.12..-0.07 [-12498016.5796..-6022.9623] | it/evals=1080/1283 eff=91.2933% N=100 Z=-17509.5(0.00%) | Like=-17033.55..-0.07 [-12498016.5796..-6022.9623] | it/evals=1081/1284 eff=91.3007% N=100 Z=-13805.2(0.00%) | Like=-13616.77..-0.07 [-12498016.5796..-6022.9623] | it/evals=1090/1293 eff=91.3663% N=100 Z=-11448.5(0.00%) | Like=-11430.06..-0.07 [-12498016.5796..-6022.9623] | it/evals=1100/1304 eff=91.3621% N=100 Z=-10886.1(0.00%) | Like=-10406.01..-0.07 [-12498016.5796..-6022.9623] | it/evals=1104/1308 eff=91.3907% N=100 Z=-9677.3(0.00%) | Like=-9405.45..-0.07 [-12498016.5796..-6022.9623] | it/evals=1110/1314 eff=91.4333% N=100 Z=-7396.0(0.00%) | Like=-7330.88..-0.07 [-12498016.5796..-6022.9623] | it/evals=1120/1325 eff=91.4286% N=100 Z=-6557.4(0.00%) | Like=-6502.58..-0.07 [-12498016.5796..-6022.9623] | it/evals=1130/1337 eff=91.3500% N=100 Z=-4918.0(0.00%) | Like=-4673.62..-0.07 [-5702.9585..-7.6159] | it/evals=1140/1348 eff=91.3462% N=100 Z=-4140.2(0.00%) | Like=-4068.57..-0.07 [-5702.9585..-7.6159] | it/evals=1150/1358 eff=91.4149% N=100 Z=-3620.6(0.00%) | Like=-3375.59..-0.07 [-5702.9585..-7.6159] | it/evals=1160/1368 eff=91.4826% N=100 Z=-2712.2(0.00%) | Like=-2672.37..-0.00 [-5702.9585..-7.6159] | it/evals=1170/1380 eff=91.4062% N=100 Z=-2576.7(0.00%) | Like=-2536.55..-0.00 [-5702.9585..-7.6159] | it/evals=1173/1383 eff=91.4263% N=100 Z=-2224.7(0.00%) | Like=-2201.36..-0.00 [-5702.9585..-7.6159] | it/evals=1180/1391 eff=91.4020% N=100 Z=-1915.5(0.00%) | Like=-1898.60..-0.00 [-5702.9585..-7.6159] | it/evals=1190/1404 eff=91.2577% N=100 Z=-1600.7(0.00%) | Like=-1576.13..-0.00 [-5702.9585..-7.6159] | it/evals=1200/1417 eff=91.1162% N=100 Z=-1273.5(0.00%) | Like=-1210.46..-0.00 [-5702.9585..-7.6159] | it/evals=1210/1429 eff=91.0459% N=100 Z=-1035.2(0.00%) | Like=-936.01..-0.00 [-5702.9585..-7.6159] | it/evals=1220/1440 eff=91.0448% N=100 Z=-747.3(0.00%) | Like=-722.16..-0.00 [-5702.9585..-7.6159] | it/evals=1230/1454 eff=90.8419% N=100 Z=-637.3(0.00%) | Like=-618.44..-0.00 [-5702.9585..-7.6159] | it/evals=1240/1466 eff=90.7760% N=100 Z=-622.1(0.00%) | Like=-567.65..-0.00 [-5702.9585..-7.6159] | it/evals=1242/1468 eff=90.7895% N=100 Z=-438.0(0.00%) | Like=-417.64..-0.00 [-5702.9585..-7.6159] | it/evals=1250/1480 eff=90.5797% N=100 Z=-339.1(0.00%) | Like=-313.99..-0.00 [-5702.9585..-7.6159] | it/evals=1260/1492 eff=90.5172% N=100 Z=-324.7(0.00%) | Like=-304.81..-0.00 [-5702.9585..-7.6159] | it/evals=1265/1498 eff=90.4864% N=100 Z=-293.1(0.00%) | Like=-274.14..-0.00 [-5702.9585..-7.6159] | it/evals=1270/1503 eff=90.5203% N=100 Z=-223.3(0.00%) | Like=-205.47..-0.00 [-5702.9585..-7.6159] | it/evals=1280/1513 eff=90.5874% N=100 Z=-173.1(0.00%) | Like=-152.53..-0.00 [-5702.9585..-7.6159] | it/evals=1288/1521 eff=90.6404% N=100 Z=-169.3(0.00%) | Like=-149.24..-0.00 [-5702.9585..-7.6159] | it/evals=1290/1523 eff=90.6535% N=100 Z=-144.2(0.00%) | Like=-126.39..-0.00 [-5702.9585..-7.6159] | it/evals=1300/1535 eff=90.5923% N=100 Z=-123.6(0.00%) | Like=-95.22..-0.00 [-5702.9585..-7.6159] | it/evals=1310/1545 eff=90.6574% N=100 Z=-112.9(0.00%) | Like=-87.52..-0.00 [-5702.9585..-7.6159] | it/evals=1311/1546 eff=90.6639% N=100 Z=-91.2(0.00%) | Like=-72.82..-0.00 [-5702.9585..-7.6159] | it/evals=1320/1555 eff=90.7216% N=100 Z=-80.2(0.00%) | Like=-62.07..-0.00 [-5702.9585..-7.6159] | it/evals=1330/1567 eff=90.6612% N=100 Z=-77.3(0.00%) | Like=-59.47..-0.00 [-5702.9585..-7.6159] | it/evals=1334/1571 eff=90.6866% N=100 Z=-73.9(0.00%) | Like=-54.30..-0.00 [-5702.9585..-7.6159] | it/evals=1340/1579 eff=90.6018% N=100 Z=-67.7(0.00%) | Like=-50.92..-0.00 [-5702.9585..-7.6159] | it/evals=1350/1591 eff=90.5433% N=100 Z=-61.6(0.00%) | Like=-41.56..-0.00 [-5702.9585..-7.6159] | it/evals=1357/1599 eff=90.5270% N=100 Z=-56.0(0.00%) | Like=-36.88..-0.00 [-5702.9585..-7.6159] | it/evals=1360/1602 eff=90.5459% N=100 Z=-47.6(0.00%) | Like=-30.24..-0.00 [-5702.9585..-7.6159] | it/evals=1370/1616 eff=90.3694% N=100 Z=-43.5(0.00%) | Like=-25.92..-0.00 [-5702.9585..-7.6159] | it/evals=1380/1628 eff=90.3141% N=100 Z=-40.0(0.00%) | Like=-22.58..-0.00 [-5702.9585..-7.6159] | it/evals=1390/1638 eff=90.3771% N=100 Z=-36.1(0.00%) | Like=-18.56..-0.00 [-5702.9585..-7.6159] | it/evals=1400/1648 eff=90.4393% N=100 Z=-35.4(0.00%) | Like=-18.04..-0.00 [-5702.9585..-7.6159] | it/evals=1403/1651 eff=90.4578% N=100 Z=-34.1(0.00%) | Like=-17.06..-0.00 [-5702.9585..-7.6159] | it/evals=1410/1658 eff=90.5006% N=100 Z=-31.6(0.00%) | Like=-13.99..-0.00 [-5702.9585..-7.6159] | it/evals=1420/1670 eff=90.4459% N=100 Z=-30.3(0.00%) | Like=-13.03..-0.00 [-5702.9585..-7.6159] | it/evals=1426/1676 eff=90.4822% N=100 Z=-29.5(0.00%) | Like=-12.38..-0.00 [-5702.9585..-7.6159] | it/evals=1430/1680 eff=90.5063% N=100 Z=-27.1(0.00%) | Like=-9.29..-0.00 [-5702.9585..-7.6159] | it/evals=1440/1690 eff=90.5660% N=100 Z=-25.4(0.01%) | Like=-8.38..-0.00 [-5702.9585..-7.6159] | it/evals=1449/1700 eff=90.5625% N=100 Z=-25.3(0.01%) | Like=-8.23..-0.00 [-5702.9585..-7.6159] | it/evals=1450/1701 eff=90.5684% N=100 Z=-24.1(0.02%) | Like=-6.61..-0.00 [-7.5645..-5.0338] | it/evals=1460/1711 eff=90.6269% N=100 Z=-22.7(0.09%) | Like=-5.47..-0.00 [-7.5645..-5.0338] | it/evals=1470/1721 eff=90.6848% N=100 Z=-22.5(0.12%) | Like=-5.39..-0.00 [-7.5645..-5.0338] | it/evals=1472/1724 eff=90.6404% N=100 Z=-21.7(0.24%) | Like=-4.60..-0.00 [-4.6036..-4.5890] | it/evals=1480/1733 eff=90.6307% N=100 Z=-20.9(0.53%) | Like=-4.03..-0.00 [-4.0261..-4.0158] | it/evals=1490/1743 eff=90.6878% N=100 Z=-20.6(0.75%) | Like=-3.67..-0.00 [-3.6696..-3.3861] | it/evals=1495/1749 eff=90.6610% N=100 Z=-20.2(1.11%) | Like=-3.12..-0.00 [-3.1597..-3.1172] | it/evals=1500/1754 eff=90.6892% N=100 Z=-19.5(2.18%) | Like=-2.47..-0.00 [-2.5635..-2.4749] | it/evals=1510/1767 eff=90.5819% N=100 Z=-19.0(3.56%) | Like=-2.08..-0.00 [-2.1242..-2.0323] | it/evals=1518/1775 eff=90.6269% N=100 Z=-18.9(4.00%) | Like=-1.91..-0.00 [-1.9052..-1.8919] | it/evals=1520/1777 eff=90.6380% N=100 Z=-18.4(6.50%) | Like=-1.66..-0.00 [-1.6797..-1.6582] | it/evals=1530/1788 eff=90.6398% N=100 Z=-18.0(9.32%) | Like=-1.41..-0.00 [-1.4243..-1.4110] | it/evals=1540/1800 eff=90.5882% N=100 Z=-18.0(9.60%) | Like=-1.39..-0.00 [-1.3865..-1.3854]*| it/evals=1541/1801 eff=90.5938% N=100 Z=-17.7(12.78%) | Like=-1.28..-0.00 [-1.2762..-1.2747]*| it/evals=1550/1810 eff=90.6433% N=100 Z=-17.5(16.42%) | Like=-1.07..-0.00 [-1.0666..-1.0439] | it/evals=1560/1820 eff=90.6977% N=100 Z=-17.3(20.46%) | Like=-0.90..-0.00 [-0.8972..-0.8790] | it/evals=1570/1832 eff=90.6467% N=100 Z=-17.1(24.79%) | Like=-0.74..-0.00 [-0.7439..-0.7361]*| it/evals=1580/1842 eff=90.7003% N=100 Z=-17.0(27.87%) | Like=-0.58..-0.00 [-0.5809..-0.5659] | it/evals=1587/1850 eff=90.6857% N=100 Z=-16.9(29.23%) | Like=-0.52..-0.00 [-0.5602..-0.5229] | it/evals=1590/1853 eff=90.7017% N=100 Z=-16.8(34.13%) | Like=-0.45..-0.00 [-0.4534..-0.4469]*| it/evals=1600/1864 eff=90.7029% N=100 Z=-16.7(38.92%) | Like=-0.37..-0.00 [-0.3710..-0.3670]*| it/evals=1610/1874 eff=90.7554% N=100 Z=-16.5(43.53%) | Like=-0.27..-0.00 [-0.2907..-0.2738] | it/evals=1620/1884 eff=90.8072% N=100 Z=-16.4(48.03%) | Like=-0.20..-0.00 [-0.2121..-0.1995] | it/evals=1630/1895 eff=90.8078% N=100 Z=-16.4(49.37%) | Like=-0.18..-0.00 [-0.1844..-0.1839]*| it/evals=1633/1898 eff=90.8231% N=100 [ultranest] Explored until L=-8e-07 [ultranest] Likelihood function evaluations: 1899 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = -15.708 +- 1.060 single instance: logZ = -15.708 +- 0.393 bootstrapped : logZ = -15.657 +- 0.980 tail : logZ = +- 0.404 insert order U test : converged: False correlation: 46.0 iterations a 0.0001 +- 0.0010 pointstore: (1735, 5) 1899 1899 0 ====== Running Gauss problem [2] ===== [ultranest] Trying to resume from previous run, but likelihood function gives different result: [0.50000003] gave -0.12675136743767793, now -0.08140231234472156 Exception as expected: Cannot resume because loglikelihood function changed, unless resume=resume-similar. To start from scratch, delete '/tmp/tmpkd3bbklq'. ====== Running Gauss problem [3] ===== [ultranest] Trying to resume from previous run, but likelihood function gives different result: [0.50000003] gave -0.12675136743767793, now -0.046053257251765144 [ultranest] trying to salvage points from previous, different run ... [ultranest] Resuming from 995 stored points Z=-inf(0.00%) | Like=-5e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=0/1899 eff=inf% N=100 Z=-4e+13(0.00%) | Like=-4.1e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=10/1899 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-3.3e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=20/1899 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-3.2e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=23/1899 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-3e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=30/1899 eff=inf% N=100 Z=-3e+13(0.00%) | Like=-2.6e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=40/1899 eff=inf% N=100 Z=-2e+13(0.00%) | Like=-2.2e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=46/1899 eff=inf% N=100 Z=-2e+13(0.00%) | Like=-2.1e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=50/1899 eff=inf% N=100 Z=-2e+13(0.00%) | Like=-1.7e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=60/1899 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=69/1899 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-1.4e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=70/1899 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-1.3e+13..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=80/1899 eff=inf% N=100 Z=-1e+13(0.00%) | Like=-9.6e+12..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=90/1899 eff=inf% N=100 Z=-8e+12(0.00%) | Like=-8.1e+12..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=100/1899 eff=inf% N=100 Z=-7e+12(0.00%) | Like=-7e+12..-1.4e+10 [-4.998e+13..-4.434e+10] | it/evals=110/1899 eff=inf% N=100 Z=-6e+12(0.00%) | Like=-6.2e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=120/1899 eff=inf% N=100 Z=-5e+12(0.00%) | Like=-5e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=130/1899 eff=inf% N=100 Z=-5e+12(0.00%) | Like=-4.6e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=138/1899 eff=inf% N=100 Z=-5e+12(0.00%) | Like=-4.5e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=140/1899 eff=inf% N=100 Z=-3e+12(0.00%) | Like=-3.4e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=150/1899 eff=inf% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=160/1899 eff=inf% N=100 Z=-3e+12(0.00%) | Like=-2.9e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=161/1899 eff=inf% N=100 Z=-2e+12(0.00%) | Like=-2.1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=170/1899 eff=inf% N=100 Z=-2e+12(0.00%) | Like=-1.8e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=180/1899 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1.5e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=190/1899 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=200/1899 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1.1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=207/1899 eff=inf% N=100 Z=-1e+12(0.00%) | Like=-1e+12..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=210/1899 eff=inf% N=100 Z=-9e+11(0.00%) | Like=-8.4e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=220/1899 eff=inf% N=100 Z=-7e+11(0.00%) | Like=-7.1e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=230/1899 eff=inf% N=100 Z=-6e+11(0.00%) | Like=-5.8e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=240/1899 eff=inf% N=100 Z=-5e+11(0.00%) | Like=-5e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=250/1899 eff=inf% N=100 Z=-4e+11(0.00%) | Like=-4.2e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=260/1899 eff=inf% N=100 Z=-3e+11(0.00%) | Like=-3.3e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=270/1899 eff=inf% N=100 Z=-3e+11(0.00%) | Like=-3e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=276/1899 eff=inf% N=100 Z=-3e+11(0.00%) | Like=-2.7e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=280/1899 eff=inf% N=100 Z=-2e+11(0.00%) | Like=-2.2e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=290/1899 eff=inf% N=100 Z=-2e+11(0.00%) | Like=-1.8e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=300/1899 eff=inf% N=100 Z=-1e+11(0.00%) | Like=-1.3e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=310/1899 eff=inf% N=100 Z=-1e+11(0.00%) | Like=-1.1e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=320/1899 eff=inf% N=100 Z=-1e+11(0.00%) | Like=-1e+11..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=322/1899 eff=inf% N=100 Z=-9e+10(0.00%) | Like=-8.4e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=330/1899 eff=inf% N=100 Z=-8e+10(0.00%) | Like=-7.8e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=340/1899 eff=inf% N=100 Z=-7e+10(0.00%) | Like=-6.5e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=350/1899 eff=inf% N=100 Z=-5e+10(0.00%) | Like=-5.2e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=360/1899 eff=inf% N=100 Z=-4e+10(0.00%) | Like=-4.5e+10..-2e+04 [-4.998e+13..-4.434e+10] | it/evals=368/1899 eff=inf% N=100 Z=-4e+10(0.00%) | Like=-4.4e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=370/1899 eff=inf% N=100 Z=-4e+10(0.00%) | Like=-3.8e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=380/1899 eff=inf% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=390/1899 eff=inf% N=100 Z=-3e+10(0.00%) | Like=-2.9e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=391/1899 eff=inf% N=100 Z=-3e+10(0.00%) | Like=-2.5e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=400/1899 eff=inf% N=100 Z=-2e+10(0.00%) | Like=-2.2e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=410/1899 eff=inf% N=100 Z=-2e+10(0.00%) | Like=-2e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=414/1899 eff=inf% N=100 Z=-2e+10(0.00%) | Like=-1.7e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=420/1899 eff=inf% N=100 Z=-1e+10(0.00%) | Like=-1.3e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=430/1899 eff=inf% N=100 Z=-1e+10(0.00%) | Like=-1.2e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=437/1899 eff=inf% N=100 Z=-1e+10(0.00%) | Like=-1.1e+10..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=440/1899 eff=inf% N=100 Z=-9e+09(0.00%) | Like=-8.8e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=450/1899 eff=inf% N=100 Z=-7e+09(0.00%) | Like=-7.3e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=460/1899 eff=inf% N=100 Z=-6e+09(0.00%) | Like=-5.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=470/1899 eff=inf% N=100 Z=-5e+09(0.00%) | Like=-4.5e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=480/1899 eff=inf% N=100 Z=-4e+09(0.00%) | Like=-4.3e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=483/1899 eff=inf% N=100 Z=-4e+09(0.00%) | Like=-3.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=490/1899 eff=inf% N=100 Z=-3e+09(0.00%) | Like=-3.1e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=500/1899 eff=inf% N=100 Z=-3e+09(0.00%) | Like=-2.7e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=506/1899 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-2.5e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=510/1899 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-2e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=520/1899 eff=inf% N=100 Z=-2e+09(0.00%) | Like=-1.6e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=530/1899 eff=inf% N=100 Z=-1e+09(0.00%) | Like=-1.3e+09..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=540/1899 eff=inf% N=100 Z=-8e+08(0.00%) | Like=-8.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=550/1899 eff=inf% N=100 Z=-8e+08(0.00%) | Like=-8.2e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=552/1899 eff=inf% N=100 Z=-8e+08(0.00%) | Like=-7.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=560/1899 eff=inf% N=100 Z=-6e+08(0.00%) | Like=-5.9e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=570/1899 eff=inf% N=100 Z=-6e+08(0.00%) | Like=-5.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=575/1899 eff=inf% N=100 Z=-5e+08(0.00%) | Like=-5.2e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=580/1899 eff=inf% N=100 Z=-4e+08(0.00%) | Like=-3.8e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=590/1899 eff=inf% N=100 Z=-3e+08(0.00%) | Like=-3.1e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=598/1899 eff=inf% N=100 Z=-3e+08(0.00%) | Like=-2.8e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=600/1899 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-2.4e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=610/1899 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-2.2e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=620/1899 eff=inf% N=100 Z=-2e+08(0.00%) | Like=-1.8e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=630/1899 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.5e+08..-2e+04 [-4.392e+10..-1.275e+07] | it/evals=640/1899 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.4e+08..-6e+03 [-4.392e+10..-1.275e+07] | it/evals=644/1899 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.3e+08..-6e+03 [-4.392e+10..-1.275e+07] | it/evals=650/1899 eff=inf% N=100 Z=-1e+08(0.00%) | Like=-1.1e+08..-6e+03 [-4.392e+10..-1.275e+07] | it/evals=660/1899 eff=inf% N=100 Z=-99582148.9(0.00%) | Like=-99059562.04..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=667/1899 eff=inf% N=100 Z=-95151375.1(0.00%) | Like=-93695215.20..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=670/1899 eff=inf% N=100 Z=-78679116.9(0.00%) | Like=-76847161.50..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=680/1899 eff=inf% N=100 Z=-67131957.9(0.00%) | Like=-66448748.01..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=690/1899 eff=inf% N=100 Z=-52435024.3(0.00%) | Like=-52096951.40..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=700/1899 eff=inf% N=100 Z=-42465191.4(0.00%) | Like=-40949386.18..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=710/1899 eff=inf% N=100 Z=-40873207.9(0.00%) | Like=-40680461.02..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=713/1899 eff=inf% N=100 Z=-34272297.5(0.00%) | Like=-34010952.05..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=720/1899 eff=inf% N=100 Z=-28152453.6(0.00%) | Like=-27575809.36..-6001.03 [-4.392e+10..-1.275e+07] | it/evals=730/1899 eff=inf% N=100 Z=-24901873.1(0.00%) | Like=-24584385.70..-24.58 [-4.392e+10..-1.275e+07] | it/evals=740/1899 eff=inf% N=100 Z=-18110812.1(0.00%) | Like=-17737948.70..-24.58 [-4.392e+10..-1.275e+07] | it/evals=750/1899 eff=inf% N=100 Z=-15302856.8(0.00%) | Like=-15168411.63..-24.58 [-4.392e+10..-1.275e+07] | it/evals=759/1899 eff=inf% N=100 Z=-15168423.8(0.00%) | Like=-14226207.64..-24.58 [-4.392e+10..-1.275e+07] | it/evals=760/1899 eff=inf% N=100 Z=-11388935.8(0.00%) | Like=-11170160.74..-24.58 [-12499016.5202..-6001.0315] | it/evals=770/1899 eff=inf% N=100 Z=-9539486.2(0.00%) | Like=-9255020.99..-24.58 [-12499016.5202..-6001.0315] | it/evals=780/1899 eff=inf% N=100 Z=-8203667.8(0.00%) | Like=-7969059.95..-24.58 [-12499016.5202..-6001.0315] | it/evals=790/1899 eff=inf% N=100 Z=-6152195.9(0.00%) | Like=-6110909.52..-24.58 [-12499016.5202..-6001.0315] | it/evals=800/1899 eff=inf% N=100 Z=-5594354.2(0.00%) | Like=-5543418.44..-24.58 [-12499016.5202..-6001.0315] | it/evals=805/1899 eff=inf% N=100 Z=-5168110.7(0.00%) | Like=-5104656.58..-24.58 [-12499016.5202..-6001.0315] | it/evals=810/1899 eff=inf% N=100 Z=-4349040.1(0.00%) | Like=-4125558.07..-24.58 [-12499016.5202..-6001.0315] | it/evals=820/1899 eff=inf% N=100 Z=-3287698.9(0.00%) | Like=-3053461.37..-24.58 [-12499016.5202..-6001.0315] | it/evals=828/1899 eff=inf% N=100 Z=-2816427.2(0.00%) | Like=-2814439.32..-24.58 [-12499016.5202..-6001.0315] | it/evals=830/1899 eff=inf% N=100 Z=-2391680.2(0.00%) | Like=-2352470.82..-24.58 [-12499016.5202..-6001.0315] | it/evals=840/1899 eff=inf% N=100 Z=-1694108.3(0.00%) | Like=-1689081.73..-24.58 [-12499016.5202..-6001.0315] | it/evals=850/1899 eff=inf% N=100 Z=-1689094.8(0.00%) | Like=-1641951.96..-24.58 [-12499016.5202..-6001.0315] | it/evals=851/1899 eff=inf% N=100 Z=-1391644.8(0.00%) | Like=-1379047.10..-24.58 [-12499016.5202..-6001.0315] | it/evals=860/1899 eff=inf% N=100 Z=-1016250.7(0.00%) | Like=-1006089.59..-24.58 [-12499016.5202..-6001.0315] | it/evals=870/1899 eff=inf% N=100 Z=-920877.0(0.00%) | Like=-900085.39..-24.58 [-12499016.5202..-6001.0315] | it/evals=874/1899 eff=inf% N=100 Z=-823336.7(0.00%) | Like=-820186.88..-24.58 [-12499016.5202..-6001.0315] | it/evals=880/1899 eff=inf% N=100 Z=-718367.8(0.00%) | Like=-716624.62..-24.58 [-12499016.5202..-6001.0315] | it/evals=890/1899 eff=inf% N=100 Z=-608545.4(0.00%) | Like=-596660.06..-24.58 [-12499016.5202..-6001.0315] | it/evals=900/1905 eff=15000.0000% N=100 Z=-504269.2(0.00%) | Like=-491516.45..-24.58 [-12499016.5202..-6001.0315] | it/evals=910/1915 eff=5687.5000% N=100 Z=-410326.4(0.00%) | Like=-403981.87..-24.58 [-12499016.5202..-6001.0315] | it/evals=920/1925 eff=3538.4615% N=100 Z=-340215.2(0.00%) | Like=-335834.83..-24.58 [-12499016.5202..-6001.0315] | it/evals=930/1935 eff=2583.3333% N=100 Z=-271880.3(0.00%) | Like=-269426.35..-24.58 [-12499016.5202..-6001.0315] | it/evals=940/1945 eff=2043.4783% N=100 Z=-266966.7(0.00%) | Like=-259391.44..-24.58 [-12499016.5202..-6001.0315] | it/evals=943/1950 eff=1849.0196% N=100 Z=-239716.6(0.00%) | Like=-232210.82..-0.01 [-12499016.5202..-6001.0315] | it/evals=950/1957 eff=1637.9310% N=100 Z=-198757.7(0.00%) | Like=-195911.74..-0.01 [-12499016.5202..-6001.0315] | it/evals=960/1969 eff=1371.4286% N=100 Z=-185641.0(0.00%) | Like=-184269.91..-0.01 [-12499016.5202..-6001.0315] | it/evals=966/1976 eff=1254.5455% N=100 Z=-181744.2(0.00%) | Like=-180026.24..-0.01 [-12499016.5202..-6001.0315] | it/evals=970/1980 eff=1197.5309% N=100 Z=-148390.1(0.00%) | Like=-140297.95..-0.01 [-12499016.5202..-6001.0315] | it/evals=980/1990 eff=1076.9231% N=100 Z=-118368.8(0.00%) | Like=-117157.22..-0.01 [-12499016.5202..-6001.0315] | it/evals=989/2000 eff=979.2079% N=100 Z=-117171.7(0.00%) | Like=-117016.29..-0.01 [-12499016.5202..-6001.0315] | it/evals=990/2001 eff=970.5882% N=100 Z=-93946.7(0.00%) | Like=-90701.89..-0.01 [-12499016.5202..-6001.0315] | it/evals=1000/2013 eff=877.1930% N=100 Z=-74083.1(0.00%) | Like=-72115.92..-0.01 [-12499016.5202..-6001.0315] | it/evals=1010/2024 eff=808.0000% N=100 Z=-71927.9(0.00%) | Like=-71266.92..-0.01 [-12499016.5202..-6001.0315] | it/evals=1012/2026 eff=796.8504% N=100 Z=-61712.7(0.00%) | Like=-61294.55..-0.01 [-12499016.5202..-6001.0315] | it/evals=1020/2034 eff=755.5556% N=100 Z=-50661.3(0.00%) | Like=-50455.04..-0.01 [-12499016.5202..-6001.0315] | it/evals=1030/2045 eff=705.4795% N=100 Z=-36920.7(0.00%) | Like=-36316.80..-0.01 [-12499016.5202..-6001.0315] | it/evals=1040/2055 eff=666.6667% N=100 Z=-31296.4(0.00%) | Like=-30981.56..-0.01 [-12499016.5202..-6001.0315] | it/evals=1050/2068 eff=621.3018% N=100 Z=-26729.0(0.00%) | Like=-26157.39..-0.01 [-12499016.5202..-6001.0315] | it/evals=1058/2077 eff=594.3820% N=100 Z=-24936.5(0.00%) | Like=-24297.02..-0.01 [-12499016.5202..-6001.0315] | it/evals=1060/2079 eff=588.8889% N=100 Z=-21677.7(0.00%) | Like=-21593.79..-0.01 [-12499016.5202..-6001.0315] | it/evals=1070/2089 eff=563.1579% N=100 Z=-18001.6(0.00%) | Like=-17955.72..-0.01 [-12499016.5202..-6001.0315] | it/evals=1080/2099 eff=540.0000% N=100 Z=-17971.1(0.00%) | Like=-17749.51..-0.01 [-12499016.5202..-6001.0315] | it/evals=1081/2100 eff=537.8109% N=100 Z=-15034.1(0.00%) | Like=-14998.53..-0.01 [-12499016.5202..-6001.0315] | it/evals=1090/2109 eff=519.0476% N=100 Z=-11730.6(0.00%) | Like=-11195.37..-0.01 [-12499016.5202..-6001.0315] | it/evals=1100/2120 eff=497.7376% N=100 Z=-10949.8(0.00%) | Like=-10403.97..-0.01 [-12499016.5202..-6001.0315] | it/evals=1104/2126 eff=486.3436% N=100 Z=-7964.1(0.00%) | Like=-7941.21..-0.01 [-12499016.5202..-6001.0315] | it/evals=1110/2132 eff=476.3948% N=100 Z=-6734.6(0.00%) | Like=-6452.19..-0.01 [-12499016.5202..-6001.0315] | it/evals=1120/2143 eff=459.0164% N=100 Z=-5901.0(0.00%) | Like=-5695.02..-0.01 [-5885.1024..-24.5791] | it/evals=1127/2150 eff=449.0040% N=100 Z=-5622.2(0.00%) | Like=-5605.71..-0.01 [-5885.1024..-24.5791] | it/evals=1130/2153 eff=444.8819% N=100 Z=-4968.5(0.00%) | Like=-4936.64..-0.01 [-5885.1024..-24.5791] | it/evals=1140/2164 eff=430.1887% N=100 Z=-4286.6(0.00%) | Like=-4223.01..-0.01 [-5885.1024..-24.5791] | it/evals=1150/2175 eff=416.6667% N=100 Z=-3312.6(0.00%) | Like=-3294.84..-0.01 [-5885.1024..-24.5791] | it/evals=1160/2185 eff=405.5944% N=100 Z=-2850.3(0.00%) | Like=-2446.38..-0.01 [-5885.1024..-24.5791] | it/evals=1170/2196 eff=393.9394% N=100 Z=-2364.0(0.00%) | Like=-2288.89..-0.01 [-5885.1024..-24.5791] | it/evals=1173/2200 eff=389.7010% N=100 Z=-2027.3(0.00%) | Like=-2001.80..-0.01 [-5885.1024..-24.5791] | it/evals=1180/2207 eff=383.1169% N=100 Z=-1745.4(0.00%) | Like=-1674.44..-0.01 [-5885.1024..-24.5791] | it/evals=1190/2217 eff=374.2138% N=100 Z=-1490.0(0.00%) | Like=-1453.18..-0.01 [-5885.1024..-24.5791] | it/evals=1196/2224 eff=368.0000% N=100 Z=-1365.2(0.00%) | Like=-1331.69..-0.01 [-5885.1024..-24.5791] | it/evals=1200/2228 eff=364.7416% N=100 Z=-1054.6(0.00%) | Like=-1002.34..-0.01 [-5885.1024..-24.5791] | it/evals=1210/2240 eff=354.8387% N=100 Z=-841.2(0.00%) | Like=-823.56..-0.01 [-5885.1024..-24.5791] | it/evals=1220/2250 eff=347.5783% N=100 Z=-707.2(0.00%) | Like=-687.88..-0.01 [-5885.1024..-24.5791] | it/evals=1230/2264 eff=336.9863% N=100 Z=-611.8(0.00%) | Like=-593.08..-0.01 [-5885.1024..-24.5791] | it/evals=1240/2276 eff=328.9125% N=100 Z=-609.1(0.00%) | Like=-592.52..-0.01 [-5885.1024..-24.5791] | it/evals=1242/2278 eff=327.7045% N=100 Z=-526.5(0.00%) | Like=-504.79..-0.01 [-5885.1024..-24.5791] | it/evals=1250/2287 eff=322.1649% N=100 Z=-415.1(0.00%) | Like=-396.58..-0.01 [-5885.1024..-24.5791] | it/evals=1260/2302 eff=312.6551% N=100 Z=-396.6(0.00%) | Like=-379.01..-0.01 [-5885.1024..-24.5791] | it/evals=1265/2307 eff=310.0490% N=100 Z=-366.1(0.00%) | Like=-344.35..-0.01 [-5885.1024..-24.5791] | it/evals=1270/2312 eff=307.5061% N=100 Z=-291.8(0.00%) | Like=-268.55..-0.01 [-5885.1024..-24.5791] | it/evals=1280/2323 eff=301.8868% N=100 Z=-252.0(0.00%) | Like=-231.30..-0.01 [-5885.1024..-24.5791] | it/evals=1288/2334 eff=296.0920% N=100 Z=-246.0(0.00%) | Like=-224.35..-0.01 [-5885.1024..-24.5791] | it/evals=1290/2336 eff=295.1945% N=100 Z=-216.0(0.00%) | Like=-194.94..-0.01 [-5885.1024..-24.5791] | it/evals=1300/2347 eff=290.1786% N=100 Z=-183.6(0.00%) | Like=-164.57..-0.01 [-5885.1024..-24.5791] | it/evals=1310/2358 eff=285.4031% N=100 Z=-182.0(0.00%) | Like=-164.33..-0.01 [-5885.1024..-24.5791] | it/evals=1311/2359 eff=285.0000% N=100 Z=-165.7(0.00%) | Like=-145.80..-0.01 [-5885.1024..-24.5791] | it/evals=1320/2368 eff=281.4499% N=100 Z=-149.7(0.00%) | Like=-129.49..-0.00 [-5885.1024..-24.5791] | it/evals=1330/2378 eff=277.6618% N=100 Z=-145.5(0.00%) | Like=-126.99..-0.00 [-5885.1024..-24.5791] | it/evals=1334/2383 eff=275.6198% N=100 Z=-133.8(0.00%) | Like=-113.88..-0.00 [-5885.1024..-24.5791] | it/evals=1340/2390 eff=272.9124% N=100 Z=-117.4(0.00%) | Like=-98.71..-0.00 [-5885.1024..-24.5791] | it/evals=1350/2401 eff=268.9243% N=100 Z=-110.9(0.00%) | Like=-91.39..-0.00 [-5885.1024..-24.5791] | it/evals=1357/2408 eff=266.6012% N=100 Z=-105.4(0.00%) | Like=-86.93..-0.00 [-5885.1024..-24.5791] | it/evals=1360/2411 eff=265.6250% N=100 Z=-95.8(0.00%) | Like=-73.15..-0.00 [-5885.1024..-24.5791] | it/evals=1370/2421 eff=262.4521% N=100 Z=-81.3(0.00%) | Like=-62.91..-0.00 [-5885.1024..-24.5791] | it/evals=1380/2432 eff=258.9118% N=100 Z=-77.1(0.00%) | Like=-59.72..-0.00 [-5885.1024..-24.5791] | it/evals=1390/2443 eff=255.5147% N=100 Z=-69.7(0.00%) | Like=-50.74..-0.00 [-5885.1024..-24.5791] | it/evals=1400/2454 eff=252.2523% N=100 Z=-64.1(0.00%) | Like=-45.48..-0.00 [-5885.1024..-24.5791] | it/evals=1410/2466 eff=248.6772% N=100 Z=-59.4(0.00%) | Like=-41.37..-0.00 [-5885.1024..-24.5791] | it/evals=1420/2476 eff=246.1005% N=100 Z=-54.4(0.00%) | Like=-35.70..-0.00 [-5885.1024..-24.5791] | it/evals=1430/2488 eff=242.7844% N=100 Z=-49.0(0.00%) | Like=-30.10..-0.00 [-5885.1024..-24.5791] | it/evals=1440/2501 eff=239.2027% N=100 Z=-43.5(0.00%) | Like=-25.40..-0.00 [-5885.1024..-24.5791] | it/evals=1450/2513 eff=236.1564% N=100 Z=-40.0(0.00%) | Like=-21.80..-0.00 [-23.0956..-5.4691] | it/evals=1460/2523 eff=233.9744% N=100 Z=-37.1(0.00%) | Like=-18.86..-0.00 [-23.0956..-5.4691] | it/evals=1470/2534 eff=231.4961% N=100 Z=-36.5(0.00%) | Like=-17.68..-0.00 [-23.0956..-5.4691] | it/evals=1472/2537 eff=230.7210% N=100 Z=-33.5(0.00%) | Like=-15.04..-0.00 [-23.0956..-5.4691] | it/evals=1480/2545 eff=229.1022% N=100 Z=-31.4(0.00%) | Like=-13.62..-0.00 [-23.0956..-5.4691] | it/evals=1490/2557 eff=226.4438% N=100 Z=-30.3(0.00%) | Like=-12.15..-0.00 [-23.0956..-5.4691] | it/evals=1495/2562 eff=225.4902% N=100 Z=-29.5(0.00%) | Like=-11.33..-0.00 [-23.0956..-5.4691] | it/evals=1500/2567 eff=224.5509% N=100 Z=-27.9(0.00%) | Like=-10.07..-0.00 [-23.0956..-5.4691] | it/evals=1510/2578 eff=222.3859% N=100 Z=-26.8(0.00%) | Like=-8.40..-0.00 [-23.0956..-5.4691] | it/evals=1518/2587 eff=220.6395% N=100 Z=-26.3(0.00%) | Like=-7.69..-0.00 [-23.0956..-5.4691] | it/evals=1520/2590 eff=219.9711% N=100 Z=-23.6(0.06%) | Like=-5.11..-0.00 [-5.4279..-4.8286] | it/evals=1530/2600 eff=218.2596% N=100 Z=-22.0(0.29%) | Like=-4.17..-0.00 [-4.1739..-3.9887] | it/evals=1540/2612 eff=215.9888% N=100 Z=-20.9(0.81%) | Like=-2.96..-0.00 [-2.9642..-2.9502] | it/evals=1550/2622 eff=214.3845% N=100 Z=-20.1(1.90%) | Like=-2.48..-0.00 [-2.5165..-2.4768] | it/evals=1560/2636 eff=211.6689% N=100 Z=-19.8(2.54%) | Like=-2.26..-0.00 [-2.2646..-2.2305] | it/evals=1564/2640 eff=211.0661% N=100 Z=-19.4(3.61%) | Like=-1.99..-0.00 [-2.1144..-1.9862] | it/evals=1570/2646 eff=210.1740% N=100 Z=-18.9(6.06%) | Like=-1.50..-0.00 [-1.5049..-1.5000]*| it/evals=1580/2656 eff=208.7186% N=100 Z=-18.5(9.50%) | Like=-1.23..-0.00 [-1.2446..-1.2315] | it/evals=1590/2667 eff=207.0312% N=100 Z=-18.1(13.47%) | Like=-0.93..-0.00 [-0.9319..-0.9283]*| it/evals=1600/2680 eff=204.8656% N=100 Z=-17.8(17.83%) | Like=-0.85..-0.00 [-0.8479..-0.8254] | it/evals=1610/2691 eff=203.2828% N=100 Z=-17.6(22.56%) | Like=-0.62..-0.00 [-0.6544..-0.6161] | it/evals=1620/2704 eff=201.2422% N=100 Z=-17.4(27.52%) | Like=-0.50..-0.00 [-0.5010..-0.4790] | it/evals=1630/2716 eff=199.5104% N=100 Z=-17.4(29.03%) | Like=-0.45..-0.00 [-0.4671..-0.4500] | it/evals=1633/2719 eff=199.1463% N=100 Z=-17.2(32.75%) | Like=-0.37..-0.00 [-0.3905..-0.3656] | it/evals=1640/2726 eff=198.3071% N=100 Z=-17.1(37.84%) | Like=-0.31..-0.00 [-0.3065..-0.3031]*| it/evals=1650/2736 eff=197.1326% N=100 Z=-17.0(40.91%) | Like=-0.27..-0.00 [-0.2666..-0.2664]*| it/evals=1656/2743 eff=196.2085% N=100 Z=-17.0(42.83%) | Like=-0.24..-0.00 [-0.2391..-0.2391]*| it/evals=1660/2747 eff=195.7547% N=100 Z=-16.9(47.55%) | Like=-0.20..-0.00 [-0.2031..-0.2004]*| it/evals=1670/2757 eff=194.6387% N=100 [ultranest] Explored until L=-1e-06 [ultranest] Likelihood function evaluations: 2763 [ultranest] Writing samples and results to disk ... [ultranest] Writing samples and results to disk ... done [ultranest] Reached maximum number of improvement loops. [ultranest] done iterating. logZ = -16.125 +- 0.761 single instance: logZ = -16.125 +- 0.400 bootstrapped : logZ = -16.020 +- 0.645 tail : logZ = +- 0.404 insert order U test : converged: False correlation: 46.0 iterations a 0.00035 +- 0.00093 pointstore: (1776, 5) 864 2763 1899 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=False, log_dir=/tmp/tmpkd3bbklq, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 100 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=101, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977128652622.04, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=112, logz=-41932563448515.12, remainder_fraction=100.0000%, Lmin=-40508378723011.33, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=122, logz=-33237565078343.30, remainder_fraction=100.0000%, Lmin=-33004788076548.36, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=132, logz=-29684133841641.27, remainder_fraction=100.0000%, Lmin=-29654731646156.86, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=143, logz=-26024311452003.38, remainder_fraction=100.0000%, Lmin=-25864311505807.76, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=46, ncalls=151, logz=-22394867389307.37, remainder_fraction=100.0000%, Lmin=-22267402908949.62, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=155, logz=-21618903469091.73, remainder_fraction=100.0000%, Lmin=-20657643852261.66, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=165, logz=-16736505395315.38, remainder_fraction=100.0000%, Lmin=-16631669273078.86, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=69, ncalls=174, logz=-14754875235796.48, remainder_fraction=100.0000%, Lmin=-13974010155653.97, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=176, logz=-13974010155659.27, remainder_fraction=100.0000%, Lmin=-13902692147308.39, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=186, logz=-12514435159574.19, remainder_fraction=100.0000%, Lmin=-12508279160474.38, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=197, logz=-10193267488313.77, remainder_fraction=100.0000%, Lmin=-9640968563235.02, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=208, logz=-8200640852030.98, remainder_fraction=100.0000%, Lmin=-8082128050878.53, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=220, logz=-7173863638817.49, remainder_fraction=100.0000%, Lmin=-6962107832262.44, Lmax=-14202345756.60 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=115, ncalls=225, logz=-6806896849592.72, remainder_fraction=100.0000%, Lmin=-6798572125612.82, Lmax=-2101560050.10 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=230, logz=-6322457704122.88, remainder_fraction=100.0000%, Lmin=-6247007877914.18, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=243, logz=-5036135578185.74, remainder_fraction=100.0000%, Lmin=-5013134155411.33, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=257, logz=-4566342513618.33, remainder_fraction=100.0000%, Lmin=-4489051812244.98, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=268, logz=-3426886969738.49, remainder_fraction=100.0000%, Lmin=-3417861015794.89, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=278, logz=-2961969420058.14, remainder_fraction=100.0000%, Lmin=-2922089236302.01, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=161, ncalls=279, logz=-2922089236308.22, remainder_fraction=100.0000%, Lmin=-2889249507418.14, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=289, logz=-2133520045718.24, remainder_fraction=100.0000%, Lmin=-2131391081808.14, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=299, logz=-1843764249986.19, remainder_fraction=100.0000%, Lmin=-1836388311150.23, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=309, logz=-1479338126812.93, remainder_fraction=100.0000%, Lmin=-1477274817822.07, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=319, logz=-1162164164059.82, remainder_fraction=100.0000%, Lmin=-1149513369148.13, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=207, ncalls=326, logz=-1098683740545.40, remainder_fraction=100.0000%, Lmin=-1085733203899.34, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=210, ncalls=329, logz=-1062199650048.03, remainder_fraction=100.0000%, Lmin=-1036687340045.72, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=220, ncalls=342, logz=-871674334253.59, remainder_fraction=100.0000%, Lmin=-839966514038.46, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=230, ncalls=352, logz=-715976483973.56, remainder_fraction=100.0000%, Lmin=-706773276409.40, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=364, logz=-593422182128.55, remainder_fraction=100.0000%, Lmin=-576444441337.76, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=376, logz=-511876960333.87, remainder_fraction=100.0000%, Lmin=-501758974682.00, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=253, ncalls=379, logz=-478675075304.45, remainder_fraction=100.0000%, Lmin=-455241053559.73, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=260, ncalls=387, logz=-423629485137.20, remainder_fraction=100.0000%, Lmin=-418959245625.39, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=401, logz=-337456305895.85, remainder_fraction=100.0000%, Lmin=-332415073979.82, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=276, ncalls=408, logz=-298475456646.05, remainder_fraction=100.0000%, Lmin=-298119333065.73, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=412, logz=-280041079556.47, remainder_fraction=100.0000%, Lmin=-266139199581.03, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=290, ncalls=422, logz=-219987159145.22, remainder_fraction=100.0000%, Lmin=-217170277506.50, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=299, ncalls=431, logz=-186287571926.49, remainder_fraction=100.0000%, Lmin=-186217150611.38, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=432, logz=-186217150618.98, remainder_fraction=100.0000%, Lmin=-176257223101.81, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=310, ncalls=446, logz=-136032296082.24, remainder_fraction=100.0000%, Lmin=-134941926834.72, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=458, logz=-106028758932.65, remainder_fraction=100.0000%, Lmin=-105574617114.81, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=322, ncalls=460, logz=-102631626890.59, remainder_fraction=100.0000%, Lmin=-101211365642.63, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=330, ncalls=468, logz=-85746886310.20, remainder_fraction=100.0000%, Lmin=-84170564177.13, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=340, ncalls=478, logz=-78454705852.75, remainder_fraction=100.0000%, Lmin=-77856855358.69, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=488, logz=-65217978077.06, remainder_fraction=100.0000%, Lmin=-65071379682.57, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=498, logz=-52784301112.17, remainder_fraction=100.0000%, Lmin=-52465515313.79, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=368, ncalls=506, logz=-44886006297.10, remainder_fraction=100.0000%, Lmin=-44881183821.51, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=370, ncalls=508, logz=-44337101807.05, remainder_fraction=100.0000%, Lmin=-43924418108.48, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=380, ncalls=518, logz=-38174116980.61, remainder_fraction=100.0000%, Lmin=-38166134224.94, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=390, ncalls=528, logz=-30564921897.35, remainder_fraction=100.0000%, Lmin=-29014402527.49, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=391, ncalls=529, logz=-29014402536.00, remainder_fraction=100.0000%, Lmin=-28739121812.84, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=539, logz=-25254381195.53, remainder_fraction=100.0000%, Lmin=-25189070092.02, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=410, ncalls=549, logz=-21660404181.26, remainder_fraction=100.0000%, Lmin=-21548375173.69, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=414, ncalls=553, logz=-20472052660.36, remainder_fraction=100.0000%, Lmin=-20078668592.97, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=420, ncalls=559, logz=-17503276366.73, remainder_fraction=100.0000%, Lmin=-16696410598.10, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=430, ncalls=569, logz=-13957975006.86, remainder_fraction=100.0000%, Lmin=-13215545136.09, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=440, ncalls=581, logz=-11354970506.81, remainder_fraction=100.0000%, Lmin=-11308593818.41, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=591, logz=-8954739289.76, remainder_fraction=100.0000%, Lmin=-8802399549.13, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=460, ncalls=603, logz=-7358620740.27, remainder_fraction=100.0000%, Lmin=-7312924005.82, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=470, ncalls=615, logz=-5913717188.92, remainder_fraction=100.0000%, Lmin=-5686842852.59, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=480, ncalls=625, logz=-4561851573.73, remainder_fraction=100.0000%, Lmin=-4534652974.21, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=483, ncalls=628, logz=-4341443065.59, remainder_fraction=100.0000%, Lmin=-4317184186.04, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=490, ncalls=635, logz=-3683655620.41, remainder_fraction=100.0000%, Lmin=-3668713486.10, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=648, logz=-3119287299.14, remainder_fraction=100.0000%, Lmin=-3077114603.52, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=506, ncalls=656, logz=-2711784349.67, remainder_fraction=100.0000%, Lmin=-2672326802.74, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=510, ncalls=660, logz=-2471295503.35, remainder_fraction=100.0000%, Lmin=-2451644303.44, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=520, ncalls=671, logz=-2046833928.20, remainder_fraction=100.0000%, Lmin=-1963025685.85, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=529, ncalls=682, logz=-1683061127.53, remainder_fraction=100.0000%, Lmin=-1655504010.18, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=530, ncalls=685, logz=-1655504020.08, remainder_fraction=100.0000%, Lmin=-1587929042.93, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=697, logz=-1345672698.85, remainder_fraction=100.0000%, Lmin=-1324107214.64, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=710, logz=-842704557.04, remainder_fraction=100.0000%, Lmin=-842098627.35, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=552, ncalls=712, logz=-829471104.02, remainder_fraction=100.0000%, Lmin=-821755543.39, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=560, ncalls=721, logz=-768681282.57, remainder_fraction=100.0000%, Lmin=-741055451.88, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=570, ncalls=731, logz=-598461526.63, remainder_fraction=100.0000%, Lmin=-588030061.40, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=580, ncalls=741, logz=-523313989.11, remainder_fraction=100.0000%, Lmin=-520429923.57, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=590, ncalls=755, logz=-389302279.60, remainder_fraction=100.0000%, Lmin=-384227190.96, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=598, ncalls=763, logz=-330216148.35, remainder_fraction=100.0000%, Lmin=-310871070.23, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=765, logz=-291718407.06, remainder_fraction=100.0000%, Lmin=-277171076.01, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=610, ncalls=775, logz=-245515440.47, remainder_fraction=100.0000%, Lmin=-244117200.51, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=620, ncalls=786, logz=-222411923.28, remainder_fraction=100.0000%, Lmin=-218434467.04, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=796, logz=-179666648.72, remainder_fraction=100.0000%, Lmin=-179079251.49, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=640, ncalls=806, logz=-147157505.55, remainder_fraction=100.0000%, Lmin=-146182858.52, Lmax=-19941.74 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=644, ncalls=810, logz=-139592730.12, remainder_fraction=100.0000%, Lmin=-139232509.33, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=816, logz=-128990960.00, remainder_fraction=100.0000%, Lmin=-127079723.98, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=660, ncalls=827, logz=-108091218.09, remainder_fraction=100.0000%, Lmin=-105743831.21, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=667, ncalls=835, logz=-99584971.45, remainder_fraction=100.0000%, Lmin=-99056746.97, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=670, ncalls=838, logz=-95148616.12, remainder_fraction=100.0000%, Lmin=-93692477.41, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=680, ncalls=849, logz=-78681625.77, remainder_fraction=100.0000%, Lmin=-76849640.99, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=690, ncalls=860, logz=-67129640.49, remainder_fraction=100.0000%, Lmin=-66446442.40, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=872, logz=-52437072.43, remainder_fraction=100.0000%, Lmin=-52098992.93, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=710, ncalls=883, logz=-42467034.54, remainder_fraction=100.0000%, Lmin=-40947576.24, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=713, ncalls=886, logz=-40875016.23, remainder_fraction=100.0000%, Lmin=-40682265.05, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=893, logz=-34273953.31, remainder_fraction=100.0000%, Lmin=-34009302.56, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=730, ncalls=904, logz=-28150952.86, remainder_fraction=100.0000%, Lmin=-27577294.66, Lmax=-6022.96 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=740, ncalls=917, logz=-24903284.59, remainder_fraction=100.0000%, Lmin=-24585788.12, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=927, logz=-18109608.41, remainder_fraction=100.0000%, Lmin=-17736757.48, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=760, ncalls=937, logz=-15169525.42, remainder_fraction=100.0000%, Lmin=-14227274.47, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=770, ncalls=949, logz=-11387981.32, remainder_fraction=100.0000%, Lmin=-11171106.07, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=780, ncalls=959, logz=-9540359.81, remainder_fraction=100.0000%, Lmin=-9254160.55, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=782, ncalls=961, logz=-9246880.24, remainder_fraction=100.0000%, Lmin=-9220004.55, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=790, ncalls=969, logz=-8202857.71, remainder_fraction=100.0000%, Lmin=-7968261.52, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=980, logz=-6151494.36, remainder_fraction=100.0000%, Lmin=-6110210.34, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=805, ncalls=986, logz=-5595023.23, remainder_fraction=100.0000%, Lmin=-5544084.40, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=991, logz=-5168753.73, remainder_fraction=100.0000%, Lmin=-5104017.56, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=820, ncalls=1001, logz=-4348450.29, remainder_fraction=100.0000%, Lmin=-4124983.59, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=828, ncalls=1010, logz=-3288211.79, remainder_fraction=100.0000%, Lmin=-3052967.15, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=830, ncalls=1012, logz=-2816901.87, remainder_fraction=100.0000%, Lmin=-2813964.84, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=840, ncalls=1022, logz=-2391242.81, remainder_fraction=100.0000%, Lmin=-2352037.02, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=1033, logz=-1694476.49, remainder_fraction=100.0000%, Lmin=-1688714.15, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=851, ncalls=1034, logz=-1688727.26, remainder_fraction=100.0000%, Lmin=-1641589.55, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=860, ncalls=1044, logz=-1391311.12, remainder_fraction=100.0000%, Lmin=-1378714.97, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=870, ncalls=1056, logz=-1016206.97, remainder_fraction=100.0000%, Lmin=-1005805.90, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=874, ncalls=1061, logz=-921148.44, remainder_fraction=100.0000%, Lmin=-899817.07, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=880, ncalls=1067, logz=-823593.32, remainder_fraction=100.0000%, Lmin=-820443.05, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=890, ncalls=1078, logz=-718128.13, remainder_fraction=100.0000%, Lmin=-716385.20, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1090, logz=-596455.20, remainder_fraction=100.0000%, Lmin=-575764.61, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=910, ncalls=1101, logz=-491331.87, remainder_fraction=100.0000%, Lmin=-490644.03, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=920, ncalls=1112, logz=-403815.91, remainder_fraction=100.0000%, Lmin=-396540.01, Lmax=-26.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=930, ncalls=1122, logz=-335464.44, remainder_fraction=100.0000%, Lmin=-335428.11, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=940, ncalls=1133, logz=-281288.10, remainder_fraction=100.0000%, Lmin=-269279.55, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=943, ncalls=1137, logz=-267112.83, remainder_fraction=100.0000%, Lmin=-259247.40, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=1144, logz=-232361.23, remainder_fraction=100.0000%, Lmin=-227851.27, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=960, ncalls=1154, logz=-195082.59, remainder_fraction=100.0000%, Lmin=-192338.76, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=970, ncalls=1165, logz=-158846.65, remainder_fraction=100.0000%, Lmin=-156838.84, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=980, ncalls=1176, logz=-123015.80, remainder_fraction=100.0000%, Lmin=-122093.92, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=989, ncalls=1186, logz=-98769.27, remainder_fraction=100.0000%, Lmin=-94308.81, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=1187, logz=-94323.31, remainder_fraction=100.0000%, Lmin=-93705.11, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=1198, logz=-75793.03, remainder_fraction=100.0000%, Lmin=-75159.71, Lmax=-4.83 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1010, ncalls=1209, logz=-69193.78, remainder_fraction=100.0000%, Lmin=-69178.34, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1012, ncalls=1212, logz=-68151.14, remainder_fraction=100.0000%, Lmin=-67031.91, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1020, ncalls=1221, logz=-59478.14, remainder_fraction=100.0000%, Lmin=-56316.63, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1030, ncalls=1232, logz=-49166.66, remainder_fraction=100.0000%, Lmin=-46314.73, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1035, ncalls=1238, logz=-42809.28, remainder_fraction=100.0000%, Lmin=-40722.23, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1040, ncalls=1243, logz=-38197.53, remainder_fraction=100.0000%, Lmin=-36533.18, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=1253, logz=-33560.94, remainder_fraction=100.0000%, Lmin=-32411.75, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1060, ncalls=1263, logz=-28364.53, remainder_fraction=100.0000%, Lmin=-28235.71, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1070, ncalls=1273, logz=-23735.59, remainder_fraction=100.0000%, Lmin=-21704.04, Lmax=-4.43 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=1283, logz=-17722.35, remainder_fraction=100.0000%, Lmin=-17494.12, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1081, ncalls=1284, logz=-17509.53, remainder_fraction=100.0000%, Lmin=-17033.55, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1090, ncalls=1293, logz=-13805.21, remainder_fraction=100.0000%, Lmin=-13616.77, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=1304, logz=-11448.52, remainder_fraction=100.0000%, Lmin=-11430.06, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1104, ncalls=1308, logz=-10886.12, remainder_fraction=100.0000%, Lmin=-10406.01, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1110, ncalls=1314, logz=-9677.28, remainder_fraction=100.0000%, Lmin=-9405.45, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1120, ncalls=1325, logz=-7395.99, remainder_fraction=100.0000%, Lmin=-7330.88, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1130, ncalls=1337, logz=-6557.37, remainder_fraction=100.0000%, Lmin=-6502.58, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1140, ncalls=1348, logz=-4917.95, remainder_fraction=100.0000%, Lmin=-4673.62, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=1358, logz=-4140.24, remainder_fraction=100.0000%, Lmin=-4068.57, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1160, ncalls=1368, logz=-3620.58, remainder_fraction=100.0000%, Lmin=-3375.59, Lmax=-0.07 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=1380, logz=-2712.22, remainder_fraction=100.0000%, Lmin=-2672.37, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1173, ncalls=1383, logz=-2576.74, remainder_fraction=100.0000%, Lmin=-2536.55, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1180, ncalls=1391, logz=-2224.70, remainder_fraction=100.0000%, Lmin=-2201.36, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1190, ncalls=1404, logz=-1915.51, remainder_fraction=100.0000%, Lmin=-1898.60, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=1417, logz=-1600.73, remainder_fraction=100.0000%, Lmin=-1576.13, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1210, ncalls=1429, logz=-1273.46, remainder_fraction=100.0000%, Lmin=-1210.46, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1220, ncalls=1440, logz=-1035.19, remainder_fraction=100.0000%, Lmin=-936.01, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1230, ncalls=1454, logz=-747.28, remainder_fraction=100.0000%, Lmin=-722.16, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1240, ncalls=1466, logz=-637.32, remainder_fraction=100.0000%, Lmin=-618.44, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1242, ncalls=1468, logz=-622.12, remainder_fraction=100.0000%, Lmin=-567.65, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=1480, logz=-438.03, remainder_fraction=100.0000%, Lmin=-417.64, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=1492, logz=-339.14, remainder_fraction=100.0000%, Lmin=-313.99, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1265, ncalls=1498, logz=-324.70, remainder_fraction=100.0000%, Lmin=-304.81, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1270, ncalls=1503, logz=-293.07, remainder_fraction=100.0000%, Lmin=-274.14, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1280, ncalls=1513, logz=-223.33, remainder_fraction=100.0000%, Lmin=-205.47, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1288, ncalls=1521, logz=-173.11, remainder_fraction=100.0000%, Lmin=-152.53, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1290, ncalls=1523, logz=-169.31, remainder_fraction=100.0000%, Lmin=-149.24, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=1535, logz=-144.22, remainder_fraction=100.0000%, Lmin=-126.39, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1310, ncalls=1545, logz=-123.63, remainder_fraction=100.0000%, Lmin=-95.22, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1311, ncalls=1546, logz=-112.93, remainder_fraction=100.0000%, Lmin=-87.52, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1320, ncalls=1555, logz=-91.18, remainder_fraction=100.0000%, Lmin=-72.82, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1330, ncalls=1567, logz=-80.18, remainder_fraction=100.0000%, Lmin=-62.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1334, ncalls=1571, logz=-77.30, remainder_fraction=100.0000%, Lmin=-59.47, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1340, ncalls=1579, logz=-73.85, remainder_fraction=100.0000%, Lmin=-54.30, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=1591, logz=-67.70, remainder_fraction=100.0000%, Lmin=-50.92, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1357, ncalls=1599, logz=-61.65, remainder_fraction=100.0000%, Lmin=-41.56, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1360, ncalls=1602, logz=-55.96, remainder_fraction=100.0000%, Lmin=-36.88, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1370, ncalls=1616, logz=-47.65, remainder_fraction=100.0000%, Lmin=-30.24, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1380, ncalls=1628, logz=-43.50, remainder_fraction=100.0000%, Lmin=-25.92, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1390, ncalls=1638, logz=-39.96, remainder_fraction=100.0000%, Lmin=-22.58, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=1648, logz=-36.12, remainder_fraction=100.0000%, Lmin=-18.56, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1403, ncalls=1651, logz=-35.37, remainder_fraction=100.0000%, Lmin=-18.04, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1410, ncalls=1658, logz=-34.09, remainder_fraction=100.0000%, Lmin=-17.06, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1420, ncalls=1670, logz=-31.61, remainder_fraction=100.0000%, Lmin=-13.99, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1426, ncalls=1676, logz=-30.27, remainder_fraction=100.0000%, Lmin=-13.03, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1430, ncalls=1680, logz=-29.53, remainder_fraction=99.9999%, Lmin=-12.38, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=1690, logz=-27.07, remainder_fraction=99.9988%, Lmin=-9.29, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1449, ncalls=1700, logz=-25.42, remainder_fraction=99.9941%, Lmin=-8.38, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=1701, logz=-25.30, remainder_fraction=99.9933%, Lmin=-8.23, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1460, ncalls=1711, logz=-24.09, remainder_fraction=99.9772%, Lmin=-6.61, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1470, ncalls=1721, logz=-22.67, remainder_fraction=99.9057%, Lmin=-5.47, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1472, ncalls=1724, logz=-22.45, remainder_fraction=99.8835%, Lmin=-5.39, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1480, ncalls=1733, logz=-21.68, remainder_fraction=99.7623%, Lmin=-4.60, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1490, ncalls=1743, logz=-20.90, remainder_fraction=99.4704%, Lmin=-4.03, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1495, ncalls=1749, logz=-20.55, remainder_fraction=99.2485%, Lmin=-3.67, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=1754, logz=-20.17, remainder_fraction=98.8885%, Lmin=-3.12, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1510, ncalls=1767, logz=-19.49, remainder_fraction=97.8169%, Lmin=-2.47, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1518, ncalls=1775, logz=-19.01, remainder_fraction=96.4374%, Lmin=-2.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1520, ncalls=1777, logz=-18.90, remainder_fraction=96.0024%, Lmin=-1.91, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=1788, logz=-18.41, remainder_fraction=93.5038%, Lmin=-1.66, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1540, ncalls=1800, logz=-18.04, remainder_fraction=90.6846%, Lmin=-1.41, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1541, ncalls=1801, logz=-18.01, remainder_fraction=90.3959%, Lmin=-1.39, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=1810, logz=-17.75, remainder_fraction=87.2152%, Lmin=-1.28, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1560, ncalls=1820, logz=-17.51, remainder_fraction=83.5761%, Lmin=-1.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1570, ncalls=1832, logz=-17.29, remainder_fraction=79.5374%, Lmin=-0.90, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1580, ncalls=1842, logz=-17.10, remainder_fraction=75.2067%, Lmin=-0.74, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1587, ncalls=1850, logz=-16.98, remainder_fraction=72.1307%, Lmin=-0.58, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1590, ncalls=1853, logz=-16.93, remainder_fraction=70.7703%, Lmin=-0.52, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=1864, logz=-16.78, remainder_fraction=65.8745%, Lmin=-0.45, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1610, ncalls=1874, logz=-16.65, remainder_fraction=61.0805%, Lmin=-0.37, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=1884, logz=-16.54, remainder_fraction=56.4700%, Lmin=-0.27, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1630, ncalls=1895, logz=-16.44, remainder_fraction=51.9701%, Lmin=-0.20, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1633, ncalls=1898, logz=-16.41, remainder_fraction=50.6347%, Lmin=-0.18, Lmax=-0.00 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=-8e-07 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 1899 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpkd3bbklq, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [35mDEBUG [0m ultranest:integrator.py:1126 Testing resume consistency: [-0.18391364 -0.12675137 0. 0.50000003 0.00060349]: u=[0.50000003] -> p=[0.00060349] -> L=-0.12675136743767793 [33mWARNING [0m ultranest:integrator.py:1137 Trying to resume from previous run, but likelihood function gives different result: [0.50000003] gave -0.12675136743767793, now -0.08140231234472156 [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=1+0, resume=True, log_dir=/tmp/tmpkd3bbklq, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [35mDEBUG [0m ultranest:integrator.py:1126 Testing resume consistency: [-0.18391364 -0.12675137 0. 0.50000003 0.00060349]: u=[0.50000003] -> p=[0.00060349] -> L=-0.12675136743767793 [33mWARNING [0m ultranest:integrator.py:1137 Trying to resume from previous run, but likelihood function gives different result: [0.50000003] gave -0.12675136743767793, now -0.046053257251765144 [32mINFO [0m ultranest:integrator.py:1059 trying to salvage points from previous, different run ... [32mINFO [0m ultranest:integrator.py:2164 Resuming from 995 stored points [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.50, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=0, min_num_live_points=100, cluster_num_live_points=0 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 100.0), (inf, 100.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=1899, logz=-inf, remainder_fraction=100.0000%, Lmin=-49977130652164.57, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=10, ncalls=1899, logz=-41932561616957.05, remainder_fraction=100.0000%, Lmin=-40508380523197.54, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=20, ncalls=1899, logz=-33237566708988.97, remainder_fraction=100.0000%, Lmin=-33004789701473.93, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=23, ncalls=1899, logz=-32543005101534.51, remainder_fraction=100.0000%, Lmin=-32265055588306.13, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=30, ncalls=1899, logz=-29684135382657.41, remainder_fraction=100.0000%, Lmin=-29654730105904.14, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=1899, logz=-26024312894898.02, remainder_fraction=100.0000%, Lmin=-25864312944260.04, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=46, ncalls=1899, logz=-22394866050804.73, remainder_fraction=100.0000%, Lmin=-22267401574261.58, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=1899, logz=-21618902153982.53, remainder_fraction=100.0000%, Lmin=-20657642566722.29, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=60, ncalls=1899, logz=-16736504238198.11, remainder_fraction=100.0000%, Lmin=-16631670426566.43, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=69, ncalls=1899, logz=-14754876322254.05, remainder_fraction=100.0000%, Lmin=-13974009098336.24, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=70, ncalls=1899, logz=-13974009098341.54, remainder_fraction=100.0000%, Lmin=-13902691092692.20, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=1899, logz=-12514434158996.97, remainder_fraction=100.0000%, Lmin=-12508280160805.51, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=1899, logz=-10193266585284.78, remainder_fraction=100.0000%, Lmin=-9640969441459.09, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=1899, logz=-8200640042061.08, remainder_fraction=100.0000%, Lmin=-8082128854974.46, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=110, ncalls=1899, logz=-7173864396385.38, remainder_fraction=100.0000%, Lmin=-6962108578565.77, Lmax=-14202379464.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=1899, logz=-6322458415316.69, remainder_fraction=100.0000%, Lmin=-6247007170976.70, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=130, ncalls=1899, logz=-5036134943448.93, remainder_fraction=100.0000%, Lmin=-5013134788697.02, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=138, ncalls=1899, logz=-4680998274552.75, remainder_fraction=100.0000%, Lmin=-4635047605209.84, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=140, ncalls=1899, logz=-4566343118025.00, remainder_fraction=100.0000%, Lmin=-4489051212975.32, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=1899, logz=-3426887493332.78, remainder_fraction=100.0000%, Lmin=-3417861538699.18, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=1899, logz=-2961968933275.30, remainder_fraction=100.0000%, Lmin=-2922088752807.32, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=161, ncalls=1899, logz=-2922088752813.53, remainder_fraction=100.0000%, Lmin=-2889249026647.98, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=170, ncalls=1899, logz=-2133520458854.56, remainder_fraction=100.0000%, Lmin=-2131391494738.28, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=1899, logz=-1843763865927.44, remainder_fraction=100.0000%, Lmin=-1836388694440.05, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=190, ncalls=1899, logz=-1479337782796.89, remainder_fraction=100.0000%, Lmin=-1477275161598.16, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=1899, logz=-1162163859144.88, remainder_fraction=100.0000%, Lmin=-1149513065897.32, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=207, ncalls=1899, logz=-1098683444075.02, remainder_fraction=100.0000%, Lmin=-1085732909181.43, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=210, ncalls=1899, logz=-1062199358541.67, remainder_fraction=100.0000%, Lmin=-1036687628030.10, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=220, ncalls=1899, logz=-871674598325.47, remainder_fraction=100.0000%, Lmin=-839966254814.02, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=230, ncalls=1899, logz=-715976244645.11, remainder_fraction=100.0000%, Lmin=-706773038624.09, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=1899, logz=-593422400013.35, remainder_fraction=100.0000%, Lmin=-576444226592.45, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=1899, logz=-511877162695.34, remainder_fraction=100.0000%, Lmin=-501759175033.50, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=260, ncalls=1899, logz=-423629301043.88, remainder_fraction=100.0000%, Lmin=-418959428701.19, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=1899, logz=-337456141589.74, remainder_fraction=100.0000%, Lmin=-332414910905.61, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=276, ncalls=1899, logz=-298475611171.27, remainder_fraction=100.0000%, Lmin=-298119487498.74, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=1899, logz=-280040929879.21, remainder_fraction=100.0000%, Lmin=-266139053666.23, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=290, ncalls=1899, logz=-219987026484.12, remainder_fraction=100.0000%, Lmin=-217170145697.48, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=1899, logz=-186217028564.21, remainder_fraction=100.0000%, Lmin=-176257104355.97, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=310, ncalls=1899, logz=-136032191762.64, remainder_fraction=100.0000%, Lmin=-134941822934.04, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=1899, logz=-106028851032.08, remainder_fraction=100.0000%, Lmin=-105574709016.78, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=322, ncalls=1899, logz=-102631536278.64, remainder_fraction=100.0000%, Lmin=-101211275659.83, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=330, ncalls=1899, logz=-85746803486.61, remainder_fraction=100.0000%, Lmin=-84170482118.36, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=340, ncalls=1899, logz=-78454626629.19, remainder_fraction=100.0000%, Lmin=-77856776437.56, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=1899, logz=-65217905845.25, remainder_fraction=100.0000%, Lmin=-65071451833.19, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=1899, logz=-52784236129.54, remainder_fraction=100.0000%, Lmin=-52465580099.93, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=368, ncalls=1899, logz=-44886066221.08, remainder_fraction=100.0000%, Lmin=-44881243742.26, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=370, ncalls=1899, logz=-44337042250.65, remainder_fraction=100.0000%, Lmin=-43924358829.89, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=380, ncalls=1899, logz=-38174061718.26, remainder_fraction=100.0000%, Lmin=-38166189481.55, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=390, ncalls=1899, logz=-30564872448.47, remainder_fraction=100.0000%, Lmin=-29014354349.17, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=391, ncalls=1899, logz=-29014354357.68, remainder_fraction=100.0000%, Lmin=-28739169762.10, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=1899, logz=-25254336247.24, remainder_fraction=100.0000%, Lmin=-25189114982.19, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=410, ncalls=1899, logz=-21660445808.58, remainder_fraction=100.0000%, Lmin=-21548416693.23, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=414, ncalls=1899, logz=-20472012191.08, remainder_fraction=100.0000%, Lmin=-20078628514.40, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=420, ncalls=1899, logz=-17503238946.67, remainder_fraction=100.0000%, Lmin=-16696447145.52, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=430, ncalls=1899, logz=-13958008423.01, remainder_fraction=100.0000%, Lmin=-13215512620.83, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=437, ncalls=1899, logz=-11682652172.69, remainder_fraction=100.0000%, Lmin=-11587026393.36, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=440, ncalls=1899, logz=-11355000646.46, remainder_fraction=100.0000%, Lmin=-11308563740.41, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=1899, logz=-8954712524.52, remainder_fraction=100.0000%, Lmin=-8802373012.54, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=460, ncalls=1899, logz=-7358645003.22, remainder_fraction=100.0000%, Lmin=-7312899818.36, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=470, ncalls=1899, logz=-5913695438.14, remainder_fraction=100.0000%, Lmin=-5686821523.11, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=480, ncalls=1899, logz=-4561832470.13, remainder_fraction=100.0000%, Lmin=-4534672020.81, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=483, ncalls=1899, logz=-4341461702.01, remainder_fraction=100.0000%, Lmin=-4317165601.80, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=490, ncalls=1899, logz=-3683672787.04, remainder_fraction=100.0000%, Lmin=-3668730617.87, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=1899, logz=-3119303096.09, remainder_fraction=100.0000%, Lmin=-3077098913.76, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=506, ncalls=1899, logz=-2711769620.72, remainder_fraction=100.0000%, Lmin=-2672341424.19, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=510, ncalls=1899, logz=-2471309564.08, remainder_fraction=100.0000%, Lmin=-2451630298.77, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=520, ncalls=1899, logz=-2046821131.87, remainder_fraction=100.0000%, Lmin=-1963038217.51, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=530, ncalls=1899, logz=-1655492511.82, remainder_fraction=100.0000%, Lmin=-1587917772.00, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=1899, logz=-1345683074.51, remainder_fraction=100.0000%, Lmin=-1324117506.82, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=1899, logz=-842696346.31, remainder_fraction=100.0000%, Lmin=-842106835.16, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=552, ncalls=1899, logz=-829479250.06, remainder_fraction=100.0000%, Lmin=-821747435.36, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=560, ncalls=1899, logz=-768673440.75, remainder_fraction=100.0000%, Lmin=-741047752.26, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=570, ncalls=1899, logz=-598454607.33, remainder_fraction=100.0000%, Lmin=-588036920.17, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=575, ncalls=1899, logz=-561645953.60, remainder_fraction=100.0000%, Lmin=-542758608.59, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=580, ncalls=1899, logz=-523320459.46, remainder_fraction=100.0000%, Lmin=-520436376.06, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=590, ncalls=1899, logz=-389296698.92, remainder_fraction=100.0000%, Lmin=-384221646.77, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=598, ncalls=1899, logz=-330211008.59, remainder_fraction=100.0000%, Lmin=-310876057.20, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=1899, logz=-291723237.97, remainder_fraction=100.0000%, Lmin=-277166367.13, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=610, ncalls=1899, logz=-245519872.33, remainder_fraction=100.0000%, Lmin=-244121619.74, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=620, ncalls=1899, logz=-222407705.13, remainder_fraction=100.0000%, Lmin=-218430286.78, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=1899, logz=-179662857.52, remainder_fraction=100.0000%, Lmin=-179075466.49, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=640, ncalls=1899, logz=-147160936.70, remainder_fraction=100.0000%, Lmin=-146186278.28, Lmax=-19901.81 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=644, ncalls=1899, logz=-139596071.91, remainder_fraction=100.0000%, Lmin=-139229171.90, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=1899, logz=-128987747.66, remainder_fraction=100.0000%, Lmin=-127082912.47, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=660, ncalls=1899, logz=-108094158.74, remainder_fraction=100.0000%, Lmin=-105746739.75, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=667, ncalls=1899, logz=-99582148.92, remainder_fraction=100.0000%, Lmin=-99059562.04, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=670, ncalls=1899, logz=-95151375.11, remainder_fraction=100.0000%, Lmin=-93695215.20, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=680, ncalls=1899, logz=-78679116.90, remainder_fraction=100.0000%, Lmin=-76847161.50, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=690, ncalls=1899, logz=-67131957.92, remainder_fraction=100.0000%, Lmin=-66448748.01, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=1899, logz=-52435024.29, remainder_fraction=100.0000%, Lmin=-52096951.40, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=710, ncalls=1899, logz=-42465191.36, remainder_fraction=100.0000%, Lmin=-40949386.18, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=713, ncalls=1899, logz=-40873207.94, remainder_fraction=100.0000%, Lmin=-40680461.02, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=1899, logz=-34272297.45, remainder_fraction=100.0000%, Lmin=-34010952.05, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=730, ncalls=1899, logz=-28152453.57, remainder_fraction=100.0000%, Lmin=-27575809.36, Lmax=-6001.03 [35mDEBUG [0m ultranest:integrator.py:1830 clustering found some stray points [need_accept=False] (array([1, 2]), array([99, 1])) [35mDEBUG [0m ultranest:integrator.py:2406 iteration=740, ncalls=1899, logz=-24901873.14, remainder_fraction=100.0000%, Lmin=-24584385.70, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=1899, logz=-18110812.08, remainder_fraction=100.0000%, Lmin=-17737948.70, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=759, ncalls=1899, logz=-15302856.79, remainder_fraction=100.0000%, Lmin=-15168411.63, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=760, ncalls=1899, logz=-15168423.83, remainder_fraction=100.0000%, Lmin=-14226207.64, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=770, ncalls=1899, logz=-11388935.83, remainder_fraction=100.0000%, Lmin=-11170160.74, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=780, ncalls=1899, logz=-9539486.20, remainder_fraction=100.0000%, Lmin=-9255020.99, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=790, ncalls=1899, logz=-8203667.81, remainder_fraction=100.0000%, Lmin=-7969059.95, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=1899, logz=-6152195.90, remainder_fraction=100.0000%, Lmin=-6110909.52, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=805, ncalls=1899, logz=-5594354.22, remainder_fraction=100.0000%, Lmin=-5543418.44, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=1899, logz=-5168110.71, remainder_fraction=100.0000%, Lmin=-5104656.58, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=820, ncalls=1899, logz=-4349040.12, remainder_fraction=100.0000%, Lmin=-4125558.07, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=828, ncalls=1899, logz=-3287698.92, remainder_fraction=100.0000%, Lmin=-3053461.37, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=830, ncalls=1899, logz=-2816427.18, remainder_fraction=100.0000%, Lmin=-2814439.32, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=840, ncalls=1899, logz=-2391680.21, remainder_fraction=100.0000%, Lmin=-2352470.82, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=1899, logz=-1694108.33, remainder_fraction=100.0000%, Lmin=-1689081.73, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=851, ncalls=1899, logz=-1689094.84, remainder_fraction=100.0000%, Lmin=-1641951.96, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=860, ncalls=1899, logz=-1391644.76, remainder_fraction=100.0000%, Lmin=-1379047.10, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=870, ncalls=1899, logz=-1016250.69, remainder_fraction=100.0000%, Lmin=-1006089.59, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=874, ncalls=1899, logz=-920877.00, remainder_fraction=100.0000%, Lmin=-900085.39, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=880, ncalls=1899, logz=-823336.66, remainder_fraction=100.0000%, Lmin=-820186.88, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=890, ncalls=1899, logz=-718367.84, remainder_fraction=100.0000%, Lmin=-716624.62, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=1905, logz=-608545.42, remainder_fraction=100.0000%, Lmin=-596660.06, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=910, ncalls=1915, logz=-504269.24, remainder_fraction=100.0000%, Lmin=-491516.45, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=920, ncalls=1925, logz=-410326.42, remainder_fraction=100.0000%, Lmin=-403981.87, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=930, ncalls=1935, logz=-340215.24, remainder_fraction=100.0000%, Lmin=-335834.83, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=940, ncalls=1945, logz=-271880.29, remainder_fraction=100.0000%, Lmin=-269426.35, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=943, ncalls=1950, logz=-266966.68, remainder_fraction=100.0000%, Lmin=-259391.44, Lmax=-24.58 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=1957, logz=-239716.57, remainder_fraction=100.0000%, Lmin=-232210.82, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=960, ncalls=1969, logz=-198757.66, remainder_fraction=100.0000%, Lmin=-195911.74, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=966, ncalls=1976, logz=-185641.03, remainder_fraction=100.0000%, Lmin=-184269.91, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=970, ncalls=1980, logz=-181744.23, remainder_fraction=100.0000%, Lmin=-180026.24, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=980, ncalls=1990, logz=-148390.14, remainder_fraction=100.0000%, Lmin=-140297.95, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=989, ncalls=2000, logz=-118368.80, remainder_fraction=100.0000%, Lmin=-117157.22, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=2001, logz=-117171.72, remainder_fraction=100.0000%, Lmin=-117016.29, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=2013, logz=-93946.74, remainder_fraction=100.0000%, Lmin=-90701.89, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1010, ncalls=2024, logz=-74083.10, remainder_fraction=100.0000%, Lmin=-72115.92, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1012, ncalls=2026, logz=-71927.95, remainder_fraction=100.0000%, Lmin=-71266.92, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1020, ncalls=2034, logz=-61712.71, remainder_fraction=100.0000%, Lmin=-61294.55, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1030, ncalls=2045, logz=-50661.27, remainder_fraction=100.0000%, Lmin=-50455.04, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1040, ncalls=2055, logz=-36920.68, remainder_fraction=100.0000%, Lmin=-36316.80, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=2068, logz=-31296.43, remainder_fraction=100.0000%, Lmin=-30981.56, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1058, ncalls=2077, logz=-26729.00, remainder_fraction=100.0000%, Lmin=-26157.39, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1060, ncalls=2079, logz=-24936.54, remainder_fraction=100.0000%, Lmin=-24297.02, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1070, ncalls=2089, logz=-21677.69, remainder_fraction=100.0000%, Lmin=-21593.79, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=2099, logz=-18001.60, remainder_fraction=100.0000%, Lmin=-17955.72, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1081, ncalls=2100, logz=-17971.13, remainder_fraction=100.0000%, Lmin=-17749.51, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1090, ncalls=2109, logz=-15034.08, remainder_fraction=100.0000%, Lmin=-14998.53, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=2120, logz=-11730.62, remainder_fraction=100.0000%, Lmin=-11195.37, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1104, ncalls=2126, logz=-10949.78, remainder_fraction=100.0000%, Lmin=-10403.97, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1110, ncalls=2132, logz=-7964.09, remainder_fraction=100.0000%, Lmin=-7941.21, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1120, ncalls=2143, logz=-6734.62, remainder_fraction=100.0000%, Lmin=-6452.19, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1127, ncalls=2150, logz=-5900.97, remainder_fraction=100.0000%, Lmin=-5695.02, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1130, ncalls=2153, logz=-5622.18, remainder_fraction=100.0000%, Lmin=-5605.71, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1140, ncalls=2164, logz=-4968.49, remainder_fraction=100.0000%, Lmin=-4936.64, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=2175, logz=-4286.64, remainder_fraction=100.0000%, Lmin=-4223.01, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1160, ncalls=2185, logz=-3312.63, remainder_fraction=100.0000%, Lmin=-3294.84, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=2196, logz=-2850.28, remainder_fraction=100.0000%, Lmin=-2446.38, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1173, ncalls=2200, logz=-2364.03, remainder_fraction=100.0000%, Lmin=-2288.89, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1180, ncalls=2207, logz=-2027.30, remainder_fraction=100.0000%, Lmin=-2001.80, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1190, ncalls=2217, logz=-1745.44, remainder_fraction=100.0000%, Lmin=-1674.44, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1196, ncalls=2224, logz=-1489.97, remainder_fraction=100.0000%, Lmin=-1453.18, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=2228, logz=-1365.20, remainder_fraction=100.0000%, Lmin=-1331.69, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1210, ncalls=2240, logz=-1054.64, remainder_fraction=100.0000%, Lmin=-1002.34, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1220, ncalls=2250, logz=-841.24, remainder_fraction=100.0000%, Lmin=-823.56, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1230, ncalls=2264, logz=-707.25, remainder_fraction=100.0000%, Lmin=-687.88, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1240, ncalls=2276, logz=-611.76, remainder_fraction=100.0000%, Lmin=-593.08, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1242, ncalls=2278, logz=-609.07, remainder_fraction=100.0000%, Lmin=-592.52, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=2287, logz=-526.53, remainder_fraction=100.0000%, Lmin=-504.79, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=2302, logz=-415.10, remainder_fraction=100.0000%, Lmin=-396.58, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1265, ncalls=2307, logz=-396.58, remainder_fraction=100.0000%, Lmin=-379.01, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1270, ncalls=2312, logz=-366.07, remainder_fraction=100.0000%, Lmin=-344.35, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1280, ncalls=2323, logz=-291.79, remainder_fraction=100.0000%, Lmin=-268.55, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1288, ncalls=2334, logz=-252.05, remainder_fraction=100.0000%, Lmin=-231.30, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1290, ncalls=2336, logz=-245.97, remainder_fraction=100.0000%, Lmin=-224.35, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=2347, logz=-216.02, remainder_fraction=100.0000%, Lmin=-194.94, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1310, ncalls=2358, logz=-183.57, remainder_fraction=100.0000%, Lmin=-164.57, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1311, ncalls=2359, logz=-182.04, remainder_fraction=100.0000%, Lmin=-164.33, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1320, ncalls=2368, logz=-165.74, remainder_fraction=100.0000%, Lmin=-145.80, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1330, ncalls=2378, logz=-149.73, remainder_fraction=100.0000%, Lmin=-129.49, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1334, ncalls=2383, logz=-145.46, remainder_fraction=100.0000%, Lmin=-126.99, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1340, ncalls=2390, logz=-133.85, remainder_fraction=100.0000%, Lmin=-113.88, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=2401, logz=-117.39, remainder_fraction=100.0000%, Lmin=-98.71, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1357, ncalls=2408, logz=-110.92, remainder_fraction=100.0000%, Lmin=-91.39, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1360, ncalls=2411, logz=-105.39, remainder_fraction=100.0000%, Lmin=-86.93, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1370, ncalls=2421, logz=-95.80, remainder_fraction=100.0000%, Lmin=-73.15, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1380, ncalls=2432, logz=-81.25, remainder_fraction=100.0000%, Lmin=-62.91, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1390, ncalls=2443, logz=-77.06, remainder_fraction=100.0000%, Lmin=-59.72, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=2454, logz=-69.74, remainder_fraction=100.0000%, Lmin=-50.74, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1410, ncalls=2466, logz=-64.15, remainder_fraction=100.0000%, Lmin=-45.48, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1420, ncalls=2476, logz=-59.45, remainder_fraction=100.0000%, Lmin=-41.37, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1430, ncalls=2488, logz=-54.42, remainder_fraction=100.0000%, Lmin=-35.70, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=2501, logz=-49.01, remainder_fraction=100.0000%, Lmin=-30.10, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=2513, logz=-43.48, remainder_fraction=100.0000%, Lmin=-25.40, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1460, ncalls=2523, logz=-40.03, remainder_fraction=100.0000%, Lmin=-21.80, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1470, ncalls=2534, logz=-37.11, remainder_fraction=100.0000%, Lmin=-18.86, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1472, ncalls=2537, logz=-36.51, remainder_fraction=100.0000%, Lmin=-17.68, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1480, ncalls=2545, logz=-33.46, remainder_fraction=100.0000%, Lmin=-15.04, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1490, ncalls=2557, logz=-31.36, remainder_fraction=100.0000%, Lmin=-13.62, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1495, ncalls=2562, logz=-30.27, remainder_fraction=99.9999%, Lmin=-12.15, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=2567, logz=-29.48, remainder_fraction=99.9998%, Lmin=-11.33, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1510, ncalls=2578, logz=-27.93, remainder_fraction=99.9992%, Lmin=-10.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1518, ncalls=2587, logz=-26.79, remainder_fraction=99.9976%, Lmin=-8.40, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1520, ncalls=2590, logz=-26.34, remainder_fraction=99.9962%, Lmin=-7.69, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=2600, logz=-23.56, remainder_fraction=99.9375%, Lmin=-5.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1540, ncalls=2612, logz=-21.99, remainder_fraction=99.7059%, Lmin=-4.17, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=2622, logz=-20.92, remainder_fraction=99.1906%, Lmin=-2.96, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1560, ncalls=2636, logz=-20.07, remainder_fraction=98.1006%, Lmin=-2.48, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1564, ncalls=2640, logz=-19.78, remainder_fraction=97.4646%, Lmin=-2.26, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1570, ncalls=2646, logz=-19.43, remainder_fraction=96.3950%, Lmin=-1.99, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1580, ncalls=2656, logz=-18.92, remainder_fraction=93.9406%, Lmin=-1.50, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1590, ncalls=2667, logz=-18.48, remainder_fraction=90.5014%, Lmin=-1.23, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=2680, logz=-18.13, remainder_fraction=86.5258%, Lmin=-0.93, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1610, ncalls=2691, logz=-17.84, remainder_fraction=82.1699%, Lmin=-0.85, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=2704, logz=-17.61, remainder_fraction=77.4374%, Lmin=-0.62, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1630, ncalls=2716, logz=-17.41, remainder_fraction=72.4768%, Lmin=-0.50, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1633, ncalls=2719, logz=-17.36, remainder_fraction=70.9666%, Lmin=-0.45, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1640, ncalls=2726, logz=-17.24, remainder_fraction=67.2535%, Lmin=-0.37, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=2736, logz=-17.09, remainder_fraction=62.1648%, Lmin=-0.31, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1656, ncalls=2743, logz=-17.02, remainder_fraction=59.0850%, Lmin=-0.27, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1660, ncalls=2747, logz=-16.97, remainder_fraction=57.1737%, Lmin=-0.24, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1670, ncalls=2757, logz=-16.87, remainder_fraction=52.4479%, Lmin=-0.20, Lmax=-0.00 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=-1e-06 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 2763 [32mINFO [0m ultranest:integrator.py:2558 Writing samples and results to disk ... [32mINFO [0m ultranest:integrator.py:2591 Writing samples and results to disk ... done [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2467 Reached maximum number of improvement loops. [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_run.py::test_run_compat | 7.34 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.30) * Expected Volume: exp(0.00) Quality: ok a: -5.0|********************************************************| +5.0 b: -5.0|********************************************************| +5.0 Z=-inf(0.00%) | Like=-289792.32..-1468.34 [-289792.3180..-1505.7221] | it/evals=0/401 eff=0.0000% N=400 Z=-153246.2(0.00%) | Like=-152327.98..-1468.34 [-289792.3180..-1505.7221] | it/evals=40/442 eff=95.2381% N=400 Z=-132229.0(0.00%) | Like=-132052.81..-527.92 [-289792.3180..-1505.7221] | it/evals=80/486 eff=93.0233% N=400 Mono-modal Volume: ~exp(-4.56) * Expected Volume: exp(-0.23) Quality: ok a: -5.0| ******************************************************| +5.0 b: -5.0| ******************************************************| +5.0 Z=-130333.8(0.00%) | Like=-129720.19..-527.92 [-289792.3180..-1505.7221] | it/evals=90/496 eff=93.7500% N=400 Z=-118444.2(0.00%) | Like=-118431.44..-527.92 [-289792.3180..-1505.7221] | it/evals=120/532 eff=90.9091% N=400 Z=-102932.2(0.00%) | Like=-102800.01..-527.92 [-289792.3180..-1505.7221] | it/evals=160/582 eff=87.9121% N=400 Mono-modal Volume: ~exp(-4.96) * Expected Volume: exp(-0.45) Quality: ok a: -5.0| ************************************************* | +5.0 b: -5.0| ************************************************ | +5.0 Z=-96577.8(0.00%) | Like=-96492.67..-527.92 [-289792.3180..-1505.7221] | it/evals=180/608 eff=86.5385% N=400 Z=-92542.9(0.00%) | Like=-92468.21..-527.92 [-289792.3180..-1505.7221] | it/evals=200/632 eff=86.2069% N=400 Z=-82963.7(0.00%) | Like=-82950.99..-527.92 [-289792.3180..-1505.7221] | it/evals=240/683 eff=84.8057% N=400 Mono-modal Volume: ~exp(-4.96) Expected Volume: exp(-0.67) Quality: ok a: -5.0| ******************************************** | +5.0 b: -5.0| ******************************************** | +5.0 Z=-76937.3(0.00%) | Like=-76844.39..-323.62 [-289792.3180..-1505.7221] | it/evals=280/735 eff=83.5821% N=400 Z=-70048.4(0.00%) | Like=-70011.52..-323.62 [-289792.3180..-1505.7221] | it/evals=320/783 eff=83.5509% N=400 Mono-modal Volume: ~exp(-5.57) * Expected Volume: exp(-0.90) Quality: ok a: -5.0| -3.0 *************************************** | +5.0 b: -5.0| -3.0 **************************************** | +5.0 Z=-62784.9(0.00%) | Like=-62189.47..-323.62 [-289792.3180..-1505.7221] | it/evals=360/842 eff=81.4480% N=400 Z=-55747.6(0.00%) | Like=-55696.70..-5.80 [-289792.3180..-1505.7221] | it/evals=400/892 eff=81.3008% N=400 Z=-50847.2(0.00%) | Like=-50657.00..-5.80 [-289792.3180..-1505.7221] | it/evals=440/949 eff=80.1457% N=400 Mono-modal Volume: ~exp(-5.57) * Expected Volume: exp(-1.12) Quality: ok a: -5.0| -2.6 ************************************ | +5.0 b: -5.0| -2.6 *********************************** | +5.0 Z=-49491.6(0.00%) | Like=-49454.94..-5.80 [-289792.3180..-1505.7221] | it/evals=450/964 eff=79.7872% N=400 Z=-46205.2(0.00%) | Like=-46015.45..-5.80 [-289792.3180..-1505.7221] | it/evals=480/1001 eff=79.8669% N=400 Z=-42109.7(0.00%) | Like=-42018.83..-5.80 [-289792.3180..-1505.7221] | it/evals=520/1047 eff=80.3709% N=400 Mono-modal Volume: ~exp(-5.64) * Expected Volume: exp(-1.35) Quality: ok a: -5.0| -2.3 ******************************** | +5.0 b: -5.0| -2.3 ******************************** | +5.0 Z=-39756.4(0.00%) | Like=-39675.83..-5.80 [-289792.3180..-1505.7221] | it/evals=540/1072 eff=80.3571% N=400 Z=-38543.0(0.00%) | Like=-38418.75..-5.80 [-289792.3180..-1505.7221] | it/evals=560/1094 eff=80.6916% N=400 Z=-34452.0(0.00%) | Like=-34345.36..-5.80 [-289792.3180..-1505.7221] | it/evals=600/1147 eff=80.3213% N=400 Mono-modal Volume: ~exp(-5.64) Expected Volume: exp(-1.57) Quality: ok a: -5.0| -2.0 ***************************** +3.0 | +5.0 b: -5.0| -2.0 ***************************** +3.0 | +5.0 Z=-31647.7(0.00%) | Like=-31620.14..-5.80 [-289792.3180..-1505.7221] | it/evals=640/1193 eff=80.7062% N=400 Z=-28966.0(0.00%) | Like=-28942.84..-5.80 [-289792.3180..-1505.7221] | it/evals=680/1253 eff=79.7186% N=400 Mono-modal Volume: ~exp(-5.84) * Expected Volume: exp(-1.80) Quality: ok a: -5.0| -1.7 ************************** +2.7 | +5.0 b: -5.0| -1.8 ************************** +2.7 | +5.0 Z=-26166.2(0.00%) | Like=-25978.19..-5.80 [-289792.3180..-1505.7221] | it/evals=720/1316 eff=78.6026% N=400 Z=-23442.8(0.00%) | Like=-23411.77..-5.80 [-289792.3180..-1505.7221] | it/evals=760/1372 eff=78.1893% N=400 Z=-21477.8(0.00%) | Like=-21370.68..-5.80 [-289792.3180..-1505.7221] | it/evals=800/1429 eff=77.7454% N=400 Mono-modal Volume: ~exp(-6.15) * Expected Volume: exp(-2.02) Quality: ok a: -5.0| -1.5 *********************** +2.5 | +5.0 b: -5.0| -1.5 *********************** +2.4 | +5.0 Z=-20582.7(0.00%) | Like=-20486.20..-5.80 [-289792.3180..-1505.7221] | it/evals=810/1441 eff=77.8098% N=400 Z=-19066.8(0.00%) | Like=-19036.84..-5.80 [-289792.3180..-1505.7221] | it/evals=840/1478 eff=77.9221% N=400 Z=-17555.0(0.00%) | Like=-17544.16..-5.80 [-289792.3180..-1505.7221] | it/evals=880/1531 eff=77.8073% N=400 Mono-modal Volume: ~exp(-6.90) * Expected Volume: exp(-2.25) Quality: ok a: -5.0| -1.3 ********************* +2.2 | +5.0 b: -5.0| -1.3 ********************* +2.3 | +5.0 Z=-16819.8(0.00%) | Like=-16792.76..-5.80 [-289792.3180..-1505.7221] | it/evals=900/1557 eff=77.7874% N=400 Z=-16162.8(0.00%) | Like=-16091.43..-5.80 [-289792.3180..-1505.7221] | it/evals=920/1581 eff=77.9001% N=400 Z=-14163.7(0.00%) | Like=-14150.97..-5.80 [-289792.3180..-1505.7221] | it/evals=960/1629 eff=78.1123% N=400 Mono-modal Volume: ~exp(-6.90) Expected Volume: exp(-2.47) Quality: ok a: -5.0| -1.0 ****************** +2.1 | +5.0 b: -5.0| -1.1 ******************* +2.1 | +5.0 Z=-12823.4(0.00%) | Like=-12808.28..-5.80 [-289792.3180..-1505.7221] | it/evals=1000/1685 eff=77.8210% N=400 Z=-11403.2(0.00%) | Like=-11379.92..-5.80 [-289792.3180..-1505.7221] | it/evals=1040/1737 eff=77.7861% N=400 Mono-modal Volume: ~exp(-6.90) Expected Volume: exp(-2.70) Quality: ok a: -5.0| -0.9 ***************** +1.9 | +5.0 b: -5.0| -0.9 ***************** +1.9 | +5.0 Z=-10445.9(0.00%) | Like=-10428.03..-5.80 [-289792.3180..-1505.7221] | it/evals=1080/1782 eff=78.1476% N=400 Z=-9441.4(0.00%) | Like=-9404.59..-5.80 [-289792.3180..-1505.7221] | it/evals=1120/1843 eff=77.6161% N=400 Z=-8247.4(0.00%) | Like=-8230.21..-5.80 [-289792.3180..-1505.7221] | it/evals=1160/1902 eff=77.2304% N=400 Mono-modal Volume: ~exp(-7.40) * Expected Volume: exp(-2.92) Quality: ok a: -5.0| -0.7 *************** +1.8 | +5.0 b: -5.0| -0.7 *************** +1.7 | +5.0 Z=-8004.0(0.00%) | Like=-7989.44..-5.80 [-289792.3180..-1505.7221] | it/evals=1170/1917 eff=77.1259% N=400 Z=-7492.5(0.00%) | Like=-7473.15..-5.80 [-289792.3180..-1505.7221] | it/evals=1200/1960 eff=76.9231% N=400 Z=-6765.0(0.00%) | Like=-6720.15..-5.80 [-289792.3180..-1505.7221] | it/evals=1240/2012 eff=76.9231% N=400 Mono-modal Volume: ~exp(-7.51) * Expected Volume: exp(-3.15) Quality: ok a: -5.0| -0.6 ************* +1.6 | +5.0 b: -5.0| -0.6 ************** +1.6 | +5.0 Z=-6432.3(0.00%) | Like=-6418.11..-5.80 [-289792.3180..-1505.7221] | it/evals=1260/2048 eff=76.4563% N=400 Z=-6200.4(0.00%) | Like=-6182.13..-5.80 [-289792.3180..-1505.7221] | it/evals=1280/2071 eff=76.6008% N=400 Z=-5649.1(0.00%) | Like=-5627.01..-0.11 [-289792.3180..-1505.7221] | it/evals=1320/2116 eff=76.9231% N=400 Mono-modal Volume: ~exp(-7.54) * Expected Volume: exp(-3.37) Quality: ok a: -5.0| -0.5 ************ +1.5 | +5.0 b: -5.0| -0.5 ************ +1.5 | +5.0 Z=-5271.3(0.00%) | Like=-5232.32..-0.11 [-289792.3180..-1505.7221] | it/evals=1350/2164 eff=76.5306% N=400 Z=-5119.8(0.00%) | Like=-5109.17..-0.11 [-289792.3180..-1505.7221] | it/evals=1360/2175 eff=76.6197% N=400 Z=-4702.6(0.00%) | Like=-4666.87..6.31 [-289792.3180..-1505.7221] | it/evals=1400/2224 eff=76.7544% N=400 Mono-modal Volume: ~exp(-7.91) * Expected Volume: exp(-3.60) Quality: ok a: -5.0| -0.4 *********** +1.4 | +5.0 b: -5.0| -0.4 *********** +1.4 | +5.0 Z=-4147.9(0.00%) | Like=-4136.34..6.31 [-289792.3180..-1505.7221] | it/evals=1440/2276 eff=76.7591% N=400 Z=-3713.3(0.00%) | Like=-3702.39..7.21 [-289792.3180..-1505.7221] | it/evals=1480/2322 eff=77.0031% N=400 Z=-3342.5(0.00%) | Like=-3326.35..7.21 [-289792.3180..-1505.7221] | it/evals=1520/2368 eff=77.2358% N=400 Mono-modal Volume: ~exp(-8.07) * Expected Volume: exp(-3.82) Quality: ok a: -5.0| -0.3 ********** +1.3 | +5.0 b: -5.0| -0.3 ********** +1.3 | +5.0 Z=-3257.7(0.00%) | Like=-3242.93..7.21 [-289792.3180..-1505.7221] | it/evals=1530/2381 eff=77.2337% N=400 Z=-3014.8(0.00%) | Like=-2995.68..7.21 [-289792.3180..-1505.7221] | it/evals=1560/2418 eff=77.3043% N=400 Z=-2728.7(0.00%) | Like=-2711.61..7.21 [-289792.3180..-1505.7221] | it/evals=1600/2473 eff=77.1828% N=400 Mono-modal Volume: ~exp(-8.65) * Expected Volume: exp(-4.05) Quality: ok a: -5.0| -0.2 ********* +1.2 | +5.0 b: -5.0| -0.2 ********* +1.2 | +5.0 Z=-2581.5(0.00%) | Like=-2567.22..7.21 [-289792.3180..-1505.7221] | it/evals=1620/2497 eff=77.2532% N=400 Z=-2443.6(0.00%) | Like=-2433.42..7.21 [-289792.3180..-1505.7221] | it/evals=1640/2517 eff=77.4681% N=400 Z=-2225.5(0.00%) | Like=-2215.32..7.21 [-289792.3180..-1505.7221] | it/evals=1680/2565 eff=77.5982% N=400 Mono-modal Volume: ~exp(-8.65) Expected Volume: exp(-4.27) Quality: ok a: -5.0| -0.1 ******** +1.1 | +5.0 b: -5.0| -0.1 ******** +1.1 | +5.0 Z=-2078.8(0.00%) | Like=-2062.03..7.21 [-289792.3180..-1505.7221] | it/evals=1720/2616 eff=77.6173% N=400 Z=-1878.3(0.00%) | Like=-1867.18..7.21 [-289792.3180..-1505.7221] | it/evals=1760/2672 eff=77.4648% N=400 Mono-modal Volume: ~exp(-8.67) * Expected Volume: exp(-4.50) Quality: ok a: -5.0e+00| -7.4e-02 ******* +1.1e+00 | +5.0e+00 b: -5.0e+00| -7.2e-02 ******** +1.1e+00 | +5.0e+00 Z=-1694.4(0.00%) | Like=-1678.08..7.21 [-289792.3180..-1505.7221] | it/evals=1800/2727 eff=77.3528% N=400 Z=-1544.4(0.00%) | Like=-1533.31..7.21 [-289792.3180..-1505.7221] | it/evals=1840/2776 eff=77.4411% N=400 Z=-1401.3(0.00%) | Like=-1388.46..7.21 [-1504.6698..0.4589] | it/evals=1880/2830 eff=77.3663% N=400 Mono-modal Volume: ~exp(-9.13) * Expected Volume: exp(-4.73) Quality: ok a: -5.0e+00| -1.8e-02 ******* +1.0e+00 | +5.0e+00 b: -5.0e+00| -1.5e-02 ******* +1.0e+00 | +5.0e+00 Z=-1364.1(0.00%) | Like=-1353.30..7.21 [-1504.6698..0.4589] | it/evals=1890/2842 eff=77.3956% N=400 Z=-1279.0(0.00%) | Like=-1263.59..7.21 [-1504.6698..0.4589] | it/evals=1920/2884 eff=77.2947% N=400 Z=-1157.0(0.00%) | Like=-1139.34..7.21 [-1504.6698..0.4589] | it/evals=1960/2932 eff=77.4092% N=400 Mono-modal Volume: ~exp(-9.13) Expected Volume: exp(-4.95) Quality: ok a: +0.00| ****************************************************** | +1.00 b: +0.00| ***************************************************** | +1.00 Z=-1068.3(0.00%) | Like=-1053.06..7.21 [-1504.6698..0.4589] | it/evals=2000/2985 eff=77.3694% N=400 Z=-967.4(0.00%) | Like=-955.89..7.21 [-1504.6698..0.4589] | it/evals=2040/3049 eff=77.0102% N=400 Mono-modal Volume: ~exp(-9.32) * Expected Volume: exp(-5.18) Quality: ok a: +0.00| *********************************************** | +1.00 b: +0.00| ************************************************ | +1.00 Z=-914.3(0.00%) | Like=-898.72..7.21 [-1504.6698..0.4589] | it/evals=2070/3093 eff=76.8659% N=400 Z=-890.2(0.00%) | Like=-877.65..7.21 [-1504.6698..0.4589] | it/evals=2080/3104 eff=76.9231% N=400 Z=-817.0(0.00%) | Like=-803.31..7.21 [-1504.6698..0.4589] | it/evals=2120/3153 eff=77.0069% N=400 Mono-modal Volume: ~exp(-9.51) * Expected Volume: exp(-5.40) Quality: ok a: +0.0| ******************************************* | +1.0 b: +0.0| ******************************************** | +1.0 Z=-749.9(0.00%) | Like=-737.44..7.21 [-1504.6698..0.4589] | it/evals=2160/3201 eff=77.1153% N=400 Z=-666.1(0.00%) | Like=-654.18..7.21 [-1504.6698..0.4589] | it/evals=2200/3253 eff=77.1118% N=400 Z=-613.0(0.00%) | Like=-601.60..7.21 [-1504.6698..0.4589] | it/evals=2240/3307 eff=77.0554% N=400 Mono-modal Volume: ~exp(-9.74) * Expected Volume: exp(-5.63) Quality: ok a: +0.0| **************************************** | +1.0 b: +0.0| *************************************** | +1.0 Z=-603.0(0.00%) | Like=-590.88..7.21 [-1504.6698..0.4589] | it/evals=2250/3322 eff=77.0021% N=400 Z=-563.2(0.00%) | Like=-551.38..7.21 [-1504.6698..0.4589] | it/evals=2280/3355 eff=77.1574% N=400 Z=-510.3(0.00%) | Like=-494.94..7.21 [-1504.6698..0.4589] | it/evals=2320/3409 eff=77.1020% N=400 Mono-modal Volume: ~exp(-10.05) * Expected Volume: exp(-5.85) Quality: ok a: +0.0| +0.2 ********************************** +0.8 | +1.0 b: +0.0| +0.2 ********************************** +0.8 | +1.0 Z=-478.4(0.00%) | Like=-464.42..7.21 [-1504.6698..0.4589] | it/evals=2340/3435 eff=77.1005% N=400 Z=-451.2(0.00%) | Like=-438.36..7.21 [-1504.6698..0.4589] | it/evals=2360/3458 eff=77.1746% N=400 Z=-411.1(0.00%) | Like=-400.02..7.21 [-1504.6698..0.4589] | it/evals=2400/3513 eff=77.0960% N=400 Mono-modal Volume: ~exp(-10.30) * Expected Volume: exp(-6.08) Quality: ok a: +0.0| +0.2 ******************************** +0.8 | +1.0 b: +0.0| +0.2 ******************************** +0.8 | +1.0 Z=-385.5(0.00%) | Like=-373.04..7.21 [-1504.6698..0.4589] | it/evals=2430/3548 eff=77.1919% N=400 Z=-379.6(0.00%) | Like=-368.32..7.21 [-1504.6698..0.4589] | it/evals=2440/3558 eff=77.2641% N=400 Z=-342.9(0.00%) | Like=-328.82..7.21 [-1504.6698..0.4589] | it/evals=2480/3610 eff=77.2586% N=400 Mono-modal Volume: ~exp(-10.30) Expected Volume: exp(-6.30) Quality: ok a: +0.0| +0.3 **************************** +0.7 | +1.0 b: +0.0| +0.3 **************************** +0.7 | +1.0 Z=-309.7(0.00%) | Like=-297.90..7.21 [-1504.6698..0.4589] | it/evals=2520/3658 eff=77.3481% N=400 Z=-279.0(0.00%) | Like=-266.89..7.21 [-1504.6698..0.4589] | it/evals=2560/3726 eff=76.9693% N=400 Z=-255.7(0.00%) | Like=-243.70..7.21 [-1504.6698..0.4589] | it/evals=2600/3782 eff=76.8776% N=400 Mono-modal Volume: ~exp(-10.79) * Expected Volume: exp(-6.53) Quality: ok a: +0.0| +0.3 ************************** +0.7 | +1.0 b: +0.0| +0.3 ************************* +0.7 | +1.0 Z=-245.9(0.00%) | Like=-232.74..7.21 [-1504.6698..0.4589] | it/evals=2610/3798 eff=76.8099% N=400 Z=-229.5(0.00%) | Like=-217.44..7.21 [-1504.6698..0.4589] | it/evals=2640/3834 eff=76.8783% N=400 Z=-205.4(0.00%) | Like=-193.23..7.21 [-1504.6698..0.4589] | it/evals=2680/3892 eff=76.7468% N=400 Mono-modal Volume: ~exp(-10.79) Expected Volume: exp(-6.75) Quality: ok a: +0.0| +0.3 ********************** +0.7 | +1.0 b: +0.0| +0.3 ********************** +0.7 | +1.0 Z=-185.3(0.00%) | Like=-173.26..7.21 [-1504.6698..0.4589] | it/evals=2720/3954 eff=76.5335% N=400 Z=-168.8(0.00%) | Like=-157.30..7.21 [-1504.6698..0.4589] | it/evals=2760/4007 eff=76.5179% N=400 Mono-modal Volume: ~exp(-11.47) * Expected Volume: exp(-6.98) Quality: ok a: +0.0| +0.3 ******************** +0.7 | +1.0 b: +0.0| +0.3 ******************** +0.7 | +1.0 Z=-159.4(0.00%) | Like=-146.89..7.21 [-1504.6698..0.4589] | it/evals=2790/4049 eff=76.4593% N=400 Z=-154.8(0.00%) | Like=-142.43..7.21 [-1504.6698..0.4589] | it/evals=2800/4059 eff=76.5236% N=400 Z=-140.8(0.00%) | Like=-128.14..7.21 [-1504.6698..0.4589] | it/evals=2840/4110 eff=76.5499% N=400 Mono-modal Volume: ~exp(-11.47) Expected Volume: exp(-7.20) Quality: ok a: +0.0| +0.3 ****************** +0.7 | +1.0 b: +0.0| +0.3 ****************** +0.7 | +1.0 Z=-127.3(0.00%) | Like=-115.67..7.21 [-1504.6698..0.4589] | it/evals=2880/4161 eff=76.5754% N=400 Z=-117.0(0.00%) | Like=-105.09..7.21 [-1504.6698..0.4589] | it/evals=2920/4213 eff=76.5801% N=400 Z=-106.2(0.00%) | Like=-93.96..7.21 [-1504.6698..0.4589] | it/evals=2960/4267 eff=76.5451% N=400 Mono-modal Volume: ~exp(-11.47) Expected Volume: exp(-7.43) Quality: ok a: +0.0| +0.4 **************** +0.6 | +1.0 b: +0.0| +0.4 **************** +0.6 | +1.0 Z=-95.7(0.00%) | Like=-83.82..7.21 [-1504.6698..0.4589] | it/evals=3000/4323 eff=76.4721% N=400 Z=-86.9(0.00%) | Like=-74.13..7.21 [-1504.6698..0.4589] | it/evals=3040/4385 eff=76.2861% N=400 Mono-modal Volume: ~exp(-12.17) * Expected Volume: exp(-7.65) Quality: ok a: +0.0| +0.4 ************** +0.6 | +1.0 b: +0.0| +0.4 ************** +0.6 | +1.0 Z=-82.6(0.00%) | Like=-70.55..7.21 [-1504.6698..0.4589] | it/evals=3060/4416 eff=76.1952% N=400 Z=-77.5(0.00%) | Like=-65.11..7.21 [-1504.6698..0.4589] | it/evals=3080/4440 eff=76.2376% N=400 Z=-70.7(0.00%) | Like=-58.81..7.21 [-1504.6698..0.4589] | it/evals=3120/4485 eff=76.3770% N=400 Mono-modal Volume: ~exp(-12.32) * Expected Volume: exp(-7.88) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 b: +0.0| +0.4 ************** +0.6 | +1.0 Z=-66.0(0.00%) | Like=-54.16..7.21 [-1504.6698..0.4589] | it/evals=3150/4527 eff=76.3266% N=400 Z=-64.7(0.00%) | Like=-52.58..7.21 [-1504.6698..0.4589] | it/evals=3160/4537 eff=76.3839% N=400 Z=-59.1(0.00%) | Like=-47.36..7.21 [-1504.6698..0.4589] | it/evals=3200/4587 eff=76.4270% N=400 Mono-modal Volume: ~exp(-12.32) Expected Volume: exp(-8.10) Quality: ok a: +0.0| +0.4 ************ +0.6 | +1.0 b: +0.0| +0.4 ************ +0.6 | +1.0 Z=-53.9(0.00%) | Like=-41.87..7.21 [-1504.6698..0.4589] | it/evals=3240/4640 eff=76.4151% N=400 Z=-49.4(0.00%) | Like=-37.63..7.21 [-1504.6698..0.4589] | it/evals=3280/4698 eff=76.3146% N=400 Z=-45.7(0.00%) | Like=-33.72..7.21 [-1504.6698..0.4589] | it/evals=3320/4757 eff=76.1992% N=400 Mono-modal Volume: ~exp(-12.82) * Expected Volume: exp(-8.33) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 b: +0.0| +0.4 ********** +0.6 | +1.0 Z=-44.4(0.00%) | Like=-31.94..7.21 [-1504.6698..0.4589] | it/evals=3330/4772 eff=76.1665% N=400 Z=-41.0(0.00%) | Like=-28.92..7.21 [-1504.6698..0.4589] | it/evals=3360/4805 eff=76.2770% N=400 Z=-37.3(0.00%) | Like=-25.18..7.21 [-1504.6698..0.4589] | it/evals=3400/4857 eff=76.2845% N=400 Mono-modal Volume: ~exp(-12.82) Expected Volume: exp(-8.55) Quality: ok a: +0.0| +0.4 ********** +0.6 | +1.0 b: +0.0| +0.4 ********** +0.6 | +1.0 Z=-34.1(0.00%) | Like=-21.58..7.21 [-1504.6698..0.4589] | it/evals=3440/4904 eff=76.3766% N=400 Z=-30.6(0.00%) | Like=-18.23..7.21 [-1504.6698..0.4589] | it/evals=3480/4954 eff=76.4163% N=400 Mono-modal Volume: ~exp(-13.38) * Expected Volume: exp(-8.78) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.0| +0.4 ******** +0.6 | +1.0 Z=-28.2(0.00%) | Like=-16.36..7.21 [-1504.6698..0.4589] | it/evals=3510/4995 eff=76.3874% N=400 Z=-27.7(0.00%) | Like=-15.80..7.21 [-1504.6698..0.4589] | it/evals=3520/5007 eff=76.4055% N=400 Z=-25.6(0.00%) | Like=-13.35..7.25 [-1504.6698..0.4589] | it/evals=3560/5060 eff=76.3948% N=400 Mono-modal Volume: ~exp(-13.38) Expected Volume: exp(-9.00) Quality: ok a: +0.0| +0.4 ******** +0.6 | +1.0 b: +0.0| +0.4 ******** +0.6 | +1.0 Z=-23.3(0.00%) | Like=-11.29..7.25 [-1504.6698..0.4589] | it/evals=3600/5106 eff=76.4981% N=400 Z=-21.6(0.00%) | Like=-9.77..7.25 [-1504.6698..0.4589] | it/evals=3640/5157 eff=76.5188% N=400 Z=-20.1(0.00%) | Like=-8.21..7.25 [-1504.6698..0.4589] | it/evals=3680/5216 eff=76.4120% N=400 Mono-modal Volume: ~exp(-13.48) * Expected Volume: exp(-9.23) Quality: ok a: +0.0| +0.4 ******* +0.6 | +1.0 b: +0.0| +0.4 ****** +0.6 | +1.0 Z=-19.7(0.00%) | Like=-7.48..7.34 [-1504.6698..0.4589] | it/evals=3690/5230 eff=76.3975% N=400 Z=-18.4(0.00%) | Like=-6.27..7.34 [-1504.6698..0.4589] | it/evals=3720/5270 eff=76.3860% N=400 Z=-17.0(0.00%) | Like=-5.02..7.34 [-1504.6698..0.4589] | it/evals=3760/5326 eff=76.3297% N=400 Mono-modal Volume: ~exp(-13.78) * Expected Volume: exp(-9.45) Quality: ok a: +0.00| +0.45 ****** +0.55 | +1.00 b: +0.00| +0.45 ****** +0.55 | +1.00 Z=-16.4(0.00%) | Like=-4.53..7.34 [-1504.6698..0.4589] | it/evals=3780/5355 eff=76.2866% N=400 Z=-15.8(0.00%) | Like=-3.80..7.34 [-1504.6698..0.4589] | it/evals=3800/5382 eff=76.2746% N=400 Z=-14.6(0.00%) | Like=-2.46..7.34 [-1504.6698..0.4589] | it/evals=3840/5429 eff=76.3571% N=400 Mono-modal Volume: ~exp(-14.08) * Expected Volume: exp(-9.68) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.00| +0.46 ****** +0.54 | +1.00 Z=-13.8(0.01%) | Like=-1.74..7.34 [-1504.6698..0.4589] | it/evals=3870/5471 eff=76.3163% N=400 Z=-13.5(0.01%) | Like=-1.52..7.34 [-1504.6698..0.4589] | it/evals=3880/5483 eff=76.3329% N=400 Z=-12.6(0.03%) | Like=-0.80..7.34 [-1504.6698..0.4589] | it/evals=3920/5535 eff=76.3389% N=400 Mono-modal Volume: ~exp(-14.25) * Expected Volume: exp(-9.90) Quality: ok a: +0.00| +0.46 ****** +0.54 | +1.00 b: +0.00| +0.46 ****** +0.54 | +1.00 Z=-11.9(0.07%) | Like=-0.06..7.34 [-1504.6698..0.4589] | it/evals=3960/5593 eff=76.2565% N=400 Z=-11.2(0.13%) | Like=0.66..7.34 [0.4613..4.0243] | it/evals=4000/5636 eff=76.3942% N=400 Z=-10.6(0.25%) | Like=1.34..7.34 [0.4613..4.0243] | it/evals=4040/5688 eff=76.3994% N=400 Mono-modal Volume: ~exp(-14.39) * Expected Volume: exp(-10.13) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.00| +0.47 **** +0.53 | +1.00 Z=-10.4(0.28%) | Like=1.45..7.34 [0.4613..4.0243] | it/evals=4050/5699 eff=76.4295% N=400 Z=-10.0(0.43%) | Like=1.94..7.34 [0.4613..4.0243] | it/evals=4080/5734 eff=76.4904% N=400 Z=-9.5(0.71%) | Like=2.46..7.34 [0.4613..4.0243] | it/evals=4120/5792 eff=76.4095% N=400 Mono-modal Volume: ~exp(-14.78) * Expected Volume: exp(-10.35) Quality: ok a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.00| +0.47 **** +0.53 | +1.00 Z=-9.2(0.90%) | Like=2.67..7.34 [0.4613..4.0243] | it/evals=4140/5820 eff=76.3838% N=400 Z=-9.0(1.10%) | Like=2.91..7.34 [0.4613..4.0243] | it/evals=4160/5842 eff=76.4425% N=400 Z=-8.5(1.70%) | Like=3.37..7.34 [0.4613..4.0243] | it/evals=4200/5890 eff=76.5027% N=400 Mono-modal Volume: ~exp(-15.01) * Expected Volume: exp(-10.58) Quality: correlation length: 145 (+) a: +0.00| +0.47 **** +0.53 | +1.00 b: +0.00| +0.47 **** +0.53 | +1.00 Z=-8.3(2.29%) | Like=3.64..7.34 [0.4613..4.0243] | it/evals=4230/5929 eff=76.5057% N=400 Z=-8.2(2.51%) | Like=3.78..7.34 [0.4613..4.0243] | it/evals=4240/5939 eff=76.5481% N=400 Z=-7.8(3.61%) | Like=4.10..7.34 [4.0249..4.7689] | it/evals=4280/5988 eff=76.5927% N=400 Mono-modal Volume: ~exp(-15.03) * Expected Volume: exp(-10.80) Quality: correlation length: 145 (+) a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.00| +0.48 **** +0.52 | +1.00 Z=-7.5(4.87%) | Like=4.47..7.34 [4.0249..4.7689] | it/evals=4320/6039 eff=76.6093% N=400 Z=-7.2(6.56%) | Like=4.77..7.35 [4.7709..4.9800] | it/evals=4360/6086 eff=76.6796% N=400 Z=-6.9(8.53%) | Like=5.08..7.35 [5.0685..5.0821] | it/evals=4400/6143 eff=76.6150% N=400 Mono-modal Volume: ~exp(-15.48) * Expected Volume: exp(-11.02) Quality: correlation length: 145 (+) a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.00| +0.48 **** +0.52 | +1.00 Z=-6.9(9.16%) | Like=5.12..7.35 [5.1201..5.1255]*| it/evals=4410/6159 eff=76.5758% N=400 Z=-6.7(11.11%) | Like=5.30..7.35 [5.2972..5.3025]*| it/evals=4440/6195 eff=76.6178% N=400 Z=-6.4(13.79%) | Like=5.46..7.36 [5.4613..5.4668]*| it/evals=4480/6244 eff=76.6598% N=400 Mono-modal Volume: ~exp(-15.48) Expected Volume: exp(-11.25) Quality: correlation length: 145 (+) a: +0.00| +0.48 **** +0.52 | +1.00 b: +0.00| +0.48 **** +0.52 | +1.00 Z=-6.3(16.89%) | Like=5.64..7.36 [5.6380..5.6384]*| it/evals=4520/6295 eff=76.6751% N=400 Z=-6.1(19.89%) | Like=5.80..7.36 [5.7917..5.8036] | it/evals=4560/6358 eff=76.5358% N=400 Mono-modal Volume: ~exp(-15.81) * Expected Volume: exp(-11.47) Quality: correlation length: 145 (+) a: +0.00| +0.48 ** +0.52 | +1.00 b: +0.00| +0.48 ** +0.52 | +1.00 Z=-6.0(22.29%) | Like=5.94..7.36 [5.9356..5.9356]*| it/evals=4590/6398 eff=76.5255% N=400 Z=-5.9(23.10%) | Like=5.98..7.36 [5.9706..5.9817] | it/evals=4600/6412 eff=76.5136% N=400 Z=-5.8(26.70%) | Like=6.12..7.36 [6.1234..6.1251]*| it/evals=4640/6467 eff=76.4793% N=400 Mono-modal Volume: ~exp(-15.89) * Expected Volume: exp(-11.70) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-5.7(30.38%) | Like=6.25..7.36 [6.2533..6.2571]*| it/evals=4680/6522 eff=76.4456% N=400 Z=-5.5(34.08%) | Like=6.36..7.36 [6.3625..6.3627]*| it/evals=4720/6576 eff=76.4249% N=400 Z=-5.4(37.93%) | Like=6.46..7.36 [6.4611..6.4627]*| it/evals=4760/6631 eff=76.3922% N=400 Mono-modal Volume: ~exp(-16.57) * Expected Volume: exp(-11.92) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-5.4(38.79%) | Like=6.48..7.36 [6.4814..6.4851]*| it/evals=4770/6643 eff=76.4056% N=400 Z=-5.3(41.66%) | Like=6.55..7.37 [6.5516..6.5519]*| it/evals=4800/6679 eff=76.4453% N=400 Z=-5.3(45.47%) | Like=6.64..7.37 [6.6389..6.6427]*| it/evals=4840/6732 eff=76.4371% N=400 Mono-modal Volume: ~exp(-16.77) * Expected Volume: exp(-12.15) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-5.2(47.35%) | Like=6.67..7.37 [6.6725..6.6739]*| it/evals=4860/6764 eff=76.3671% N=400 Z=-5.2(49.04%) | Like=6.71..7.37 [6.7054..6.7060]*| it/evals=4880/6790 eff=76.3693% N=400 Z=-5.1(52.51%) | Like=6.76..7.37 [6.7589..6.7596]*| it/evals=4920/6838 eff=76.4212% N=400 Mono-modal Volume: ~exp(-16.83) * Expected Volume: exp(-12.37) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-5.1(55.01%) | Like=6.81..7.37 [6.8144..6.8150]*| it/evals=4950/6887 eff=76.3065% N=400 Z=-5.0(55.83%) | Like=6.83..7.37 [6.8271..6.8294]*| it/evals=4960/6900 eff=76.3077% N=400 Z=-5.0(59.01%) | Like=6.88..7.37 [6.8805..6.8808]*| it/evals=5000/6956 eff=76.2660% N=400 Mono-modal Volume: ~exp(-17.17) * Expected Volume: exp(-12.60) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-4.9(62.14%) | Like=6.94..7.37 [6.9417..6.9419]*| it/evals=5040/7009 eff=76.2596% N=400 Z=-4.9(65.15%) | Like=6.98..7.37 [6.9812..6.9822]*| it/evals=5080/7063 eff=76.2419% N=400 Z=-4.9(67.94%) | Like=7.02..7.37 [7.0179..7.0188]*| it/evals=5120/7117 eff=76.2245% N=400 Mono-modal Volume: ~exp(-17.17) Expected Volume: exp(-12.82) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-4.8(70.53%) | Like=7.05..7.37 [7.0486..7.0489]*| it/evals=5160/7173 eff=76.1849% N=400 Z=-4.8(72.91%) | Like=7.08..7.37 [7.0769..7.0769]*| it/evals=5200/7229 eff=76.1458% N=400 Mono-modal Volume: ~exp(-17.60) * Expected Volume: exp(-13.05) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-4.8(74.02%) | Like=7.10..7.37 [7.0976..7.0977]*| it/evals=5220/7258 eff=76.1155% N=400 Z=-4.8(75.14%) | Like=7.11..7.37 [7.1067..7.1072]*| it/evals=5240/7280 eff=76.1628% N=400 Z=-4.7(77.25%) | Like=7.13..7.37 [7.1293..7.1296]*| it/evals=5280/7336 eff=76.1246% N=400 Mono-modal Volume: ~exp(-17.84) * Expected Volume: exp(-13.27) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-4.7(78.72%) | Like=7.15..7.37 [7.1455..7.1472]*| it/evals=5310/7380 eff=76.0745% N=400 Z=-4.7(79.19%) | Like=7.15..7.37 [7.1526..7.1527]*| it/evals=5320/7392 eff=76.0870% N=400 Z=-4.7(80.99%) | Like=7.18..7.37 [7.1787..7.1789]*| it/evals=5360/7444 eff=76.0931% N=400 Mono-modal Volume: ~exp(-17.84) Expected Volume: exp(-13.50) Quality: correlation length: 145 (+) a: +0.00| +0.49 ** +0.51 | +1.00 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-4.7(82.62%) | Like=7.19..7.37 [7.1943..7.1959]*| it/evals=5400/7497 eff=76.0885% N=400 Z=-4.6(84.15%) | Like=7.21..7.37 [7.2144..7.2146]*| it/evals=5440/7546 eff=76.1265% N=400 Z=-4.6(85.56%) | Like=7.23..7.37 [7.2315..7.2319]*| it/evals=5480/7597 eff=76.1428% N=400 Mono-modal Volume: ~exp(-17.95) * Expected Volume: exp(-13.72) Quality: correlation length: 145 (+) a: +0.000| +0.495 ** +0.505 | +1.000 b: +0.00| +0.49 ** +0.51 | +1.00 Z=-4.6(85.89%) | Like=7.23..7.37 [7.2341..7.2344]*| it/evals=5490/7611 eff=76.1337% N=400 Z=-4.6(86.84%) | Like=7.25..7.37 [7.2466..7.2469]*| it/evals=5520/7647 eff=76.1694% N=400 Z=-4.6(88.03%) | Like=7.26..7.37 [7.2568..7.2573]*| it/evals=5560/7705 eff=76.1123% N=400 Mono-modal Volume: ~exp(-18.39) * Expected Volume: exp(-13.95) Quality: correlation length: 145 (+) a: +0.000| +0.495 ** +0.505 | +1.000 b: +0.000| +0.495 ** +0.505 | +1.000 Z=-4.6(88.58%) | Like=7.26..7.37 [7.2611..7.2611]*| it/evals=5580/7733 eff=76.0944% N=400 Z=-4.6(89.11%) | Like=7.27..7.37 [7.2668..7.2669]*| it/evals=5600/7757 eff=76.1180% N=400 Z=-4.6(90.10%) | Like=7.28..7.37 [7.2754..7.2757]*| it/evals=5640/7804 eff=76.1750% N=400 Mono-modal Volume: ~exp(-18.93) * Expected Volume: exp(-14.17) Quality: correlation length: 145 (+) a: +0.000| +0.496 ** +0.504 | +1.000 b: +0.000| +0.496 ** +0.504 | +1.000 Z=-4.6(90.78%) | Like=7.28..7.37 [7.2824..7.2824]*| it/evals=5670/7843 eff=76.1790% N=400 Z=-4.6(90.99%) | Like=7.28..7.37 [7.2847..7.2849]*| it/evals=5680/7854 eff=76.2007% N=400 Z=-4.6(91.81%) | Like=7.29..7.37 [7.2915..7.2916]*| it/evals=5720/7902 eff=76.2463% N=400 Mono-modal Volume: ~exp(-18.97) * Expected Volume: exp(-14.40) Quality: correlation length: 145 (+) a: +0.000| +0.496 ** +0.504 | +1.000 b: +0.000| +0.496 ** +0.504 | +1.000 Z=-4.5(92.57%) | Like=7.30..7.37 [7.2999..7.3006]*| it/evals=5760/7952 eff=76.2712% N=400 Z=-4.5(93.25%) | Like=7.31..7.37 [7.3068..7.3069]*| it/evals=5800/8001 eff=76.3057% N=400 Z=-4.5(93.87%) | Like=7.31..7.37 [7.3127..7.3127]*| it/evals=5840/8050 eff=76.3399% N=400 Mono-modal Volume: ~exp(-18.97) Expected Volume: exp(-14.62) Quality: correlation length: 145 (+) a: +0.000| +0.497 ** +0.503 | +1.000 b: +0.000| +0.497 ** +0.503 | +1.000 Z=-4.5(94.44%) | Like=7.32..7.37 [7.3188..7.3189]*| it/evals=5880/8109 eff=76.2745% N=400 Z=-4.5(94.95%) | Like=7.33..7.37 [7.3252..7.3253]*| it/evals=5920/8175 eff=76.1415% N=400 Mono-modal Volume: ~exp(-19.23) * Expected Volume: exp(-14.85) Quality: correlation length: 145 (+) a: +0.000| +0.497 ** +0.503 | +1.000 b: +0.000| +0.497 ** +0.503 | +1.000 Z=-4.5(95.19%) | Like=7.33..7.37 [7.3270..7.3270]*| it/evals=5940/8201 eff=76.1441% N=400 Z=-4.5(95.42%) | Like=7.33..7.37 [7.3289..7.3289]*| it/evals=5960/8224 eff=76.1759% N=400 Z=-4.5(95.85%) | Like=7.33..7.37 [7.3323..7.3323]*| it/evals=6000/8267 eff=76.2680% N=400 Mono-modal Volume: ~exp(-19.52) * Expected Volume: exp(-15.07) Quality: correlation length: 145 (+) a: +0.000| +0.497 ** +0.503 | +1.000 b: +0.000| +0.497 ** +0.503 | +1.000 Z=-4.5(96.15%) | Like=7.33..7.37 [7.3347..7.3348]*| it/evals=6030/8312 eff=76.2133% N=400 Z=-4.5(96.24%) | Like=7.34..7.37 [7.3356..7.3356]*| it/evals=6040/8325 eff=76.2145% N=400 Z=-4.5(96.59%) | Like=7.34..7.37 [7.3400..7.3400]*| it/evals=6080/8385 eff=76.1428% N=400 Mono-modal Volume: ~exp(-19.52) Expected Volume: exp(-15.30) Quality: correlation length: 145 (+) a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.000| +0.498 ** +0.502 | +1.000 Z=-4.5(96.91%) | Like=7.34..7.37 [7.3428..7.3429]*| it/evals=6120/8447 eff=76.0532% N=400 Z=-4.5(97.20%) | Like=7.35..7.37 [7.3459..7.3460]*| it/evals=6160/8505 eff=76.0025% N=400 Z=-4.5(97.46%) | Like=7.35..7.37 [7.3480..7.3480]*| it/evals=6200/8563 eff=75.9525% N=400 Mono-modal Volume: ~exp(-20.33) * Expected Volume: exp(-15.52) Quality: correlation length: 145 (+) a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.000| +0.498 ** +0.502 | +1.000 Z=-4.5(97.53%) | Like=7.35..7.37 [7.3482..7.3485]*| it/evals=6210/8575 eff=75.9633% N=400 Z=-4.5(97.70%) | Like=7.35..7.37 [7.3501..7.3501]*| it/evals=6240/8613 eff=75.9771% N=400 Z=-4.5(97.92%) | Like=7.35..7.37 [7.3520..7.3520]*| it/evals=6280/8662 eff=76.0107% N=400 Mono-modal Volume: ~exp(-20.41) * Expected Volume: exp(-15.75) Quality: correlation length: 2124 (+) a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.000| +0.498 ** +0.502 | +1.000 Z=-4.5(98.02%) | Like=7.35..7.37 [7.3531..7.3531]*| it/evals=6300/8688 eff=76.0135% N=400 Z=-4.5(98.11%) | Like=7.35..7.37 [7.3541..7.3541]*| it/evals=6320/8712 eff=76.0346% N=400 Z=-4.5(98.29%) | Like=7.36..7.37 [7.3557..7.3558]*| it/evals=6360/8766 eff=76.0220% N=400 Mono-modal Volume: ~exp(-20.47) * Expected Volume: exp(-15.97) Quality: correlation length: 2124 (+) a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.000| +0.498 ** +0.502 | +1.000 Z=-4.5(98.42%) | Like=7.36..7.37 [7.3569..7.3569]*| it/evals=6390/8799 eff=76.0805% N=400 Z=-4.5(98.45%) | Like=7.36..7.37 [7.3572..7.3572]*| it/evals=6400/8810 eff=76.0999% N=400 Z=-4.5(98.60%) | Like=7.36..7.37 [7.3584..7.3585]*| it/evals=6440/8865 eff=76.0780% N=400 Mono-modal Volume: ~exp(-20.68) * Expected Volume: exp(-16.20) Quality: correlation length: 2124 (+) a: +0.000| +0.498 ** +0.502 | +1.000 b: +0.000| +0.498 ** +0.502 | +1.000 Z=-4.5(98.73%) | Like=7.36..7.37 [7.3599..7.3600]*| it/evals=6480/8930 eff=75.9672% N=400 Z=-4.5(98.85%) | Like=7.36..7.37 [7.3610..7.3610]*| it/evals=6520/8975 eff=76.0350% N=400 Z=-4.5(98.96%) | Like=7.36..7.37 [7.3619..7.3619]*| it/evals=6560/9033 eff=75.9875% N=400 Mono-modal Volume: ~exp(-20.92) * Expected Volume: exp(-16.42) Quality: correlation length: 2124 (+) a: +0.000| +0.499 ** +0.501 | +1.000 b: +0.000| +0.499 ** +0.501 | +1.000 Z=-4.5(98.99%) | Like=7.36..7.37 [7.3622..7.3622]*| it/evals=6570/9046 eff=75.9889% N=400 [ultranest] Explored until L=7 [ultranest] Likelihood function evaluations: 9051 [ultranest] logZ = -4.45 +- 0.1628 [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.47+-0.04 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.34, need <0.5) [ultranest] logZ error budget: single: 0.16 bs:0.16 tail:0.01 total:0.16 required:<0.50 [ultranest] done iterating. logZ = -4.466 +- 0.338 single instance: logZ = -4.466 +- 0.165 bootstrapped : logZ = -4.450 +- 0.338 tail : logZ = +- 0.010 insert order U test : converged: True correlation: inf iterations a 0.4997 +- 0.0099 b 0.5001 +- 0.0096 evidence: -4.5 +- 0.3 parameter values: a : 0.500 +- 0.010 b : 0.500 +- 0.010 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=2+0, resume=True, log_dir=None, backend=hdf5, vectorized=False, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=0 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=401, logz=-inf, remainder_fraction=100.0000%, Lmin=-289792.32, Lmax=-1468.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=40, ncalls=442, logz=-153246.22, remainder_fraction=100.0000%, Lmin=-152327.98, Lmax=-1468.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=80, ncalls=486, logz=-132228.95, remainder_fraction=100.0000%, Lmin=-132052.81, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=496, logz=-130333.84, remainder_fraction=100.0000%, Lmin=-129720.19, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=120, ncalls=532, logz=-118444.16, remainder_fraction=100.0000%, Lmin=-118431.44, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=160, ncalls=582, logz=-102932.16, remainder_fraction=100.0000%, Lmin=-102800.01, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=608, logz=-96577.75, remainder_fraction=100.0000%, Lmin=-96492.67, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=632, logz=-92542.85, remainder_fraction=100.0000%, Lmin=-92468.21, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=240, ncalls=683, logz=-82963.72, remainder_fraction=100.0000%, Lmin=-82950.99, Lmax=-527.92 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=280, ncalls=735, logz=-76937.28, remainder_fraction=100.0000%, Lmin=-76844.39, Lmax=-323.62 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=320, ncalls=783, logz=-70048.37, remainder_fraction=100.0000%, Lmin=-70011.52, Lmax=-323.62 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=842, logz=-62784.95, remainder_fraction=100.0000%, Lmin=-62189.47, Lmax=-323.62 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=892, logz=-55747.59, remainder_fraction=100.0000%, Lmin=-55696.70, Lmax=-5.80 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=440, ncalls=949, logz=-50847.21, remainder_fraction=100.0000%, Lmin=-50657.00, Lmax=-5.80 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=964, logz=-49491.57, remainder_fraction=100.0000%, Lmin=-49454.94, Lmax=-5.80 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=480, ncalls=1001, logz=-46205.16, remainder_fraction=100.0000%, Lmin=-46015.45, Lmax=-5.80 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=520, ncalls=1047, logz=-42109.72, remainder_fraction=100.0000%, Lmin=-42018.83, Lmax=-5.80 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=1072, logz=-39756.43, remainder_fraction=100.0000%, Lmin=-39675.83, Lmax=-5.80 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remainder_fraction=99.9670%, Lmin=-0.80, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3960, ncalls=5593, logz=-11.89, remainder_fraction=99.9331%, Lmin=-0.06, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4000, ncalls=5636, logz=-11.22, remainder_fraction=99.8702%, Lmin=0.66, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4040, ncalls=5688, logz=-10.55, remainder_fraction=99.7520%, Lmin=1.34, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4050, ncalls=5699, logz=-10.41, remainder_fraction=99.7174%, Lmin=1.45, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4080, ncalls=5734, logz=-10.00, remainder_fraction=99.5698%, Lmin=1.94, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4120, ncalls=5792, logz=-9.46, remainder_fraction=99.2931%, Lmin=2.46, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4140, ncalls=5820, logz=-9.22, remainder_fraction=99.1046%, Lmin=2.67, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4160, ncalls=5842, logz=-8.99, remainder_fraction=98.8977%, Lmin=2.91, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4200, ncalls=5890, logz=-8.54, remainder_fraction=98.2950%, Lmin=3.37, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4230, ncalls=5929, logz=-8.25, remainder_fraction=97.7108%, Lmin=3.64, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4240, ncalls=5939, logz=-8.16, remainder_fraction=97.4880%, Lmin=3.78, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4280, ncalls=5988, logz=-7.80, remainder_fraction=96.3870%, Lmin=4.10, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4320, ncalls=6039, logz=-7.48, remainder_fraction=95.1295%, Lmin=4.47, Lmax=7.34 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4360, ncalls=6086, logz=-7.19, remainder_fraction=93.4361%, Lmin=4.77, Lmax=7.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4400, ncalls=6143, logz=-6.92, remainder_fraction=91.4662%, Lmin=5.08, Lmax=7.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4410, ncalls=6159, logz=-6.85, remainder_fraction=90.8438%, Lmin=5.12, Lmax=7.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4440, ncalls=6195, logz=-6.67, remainder_fraction=88.8885%, Lmin=5.30, Lmax=7.35 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4480, ncalls=6244, logz=-6.45, remainder_fraction=86.2141%, Lmin=5.46, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4520, ncalls=6295, logz=-6.26, remainder_fraction=83.1088%, Lmin=5.64, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4560, ncalls=6358, logz=-6.08, remainder_fraction=80.1077%, Lmin=5.80, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4590, ncalls=6398, logz=-5.97, remainder_fraction=77.7070%, Lmin=5.94, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4600, ncalls=6412, logz=-5.93, remainder_fraction=76.8977%, Lmin=5.98, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4640, ncalls=6467, logz=-5.78, remainder_fraction=73.3003%, Lmin=6.12, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4680, ncalls=6522, logz=-5.66, remainder_fraction=69.6175%, Lmin=6.25, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4720, ncalls=6576, logz=-5.54, remainder_fraction=65.9193%, Lmin=6.36, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4760, ncalls=6631, logz=-5.44, remainder_fraction=62.0653%, Lmin=6.46, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4770, ncalls=6643, logz=-5.41, remainder_fraction=61.2145%, Lmin=6.48, Lmax=7.36 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4800, ncalls=6679, logz=-5.34, remainder_fraction=58.3416%, Lmin=6.55, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4840, ncalls=6732, logz=-5.26, remainder_fraction=54.5310%, Lmin=6.64, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4860, ncalls=6764, logz=-5.22, remainder_fraction=52.6550%, Lmin=6.67, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4880, ncalls=6790, logz=-5.18, remainder_fraction=50.9620%, Lmin=6.71, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4920, ncalls=6838, logz=-5.11, remainder_fraction=47.4867%, Lmin=6.76, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4950, ncalls=6887, logz=-5.06, remainder_fraction=44.9851%, Lmin=6.81, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=4960, ncalls=6900, logz=-5.05, remainder_fraction=44.1658%, Lmin=6.83, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5000, ncalls=6956, logz=-4.99, remainder_fraction=40.9914%, Lmin=6.88, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5040, ncalls=7009, logz=-4.94, remainder_fraction=37.8567%, Lmin=6.94, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5080, ncalls=7063, logz=-4.90, remainder_fraction=34.8538%, Lmin=6.98, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5120, ncalls=7117, logz=-4.85, remainder_fraction=32.0612%, Lmin=7.02, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5160, ncalls=7173, logz=-4.82, remainder_fraction=29.4734%, Lmin=7.05, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5200, ncalls=7229, logz=-4.78, remainder_fraction=27.0907%, Lmin=7.08, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5220, ncalls=7258, logz=-4.77, remainder_fraction=25.9764%, Lmin=7.10, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5240, ncalls=7280, logz=-4.75, remainder_fraction=24.8576%, Lmin=7.11, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5280, ncalls=7336, logz=-4.72, remainder_fraction=22.7461%, Lmin=7.13, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5310, ncalls=7380, logz=-4.71, remainder_fraction=21.2788%, Lmin=7.15, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5320, ncalls=7392, logz=-4.70, remainder_fraction=20.8125%, Lmin=7.15, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5360, ncalls=7444, logz=-4.68, remainder_fraction=19.0139%, Lmin=7.18, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5400, ncalls=7497, logz=-4.66, remainder_fraction=17.3812%, Lmin=7.19, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5440, ncalls=7546, logz=-4.64, remainder_fraction=15.8491%, Lmin=7.21, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5480, ncalls=7597, logz=-4.62, remainder_fraction=14.4425%, Lmin=7.23, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5490, ncalls=7611, logz=-4.62, remainder_fraction=14.1094%, Lmin=7.23, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5520, ncalls=7647, logz=-4.61, remainder_fraction=13.1570%, Lmin=7.25, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5560, ncalls=7705, logz=-4.59, remainder_fraction=11.9711%, Lmin=7.26, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5580, ncalls=7733, logz=-4.59, remainder_fraction=11.4173%, Lmin=7.26, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5600, ncalls=7757, logz=-4.58, remainder_fraction=10.8882%, Lmin=7.27, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5640, ncalls=7804, logz=-4.57, remainder_fraction=9.9042%, Lmin=7.28, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5670, ncalls=7843, logz=-4.56, remainder_fraction=9.2247%, Lmin=7.28, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5680, ncalls=7854, logz=-4.56, remainder_fraction=9.0086%, Lmin=7.28, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5720, ncalls=7902, logz=-4.55, remainder_fraction=8.1860%, Lmin=7.29, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5760, ncalls=7952, logz=-4.54, remainder_fraction=7.4348%, Lmin=7.30, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5800, ncalls=8001, logz=-4.54, remainder_fraction=6.7504%, Lmin=7.31, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5840, ncalls=8050, logz=-4.53, remainder_fraction=6.1282%, Lmin=7.31, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5880, ncalls=8109, logz=-4.52, remainder_fraction=5.5627%, Lmin=7.32, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5920, ncalls=8175, logz=-4.52, remainder_fraction=5.0455%, Lmin=7.33, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5940, ncalls=8201, logz=-4.52, remainder_fraction=4.8057%, Lmin=7.33, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=5960, ncalls=8224, logz=-4.51, remainder_fraction=4.5766%, Lmin=7.33, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6000, ncalls=8267, logz=-4.51, remainder_fraction=4.1493%, Lmin=7.33, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6030, ncalls=8312, logz=-4.51, remainder_fraction=3.8546%, Lmin=7.33, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6040, ncalls=8325, logz=-4.50, remainder_fraction=3.7614%, Lmin=7.34, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6080, ncalls=8385, logz=-4.50, remainder_fraction=3.4093%, Lmin=7.34, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6120, ncalls=8447, logz=-4.50, remainder_fraction=3.0895%, Lmin=7.34, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6160, ncalls=8505, logz=-4.49, remainder_fraction=2.7997%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6200, ncalls=8563, logz=-4.49, remainder_fraction=2.5364%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6210, ncalls=8575, logz=-4.49, remainder_fraction=2.4745%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6240, ncalls=8613, logz=-4.49, remainder_fraction=2.2979%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6280, ncalls=8662, logz=-4.49, remainder_fraction=2.0815%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6300, ncalls=8688, logz=-4.49, remainder_fraction=1.9810%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6320, ncalls=8712, logz=-4.48, remainder_fraction=1.8853%, Lmin=7.35, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6360, ncalls=8766, logz=-4.48, remainder_fraction=1.7073%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6390, ncalls=8799, logz=-4.48, remainder_fraction=1.5848%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6400, ncalls=8810, logz=-4.48, remainder_fraction=1.5459%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6440, ncalls=8865, logz=-4.48, remainder_fraction=1.3997%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6480, ncalls=8930, logz=-4.48, remainder_fraction=1.2673%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6520, ncalls=8975, logz=-4.48, remainder_fraction=1.1474%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6560, ncalls=9033, logz=-4.48, remainder_fraction=1.0388%, Lmin=7.36, Lmax=7.37 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=6570, ncalls=9046, logz=-4.48, remainder_fraction=1.0134%, Lmin=7.36, Lmax=7.37 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=7 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 9051 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -4.45 +- 0.1628 [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.47+-0.04 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.34, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.16 bs:0.16 tail:0.01 total:0.16 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. [35mDEBUG [0m ultranest:integrator.py:2647 Making corner plot ... [35mDEBUG [0m ultranest:integrator.py:2693 Making run plot ... [35mDEBUG [0m ultranest:integrator.py:2669 Making trace plot ... | |||
Passed | tests/test_samplingpath.py::test_horizontal | 0.00 | |
------------------------------Captured stdout call------------------------------ (array([0.5, 0. ]), array([1])) (array([0.5, 1. ]), array([1])) (array([0. , 0.3]), array([0])) (array([1. , 0.3]), array([0])) | |||
Passed | tests/test_samplingpath.py::test_corner | 0.00 | |
------------------------------Captured stdout call------------------------------ starting ray: [0.6 0.5] [0.4 0.5] (array([0.2, 0. ]), array([1])) (array([1., 1.]), array([0, 1])) restarting ray: [1. 1.] [-0.4 -0.5] (array([1., 1.]), array([0, 1])) (array([0.2, 0. ]), array([1])) (array([0.2, 0. ]), array([1])) (array([0. , 0.25]), array([0])) | |||
Passed | tests/test_samplingpath.py::test_wrap | 0.01 | |
No log output captured. | |||
Passed | tests/test_samplingpath.py::test_random | 0.22 | |
No log output captured. | |||
Passed | tests/test_samplingpath.py::test_forward | 1.01 | |
No log output captured. | |||
Passed | tests/test_samplingpath.py::test_samplingpath | 0.00 | |
No log output captured. | |||
Passed | tests/test_samplingpath.py::test_samplingpath_cubereflect | 0.00 | |
No log output captured. | |||
Passed | tests/test_samplingpath.py::test_samplingpath_oddcase | 0.00 | |
No log output captured. | |||
Passed | tests/test_samplingpath.py::test_reversible_gradient | 0.71 | |
------------------------------Captured stdout call------------------------------ setting seed = 84 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] chose normal [-0.17706516 0.98419913] 53 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] reflecting with [-0.51082933 0.85968215] new direction [-0.00074369 0.03999309] re-reflecting gives direction [ 0.03477044 -0.01977415] FORWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] BACKWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] setting seed = 1 reflecting at [0.49345332 0.62079968] with direction [6.48453852e-06 3.99999995e-02] chose normal [-0.14594849 -0.98929219] 33 reflecting at [0.49345332 0.62079968] with direction [6.48453852e-06 3.99999995e-02] reflecting with [-0.84015394 -0.54234801] new direction [-0.03645513 0.01646278] re-reflecting gives direction [6.48453852e-06 3.99999995e-02] FORWARD: [6.48453852e-06 3.99999995e-02] [0.49345332 0.62079968] BACKWARD: [6.48453852e-06 3.99999995e-02] [0.49345332 0.62079968] setting seed = 2 reflecting at [0.58951993 0.53010934] with direction [-0.028441 0.02812667] chose normal [-0.55268598 -0.83338959] 75 reflecting at [0.58951993 0.53010934] with direction [-0.028441 0.02812667] reflecting with [-0.38762042 -0.92181908] new direction [-0.03999471 0.00065022] re-reflecting gives direction [-0.028441 0.02812667] FORWARD: [-0.028441 0.02812667] [0.58951993 0.53010934] BACKWARD: [-0.028441 0.02812667] [0.58951993 0.53010934] setting seed = 3 reflecting at [0.18920214 0.52959253] with direction [ 0.00939036 -0.03888214] chose normal [-0.96649142 0.25669891] 45 reflecting at [0.18920214 0.52959253] with direction [ 0.00939036 -0.03888214] reflecting with [-0.98467624 0.17439239] new direction [-0.02217288 -0.03329209] re-reflecting gives direction [ 0.00939036 -0.03888214] FORWARD: [ 0.00939036 -0.03888214] [0.18920214 0.52959253] BACKWARD: [ 0.00939036 -0.03888214] [0.18920214 0.52959253] setting seed = 4 reflecting at [0.9934771 0.55358031] with direction [ 0.03949306 -0.00634806] chose normal [-0.97238131 -0.23339792] 0 reflecting at [0.9934771 0.55358031] with direction [ 0.03949306 -0.00634806] reflecting with [-0.97238131 -0.23339792] new direction [-0.03230892 -0.02358248] re-reflecting gives direction [ 0.03949306 -0.00634806] FORWARD: [ 0.03949306 -0.00634806] [0.9934771 0.55358031] BACKWARD: [ 0.03949306 -0.00634806] [0.9934771 0.55358031] setting seed = 5 reflecting at [0.56643207 0.39286012] with direction [ 0.03173046 -0.02435524] chose normal [0.31678437 0.94849758] 12 reflecting at [0.56643207 0.39286012] with direction [ 0.03173046 -0.02435524] reflecting with [-0.33575666 0.94194876] new direction [0.0091709 0.03893449] re-reflecting gives direction [ 0.03173046 -0.02435524] FORWARD: [ 0.03173046 -0.02435524] [0.56643207 0.39286012] BACKWARD: [ 0.03173046 -0.02435524] [0.56643207 0.39286012] setting seed = 6 reflecting at [0.86938756 0.54911538] with direction [-0.03790637 -0.01277133] chose normal [0.83159266 0.55538603] 69 reflecting at [0.86938756 0.54911538] with direction [-0.03790637 -0.01277133] reflecting with [ 0.43246121 -0.90165254] new direction [-0.03368751 -0.02156737] re-reflecting gives direction [-0.03790637 -0.01277133] FORWARD: [-0.03790637 -0.01277133] [0.86938756 0.54911538] BACKWARD: [-0.03790637 -0.01277133] [0.86938756 0.54911538] setting seed = 7 reflecting at [0.93312443 0.57556133] with direction [0.02306847 0.0326779 ] chose normal [-0.99882119 0.04854104] 39 reflecting at [0.93312443 0.57556133] with direction [0.02306847 0.0326779 ] reflecting with [ 0.77093646 -0.63691206] new direction [0.02773823 0.02881997] re-reflecting gives direction [0.02306847 0.0326779 ] FORWARD: [0.02306847 0.0326779 ] [0.93312443 0.57556133] BACKWARD: [0.02306847 0.0326779 ] [0.93312443 0.57556133] setting seed = 8 reflecting at [0.00974824 0.44465421] with direction [ 0.03582603 -0.01779032] chose normal [0.34627653 0.93813249] 99 reflecting at [0.00974824 0.44465421] with direction [ 0.03582603 -0.01779032] reflecting with [0.34760793 0.93763998] new direction [ 0.03876506 -0.00986257] re-reflecting gives direction [ 0.03582603 -0.01779032] FORWARD: [ 0.03582603 -0.01779032] [0.00974824 0.44465421] BACKWARD: [ 0.03582603 -0.01779032] [0.00974824 0.44465421] setting seed = 9 reflecting at [0.26300846 0.47112128] with direction [-0.03826888 0.01164015] chose normal [ 0.99593603 -0.09006347] 4 reflecting at [0.26300846 0.47112128] with direction [-0.03826888 0.01164015] reflecting with [0.97389943 0.22697994] new direction [0.02917942 0.02735986] re-reflecting gives direction [-0.03826888 0.01164015] FORWARD: [-0.03826888 0.01164015] [0.26300846 0.47112128] BACKWARD: [-0.03826888 0.01164015] [0.26300846 0.47112128] setting seed = 10 reflecting at [0.00412903 0.35451302] with direction [0.0367006 0.01590805] chose normal [ 0.22487937 -0.97438661] 90 reflecting at [0.00412903 0.35451302] with direction [0.0367006 0.01590805] reflecting with [ 0.22487937 -0.97438661] new direction [0.03996017 0.00178454] re-reflecting gives direction [0.0367006 0.01590805] FORWARD: [0.0367006 0.01590805] [0.00412903 0.35451302] BACKWARD: [0.0367006 0.01590805] [0.00412903 0.35451302] setting seed = 11 reflecting at [0.32155555 0.41865196] with direction [-0.03895091 0.0091009 ] chose normal [0.54430488 0.83888747] 16 reflecting at [0.32155555 0.41865196] with direction [-0.03895091 0.0091009 ] reflecting with [0.82811727 0.56055489] new direction [0.0060231 0.03954393] re-reflecting gives direction [-0.03895091 0.0091009 ] FORWARD: [-0.03895091 0.0091009 ] [0.32155555 0.41865196] BACKWARD: [-0.03895091 0.0091009 ] [0.32155555 0.41865196] setting seed = 12 reflecting at [0.35995727 0.3150146 ] with direction [0.03186583 0.02417786] chose normal [-0.99011844 0.14023365] 82 reflecting at [0.35995727 0.3150146 ] with direction [0.03186583 0.02417786] reflecting with [-0.86634575 0.49944472] new direction [0.00495484 0.03969193] re-reflecting gives direction [0.03186583 0.02417786] FORWARD: [0.03186583 0.02417786] [0.35995727 0.3150146 ] BACKWARD: [0.03186583 0.02417786] [0.35995727 0.3150146 ] setting seed = 13 reflecting at [0.73099081 0.54090516] with direction [0.02100007 0.03404404] chose normal [-0.98685102 0.16163249] 5 reflecting at [0.73099081 0.54090516] with direction [0.02100007 0.03404404] reflecting with [-0.93229687 0.36169401] new direction [0.00745422 0.0392993 ] re-reflecting gives direction [0.02100007 0.03404404] FORWARD: [0.02100007 0.03404404] [0.73099081 0.54090516] BACKWARD: [0.02100007 0.03404404] [0.73099081 0.54090516] setting seed = 14 reflecting at [0.31165599 0.36756094] with direction [-0.02635429 0.03009072] chose normal [ 0.82456261 -0.56577072] 96 reflecting at [0.31165599 0.36756094] with direction [-0.02635429 0.03009072] reflecting with [0.77339836 0.63392033] new direction [-0.02433225 0.0317481 ] re-reflecting gives direction [-0.02635429 0.03009072] FORWARD: [-0.02635429 0.03009072] [0.31165599 0.36756094] BACKWARD: [-0.02635429 0.03009072] [0.31165599 0.36756094] setting seed = 15 reflecting at [0.02715254 0.60855026] with direction [-0.03253657 -0.0232674 ] chose normal [ 0.98353428 -0.18072169] 52 reflecting at [0.02715254 0.60855026] with direction [-0.03253657 -0.0232674 ] reflecting with [ 0.95341068 -0.30167545] new direction [ 0.01323002 -0.03774873] re-reflecting gives direction [-0.03253657 -0.0232674 ] FORWARD: [-0.03253657 -0.0232674 ] [0.02715254 0.60855026] BACKWARD: [-0.03253657 -0.0232674 ] [0.02715254 0.60855026] setting seed = 16 reflecting at [0.23486289 0.63976911] with direction [-0.03505464 -0.01926583] chose normal [0.98410666 0.17757839] 28 reflecting at [0.23486289 0.63976911] with direction [-0.03505464 -0.01926583] reflecting with [ 0.93475612 -0.35529003] new direction [ 0.01340794 -0.0376859 ] re-reflecting gives direction [-0.03505464 -0.01926583] FORWARD: [-0.03505464 -0.01926583] [0.23486289 0.63976911] BACKWARD: [-0.03505464 -0.01926583] [0.23486289 0.63976911] setting seed = 17 reflecting at [0.15079862 0.63070329] with direction [-0.02987327 -0.02660052] chose normal [0.77877968 0.62729755] 76 reflecting at [0.15079862 0.63070329] with direction [-0.02987327 -0.02660052] reflecting with [ 0.82081006 -0.57120123] new direction [-0.01456347 -0.0372546 ] re-reflecting gives direction [-0.02987327 -0.02660052] FORWARD: [-0.02987327 -0.02660052] [0.15079862 0.63070329] BACKWARD: [-0.02987327 -0.02660052] [0.15079862 0.63070329] setting seed = 18 reflecting at [0.31819943 0.33216186] with direction [0.03839271 0.01122497] chose normal [-0.33803901 -0.9411321 ] 41 reflecting at [0.31819943 0.33216186] with direction [0.03839271 0.01122497] reflecting with [-0.34524316 0.93851327] new direction [0.03651456 0.01633055] re-reflecting gives direction [0.03839271 0.01122497] FORWARD: [0.03839271 0.01122497] [0.31819943 0.33216186] BACKWARD: [0.03839271 0.01122497] [0.31819943 0.33216186] setting seed = 19 reflecting at [0.06335039 0.66864627] with direction [-0.00412734 -0.03978649] chose normal [0.93844564 0.34542696] 79 reflecting at [0.06335039 0.66864627] with direction [-0.00412734 -0.03978649] reflecting with [ 0.99641622 -0.08458558] new direction [-0.00263833 -0.0399129 ] re-reflecting gives direction [-0.00412734 -0.03978649] FORWARD: [-0.00412734 -0.03978649] [0.06335039 0.66864627] BACKWARD: [-0.00412734 -0.03978649] [0.06335039 0.66864627] setting seed = 20 reflecting at [0.6289178 0.59036263] with direction [0.03621666 0.01698097] chose normal [ 0.02238176 -0.9997495 ] 63 reflecting at [0.6289178 0.59036263] with direction [0.03621666 0.01698097] reflecting with [-0.98569607 0.16853264] new direction [-0.0285175 0.02804911] re-reflecting gives direction [0.03621666 0.01698097] FORWARD: [0.03621666 0.01698097] [0.6289178 0.59036263] BACKWARD: [0.03621666 0.01698097] [0.6289178 0.59036263] setting seed = 21 reflecting at [0.0479965 0.3622258] with direction [ 0.01189335 -0.03819094] chose normal [0.69255841 0.7213618 ] 45 reflecting at [0.0479965 0.3622258] with direction [ 0.01189335 -0.03819094] reflecting with [0.64446979 0.76462977] new direction [ 0.03965328 -0.00525524] re-reflecting gives direction [ 0.01189335 -0.03819094] FORWARD: [ 0.01189335 -0.03819094] [0.0479965 0.3622258] BACKWARD: [ 0.01189335 -0.03819094] [0.0479965 0.3622258] setting seed = 22 reflecting at [0.45364136 0.3073653 ] with direction [-0.03917472 -0.00808342] chose normal [0.73205365 0.68124698] 97 reflecting at [0.45364136 0.3073653 ] with direction [-0.03917472 -0.00808342] reflecting with [-0.09378428 0.99559254] new direction [-0.03999511 0.00062567] re-reflecting gives direction [-0.03917472 -0.00808342] FORWARD: [-0.03917472 -0.00808342] [0.45364136 0.3073653 ] BACKWARD: [-0.03917472 -0.00808342] [0.45364136 0.3073653 ] setting seed = 23 reflecting at [0.13591686 0.30336076] with direction [-0.00025999 0.03999916] setting seed = 24 reflecting at [0.47619867 0.49486522] with direction [-0.02598612 -0.03040923] chose normal [-0.53400133 0.84548364] 50 reflecting at [0.47619867 0.49486522] with direction [-0.02598612 -0.03040923] reflecting with [0.94624486 0.32345119] new direction [ 0.0391631 -0.00813953] re-reflecting gives direction [-0.02598612 -0.03040923] FORWARD: [-0.02598612 -0.03040923] [0.47619867 0.49486522] BACKWARD: [-0.02598612 -0.03040923] [0.47619867 0.49486522] setting seed = 25 reflecting at [0.37122823 0.26399608] with direction [0.03256293 0.02323049] chose normal [-0.97667717 0.21471306] 60 reflecting at [0.37122823 0.26399608] with direction [0.03256293 0.02323049] reflecting with [-0.63178483 0.77514381] new direction [0.02932087 0.02720821] re-reflecting gives direction [0.03256293 0.02323049] FORWARD: [0.03256293 0.02323049] [0.37122823 0.26399608] BACKWARD: [0.03256293 0.02323049] [0.37122823 0.26399608] setting seed = 26 reflecting at [0.39378009 0.46705711] with direction [ 0.03979792 -0.0040157 ] chose normal [-0.50091154 0.86549848] 85 reflecting at [0.39378009 0.46705711] with direction [ 0.03979792 -0.0040157 ] reflecting with [-0.85384138 0.52053328] new direction [-0.02180062 0.03353704] re-reflecting gives direction [ 0.03979792 -0.0040157 ] FORWARD: [ 0.03979792 -0.0040157 ] [0.39378009 0.46705711] BACKWARD: [ 0.03979792 -0.0040157 ] [0.39378009 0.46705711] setting seed = 27 reflecting at [0.68895564 0.43889187] with direction [-0.00127249 0.03997975] chose normal [ 0.92407929 -0.38220081] 25 reflecting at [0.68895564 0.43889187] with direction [-0.00127249 0.03997975] reflecting with [-0.97547221 -0.22012263] new direction [-0.01602001 0.03665187] re-reflecting gives direction [-0.00127249 0.03997975] FORWARD: [-0.00127249 0.03997975] [0.68895564 0.43889187] BACKWARD: [-0.00127249 0.03997975] [0.68895564 0.43889187] setting seed = 28 reflecting at [0.93475923 0.56225156] with direction [-0.03108561 0.02517309] chose normal [ 0.25028455 -0.96817232] 53 reflecting at [0.93475923 0.56225156] with direction [-0.03108561 0.02517309] reflecting with [-0.0753835 -0.99715462] new direction [-0.03451679 -0.02021364] re-reflecting gives direction [-0.03108561 0.02517309] FORWARD: [-0.03108561 0.02517309] [0.93475923 0.56225156] BACKWARD: [-0.03108561 0.02517309] [0.93475923 0.56225156] setting seed = 29 reflecting at [0.15001162 0.39313651] with direction [-0.02702503 0.02948979] chose normal [ 0.93787043 -0.34698568] 15 reflecting at [0.15001162 0.39313651] with direction [-0.02702503 0.02948979] reflecting with [0.8970119 0.44200639] new direction [-0.00691923 0.03939701] re-reflecting gives direction [-0.02702503 0.02948979] FORWARD: [-0.02702503 0.02948979] [0.15001162 0.39313651] BACKWARD: [-0.02702503 0.02948979] [0.15001162 0.39313651] setting seed = 30 reflecting at [0.79559868 0.6204715 ] with direction [-0.01106701 0.03843854] chose normal [-0.94320997 -0.33219716] 57 reflecting at [0.79559868 0.6204715 ] with direction [-0.01106701 0.03843854] reflecting with [-0.53412191 -0.84540746] new direction [-0.03946637 -0.00651194] re-reflecting gives direction [-0.01106701 0.03843854] FORWARD: [-0.01106701 0.03843854] [0.79559868 0.6204715 ] BACKWARD: [-0.01106701 0.03843854] [0.79559868 0.6204715 ] setting seed = 31 reflecting at [0.70465924 0.58796209] with direction [0.00622801 0.03951217] chose normal [ 0.91849248 -0.39543844] 40 reflecting at [0.70465924 0.58796209] with direction [0.00622801 0.03951217] reflecting with [-0.99751744 -0.0704199 ] new direction [-0.01171731 0.03824532] re-reflecting gives direction [0.00622801 0.03951217] FORWARD: [0.00622801 0.03951217] [0.70465924 0.58796209] BACKWARD: [0.00622801 0.03951217] [0.70465924 0.58796209] setting seed = 32 reflecting at [0.41358712 0.44153528] with direction [ 0.02149569 -0.0337333 ] chose normal [-0.86603501 0.49998337] 44 reflecting at [0.41358712 0.44153528] with direction [ 0.02149569 -0.0337333 ] reflecting with [0.78359729 0.6212691 ] new direction [ 0.02794233 -0.02862213] re-reflecting gives direction [ 0.02149569 -0.0337333 ] FORWARD: [ 0.02149569 -0.0337333 ] [0.41358712 0.44153528] BACKWARD: [ 0.02149569 -0.0337333 ] [0.41358712 0.44153528] setting seed = 33 reflecting at [0.18839637 0.583353 ] with direction [0.00876515 0.03902784] chose normal [ 0.94116632 -0.33794371] 14 reflecting at [0.18839637 0.583353 ] with direction [0.00876515 0.03902784] reflecting with [ 0.41089806 -0.91168129] new direction [ 0.03504567 -0.01928214] re-reflecting gives direction [0.00876515 0.03902784] FORWARD: [0.00876515 0.03902784] [0.18839637 0.583353 ] BACKWARD: [0.00876515 0.03902784] [0.18839637 0.583353 ] setting seed = 34 reflecting at [0.69837732 0.63815456] with direction [0.0248712 0.03132767] chose normal [-0.9662808 -0.2574906] 59 reflecting at [0.69837732 0.63815456] with direction [0.0248712 0.03132767] reflecting with [-0.99996226 -0.00868732] new direction [-0.02541174 0.03089083] re-reflecting gives direction [0.0248712 0.03132767] FORWARD: [0.0248712 0.03132767] [0.69837732 0.63815456] BACKWARD: [0.0248712 0.03132767] [0.69837732 0.63815456] setting seed = 35 reflecting at [0.65608784 0.48141142] with direction [-0.03633999 -0.01671541] chose normal [ 0.81909097 -0.57366365] 13 reflecting at [0.65608784 0.48141142] with direction [-0.03633999 -0.01671541] reflecting with [0.99064996 0.13642818] new direction [ 0.03950549 -0.00627028] re-reflecting gives direction [-0.03633999 -0.01671541] FORWARD: [-0.03633999 -0.01671541] [0.65608784 0.48141142] BACKWARD: [-0.03633999 -0.01671541] [0.65608784 0.48141142] setting seed = 36 reflecting at [0.61006515 0.4226952 ] with direction [-0.00656845 0.03945701] chose normal [ 0.99395085 -0.10982581] 7 reflecting at [0.61006515 0.4226952 ] with direction [-0.00656845 0.03945701] reflecting with [-0.98326229 -0.18219571] new direction [-0.00800478 0.03919086] re-reflecting gives direction [-0.00656845 0.03945701] FORWARD: [-0.00656845 0.03945701] [0.61006515 0.4226952 ] BACKWARD: [-0.00656845 0.03945701] [0.61006515 0.4226952 ] setting seed = 37 reflecting at [0.74783048 0.44838258] with direction [-0.03830604 -0.01151726] chose normal [0.24749873 0.96888822] 9 reflecting at [0.74783048 0.44838258] with direction [-0.03830604 -0.01151726] reflecting with [0.9968224 0.07965612] new direction [ 0.03964894 -0.00528788] re-reflecting gives direction [-0.03830604 -0.01151726] FORWARD: [-0.03830604 -0.01151726] [0.74783048 0.44838258] BACKWARD: [-0.03830604 -0.01151726] [0.74783048 0.44838258] setting seed = 38 reflecting at [0.62632487 0.50336921] with direction [ 0.00520512 -0.03965989] chose normal [-0.47920534 0.87770282] 91 reflecting at [0.62632487 0.50336921] with direction [ 0.00520512 -0.03965989] reflecting with [0.07106544 0.99747166] new direction [0.01077519 0.03852136] re-reflecting gives direction [ 0.00520512 -0.03965989] FORWARD: [ 0.00520512 -0.03965989] [0.62632487 0.50336921] BACKWARD: [ 0.00520512 -0.03965989] [0.62632487 0.50336921] setting seed = 39 reflecting at [0.37707531 0.58289575] with direction [0.03440183 0.02040867] chose normal [-0.96803752 0.25080543] 26 reflecting at [0.37707531 0.58289575] with direction [0.03440183 0.02040867] reflecting with [ 0.48195217 -0.87619753] new direction [0.03565683 0.01812707] re-reflecting gives direction [0.03440183 0.02040867] FORWARD: [0.03440183 0.02040867] [0.37707531 0.58289575] BACKWARD: [0.03440183 0.02040867] [0.37707531 0.58289575] setting seed = 40 reflecting at [0.40535643 0.66852681] with direction [-0.0084009 -0.03910786] chose normal [ 0.99762991 -0.06880816] 34 reflecting at [0.40535643 0.66852681] with direction [-0.0084009 -0.03910786] reflecting with [ 0.98422636 -0.17691375] new direction [-0.00574414 -0.03958541] re-reflecting gives direction [-0.0084009 -0.03910786] FORWARD: [-0.0084009 -0.03910786] [0.40535643 0.66852681] BACKWARD: [-0.0084009 -0.03910786] [0.40535643 0.66852681] setting seed = 41 reflecting at [0.4304033 0.37361026] with direction [ 0.02446896 -0.03164285] chose normal [-0.39185582 0.92002664] 4 reflecting at [0.4304033 0.37361026] with direction [ 0.02446896 -0.03164285] reflecting with [-0.80640044 0.59136988] new direction [-0.03753422 0.01382688] re-reflecting gives direction [ 0.02446896 -0.03164285] FORWARD: [ 0.02446896 -0.03164285] [0.4304033 0.37361026] BACKWARD: [ 0.02446896 -0.03164285] [0.4304033 0.37361026] setting seed = 42 reflecting at [0.78988169 0.54673494] with direction [-0.01964246 0.034845 ] chose normal [0.95525297 0.29579006] 28 reflecting at [0.78988169 0.54673494] with direction [-0.01964246 0.034845 ] reflecting with [-0.70398882 -0.71021105] new direction [-0.03501649 0.01933508] re-reflecting gives direction [-0.01964246 0.034845 ] FORWARD: [-0.01964246 0.034845 ] [0.78988169 0.54673494] BACKWARD: [-0.01964246 0.034845 ] [0.78988169 0.54673494] setting seed = 43 reflecting at [0.33809302 0.34038204] with direction [-0.03061347 -0.0257452 ] chose normal [-0.59139425 0.80638257] 29 reflecting at [0.33809302 0.34038204] with direction [-0.03061347 -0.0257452 ] reflecting with [-0.63872083 0.76943856] new direction [-0.03094035 -0.02535142] re-reflecting gives direction [-0.03061347 -0.0257452 ] FORWARD: [-0.03061347 -0.0257452 ] [0.33809302 0.34038204] BACKWARD: [-0.03061347 -0.0257452 ] [0.33809302 0.34038204] setting seed = 44 reflecting at [0.56836523 0.39005034] with direction [-0.01068318 -0.03854698] chose normal [ 0.99893451 -0.04615032] 29 reflecting at [0.56836523 0.39005034] with direction [-0.01068318 -0.03854698] reflecting with [-0.69018106 0.72363672] new direction [-0.03900915 -0.00884794] re-reflecting gives direction [-0.01068318 -0.03854698] FORWARD: [-0.01068318 -0.03854698] [0.56836523 0.39005034] BACKWARD: [-0.01068318 -0.03854698] [0.56836523 0.39005034] setting seed = 45 reflecting at [0.94160314 0.52051464] with direction [-0.0399819 -0.00120333] chose normal [ 0.06446741 -0.99791981] 84 reflecting at [0.94160314 0.52051464] with direction [-0.0399819 -0.00120333] reflecting with [ 0.06446741 -0.99791981] new direction [-0.03980439 -0.00395101] re-reflecting gives direction [-0.0399819 -0.00120333] FORWARD: [-0.0399819 -0.00120333] [0.94160314 0.52051464] BACKWARD: [-0.0399819 -0.00120333] [0.94160314 0.52051464] setting seed = 46 reflecting at [0.25975823 0.44354413] with direction [-0.02164327 0.0336388 ] chose normal [ 0.9478891 -0.31860046] 70 reflecting at [0.25975823 0.44354413] with direction [-0.02164327 0.0336388 ] reflecting with [0.99984603 0.01754771] new direction [0.02044956 0.03437754] re-reflecting gives direction [-0.02164327 0.0336388 ] FORWARD: [-0.02164327 0.0336388 ] [0.25975823 0.44354413] BACKWARD: [-0.02164327 0.0336388 ] [0.25975823 0.44354413] setting seed = 47 reflecting at [0.01926161 0.63431919] with direction [-0.03559232 -0.0182534 ] chose normal [0.74369889 0.66851474] 81 reflecting at [0.01926161 0.63431919] with direction [-0.03559232 -0.0182534 ] reflecting with [ 0.9436164 -0.33104091] new direction [ 0.0163875 -0.03648904] re-reflecting gives direction [-0.03559232 -0.0182534 ] FORWARD: [-0.03559232 -0.0182534 ] [0.01926161 0.63431919] BACKWARD: [-0.03559232 -0.0182534 ] [0.01926161 0.63431919] setting seed = 48 reflecting at [0.14141263 0.72381215] with direction [ 0.01008992 -0.03870651] setting seed = 49 reflecting at [0.16156443 0.4674537 ] with direction [-0.02888115 -0.02767453] chose normal [ 0.78315843 -0.62182223] 61 reflecting at [0.16156443 0.4674537 ] with direction [-0.02888115 -0.02767453] reflecting with [0.98231877 0.187216 ] new direction [ 0.0370356 -0.01511173] re-reflecting gives direction [-0.02888115 -0.02767453] FORWARD: [-0.02888115 -0.02767453] [0.16156443 0.4674537 ] BACKWARD: [-0.02888115 -0.02767453] [0.16156443 0.4674537 ] setting seed = 50 reflecting at [0.79282295 0.55686971] with direction [0.00526153 0.03965244] chose normal [-0.9091523 -0.4164638] 59 reflecting at [0.79282295 0.55686971] with direction [0.00526153 0.03965244] reflecting with [-0.95815198 -0.28626 ] new direction [-0.02615101 0.03026755] re-reflecting gives direction [0.00526153 0.03965244] FORWARD: [0.00526153 0.03965244] [0.79282295 0.55686971] BACKWARD: [0.00526153 0.03965244] [0.79282295 0.55686971] setting seed = 51 reflecting at [0.62787959 0.51878844] with direction [0.02807295 0.02849403] chose normal [-0.99167671 -0.12875285] 11 reflecting at [0.62787959 0.51878844] with direction [0.02807295 0.02849403] reflecting with [-0.91529383 0.4027868 ] new direction [0.00204569 0.03994765] re-reflecting gives direction [0.02807295 0.02849403] FORWARD: [0.02807295 0.02849403] [0.62787959 0.51878844] BACKWARD: [0.02807295 0.02849403] [0.62787959 0.51878844] setting seed = 52 reflecting at [0.10765197 0.43679951] with direction [-0.03566072 -0.01811941] chose normal [0.97430448 0.22523493] 14 reflecting at [0.10765197 0.43679951] with direction [-0.03566072 -0.01811941] reflecting with [0.49373504 0.86961239] new direction [-0.00271496 0.03990776] re-reflecting gives direction [-0.03566072 -0.01811941] FORWARD: [-0.03566072 -0.01811941] [0.10765197 0.43679951] BACKWARD: [-0.03566072 -0.01811941] [0.10765197 0.43679951] setting seed = 53 reflecting at [0.38071412 0.62351758] with direction [-0.01441546 -0.03731212] chose normal [-0.78010783 0.62564509] 68 reflecting at [0.38071412 0.62351758] with direction [-0.01441546 -0.03731212] reflecting with [ 0.99116492 -0.13263523] new direction [ 0.00409791 -0.03978954] re-reflecting gives direction [-0.01441546 -0.03731212] FORWARD: [-0.01441546 -0.03731212] [0.38071412 0.62351758] BACKWARD: [-0.01441546 -0.03731212] [0.38071412 0.62351758] setting seed = 54 reflecting at [0.35419835 0.39601134] with direction [-0.03646926 -0.01643148] chose normal [0.97346802 0.2288231 ] 2 reflecting at [0.35419835 0.39601134] with direction [-0.03646926 -0.01643148] reflecting with [ 0.89562093 -0.44481812] new direction [ 0.00894519 -0.03898697] re-reflecting gives direction [-0.03646926 -0.01643148] FORWARD: [-0.03646926 -0.01643148] [0.35419835 0.39601134] BACKWARD: [-0.03646926 -0.01643148] [0.35419835 0.39601134] setting seed = 55 reflecting at [0.41253863 0.54222452] with direction [-0.00327261 -0.0398659 ] chose normal [0.7228596 0.69099493] 3 reflecting at [0.41253863 0.54222452] with direction [-0.00327261 -0.0398659 ] reflecting with [-0.98267299 0.18534775] new direction [-0.01147429 -0.03831893] re-reflecting gives direction [-0.00327261 -0.0398659 ] FORWARD: [-0.00327261 -0.0398659 ] [0.41253863 0.54222452] BACKWARD: [-0.00327261 -0.0398659 ] [0.41253863 0.54222452] setting seed = 56 reflecting at [-0.00082259 0.55972911] with direction [ 0.02032516 -0.03445124] chose normal [0.6437137 0.7652664] 92 reflecting at [-0.00082259 0.55972911] with direction [ 0.02032516 -0.03445124] reflecting with [0.6437137 0.7652664] new direction [ 0.03742321 -0.01412455] re-reflecting gives direction [ 0.02032516 -0.03445124] FORWARD: [ 0.02032516 -0.03445124] [-0.00082259 0.55972911] BACKWARD: [ 0.02032516 -0.03445124] [-0.00082259 0.55972911] setting seed = 57 reflecting at [0.32852629 0.48443255] with direction [ 0.03482865 -0.01967144] chose normal [-0.9653418 -0.26098892] 66 reflecting at [0.32852629 0.48443255] with direction [ 0.03482865 -0.01967144] reflecting with [-0.95158108 -0.30739787] new direction [-0.01673815 -0.03632952] re-reflecting gives direction [ 0.03482865 -0.01967144] FORWARD: [ 0.03482865 -0.01967144] [0.32852629 0.48443255] BACKWARD: [ 0.03482865 -0.01967144] [0.32852629 0.48443255] setting seed = 58 reflecting at [0.00831403 0.22576864] with direction [0.03708157 0.01499858] setting seed = 59 reflecting at [0.55842175 0.63618532] with direction [-0.03817546 -0.01194295] chose normal [ 0.96677775 -0.25561844] 29 reflecting at [0.55842175 0.63618532] with direction [-0.03817546 -0.01194295] reflecting with [ 0.9754194 -0.22035653] new direction [ 0.02933405 -0.027194 ] re-reflecting gives direction [-0.03817546 -0.01194295] FORWARD: [-0.03817546 -0.01194295] [0.55842175 0.63618532] BACKWARD: [-0.03817546 -0.01194295] [0.55842175 0.63618532] setting seed = 60 reflecting at [0.30258664 0.49076018] with direction [ 0.0205427 -0.03432197] chose normal [-0.99186614 -0.12728533] 21 reflecting at [0.30258664 0.49076018] with direction [ 0.0205427 -0.03432197] reflecting with [0.11689192 0.99314464] new direction [0.02795024 0.02861441] re-reflecting gives direction [ 0.0205427 -0.03432197] FORWARD: [ 0.0205427 -0.03432197] [0.30258664 0.49076018] BACKWARD: [ 0.0205427 -0.03432197] [0.30258664 0.49076018] setting seed = 61 reflecting at [0.35821533 0.55032466] with direction [ 0.02436953 -0.03171949] chose normal [-0.96739827 -0.25325991] 26 reflecting at [0.35821533 0.55032466] with direction [ 0.02436953 -0.03171949] reflecting with [-0.96012904 -0.2795572 ] new direction [-0.00353274 -0.03984369] re-reflecting gives direction [ 0.02436953 -0.03171949] FORWARD: [ 0.02436953 -0.03171949] [0.35821533 0.55032466] BACKWARD: [ 0.02436953 -0.03171949] [0.35821533 0.55032466] setting seed = 62 reflecting at [0.23626136 0.3035377 ] with direction [-0.03993416 -0.00229416] chose normal [0.93863157 0.34492141] 54 reflecting at [0.23626136 0.3035377 ] with direction [-0.03993416 -0.00229416] reflecting with [0.98471485 0.17417424] new direction [0.03829817 0.0115434 ] re-reflecting gives direction [-0.03993416 -0.00229416] FORWARD: [-0.03993416 -0.00229416] [0.23626136 0.3035377 ] BACKWARD: [-0.03993416 -0.00229416] [0.23626136 0.3035377 ] setting seed = 63 reflecting at [0.77738168 0.40200899] with direction [ 0.02915488 -0.027386 ] chose normal [-0.99656293 0.08283919] 19 reflecting at [0.77738168 0.40200899] with direction [ 0.02915488 -0.027386 ] reflecting with [-0.99966777 -0.02577498] new direction [-0.02770486 -0.02885205] re-reflecting gives direction [ 0.02915488 -0.027386 ] FORWARD: [ 0.02915488 -0.027386 ] [0.77738168 0.40200899] BACKWARD: [ 0.02915488 -0.027386 ] [0.77738168 0.40200899] setting seed = 64 reflecting at [0.00700152 0.5434836 ] with direction [ 0.03157176 -0.02456061] chose normal [0.0269266 0.99963741] 88 reflecting at [0.00700152 0.5434836 ] with direction [ 0.03157176 -0.02456061] reflecting with [0.16834631 0.98572791] new direction [0.0379336 0.01269023] re-reflecting gives direction [ 0.03157176 -0.02456061] FORWARD: [ 0.03157176 -0.02456061] [0.00700152 0.5434836 ] BACKWARD: [ 0.03157176 -0.02456061] [0.00700152 0.5434836 ] setting seed = 65 reflecting at [0.23297922 0.47284723] with direction [-0.02999187 0.02646673] chose normal [ 0.87714796 -0.48022022] 19 reflecting at [0.23297922 0.47284723] with direction [-0.02999187 0.02646673] reflecting with [ 0.99603093 -0.08900784] new direction [0.03420944 0.02072954] re-reflecting gives direction [-0.02999187 0.02646673] FORWARD: [-0.02999187 0.02646673] [0.23297922 0.47284723] BACKWARD: [-0.02999187 0.02646673] [0.23297922 0.47284723] setting seed = 66 reflecting at [0.63307038 0.58558882] with direction [0.03311318 0.02243919] chose normal [ 0.37536664 -0.92687641] 71 reflecting at [0.63307038 0.58558882] with direction [0.03311318 0.02243919] reflecting with [-0.94506677 0.32687734] new direction [-0.0121731 0.0381027] re-reflecting gives direction [0.03311318 0.02243919] FORWARD: [0.03311318 0.02243919] [0.63307038 0.58558882] BACKWARD: [0.03311318 0.02243919] [0.63307038 0.58558882] setting seed = 67 reflecting at [0.11399496 0.36469248] with direction [-0.031706 -0.02438707] chose normal [0.98377071 0.17943018] 38 reflecting at [0.11399496 0.36469248] with direction [-0.031706 -0.02438707] reflecting with [0.95209698 0.30579625] new direction [ 0.03997674 -0.00136388] re-reflecting gives direction [-0.031706 -0.02438707] FORWARD: [-0.031706 -0.02438707] [0.11399496 0.36469248] BACKWARD: [-0.031706 -0.02438707] [0.11399496 0.36469248] setting seed = 68 reflecting at [0.85336104 0.43151834] with direction [0.03964926 0.00528548] chose normal [-0.79459132 0.60714466] 17 reflecting at [0.85336104 0.43151834] with direction [0.03964926 0.00528548] reflecting with [-0.43881146 0.89857916] new direction [0.0285481 0.02801796] re-reflecting gives direction [0.03964926 0.00528548] FORWARD: [0.03964926 0.00528548] [0.85336104 0.43151834] BACKWARD: [0.03964926 0.00528548] [0.85336104 0.43151834] setting seed = 69 reflecting at [0.34957318 0.4747182 ] with direction [0.0381706 0.01195847] chose normal [-0.7961656 -0.60507879] 1 reflecting at [0.34957318 0.4747182 ] with direction [0.0381706 0.01195847] reflecting with [-0.86697568 -0.49835046] new direction [-0.02954452 -0.02696519] re-reflecting gives direction [0.0381706 0.01195847] FORWARD: [0.0381706 0.01195847] [0.34957318 0.4747182 ] BACKWARD: [0.0381706 0.01195847] [0.34957318 0.4747182 ] setting seed = 70 reflecting at [0.03434818 0.6149331 ] with direction [0.0266774 0.02980464] chose normal [ 0.39947727 -0.9167431 ] 42 reflecting at [0.03434818 0.6149331 ] with direction [0.0266774 0.02980464] reflecting with [ 0.6826168 -0.73077651] new direction [0.03155141 0.02458676] re-reflecting gives direction [0.0266774 0.02980464] FORWARD: [0.0266774 0.02980464] [0.03434818 0.6149331 ] BACKWARD: [0.0266774 0.02980464] [0.03434818 0.6149331 ] setting seed = 71 reflecting at [0.3301237 0.63863365] with direction [-0.00888267 0.03900126] chose normal [-0.97291035 -0.23118274] 69 reflecting at [0.3301237 0.63863365] with direction [-0.00888267 0.03900126] reflecting with [-0.49751035 -0.86745804] new direction [-0.03814895 -0.01202737] re-reflecting gives direction [-0.00888267 0.03900126] FORWARD: [-0.00888267 0.03900126] [0.3301237 0.63863365] BACKWARD: [-0.00888267 0.03900126] [0.3301237 0.63863365] setting seed = 72 reflecting at [0.56607085 0.38288097] with direction [-0.03933418 -0.00726789] chose normal [ 0.99936155 -0.03572801] 44 reflecting at [0.56607085 0.38288097] with direction [-0.03933418 -0.00726789] reflecting with [0.20311685 0.97915451] new direction [-0.03319769 0.02231398] re-reflecting gives direction [-0.03933418 -0.00726789] FORWARD: [-0.03933418 -0.00726789] [0.56607085 0.38288097] BACKWARD: [-0.03933418 -0.00726789] [0.56607085 0.38288097] setting seed = 73 reflecting at [0.13597885 0.63503832] with direction [-0.03999972 0.0001487 ] chose normal [ 0.95068267 -0.31016523] 56 reflecting at [0.13597885 0.63503832] with direction [-0.03999972 0.0001487 ] reflecting with [ 0.98237383 -0.18692688] new direction [ 0.03725902 -0.01455216] re-reflecting gives direction [-0.03999972 0.0001487 ] FORWARD: [-0.03999972 0.0001487 ] [0.13597885 0.63503832] BACKWARD: [-0.03999972 0.0001487 ] [0.13597885 0.63503832] setting seed = 74 reflecting at [0.05551036 0.43775811] with direction [0.03895671 0.00907606] chose normal [-0.96711996 0.25432065] 26 reflecting at [0.05551036 0.43775811] with direction [0.03895671 0.00907606] reflecting with [-0.28345858 0.95898448] new direction [0.0376308 0.01356183] re-reflecting gives direction [0.03895671 0.00907606] FORWARD: [0.03895671 0.00907606] [0.05551036 0.43775811] BACKWARD: [0.03895671 0.00907606] [0.05551036 0.43775811] setting seed = 75 reflecting at [0.50973295 0.32522409] with direction [-0.02789929 0.02866409] chose normal [0.96607282 0.25826984] 98 reflecting at [0.50973295 0.32522409] with direction [-0.02789929 0.02866409] reflecting with [0.85293874 0.52201103] new direction [-0.01283057 0.03788636] re-reflecting gives direction [-0.02789929 0.02866409] FORWARD: [-0.02789929 0.02866409] [0.50973295 0.32522409] BACKWARD: [-0.02789929 0.02866409] [0.50973295 0.32522409] setting seed = 76 reflecting at [0.32690662 0.39635018] with direction [-0.02471798 -0.03144871] chose normal [0.99980546 0.01972428] 96 reflecting at [0.32690662 0.39635018] with direction [-0.02471798 -0.03144871] reflecting with [ 0.99668345 -0.08137624] new direction [ 0.01928923 -0.03504177] re-reflecting gives direction [-0.02471798 -0.03144871] FORWARD: [-0.02471798 -0.03144871] [0.32690662 0.39635018] BACKWARD: [-0.02471798 -0.03144871] [0.32690662 0.39635018] setting seed = 77 reflecting at [0.159784 0.66828224] with direction [-0.03865662 -0.0102794 ] chose normal [0.99421477 0.10741039] 67 reflecting at [0.159784 0.66828224] with direction [-0.03865662 -0.0102794 ] reflecting with [ 0.79437479 -0.60742794] new direction [ 0.00021031 -0.03999945] re-reflecting gives direction [-0.03865662 -0.0102794 ] FORWARD: [-0.03865662 -0.0102794 ] [0.159784 0.66828224] BACKWARD: [-0.03865662 -0.0102794 ] [0.159784 0.66828224] setting seed = 78 reflecting at [0.20239385 0.43885819] with direction [-0.03864408 0.01032644] chose normal [-0.00914844 -0.99995815] 42 reflecting at [0.20239385 0.43885819] with direction [-0.03864408 0.01032644] reflecting with [0.81401512 0.58084368] new direction [0.00280365 0.03990162] re-reflecting gives direction [-0.03864408 0.01032644] FORWARD: [-0.03864408 0.01032644] [0.20239385 0.43885819] BACKWARD: [-0.03864408 0.01032644] [0.20239385 0.43885819] setting seed = 79 reflecting at [0.02295645 0.52977859] with direction [ 0.01690173 -0.03625371] chose normal [0.11595433 0.99325455] 54 reflecting at [0.02295645 0.52977859] with direction [ 0.01690173 -0.03625371] reflecting with [-0.11517722 0.99334496] new direction [0.00815767 0.03915932] re-reflecting gives direction [ 0.01690173 -0.03625371] FORWARD: [ 0.01690173 -0.03625371] [0.02295645 0.52977859] BACKWARD: [ 0.01690173 -0.03625371] [0.02295645 0.52977859] setting seed = 80 reflecting at [0.37096745 0.70643199] with direction [ 0.00949935 -0.03885566] chose normal [-0.99209853 -0.1254612 ] 94 reflecting at [0.37096745 0.70643199] with direction [ 0.00949935 -0.03885566] reflecting with [-0.97468899 -0.22356515] new direction [ 0.00838404 -0.03911148] re-reflecting gives direction [ 0.00949935 -0.03885566] FORWARD: [ 0.00949935 -0.03885566] [0.37096745 0.70643199] BACKWARD: [ 0.00949935 -0.03885566] [0.37096745 0.70643199] setting seed = 81 reflecting at [0.78116639 0.59011031] with direction [-0.01447537 -0.03728892] chose normal [-0.58455495 0.81135412] 52 reflecting at [0.78116639 0.59011031] with direction [-0.01447537 -0.03728892] reflecting with [ 0.9366811 -0.35018355] new direction [-0.01353712 -0.03763969] re-reflecting gives direction [-0.01447537 -0.03728892] FORWARD: [-0.01447537 -0.03728892] [0.78116639 0.59011031] BACKWARD: [-0.01447537 -0.03728892] [0.78116639 0.59011031] setting seed = 82 reflecting at [0.90241618 0.37140442] with direction [0.00489491 0.03969937] chose normal [-0.99997753 0.00670296] 37 reflecting at [0.90241618 0.37140442] with direction [0.00489491 0.03969937] reflecting with [-0.99945421 -0.03303454] new direction [-0.0075057 0.0392895] re-reflecting gives direction [0.00489491 0.03969937] FORWARD: [0.00489491 0.03969937] [0.90241618 0.37140442] BACKWARD: [0.00489491 0.03969937] [0.90241618 0.37140442] setting seed = 83 reflecting at [0.73947248 0.50969906] with direction [ 0.02973828 -0.02675135] chose normal [-0.83995537 0.54265548] 16 reflecting at [0.73947248 0.50969906] with direction [ 0.02973828 -0.02675135] reflecting with [-0.94063007 0.33943345] new direction [-0.0399681 -0.00159728] re-reflecting gives direction [ 0.02973828 -0.02675135] FORWARD: [ 0.02973828 -0.02675135] [0.73947248 0.50969906] BACKWARD: [ 0.02973828 -0.02675135] [0.73947248 0.50969906] setting seed = 84 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] chose normal [-0.17706516 0.98419913] 53 reflecting at [0.09304075 0.29114574] with direction [ 0.03477044 -0.01977415] reflecting with [-0.51082933 0.85968215] new direction [-0.00074369 0.03999309] re-reflecting gives direction [ 0.03477044 -0.01977415] FORWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] BACKWARD: [ 0.03477044 -0.01977415] [0.09304075 0.29114574] setting seed = 85 reflecting at [0.09269465 0.40624046] with direction [ 0.02781881 -0.02874219] chose normal [-0.96043218 0.27851395] 24 reflecting at [0.09269465 0.40624046] with direction [ 0.02781881 -0.02874219] reflecting with [0.63881082 0.76936385] new direction [ 0.03336656 -0.02206066] re-reflecting gives direction [ 0.02781881 -0.02874219] FORWARD: [ 0.02781881 -0.02874219] [0.09269465 0.40624046] BACKWARD: [ 0.02781881 -0.02874219] [0.09269465 0.40624046] setting seed = 86 reflecting at [0.0772825 0.7321639] with direction [-0.0017544 -0.03996151] setting seed = 87 reflecting at [0.3542791 0.40874116] with direction [ 0.03874902 -0.0099254 ] chose normal [-0.12256498 0.99246049] 84 reflecting at [0.3542791 0.40874116] with direction [ 0.03874902 -0.0099254 ] reflecting with [-0.96541456 -0.26071962] new direction [-0.02848461 -0.0280825 ] re-reflecting gives direction [ 0.03874902 -0.0099254 ] FORWARD: [ 0.03874902 -0.0099254 ] [0.3542791 0.40874116] BACKWARD: [ 0.03874902 -0.0099254 ] [0.3542791 0.40874116] setting seed = 88 reflecting at [0.67093864 0.56773172] with direction [ 0.03197838 -0.0240288 ] chose normal [-0.97498227 0.22228264] 41 reflecting at [0.67093864 0.56773172] with direction [ 0.03197838 -0.0240288 ] reflecting with [-0.97588769 -0.21827326] new direction [-0.01869452 -0.03536262] re-reflecting gives direction [ 0.03197838 -0.0240288 ] FORWARD: [ 0.03197838 -0.0240288 ] [0.67093864 0.56773172] BACKWARD: [ 0.03197838 -0.0240288 ] [0.67093864 0.56773172] setting seed = 89 reflecting at [0.80828603 0.53459992] with direction [0.02786633 0.02869612] chose normal [-0.73290905 0.68032663] 80 reflecting at [0.80828603 0.53459992] with direction [0.02786633 0.02869612] reflecting with [-0.99658198 -0.08260969] new direction [-0.03221094 0.02371614] re-reflecting gives direction [0.02786633 0.02869612] FORWARD: [0.02786633 0.02869612] [0.80828603 0.53459992] BACKWARD: [0.02786633 0.02869612] [0.80828603 0.53459992] setting seed = 90 reflecting at [0.15933834 0.65311074] with direction [-0.02409888 -0.0319256 ] chose normal [ 0.8841271 -0.46724648] 74 reflecting at [0.15933834 0.65311074] with direction [-0.02409888 -0.0319256 ] reflecting with [ 0.99881338 -0.04870138] new direction [ 0.02087861 -0.03411867] re-reflecting gives direction [-0.02409888 -0.0319256 ] FORWARD: [-0.02409888 -0.0319256 ] [0.15933834 0.65311074] BACKWARD: [-0.02409888 -0.0319256 ] [0.15933834 0.65311074] setting seed = 91 reflecting at [0.06220912 0.5649269 ] with direction [-0.01395947 0.0374851 ] chose normal [-0.92831744 -0.37178856] 63 reflecting at [0.06220912 0.5649269 ] with direction [-0.01395947 0.0374851 ] reflecting with [ 0.50709066 -0.86189272] new direction [ 0.02598594 -0.03040939] re-reflecting gives direction [-0.01395947 0.0374851 ] FORWARD: [-0.01395947 0.0374851 ] [0.06220912 0.5649269 ] BACKWARD: [-0.01395947 0.0374851 ] [0.06220912 0.5649269 ] setting seed = 92 reflecting at [0.86691228 0.47991436] with direction [-0.02693892 -0.02956847] chose normal [-0.19961852 0.97987369] 68 reflecting at [0.86691228 0.47991436] with direction [-0.02693892 -0.02956847] reflecting with [0.80447377 0.59398817] new direction [0.0361881 0.01704175] re-reflecting gives direction [-0.02693892 -0.02956847] FORWARD: [-0.02693892 -0.02956847] [0.86691228 0.47991436] BACKWARD: [-0.02693892 -0.02956847] [0.86691228 0.47991436] setting seed = 93 reflecting at [0.40847232 0.38353044] with direction [-0.02290158 0.03279509] chose normal [0.97810947 0.20809099] 55 reflecting at [0.40847232 0.38353044] with direction [-0.02290158 0.03279509] reflecting with [0.99871915 0.05059696] new direction [0.01946991 0.0349417 ] re-reflecting gives direction [-0.02290158 0.03279509] FORWARD: [-0.02290158 0.03279509] [0.40847232 0.38353044] BACKWARD: [-0.02290158 0.03279509] [0.40847232 0.38353044] setting seed = 94 reflecting at [0.18607047 0.43045606] with direction [0.03999576 0.00058272] chose normal [-0.99138772 -0.13095947] 38 reflecting at [0.18607047 0.43045606] with direction [0.03999576 0.00058272] reflecting with [-0.85869194 0.51249211] new direction [-0.01847325 0.03547871] re-reflecting gives direction [0.03999576 0.00058272] FORWARD: [0.03999576 0.00058272] [0.18607047 0.43045606] BACKWARD: [0.03999576 0.00058272] [0.18607047 0.43045606] setting seed = 95 reflecting at [0.1329267 0.27135336] with direction [0.00593512 0.03955723] setting seed = 96 reflecting at [0.57282441 0.43763627] with direction [0.02371945 0.0322085 ] chose normal [-0.98828152 0.15264217] 98 reflecting at [0.57282441 0.43763627] with direction [0.02371945 0.0322085 ] reflecting with [-0.96810281 0.25055328] new direction [-0.00511631 0.03967144] re-reflecting gives direction [0.02371945 0.0322085 ] FORWARD: [0.02371945 0.0322085 ] [0.57282441 0.43763627] BACKWARD: [0.02371945 0.0322085 ] [0.57282441 0.43763627] setting seed = 97 reflecting at [0.59701368 0.45505001] with direction [0.00858305 0.03906829] chose normal [ 0.97234847 -0.23353469] 26 reflecting at [0.59701368 0.45505001] with direction [0.00858305 0.03906829] reflecting with [-0.96293126 -0.26974691] new direction [-0.02762979 0.02892395] re-reflecting gives direction [0.00858305 0.03906829] FORWARD: [0.00858305 0.03906829] [0.59701368 0.45505001] BACKWARD: [0.00858305 0.03906829] [0.59701368 0.45505001] setting seed = 98 reflecting at [0.05036115 0.45117145] with direction [-0.0046699 -0.03972646] chose normal [0.50785771 0.86144097] 48 reflecting at [0.05036115 0.45117145] with direction [-0.0046699 -0.03972646] reflecting with [0.9858335 0.16772692] new direction [ 0.01754476 -0.03594693] re-reflecting gives direction [-0.0046699 -0.03972646] FORWARD: [-0.0046699 -0.03972646] [0.05036115 0.45117145] BACKWARD: [-0.0046699 -0.03972646] [0.05036115 0.45117145] setting seed = 99 reflecting at [0.50555553 0.58688913] with direction [-0.03999867 -0.00032601] chose normal [0.99595977 0.08980054] 53 reflecting at [0.50555553 0.58688913] with direction [-0.03999867 -0.00032601] reflecting with [ 0.8602646 -0.50984784] new direction [ 0.01891779 -0.03524368] re-reflecting gives direction [-0.03999867 -0.00032601] FORWARD: [-0.03999867 -0.00032601] [0.50555553 0.58688913] BACKWARD: [-0.03999867 -0.00032601] [0.50555553 0.58688913] | |||
Passed | tests/test_stepsampling.py::test_stepsampler_cubemh | 5.13 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.16) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.0000|***************************************************| +1.0000 param2: +0.000|***************************************************| +1.000 ineffective proposal scale (1). shrinking... ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.853124). shrinking... ineffective proposal scale (0.787986). shrinking... ineffective proposal scale (0.727821). shrinking... ineffective proposal scale (0.672249). shrinking... Z=-inf(0.00%) | Like=-30.68..-0.33 [-30.6766..-0.5047] | it/evals=0/412 eff=0.0000% N=400 ineffective proposal scale (0.672249). shrinking... ineffective proposal scale (0.620921). shrinking... ineffective proposal scale (0.573512). shrinking... ineffective proposal scale (0.529723). shrinking... ineffective proposal scale (0.573512). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.493179). shrinking... ineffective proposal scale (0.493179). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.493179). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.493179). shrinking... ineffective proposal scale (0.538205). shrinking... ineffective proposal scale (0.538205). shrinking... ineffective proposal scale (0.582695). shrinking... ineffective proposal scale (0.538205). shrinking... ineffective proposal scale (0.497111). shrinking... ineffective proposal scale (0.505071). shrinking... ineffective proposal scale (0.509098). shrinking... ineffective proposal scale (0.513158). shrinking... ineffective proposal scale (0.473977). shrinking... ineffective proposal scale (0.437788). shrinking... ineffective proposal scale (0.473977). shrinking... ineffective proposal scale (0.441279). shrinking... ineffective proposal scale (0.407586). shrinking... ineffective proposal scale (0.407586). shrinking... ineffective proposal scale (0.427479). shrinking... Z=-24.1(0.00%) | Like=-20.28..-0.33 [-30.6766..-0.5047] | it/evals=50/1012 eff=8.1699% N=400 ineffective proposal scale (0.505071). shrinking... ineffective proposal scale (0.466507). shrinking... ineffective proposal scale (0.401162). shrinking... ineffective proposal scale (0.370532). shrinking... ineffective proposal scale (0.350494). shrinking... ineffective proposal scale (0.350494). shrinking... ineffective proposal scale (0.326314). shrinking... ineffective proposal scale (0.414112). shrinking... ineffective proposal scale (0.388618). shrinking... Mono-modal Volume: ~exp(-4.44) * Expected Volume: exp(-0.23) Quality: correlation length: 6 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-20.0(0.00%) | Like=-16.08..-0.33 [-30.6766..-0.5047] | it/evals=90/1492 eff=8.2418% N=400 Z=-19.2(0.00%) | Like=-15.59..-0.33 [-30.6766..-0.5047] | it/evals=100/1612 eff=8.2508% N=400 ineffective proposal scale (0.226446). shrinking... Z=-16.2(0.00%) | Like=-12.77..-0.21 [-30.6766..-0.5047] | it/evals=150/2213 eff=8.2736% N=400 Mono-modal Volume: ~exp(-4.44) Expected Volume: exp(-0.45) Quality: correlation length: 6 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|**** **********************************************| +1.000 Z=-14.0(0.00%) | Like=-10.95..-0.21 [-30.6766..-0.5047] | it/evals=200/2813 eff=8.2884% N=400 ineffective proposal scale (0.12091). shrinking... Z=-12.5(0.01%) | Like=-9.48..-0.21 [-30.6766..-0.5047] | it/evals=250/3413 eff=8.2974% N=400 Mono-modal Volume: ~exp(-4.87) * Expected Volume: exp(-0.67) Quality: correlation length: 6 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-12.0(0.02%) | Like=-8.96..-0.21 [-30.6766..-0.5047] | it/evals=270/3653 eff=8.3000% N=400 Z=-11.3(0.04%) | Like=-8.26..-0.21 [-30.6766..-0.5047] | it/evals=300/4013 eff=8.3033% N=400 Z=-10.2(0.12%) | Like=-7.34..-0.02 [-30.6766..-0.5047] | it/evals=350/4613 eff=8.3076% N=400 Mono-modal Volume: ~exp(-4.99) * Expected Volume: exp(-0.90) Quality: correlation length: 6 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-10.0(0.14%) | Like=-7.11..-0.02 [-30.6766..-0.5047] | it/evals=360/4733 eff=8.3083% N=400 Z=-9.4(0.26%) | Like=-6.61..-0.02 [-30.6766..-0.5047] | it/evals=400/5213 eff=8.3108% N=400 Mono-modal Volume: ~exp(-5.15) * Expected Volume: exp(-1.12) Quality: correlation length: 6 (+) param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-8.7(0.52%) | Like=-5.97..-0.02 [-30.6766..-0.5047] | it/evals=450/5813 eff=8.3133% N=400 Z=-8.1(0.94%) | Like=-5.33..-0.02 [-30.6766..-0.5047] | it/evals=500/6413 eff=8.3153% N=400 Mono-modal Volume: ~exp(-5.66) * Expected Volume: exp(-1.35) Quality: correlation length: 6 (+) param0: +0.00|***************************************************| +1.00 param1: +0.00| **************************************************| +1.00 param2: +0.00| *********************************************** *| +1.00 Z=-7.7(1.37%) | Like=-5.00..-0.02 [-30.6766..-0.5047] | it/evals=540/6893 eff=8.3166% N=400 Z=-7.6(1.47%) | Like=-4.94..-0.02 [-30.6766..-0.5047] | it/evals=550/7013 eff=8.3170% N=400 Z=-7.2(2.30%) | Like=-4.53..-0.02 [-30.6766..-0.5047] | it/evals=600/7613 eff=8.3183% N=400 Mono-modal Volume: ~exp(-5.66) Expected Volume: exp(-1.57) Quality: correlation length: 6 (+) param0: +0.00| ** ******************************************** * | +1.00 param1: +0.00| ************************************************ | +1.00 param2: +0.00| ************************************************ | +1.00 Z=-6.8(3.48%) | Like=-4.09..-0.02 [-30.6766..-0.5047] | it/evals=650/8213 eff=8.3195% N=400 Z=-6.4(4.89%) | Like=-3.67..-0.02 [-30.6766..-0.5047] | it/evals=700/8813 eff=8.3205% N=400 Mono-modal Volume: ~exp(-5.66) Expected Volume: exp(-1.80) Quality: correlation length: 6 (+) param0: +0.00| * ******************************************** | +1.00 param1: +0.00| *********************************************** | +1.00 param2: +0.00| * ********************************************* | +1.00 Z=-6.1(6.62%) | Like=-3.35..-0.02 [-30.6766..-0.5047] | it/evals=750/9413 eff=8.3213% N=400 Z=-5.8(8.72%) | Like=-3.11..-0.02 [-30.6766..-0.5047] | it/evals=800/10013 eff=8.3221% N=400 Mono-modal Volume: ~exp(-6.18) * Expected Volume: exp(-2.02) Quality: correlation length: 6 (+) param0: +0.00| ******************************************* * | +1.00 param1: +0.00| ********************************************* | +1.00 param2: +0.00| * ******************************************* | +1.00 Z=-5.8(9.19%) | Like=-3.07..-0.02 [-30.6766..-0.5047] | it/evals=810/10133 eff=8.3222% N=400 Z=-5.6(11.13%) | Like=-2.85..-0.02 [-30.6766..-0.5047] | it/evals=850/10613 eff=8.3227% N=400 Have 2 modes Volume: ~exp(-6.34) * Expected Volume: exp(-2.25) Quality: correlation length: 6 (+) param0: +0.00| 11111111111111111111122222222222222222222222 | +1.00 param1: +0.00| 111111111111111111111222222222222222222222 | +1.00 param2: +0.0| 111111111111111111112222222222222222222222 | +1.0 Z=-5.4(13.81%) | Like=-2.58..-0.02 [-30.6766..-0.5047] | it/evals=900/11213 eff=8.3233% N=400 Z=-5.2(16.80%) | Like=-2.36..-0.02 [-30.6766..-0.5047] | it/evals=950/11813 eff=8.3238% N=400 Have 2 modes Volume: ~exp(-6.35) * Expected Volume: exp(-2.47) Quality: correlation length: 6 (+) param0: +0.0| 11111111111111111111222222222222222222222 | +1.0 param1: +0.0| 11111111111111111111122222222222222222222 | +1.0 param2: +0.0| 11111111111111111111222222222222222222222 | +1.0 Z=-5.0(19.57%) | Like=-2.19..-0.02 [-30.6766..-0.5047] | it/evals=990/12293 eff=8.3242% N=400 Z=-5.0(20.31%) | Like=-2.15..-0.02 [-30.6766..-0.5047] | it/evals=1000/12413 eff=8.3243% N=400 Z=-4.8(23.91%) | Like=-1.96..-0.02 [-30.6766..-0.5047] | it/evals=1050/13013 eff=8.3247% N=400 Have 2 modes Volume: ~exp(-6.65) * Expected Volume: exp(-2.70) Quality: correlation length: 6 (+) param0: +0.0| 1111111111111111111112222222222222222222 | +1.0 param1: +0.0| 1111111111111111111 2222222222222222222 | +1.0 param2: +0.0| 111111111111111111 222222222222222222222 | +1.0 Z=-4.7(26.28%) | Like=-1.87..-0.02 [-30.6766..-0.5047] | it/evals=1080/13373 eff=8.3250% N=400 Z=-4.7(27.88%) | Like=-1.80..-0.02 [-30.6766..-0.5047] | it/evals=1100/13613 eff=8.3251% N=400 Z=-4.5(31.57%) | Like=-1.61..-0.02 [-30.6766..-0.5047] | it/evals=1150/14213 eff=8.3255% N=400 Have 2 modes Volume: ~exp(-7.41) * Expected Volume: exp(-2.92) Quality: correlation length: 6 (+) param0: +0.0| 11111111111111111 222222222222222222 | +1.0 param1: +0.0| 11111111111111111 2222222222222222222 | +1.0 param2: +0.0| 1 1111111111111111 222222222222222222 | +1.0 Z=-4.5(33.22%) | Like=-1.57..-0.02 [-30.6766..-0.5047] | it/evals=1170/14453 eff=8.3256% N=400 Z=-4.4(35.67%) | Like=-1.46..-0.02 [-30.6766..-0.5047] | it/evals=1200/14813 eff=8.3258% N=400 Z=-4.3(39.88%) | Like=-1.35..-0.02 [-30.6766..-0.5047] | it/evals=1250/15413 eff=8.3261% N=400 Have 2 modes Volume: ~exp(-7.47) * Expected Volume: exp(-3.15) Quality: correlation length: 6 (+) param0: +0.0| 11111111111111111 22222222222222222 | +1.0 param1: +0.0| 1111111111111111 2222222222222222 | +1.0 param2: +0.0| 111111111111111 22222222222222222 | +1.0 Z=-4.3(40.82%) | Like=-1.33..-0.02 [-30.6766..-0.5047] | it/evals=1260/15533 eff=8.3262% N=400 Z=-4.2(44.05%) | Like=-1.26..-0.02 [-30.6766..-0.5047] | it/evals=1300/16013 eff=8.3264% N=400 Have 2 modes Volume: ~exp(-7.52) * Expected Volume: exp(-3.37) Quality: correlation length: 6 (+) param0: +0.0| 111111111111111 222222222222222 | +1.0 param1: +0.0| 1111111111111111 222222222222222 | +1.0 param2: +0.0| 111111111111111 2222222222222222 | +1.0 Z=-4.1(47.94%) | Like=-1.16..-0.02 [-30.6766..-0.5047] | it/evals=1350/16614 eff=8.3261% N=400 Z=-4.0(51.81%) | Like=-1.07..-0.02 [-30.6766..-0.5047] | it/evals=1400/17214 eff=8.3264% N=400 Have 2 modes Volume: ~exp(-7.99) * Expected Volume: exp(-3.60) Quality: correlation length: 6 (+) param0: +0.0| 11111111111111 222222222222222 | +1.0 param1: +0.0| 111111111111111 2222222222222 | +1.0 param2: +0.0| 1111111111111 222222222222222 | +1.0 Z=-4.0(54.61%) | Like=-0.99..-0.01 [-30.6766..-0.5047] | it/evals=1440/17694 eff=8.3266% N=400 Z=-4.0(55.34%) | Like=-0.97..-0.01 [-30.6766..-0.5047] | it/evals=1450/17814 eff=8.3333% N=400 Z=-3.9(58.99%) | Like=-0.90..-0.01 [-30.6766..-0.5047] | it/evals=1500/18414 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-7.99) Expected Volume: exp(-3.82) Quality: correlation length: 6 (+) param0: +0.0| 1111111111111 22222222222220 | +1.0 param1: +0.0| 1111111111111 2222222222220 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-3.8(62.47%) | Like=-0.83..-0.01 [-30.6766..-0.5047] | it/evals=1550/19014 eff=8.3333% N=400 Z=-3.8(65.69%) | Like=-0.77..-0.01 [-30.6766..-0.5047] | it/evals=1600/19614 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.01) * Expected Volume: exp(-4.05) Quality: correlation length: 6 (+) param0: +0.0| 1111111111111 2222222222222 | +1.0 param1: +0.0| 111111111111 222222222222 +0.8 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-3.8(67.00%) | Like=-0.75..-0.01 [-30.6766..-0.5047] | it/evals=1620/19854 eff=8.3333% N=400 Z=-3.8(68.75%) | Like=-0.72..-0.01 [-30.6766..-0.5047] | it/evals=1650/20214 eff=8.3333% N=400 Z=-3.7(71.47%) | Like=-0.64..-0.01 [-30.6766..-0.5047] | it/evals=1700/20815 eff=8.3195% N=400 Have 2 modes Volume: ~exp(-8.37) * Expected Volume: exp(-4.27) Quality: correlation length: 6 (+) param0: +0.0| 11111111111 222222222222 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 111111111111 22222222222 +0.8 | +1.0 Z=-3.7(72.05%) | Like=-0.63..-0.01 [-30.6766..-0.5047] | it/evals=1710/20935 eff=8.3333% N=400 Z=-3.7(74.08%) | Like=-0.59..-0.01 [-30.6766..-0.5047] | it/evals=1750/21416 eff=8.3160% N=400 Have 2 modes Volume: ~exp(-8.64) * Expected Volume: exp(-4.50) Quality: correlation length: 6 (+) param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.6(76.51%) | Like=-0.55..-0.01 [-30.6766..-0.5047] | it/evals=1800/22016 eff=8.3333% N=400 Z=-3.6(78.77%) | Like=-0.51..-0.01 [-30.6766..-0.5047] | it/evals=1850/22616 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.89) * Expected Volume: exp(-4.73) Quality: correlation length: 6 (+) param0: +0.0| 1111111111 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 2222222222 +0.8 | +1.0 Z=-3.6(80.44%) | Like=-0.48..-0.01 [-0.4824..-0.4813]*| it/evals=1890/23096 eff=8.3333% N=400 Z=-3.6(80.85%) | Like=-0.47..-0.01 [-0.4745..-0.4744]*| it/evals=1900/23216 eff=8.3333% N=400 Z=-3.6(82.69%) | Like=-0.44..-0.01 [-0.4429..-0.4416]*| it/evals=1950/23816 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.06) * Expected Volume: exp(-4.95) Quality: correlation length: 6 (+) param0: +0.0| 1111111111 222222222 +0.8 | +1.0 param1: +0.0| 1111111111 222222222 +0.8 | +1.0 param2: +0.0| 1111111111 2222222222 +0.8 | +1.0 Z=-3.6(83.74%) | Like=-0.42..-0.01 [-0.4247..-0.4246]*| it/evals=1980/24176 eff=8.3333% N=400 Z=-3.5(84.40%) | Like=-0.41..-0.01 [-0.4058..-0.4044]*| it/evals=2000/24416 eff=8.3333% N=400 Z=-3.5(85.96%) | Like=-0.37..-0.01 [-0.3726..-0.3725]*| it/evals=2050/25016 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.27) * Expected Volume: exp(-5.18) Quality: correlation length: 6 (+) param0: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.5(86.56%) | Like=-0.36..-0.01 [-0.3632..-0.3621]*| it/evals=2070/25256 eff=8.3333% N=400 Z=-3.5(87.40%) | Like=-0.34..-0.01 [-0.3448..-0.3445]*| it/evals=2100/25616 eff=8.3333% N=400 Z=-3.5(88.71%) | Like=-0.32..-0.01 [-0.3168..-0.3165]*| it/evals=2150/26216 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.92) * Expected Volume: exp(-5.40) Quality: correlation length: 6 (+) param0: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 Z=-3.5(88.95%) | Like=-0.31..-0.01 [-0.3094..-0.3094]*| it/evals=2160/26336 eff=8.3333% N=400 Z=-3.5(89.88%) | Like=-0.29..-0.01 [-0.2888..-0.2884]*| it/evals=2200/26816 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.92) Expected Volume: exp(-5.63) Quality: correlation length: 6 (+) param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(90.95%) | Like=-0.26..-0.01 [-0.2621..-0.2610]*| it/evals=2250/27417 eff=8.3195% N=400 Z=-3.5(91.90%) | Like=-0.24..-0.01 [-0.2392..-0.2389]*| it/evals=2300/28017 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.33) * Expected Volume: exp(-5.85) Quality: correlation length: 6 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(92.60%) | Like=-0.22..-0.01 [-0.2239..-0.2238]*| it/evals=2340/28497 eff=8.3333% N=400 Z=-3.5(92.77%) | Like=-0.22..-0.01 [-0.2201..-0.2192]*| it/evals=2350/28617 eff=8.3333% N=400 Z=-3.4(93.56%) | Like=-0.20..-0.01 [-0.1985..-0.1984]*| it/evals=2400/29217 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.33) Expected Volume: exp(-6.08) Quality: correlation length: 6 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.4(94.26%) | Like=-0.18..-0.01 [-0.1828..-0.1825]*| it/evals=2450/29817 eff=8.3333% N=400 Z=-3.4(94.89%) | Like=-0.17..-0.01 [-0.1688..-0.1685]*| it/evals=2500/30417 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.64) * Expected Volume: exp(-6.30) Quality: correlation length: 6 (+) param0: +0.0| +0.2 111111 222222 +0.8 | +1.0 param1: +0.0| +0.2 111111 2222222 +0.8 | +1.0 param2: +0.0| +0.3 111111 2222222 +0.7 | +1.0 Z=-3.4(95.12%) | Like=-0.16..-0.01 [-0.1608..-0.1607]*| it/evals=2520/30657 eff=8.3333% N=400 Z=-3.4(95.45%) | Like=-0.15..-0.01 [-0.1513..-0.1507]*| it/evals=2550/31017 eff=8.3333% N=400 Z=-3.4(95.96%) | Like=-0.14..-0.01 [-0.1375..-0.1371]*| it/evals=2600/31617 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.04) * Expected Volume: exp(-6.53) Quality: correlation length: 6 (+) param0: +0.0| +0.2 111111 222222 +0.7 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 1111111 222222 +0.7 | +1.0 Z=-3.4(96.05%) | Like=-0.13..-0.01 [-0.1344..-0.1341]*| it/evals=2610/31737 eff=8.3333% N=400 Z=-3.4(96.41%) | Like=-0.12..-0.01 [-0.1243..-0.1242]*| it/evals=2650/32217 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.04) Expected Volume: exp(-6.75) Quality: correlation length: 6 (+) param0: +0.0| +0.3 11111 222222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(96.81%) | Like=-0.12..-0.01 [-0.1158..-0.1154]*| it/evals=2700/32817 eff=8.3333% N=400 Z=-3.4(97.17%) | Like=-0.11..-0.00 [-0.1064..-0.1063]*| it/evals=2750/33417 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.04) Expected Volume: exp(-6.98) Quality: correlation length: 6 (+) param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(97.49%) | Like=-0.10..-0.00 [-0.0984..-0.0984]*| it/evals=2800/34017 eff=8.3333% N=400 Z=-3.4(97.78%) | Like=-0.09..-0.00 [-0.0911..-0.0911]*| it/evals=2850/34618 eff=8.3195% N=400 Have 2 modes Volume: ~exp(-11.40) * Expected Volume: exp(-7.20) Quality: correlation length: 63 (-) param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(97.93%) | Like=-0.09..-0.00 [-0.0880..-0.0879]*| it/evals=2880/34978 eff=8.3333% N=400 Z=-3.4(98.03%) | Like=-0.09..-0.00 [-0.0855..-0.0855]*| it/evals=2900/35218 eff=8.3333% N=400 Z=-3.4(98.25%) | Like=-0.08..-0.00 [-0.0790..-0.0790]*| it/evals=2950/35818 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.43) * Expected Volume: exp(-7.43) Quality: correlation length: 63 (-) param0: +0.0| +0.3 11111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(98.34%) | Like=-0.08..-0.00 [-0.0769..-0.0768]*| it/evals=2970/36058 eff=8.3333% N=400 Z=-3.4(98.45%) | Like=-0.07..-0.00 [-0.0729..-0.0728]*| it/evals=3000/36418 eff=8.3333% N=400 Z=-3.4(98.63%) | Like=-0.07..-0.00 [-0.0666..-0.0666]*| it/evals=3050/37018 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-12.06) * Expected Volume: exp(-7.65) Quality: correlation length: 63 (-) param0: +0.0| +0.3 1111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 2222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(98.66%) | Like=-0.07..-0.00 [-0.0656..-0.0656]*| it/evals=3060/37138 eff=8.3333% N=400 Z=-3.4(98.79%) | Like=-0.06..-0.00 [-0.0614..-0.0614]*| it/evals=3100/37618 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-12.08) * Expected Volume: exp(-7.88) Quality: correlation length: 218 (+) param0: +0.0| +0.3 1111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 2222 +0.7 | +1.0 param2: +0.0| +0.3 11111 2222 +0.7 | +1.0 Z=-3.4(98.93%) | Like=-0.06..-0.00 [-0.0577..-0.0576]*| it/evals=3150/38218 eff=8.3333% N=400 [ultranest] Explored until L=-0.0004 [ultranest] Likelihood function evaluations: 38554 [ultranest] logZ = -3.368 +- 0.04159 [ultranest] Effective samples strategy satisfied (ESS = 1795.2, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.45+-0.06 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.09, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.04 tail:0.01 total:0.04 required:<0.50 [ultranest] done iterating. logZ = -3.375 +- 0.088 single instance: logZ = -3.375 +- 0.070 bootstrapped : logZ = -3.368 +- 0.087 tail : logZ = +- 0.010 insert order U test : converged: False correlation: 6.0 iterations param0 0.54 +- 0.21 param1 0.54 +- 0.21 param2 0.55 +- 0.22 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=412, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.68, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=1012, logz=-24.12, remainder_fraction=100.0000%, Lmin=-20.28, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=1492, logz=-20.01, remainder_fraction=100.0000%, Lmin=-16.08, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=1612, logz=-19.20, remainder_fraction=100.0000%, Lmin=-15.59, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=2213, logz=-16.23, remainder_fraction=99.9997%, Lmin=-12.77, Lmax=-0.21 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=2813, logz=-14.00, remainder_fraction=99.9971%, Lmin=-10.95, Lmax=-0.21 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=3413, logz=-12.52, remainder_fraction=99.9875%, Lmin=-9.48, Lmax=-0.21 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=3653, logz=-12.01, remainder_fraction=99.9786%, Lmin=-8.96, Lmax=-0.21 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=4013, logz=-11.27, remainder_fraction=99.9566%, Lmin=-8.26, Lmax=-0.21 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=4613, logz=-10.20, remainder_fraction=99.8806%, Lmin=-7.34, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=4733, logz=-10.02, remainder_fraction=99.8618%, Lmin=-7.11, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=5213, logz=-9.37, remainder_fraction=99.7396%, Lmin=-6.61, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=5813, logz=-8.69, remainder_fraction=99.4756%, Lmin=-5.97, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=6413, logz=-8.10, remainder_fraction=99.0576%, Lmin=-5.33, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=6893, logz=-7.69, remainder_fraction=98.6256%, Lmin=-5.00, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=7013, logz=-7.60, remainder_fraction=98.5324%, Lmin=-4.94, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=7613, logz=-7.18, remainder_fraction=97.6999%, Lmin=-4.53, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=8213, logz=-6.79, remainder_fraction=96.5221%, Lmin=-4.09, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=8813, logz=-6.44, remainder_fraction=95.1142%, Lmin=-3.67, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=9413, logz=-6.12, remainder_fraction=93.3816%, Lmin=-3.35, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=10013, logz=-5.83, remainder_fraction=91.2752%, Lmin=-3.11, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=10133, logz=-5.78, remainder_fraction=90.8118%, Lmin=-3.07, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=10613, logz=-5.59, remainder_fraction=88.8652%, Lmin=-2.85, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=11213, logz=-5.36, remainder_fraction=86.1853%, Lmin=-2.58, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=11813, logz=-5.16, remainder_fraction=83.2014%, Lmin=-2.36, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=12293, logz=-5.02, remainder_fraction=80.4317%, Lmin=-2.19, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=12413, logz=-4.98, remainder_fraction=79.6870%, Lmin=-2.15, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=13013, logz=-4.82, remainder_fraction=76.0923%, Lmin=-1.96, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=13373, logz=-4.73, remainder_fraction=73.7194%, Lmin=-1.87, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=13613, logz=-4.67, remainder_fraction=72.1176%, Lmin=-1.80, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=14213, logz=-4.53, remainder_fraction=68.4322%, Lmin=-1.61, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=14453, logz=-4.48, remainder_fraction=66.7787%, Lmin=-1.57, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=14813, logz=-4.41, remainder_fraction=64.3335%, Lmin=-1.46, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=15413, logz=-4.30, remainder_fraction=60.1157%, Lmin=-1.35, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=15533, logz=-4.28, remainder_fraction=59.1751%, Lmin=-1.33, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=16013, logz=-4.20, remainder_fraction=55.9507%, Lmin=-1.26, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=16614, logz=-4.11, remainder_fraction=52.0635%, Lmin=-1.16, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=17214, logz=-4.04, remainder_fraction=48.1906%, Lmin=-1.07, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=17694, logz=-3.98, remainder_fraction=45.3870%, Lmin=-0.99, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=17814, logz=-3.97, remainder_fraction=44.6612%, Lmin=-0.97, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=18414, logz=-3.90, remainder_fraction=41.0093%, Lmin=-0.90, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=19014, logz=-3.85, remainder_fraction=37.5253%, Lmin=-0.83, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=19614, logz=-3.80, remainder_fraction=34.3055%, Lmin=-0.77, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=19854, logz=-3.78, remainder_fraction=32.9986%, Lmin=-0.75, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=20214, logz=-3.75, remainder_fraction=31.2540%, Lmin=-0.72, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=20815, logz=-3.71, remainder_fraction=28.5275%, Lmin=-0.64, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=20935, logz=-3.70, remainder_fraction=27.9546%, Lmin=-0.63, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=21416, logz=-3.68, remainder_fraction=25.9233%, Lmin=-0.59, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=22016, logz=-3.64, remainder_fraction=23.4897%, Lmin=-0.55, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=22616, logz=-3.61, remainder_fraction=21.2318%, Lmin=-0.51, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=23096, logz=-3.59, remainder_fraction=19.5637%, Lmin=-0.48, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=23216, logz=-3.59, remainder_fraction=19.1498%, Lmin=-0.47, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=23816, logz=-3.57, remainder_fraction=17.3096%, Lmin=-0.44, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=24176, logz=-3.55, remainder_fraction=16.2621%, Lmin=-0.42, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=24416, logz=-3.54, remainder_fraction=15.5958%, Lmin=-0.41, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=25016, logz=-3.53, remainder_fraction=14.0405%, Lmin=-0.37, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=25256, logz=-3.52, remainder_fraction=13.4402%, Lmin=-0.36, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=25616, logz=-3.51, remainder_fraction=12.5988%, Lmin=-0.34, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=26216, logz=-3.50, remainder_fraction=11.2943%, Lmin=-0.32, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=26336, logz=-3.49, remainder_fraction=11.0523%, Lmin=-0.31, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=26816, logz=-3.48, remainder_fraction=10.1214%, Lmin=-0.29, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=27417, logz=-3.47, remainder_fraction=9.0545%, Lmin=-0.26, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=28017, logz=-3.46, remainder_fraction=8.0955%, Lmin=-0.24, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2340, ncalls=28497, logz=-3.45, remainder_fraction=7.3996%, Lmin=-0.22, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=28617, logz=-3.45, remainder_fraction=7.2341%, Lmin=-0.22, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=29217, logz=-3.44, remainder_fraction=6.4437%, Lmin=-0.20, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=29817, logz=-3.43, remainder_fraction=5.7428%, Lmin=-0.18, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=30417, logz=-3.43, remainder_fraction=5.1144%, Lmin=-0.17, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=30657, logz=-3.43, remainder_fraction=4.8797%, Lmin=-0.16, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=31017, logz=-3.42, remainder_fraction=4.5497%, Lmin=-0.15, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=31617, logz=-3.42, remainder_fraction=4.0443%, Lmin=-0.14, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=31737, logz=-3.42, remainder_fraction=3.9490%, Lmin=-0.13, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=32217, logz=-3.41, remainder_fraction=3.5905%, Lmin=-0.12, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=32817, logz=-3.41, remainder_fraction=3.1858%, Lmin=-0.12, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=33417, logz=-3.40, remainder_fraction=2.8270%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=34017, logz=-3.40, remainder_fraction=2.5079%, Lmin=-0.10, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=34618, logz=-3.40, remainder_fraction=2.2226%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2880, ncalls=34978, logz=-3.40, remainder_fraction=2.0666%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2900, ncalls=35218, logz=-3.40, remainder_fraction=1.9689%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2950, ncalls=35818, logz=-3.39, remainder_fraction=1.7451%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2970, ncalls=36058, logz=-3.39, remainder_fraction=1.6626%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3000, ncalls=36418, logz=-3.39, remainder_fraction=1.5455%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3050, ncalls=37018, logz=-3.39, remainder_fraction=1.3683%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3060, ncalls=37138, logz=-3.39, remainder_fraction=1.3359%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3100, ncalls=37618, logz=-3.39, remainder_fraction=1.2124%, Lmin=-0.06, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3150, ncalls=38218, logz=-3.39, remainder_fraction=1.0730%, Lmin=-0.06, Lmax=-0.00 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=-0.0004 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 38554 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -3.368 +- 0.04159 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1795.2, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.45+-0.06 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.09, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.07 bs:0.04 tail:0.01 total:0.04 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_stepsampling.py::test_stepsampler_regionmh | 5.76 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.16) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.0000|***************************************************| +1.0000 param2: +0.000|***************************************************| +1.000 ineffective proposal scale (1). shrinking... ineffective proposal scale (0.923647). shrinking... Z=-inf(0.00%) | Like=-30.68..-0.33 [-30.6766..-0.5047] | it/evals=0/412 eff=0.0000% N=400 ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.853124). shrinking... ineffective proposal scale (0.853124). shrinking... ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.853124). shrinking... ineffective proposal scale (0.853124). shrinking... ineffective proposal scale (0.923647). shrinking... ineffective proposal scale (0.853124). shrinking... ineffective proposal scale (0.787986). shrinking... ineffective proposal scale (0.727821). shrinking... ineffective proposal scale (0.733624). shrinking... ineffective proposal scale (0.733624). shrinking... ineffective proposal scale (0.67761). shrinking... ineffective proposal scale (0.67761). shrinking... ineffective proposal scale (0.67761). shrinking... ineffective proposal scale (0.733624). shrinking... ineffective proposal scale (0.733624). shrinking... ineffective proposal scale (0.733624). shrinking... ineffective proposal scale (0.739474). shrinking... ineffective proposal scale (0.806987). shrinking... ineffective proposal scale (0.806987). shrinking... ineffective proposal scale (0.806987). shrinking... ineffective proposal scale (0.806987). shrinking... ineffective proposal scale (0.806987). shrinking... ineffective proposal scale (0.745371). shrinking... ineffective proposal scale (0.745371). shrinking... ineffective proposal scale (0.68846). shrinking... ineffective proposal scale (0.640965). shrinking... ineffective proposal scale (0.592025). shrinking... ineffective proposal scale (0.601505). shrinking... ineffective proposal scale (0.555578). shrinking... ineffective proposal scale (0.601505). shrinking... ineffective proposal scale (0.611136). shrinking... ineffective proposal scale (0.616009). shrinking... ineffective proposal scale (0.573512). shrinking... ineffective proposal scale (0.533947). shrinking... ineffective proposal scale (0.630863). shrinking... ineffective proposal scale (0.538205). shrinking... ineffective proposal scale (0.497111). shrinking... Z=-24.1(0.00%) | Like=-20.30..-0.08 [-30.6766..-0.5047] | it/evals=50/1012 eff=8.1699% N=400 ineffective proposal scale (0.546822). shrinking... ineffective proposal scale (0.505071). shrinking... ineffective proposal scale (0.551183). shrinking... ineffective proposal scale (0.560008). shrinking... Mono-modal Volume: ~exp(-4.23) * Expected Volume: exp(-0.23) Quality: correlation length: 35 (+) param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-20.3(0.00%) | Like=-16.37..-0.08 [-30.6766..-0.5047] | it/evals=90/1492 eff=8.2418% N=400 ineffective proposal scale (0.455523). shrinking... ineffective proposal scale (0.391717). shrinking... Z=-19.4(0.00%) | Like=-15.70..-0.08 [-30.6766..-0.5047] | it/evals=100/1612 eff=8.2508% N=400 ineffective proposal scale (0.201013). shrinking... Z=-16.5(0.00%) | Like=-13.13..-0.08 [-30.6766..-0.5047] | it/evals=150/2212 eff=8.2781% N=400 Mono-modal Volume: ~exp(-4.58) * Expected Volume: exp(-0.45) Quality: correlation length: 35 (+) param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-14.8(0.00%) | Like=-11.44..-0.08 [-30.6766..-0.5047] | it/evals=180/2572 eff=8.2873% N=400 Z=-14.0(0.00%) | Like=-10.81..-0.08 [-30.6766..-0.5047] | it/evals=200/2812 eff=8.2919% N=400 Z=-12.4(0.01%) | Like=-9.35..-0.08 [-30.6766..-0.5047] | it/evals=250/3412 eff=8.3001% N=400 Mono-modal Volume: ~exp(-4.96) * Expected Volume: exp(-0.67) Quality: correlation length: 35 (+) param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-11.8(0.02%) | Like=-8.72..-0.08 [-30.6766..-0.5047] | it/evals=270/3652 eff=8.3026% N=400 Z=-11.0(0.05%) | Like=-7.94..-0.08 [-30.6766..-0.5047] | it/evals=300/4012 eff=8.3056% N=400 Z=-10.0(0.13%) | Like=-7.09..-0.03 [-30.6766..-0.5047] | it/evals=350/4612 eff=8.3096% N=400 Mono-modal Volume: ~exp(-5.14) * Expected Volume: exp(-0.90) Quality: correlation length: 259 (+) param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|************************************************** | +1.000 Z=-9.8(0.15%) | Like=-6.96..-0.03 [-30.6766..-0.5047] | it/evals=360/4732 eff=8.3102% N=400 Z=-9.2(0.29%) | Like=-6.34..-0.03 [-30.6766..-0.5047] | it/evals=400/5212 eff=8.3126% N=400 Mono-modal Volume: ~exp(-5.14) Expected Volume: exp(-1.12) Quality: correlation length: 259 (+) param0: +0.00|***************************************************| +1.00 param1: +0.00|***************************************************| +1.00 param2: +0.000|************************************************** | +1.000 Z=-8.5(0.61%) | Like=-5.84..-0.03 [-30.6766..-0.5047] | it/evals=450/5812 eff=8.3149% N=400 Z=-7.9(1.02%) | Like=-5.33..-0.03 [-30.6766..-0.5047] | it/evals=500/6412 eff=8.3167% N=400 Mono-modal Volume: ~exp(-5.28) * Expected Volume: exp(-1.35) Quality: correlation length: 259 (+) param0: +0.00|***************************************************| +1.00 param1: +0.00| ************************************************ *| +1.00 param2: +0.00| ************************************************ | +1.00 Z=-7.6(1.51%) | Like=-5.00..-0.03 [-30.6766..-0.5047] | it/evals=540/6892 eff=8.3179% N=400 Z=-7.5(1.62%) | Like=-4.93..-0.03 [-30.6766..-0.5047] | it/evals=550/7012 eff=8.3182% N=400 Z=-7.1(2.37%) | Like=-4.50..-0.03 [-30.6766..-0.5047] | it/evals=600/7612 eff=8.3195% N=400 Mono-modal Volume: ~exp(-5.76) * Expected Volume: exp(-1.57) Quality: correlation length: 259 (+) param0: +0.00| *********************************************** **| +1.00 param1: +0.00| ************************************************ | +1.00 param2: +0.00| ************************************************ | +1.00 Z=-6.9(2.98%) | Like=-4.32..-0.03 [-30.6766..-0.5047] | it/evals=630/7972 eff=8.3201% N=400 Z=-6.8(3.44%) | Like=-4.15..-0.03 [-30.6766..-0.5047] | it/evals=650/8212 eff=8.3205% N=400 Z=-6.4(4.77%) | Like=-3.80..-0.03 [-30.6766..-0.5047] | it/evals=700/8812 eff=8.3214% N=400 Mono-modal Volume: ~exp(-5.76) Expected Volume: exp(-1.80) Quality: correlation length: 259 (+) positive degeneracy between param2 and param0: rho=0.76 param0: +0.00| ******************************************** ** | +1.00 param1: +0.00| ********************************************** | +1.00 param2: +0.00| * ********************************************* | +1.00 Z=-6.1(6.68%) | Like=-3.37..-0.03 [-30.6766..-0.5047] | it/evals=750/9412 eff=8.3222% N=400 Z=-5.8(9.06%) | Like=-3.07..-0.03 [-30.6766..-0.5047] | it/evals=800/10012 eff=8.3229% N=400 Mono-modal Volume: ~exp(-5.76) Expected Volume: exp(-2.02) Quality: correlation length: 259 (+) positive degeneracy between param2 and param0: rho=0.77 param0: +0.00| * ***************************************** | +1.00 param1: +0.00| ********************************************** | +1.00 param2: +0.00| ******************************************** | +1.00 Z=-5.6(11.78%) | Like=-2.81..-0.03 [-30.6766..-0.5047] | it/evals=850/10612 eff=8.3235% N=400 Have 2 modes Volume: ~exp(-6.69) * Expected Volume: exp(-2.25) Quality: correlation length: 259 (+) positive degeneracy between param2 and param0: rho=0.77 param0: +0.00| 11111111111111111111112222222222222222222 | +1.00 param1: +0.00| 1111111111111111111112222222222222222222222 | +1.00 param2: +0.00| 11111111111111111111112 2222222222222222222 | +1.00 Z=-5.4(14.61%) | Like=-2.60..-0.03 [-30.6766..-0.5047] | it/evals=900/11212 eff=8.3241% N=400 Z=-5.2(17.52%) | Like=-2.36..-0.03 [-30.6766..-0.5047] | it/evals=950/11812 eff=8.3246% N=400 Have 2 modes Volume: ~exp(-6.69) Expected Volume: exp(-2.47) Quality: correlation length: 259 (+) positive degeneracy between param2 and param0: rho=0.77 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 1111111111111111111122222222222222222222 | +1.0 param1: +0.00| 1111111111111111111112222222222222222222220 | +1.00 param2: +0.0| 1111111111111111111112 2222222222222222222 | +1.0 Z=-5.0(21.00%) | Like=-2.15..-0.03 [-30.6766..-0.5047] | it/evals=1000/12412 eff=8.3250% N=400 Z=-4.8(24.53%) | Like=-2.01..-0.03 [-30.6766..-0.5047] | it/evals=1050/13012 eff=8.3254% N=400 Have 2 modes Volume: ~exp(-6.69) Expected Volume: exp(-2.70) Quality: correlation length: 259 (+) positive degeneracy between param2 and param0: rho=0.77 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 10111111111111111111 222222222222222222 | +1.0 param1: +0.0| 0 111111111111111111022222222222222222222 | +1.0 param2: +0.0| 01111111111111111111 0222222222222222222 | +1.0 Z=-4.7(28.14%) | Like=-1.87..-0.03 [-30.6766..-0.5047] | it/evals=1100/13612 eff=8.3258% N=400 Z=-4.5(31.31%) | Like=-1.70..-0.03 [-30.6766..-0.5047] | it/evals=1150/14212 eff=8.3261% N=400 Have 2 modes Volume: ~exp(-6.89) * Expected Volume: exp(-2.92) Quality: correlation length: 259 (+) positive degeneracy between param2 and param0: rho=0.75 param0: +0.0| 1111111111111111111 22222222222222222 | +1.0 param1: +0.0| 1111111111111111 1 222222222222222222 | +1.0 param2: +0.0| 111111111111111111 22222222222222222 | +1.0 Z=-4.5(32.89%) | Like=-1.65..-0.03 [-30.6766..-0.5047] | it/evals=1170/14452 eff=8.3262% N=400 Z=-4.4(35.29%) | Like=-1.54..-0.03 [-30.6766..-0.5047] | it/evals=1200/14812 eff=8.3264% N=400 Z=-4.3(39.18%) | Like=-1.42..-0.03 [-30.6766..-0.5047] | it/evals=1250/15412 eff=8.3267% N=400 Have 2 modes Volume: ~exp(-6.89) Expected Volume: exp(-3.15) Quality: correlation length: 259 (+) positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 1111111111111111 22222222222222222 | +1.0 param1: +0.0| 1111111111111111 22222222222222222 | +1.0 param2: +0.0| 11111111111111111 2222222222222222 | +1.0 Z=-4.2(43.12%) | Like=-1.31..-0.03 [-30.6766..-0.5047] | it/evals=1300/16012 eff=8.3269% N=400 Have 2 modes Volume: ~exp(-7.37) * Expected Volume: exp(-3.37) Quality: correlation length: 259 (+) param0: +0.0| 1111111111111111 222222222222222 | +1.0 param1: +0.0| 11111111111111 222222222222222 | +1.0 param2: +0.0| 1111111111111111 222222222222222 | +1.0 Z=-4.1(47.09%) | Like=-1.21..-0.03 [-30.6766..-0.5047] | it/evals=1350/16612 eff=8.3272% N=400 Z=-4.1(50.85%) | Like=-1.12..-0.03 [-30.6766..-0.5047] | it/evals=1400/17212 eff=8.3274% N=400 Have 2 modes Volume: ~exp(-7.63) * Expected Volume: exp(-3.60) Quality: correlation length: 259 (+) param0: +0.0| 11111111111111 222222222222222 | +1.0 param1: +0.0| 11111111111111 222222222222222 | +1.0 param2: +0.0| 111111111111111 222222222222222 | +1.0 Z=-4.0(53.82%) | Like=-1.04..-0.03 [-30.6766..-0.5047] | it/evals=1440/17692 eff=8.3276% N=400 Z=-4.0(54.48%) | Like=-1.01..-0.03 [-30.6766..-0.5047] | it/evals=1450/17812 eff=8.3333% N=400 Z=-3.9(58.09%) | Like=-0.94..-0.03 [-30.6766..-0.5047] | it/evals=1500/18412 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.19) * Expected Volume: exp(-3.82) Quality: correlation length: 259 (+) param0: +0.0| 1111111111111 222222222222 2 | +1.0 param1: +0.0| 1111111111111 2222222222222 | +1.0 param2: +0.0| 11111111111111 2222222222222 | +1.0 Z=-3.9(60.25%) | Like=-0.88..-0.03 [-30.6766..-0.5047] | it/evals=1530/18772 eff=8.3333% N=400 Z=-3.9(61.68%) | Like=-0.85..-0.03 [-30.6766..-0.5047] | it/evals=1550/19012 eff=8.3333% N=400 Z=-3.8(64.92%) | Like=-0.76..-0.03 [-30.6766..-0.5047] | it/evals=1600/19612 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.19) Expected Volume: exp(-4.05) Quality: correlation length: 259 (+) param0: +0.0| 1111111111111 222222222220 | +1.0 param1: +0.0| 111111111111 2222222222222 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-3.8(67.97%) | Like=-0.70..-0.03 [-30.6766..-0.5047] | it/evals=1650/20212 eff=8.3333% N=400 Z=-3.7(70.93%) | Like=-0.65..-0.03 [-30.6766..-0.5047] | it/evals=1700/20812 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.19) Expected Volume: exp(-4.27) Quality: correlation length: 259 (+) param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 011111111111 222222222220 | +1.0 Z=-3.7(73.50%) | Like=-0.60..-0.03 [-30.6766..-0.5047] | it/evals=1750/21412 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.88) * Expected Volume: exp(-4.50) Quality: correlation length: 259 (+) param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.7(76.00%) | Like=-0.55..-0.03 [-30.6766..-0.5047] | it/evals=1800/22012 eff=8.3333% N=400 Z=-3.6(78.28%) | Like=-0.51..-0.03 [-30.6766..-0.5047] | it/evals=1850/22612 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-8.88) Expected Volume: exp(-4.73) Quality: correlation length: 259 (+) param0: +0.0| +0.2 1111111111 2222222222 +0.8 | +1.0 param1: +0.0| 01111111110 22222222222 +0.8 | +1.0 param2: +0.0| 1111111111 22222222222 +0.8 | +1.0 Z=-3.6(80.31%) | Like=-0.47..-0.03 [-0.4651..-0.4650]*| it/evals=1900/23213 eff=8.3195% N=400 Z=-3.6(82.25%) | Like=-0.43..-0.00 [-0.4271..-0.4263]*| it/evals=1950/23813 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.29) * Expected Volume: exp(-4.95) Quality: correlation length: 259 (+) param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 Z=-3.6(83.37%) | Like=-0.41..-0.00 [-0.4087..-0.4077]*| it/evals=1980/24173 eff=8.3333% N=400 Z=-3.6(84.05%) | Like=-0.40..-0.00 [-0.3983..-0.3975]*| it/evals=2000/24413 eff=8.3333% N=400 Z=-3.6(85.66%) | Like=-0.36..-0.00 [-0.3617..-0.3609]*| it/evals=2050/25013 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.29) * Expected Volume: exp(-5.18) Quality: correlation length: 259 (+) param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 Z=-3.5(86.28%) | Like=-0.35..-0.00 [-0.3487..-0.3486]*| it/evals=2070/25253 eff=8.3333% N=400 Z=-3.5(87.14%) | Like=-0.33..-0.00 [-0.3322..-0.3321]*| it/evals=2100/25613 eff=8.3333% N=400 Z=-3.5(88.46%) | Like=-0.31..-0.00 [-0.3068..-0.3020]*| it/evals=2150/26213 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-9.83) * Expected Volume: exp(-5.40) Quality: correlation length: 259 (+) param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 Z=-3.5(88.70%) | Like=-0.29..-0.00 [-0.2935..-0.2929]*| it/evals=2160/26333 eff=8.3333% N=400 Z=-3.5(89.66%) | Like=-0.28..-0.00 [-0.2755..-0.2749]*| it/evals=2200/26813 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.17) * Expected Volume: exp(-5.63) Quality: correlation length: 259 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 Z=-3.5(90.76%) | Like=-0.25..-0.00 [-0.2534..-0.2524]*| it/evals=2250/27413 eff=8.3333% N=400 Z=-3.5(91.75%) | Like=-0.23..-0.00 [-0.2319..-0.2309]*| it/evals=2300/28013 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.17) Expected Volume: exp(-5.85) Quality: correlation length: 259 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(92.64%) | Like=-0.21..-0.00 [-0.2107..-0.2106]*| it/evals=2350/28613 eff=8.3333% N=400 Z=-3.5(93.44%) | Like=-0.20..-0.00 [-0.1990..-0.1987]*| it/evals=2400/29213 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.23) * Expected Volume: exp(-6.08) Quality: correlation length: 259 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(93.88%) | Like=-0.19..-0.00 [-0.1901..-0.1899]*| it/evals=2430/29574 eff=8.3102% N=400 Z=-3.5(94.16%) | Like=-0.18..-0.00 [-0.1839..-0.1838]*| it/evals=2450/29814 eff=8.3333% N=400 Z=-3.4(94.80%) | Like=-0.17..-0.00 [-0.1674..-0.1673]*| it/evals=2500/30414 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.27) * Expected Volume: exp(-6.30) Quality: correlation length: 259 (+) param0: +0.0| +0.2 111111 2222222 +0.8 | +1.0 param1: +0.0| +0.3 111111 2222222 +0.7 | +1.0 param2: +0.0| +0.3 1111111 2222222 +0.8 | +1.0 Z=-3.4(95.04%) | Like=-0.16..-0.00 [-0.1631..-0.1627]*| it/evals=2520/30654 eff=8.3333% N=400 Z=-3.4(95.38%) | Like=-0.16..-0.00 [-0.1557..-0.1556]*| it/evals=2550/31014 eff=8.3333% N=400 Z=-3.4(95.89%) | Like=-0.14..-0.00 [-0.1427..-0.1426]*| it/evals=2600/31614 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.52) * Expected Volume: exp(-6.53) Quality: correlation length: 259 (+) param0: +0.0| +0.2 111111 222222 +0.8 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 111111 222222 +0.7 | +1.0 Z=-3.4(95.98%) | Like=-0.14..-0.00 [-0.1409..-0.1408]*| it/evals=2610/31734 eff=8.3333% N=400 Z=-3.4(96.35%) | Like=-0.13..-0.00 [-0.1338..-0.1338]*| it/evals=2650/32214 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-10.91) * Expected Volume: exp(-6.75) Quality: correlation length: 259 (+) param0: +0.0| +0.3 111111 222222 +0.7 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 11111 222222 +0.7 | +1.0 Z=-3.4(96.76%) | Like=-0.12..-0.00 [-0.1247..-0.1239]*| it/evals=2700/32814 eff=8.3333% N=400 Z=-3.4(97.12%) | Like=-0.11..-0.00 [-0.1148..-0.1148]*| it/evals=2750/33414 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.21) * Expected Volume: exp(-6.98) Quality: correlation length: 259 (+) param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(97.39%) | Like=-0.11..-0.00 [-0.1075..-0.1075]*| it/evals=2790/33894 eff=8.3333% N=400 Z=-3.4(97.45%) | Like=-0.11..-0.00 [-0.1063..-0.1063]*| it/evals=2800/34014 eff=8.3333% N=400 Z=-3.4(97.74%) | Like=-0.10..-0.00 [-0.0990..-0.0988]*| it/evals=2850/34614 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.29) * Expected Volume: exp(-7.20) Quality: correlation length: 259 (+) param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(97.90%) | Like=-0.09..-0.00 [-0.0942..-0.0937]*| it/evals=2880/34974 eff=8.3333% N=400 Z=-3.4(98.00%) | Like=-0.09..-0.00 [-0.0901..-0.0898]*| it/evals=2900/35214 eff=8.3333% N=400 Z=-3.4(98.22%) | Like=-0.08..-0.00 [-0.0831..-0.0828]*| it/evals=2950/35814 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-11.29) Expected Volume: exp(-7.43) Quality: correlation length: 259 (+) param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(98.43%) | Like=-0.08..-0.00 [-0.0761..-0.0760]*| it/evals=3000/36414 eff=8.3333% N=400 Z=-3.4(98.60%) | Like=-0.07..-0.00 [-0.0711..-0.0711]*| it/evals=3050/37015 eff=8.3195% N=400 Have 2 modes Volume: ~exp(-11.92) * Expected Volume: exp(-7.65) Quality: correlation length: 259 (+) param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.4(98.64%) | Like=-0.07..-0.00 [-0.0700..-0.0699]*| it/evals=3060/37136 eff=8.2645% N=400 Z=-3.4(98.76%) | Like=-0.07..-0.00 [-0.0656..-0.0652]*| it/evals=3100/37616 eff=8.3333% N=400 Have 2 modes Volume: ~exp(-12.03) * Expected Volume: exp(-7.88) Quality: correlation length: 259 (+) param0: +0.0| +0.3 1111 2222 +0.7 | +1.0 param1: +0.0| +0.3 1111 2222 +0.7 | +1.0 param2: +0.0| +0.3 111 22222 +0.7 | +1.0 Z=-3.4(98.91%) | Like=-0.06..-0.00 [-0.0580..-0.0580]*| it/evals=3150/38216 eff=8.3333% N=400 [ultranest] Explored until L=-0.002 [ultranest] Likelihood function evaluations: 38648 [ultranest] logZ = -3.397 +- 0.05671 [ultranest] Effective samples strategy satisfied (ESS = 1830.5, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.14, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -3.396 +- 0.084 single instance: logZ = -3.396 +- 0.070 bootstrapped : logZ = -3.397 +- 0.084 tail : logZ = +- 0.010 insert order U test : converged: False correlation: 35.0 iterations param0 0.52 +- 0.21 param1 0.53 +- 0.21 param2 0.53 +- 0.23 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=412, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.68, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=1012, logz=-24.15, remainder_fraction=100.0000%, Lmin=-20.30, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=1492, logz=-20.33, remainder_fraction=100.0000%, Lmin=-16.37, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=1612, logz=-19.41, remainder_fraction=100.0000%, Lmin=-15.70, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=2212, logz=-16.51, remainder_fraction=99.9998%, Lmin=-13.13, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=2572, logz=-14.79, remainder_fraction=99.9987%, Lmin=-11.44, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=2812, logz=-13.99, remainder_fraction=99.9971%, Lmin=-10.81, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=3412, logz=-12.42, remainder_fraction=99.9875%, Lmin=-9.35, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=3652, logz=-11.82, remainder_fraction=99.9786%, Lmin=-8.72, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=4012, logz=-11.02, remainder_fraction=99.9544%, Lmin=-7.94, Lmax=-0.08 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=4612, logz=-9.96, remainder_fraction=99.8720%, Lmin=-7.09, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=4732, logz=-9.78, remainder_fraction=99.8480%, Lmin=-6.96, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=5212, logz=-9.16, remainder_fraction=99.7116%, Lmin=-6.34, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=5812, logz=-8.48, remainder_fraction=99.3903%, Lmin=-5.84, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=6412, logz=-7.95, remainder_fraction=98.9755%, Lmin=-5.33, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=6892, logz=-7.58, remainder_fraction=98.4889%, Lmin=-5.00, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=7012, logz=-7.50, remainder_fraction=98.3817%, Lmin=-4.93, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=7612, logz=-7.10, remainder_fraction=97.6281%, Lmin=-4.50, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=7972, logz=-6.89, remainder_fraction=97.0237%, Lmin=-4.32, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=8212, logz=-6.76, remainder_fraction=96.5641%, Lmin=-4.15, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=8812, logz=-6.44, remainder_fraction=95.2252%, Lmin=-3.80, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=9412, logz=-6.13, remainder_fraction=93.3247%, Lmin=-3.37, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=10012, logz=-5.84, remainder_fraction=90.9428%, Lmin=-3.07, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=10612, logz=-5.59, remainder_fraction=88.2170%, Lmin=-2.81, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=11212, logz=-5.36, remainder_fraction=85.3916%, Lmin=-2.60, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=11812, logz=-5.16, remainder_fraction=82.4791%, Lmin=-2.36, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=12412, logz=-4.98, remainder_fraction=79.0006%, Lmin=-2.15, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=13012, logz=-4.82, remainder_fraction=75.4711%, Lmin=-2.01, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=13612, logz=-4.68, remainder_fraction=71.8621%, Lmin=-1.87, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=14212, logz=-4.55, remainder_fraction=68.6860%, Lmin=-1.70, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=14452, logz=-4.50, remainder_fraction=67.1111%, Lmin=-1.65, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=14812, logz=-4.43, remainder_fraction=64.7066%, Lmin=-1.54, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=15412, logz=-4.33, remainder_fraction=60.8188%, Lmin=-1.42, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=16012, logz=-4.23, remainder_fraction=56.8792%, Lmin=-1.31, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=16612, logz=-4.15, remainder_fraction=52.9148%, Lmin=-1.21, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=17212, logz=-4.07, remainder_fraction=49.1457%, Lmin=-1.12, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=17692, logz=-4.01, remainder_fraction=46.1834%, Lmin=-1.04, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=17812, logz=-4.00, remainder_fraction=45.5181%, Lmin=-1.01, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=18412, logz=-3.94, remainder_fraction=41.9073%, Lmin=-0.94, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=18772, logz=-3.90, remainder_fraction=39.7520%, Lmin=-0.88, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=19012, logz=-3.88, remainder_fraction=38.3214%, Lmin=-0.85, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=19612, logz=-3.83, remainder_fraction=35.0763%, Lmin=-0.76, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=20212, logz=-3.78, remainder_fraction=32.0317%, Lmin=-0.70, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=20812, logz=-3.74, remainder_fraction=29.0732%, Lmin=-0.65, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=21412, logz=-3.71, remainder_fraction=26.5007%, Lmin=-0.60, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=22012, logz=-3.67, remainder_fraction=23.9962%, Lmin=-0.55, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=22612, logz=-3.64, remainder_fraction=21.7180%, Lmin=-0.51, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=23213, logz=-3.62, remainder_fraction=19.6866%, Lmin=-0.47, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=23813, logz=-3.59, remainder_fraction=17.7493%, Lmin=-0.43, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=24173, logz=-3.58, remainder_fraction=16.6316%, Lmin=-0.41, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=24413, logz=-3.57, remainder_fraction=15.9487%, Lmin=-0.40, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=25013, logz=-3.55, remainder_fraction=14.3408%, Lmin=-0.36, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=25253, logz=-3.54, remainder_fraction=13.7241%, Lmin=-0.35, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=25613, logz=-3.53, remainder_fraction=12.8648%, Lmin=-0.33, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=26213, logz=-3.52, remainder_fraction=11.5425%, Lmin=-0.31, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=26333, logz=-3.52, remainder_fraction=11.2958%, Lmin=-0.29, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=26813, logz=-3.51, remainder_fraction=10.3358%, Lmin=-0.28, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=27413, logz=-3.49, remainder_fraction=9.2433%, Lmin=-0.25, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=28013, logz=-3.48, remainder_fraction=8.2545%, Lmin=-0.23, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=28613, logz=-3.47, remainder_fraction=7.3640%, Lmin=-0.21, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=29213, logz=-3.46, remainder_fraction=6.5639%, Lmin=-0.20, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=29574, logz=-3.46, remainder_fraction=6.1246%, Lmin=-0.19, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=29814, logz=-3.46, remainder_fraction=5.8446%, Lmin=-0.18, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=30414, logz=-3.45, remainder_fraction=5.1969%, Lmin=-0.17, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=30654, logz=-3.45, remainder_fraction=4.9634%, Lmin=-0.16, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=31014, logz=-3.44, remainder_fraction=4.6248%, Lmin=-0.16, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=31614, logz=-3.44, remainder_fraction=4.1096%, Lmin=-0.14, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=31734, logz=-3.44, remainder_fraction=4.0163%, Lmin=-0.14, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=32214, logz=-3.43, remainder_fraction=3.6522%, Lmin=-0.13, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=32814, logz=-3.43, remainder_fraction=3.2435%, Lmin=-0.12, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=33414, logz=-3.43, remainder_fraction=2.8777%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=33894, logz=-3.42, remainder_fraction=2.6131%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=34014, logz=-3.42, remainder_fraction=2.5516%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=34614, logz=-3.42, remainder_fraction=2.2626%, Lmin=-0.10, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2880, ncalls=34974, logz=-3.42, remainder_fraction=2.1036%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2900, ncalls=35214, logz=-3.42, remainder_fraction=2.0041%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2950, ncalls=35814, logz=-3.41, remainder_fraction=1.7764%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3000, ncalls=36414, logz=-3.41, remainder_fraction=1.5748%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3050, ncalls=37015, logz=-3.41, remainder_fraction=1.3950%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3060, ncalls=37136, logz=-3.41, remainder_fraction=1.3618%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3100, ncalls=37616, logz=-3.41, remainder_fraction=1.2356%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3150, ncalls=38216, logz=-3.41, remainder_fraction=1.0939%, Lmin=-0.06, Lmax=-0.00 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=-0.002 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 38648 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -3.397 +- 0.05671 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1830.5, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.08 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.14, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_stepsampling.py::test_stepsampler_cubeslice | 5.04 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.16) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.0000|***************************************************| +1.0000 param2: +0.000|***************************************************| +1.000 Z=-inf(0.00%) | Like=-30.68..-0.33 [-30.6766..-0.5047] | it/evals=0/403 eff=0.0000% N=400 Z=-24.1(0.00%) | Like=-20.28..-0.33 [-30.6766..-0.5047] | it/evals=50/622 eff=22.5225% N=400 Mono-modal Volume: ~exp(-4.36) * Expected Volume: exp(-0.23) Quality: correlation length: 22 (-) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-20.2(0.00%) | Like=-16.37..-0.33 [-30.6766..-0.5047] | it/evals=90/803 eff=22.3325% N=400 Z=-19.4(0.00%) | Like=-15.82..-0.33 [-30.6766..-0.5047] | it/evals=100/854 eff=22.0264% N=400 Z=-16.6(0.00%) | Like=-13.17..-0.02 [-30.6766..-0.5047] | it/evals=150/1116 eff=20.9497% N=400 Mono-modal Volume: ~exp(-4.37) * Expected Volume: exp(-0.45) Quality: correlation length: 22 (-) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-15.0(0.00%) | Like=-11.69..-0.02 [-30.6766..-0.5047] | it/evals=180/1281 eff=20.4313% N=400 Z=-14.3(0.00%) | Like=-11.29..-0.02 [-30.6766..-0.5047] | it/evals=200/1389 eff=20.2224% N=400 Z=-12.8(0.01%) | Like=-9.82..-0.02 [-30.6766..-0.5047] | it/evals=250/1683 eff=19.4856% N=400 Mono-modal Volume: ~exp(-4.79) * Expected Volume: exp(-0.67) Quality: correlation length: 189 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-12.3(0.02%) | Like=-9.25..-0.02 [-30.6766..-0.5047] | it/evals=270/1808 eff=19.1761% N=400 Z=-11.5(0.03%) | Like=-8.31..-0.02 [-30.6766..-0.5047] | it/evals=300/2003 eff=18.7149% N=400 Z=-10.2(0.12%) | Like=-7.15..-0.02 [-30.6766..-0.5047] | it/evals=350/2363 eff=17.8299% N=400 Mono-modal Volume: ~exp(-5.01) * Expected Volume: exp(-0.90) Quality: correlation length: 189 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-10.0(0.15%) | Like=-7.01..-0.02 [-30.6766..-0.5047] | it/evals=360/2449 eff=17.5695% N=400 Z=-9.3(0.30%) | Like=-6.50..-0.02 [-30.6766..-0.5047] | it/evals=400/2761 eff=16.9420% N=400 Mono-modal Volume: ~exp(-5.37) * Expected Volume: exp(-1.12) Quality: correlation length: 189 (+) param0: +0.000|***************************************************| +1.000 param1: +0.000|* *************************************************| +1.000 param2: +0.00|***************************************************| +1.00 Z=-8.6(0.63%) | Like=-5.80..-0.02 [-30.6766..-0.5047] | it/evals=450/3183 eff=16.1696% N=400 Z=-8.0(1.19%) | Like=-5.29..-0.02 [-30.6766..-0.5047] | it/evals=500/3594 eff=15.6544% N=400 Mono-modal Volume: ~exp(-5.50) * Expected Volume: exp(-1.35) Quality: correlation length: 189 (+) param0: +0.00|***************************************************| +1.00 param1: +0.00| **************************************************| +1.00 param2: +0.00|* ************************************************ | +1.00 Z=-7.6(1.77%) | Like=-5.00..-0.02 [-30.6766..-0.5047] | it/evals=540/3966 eff=15.1430% N=400 Z=-7.5(1.92%) | Like=-4.88..-0.02 [-30.6766..-0.5047] | it/evals=550/4058 eff=15.0355% N=400 Z=-7.1(2.90%) | Like=-4.46..-0.02 [-30.6766..-0.5047] | it/evals=600/4511 eff=14.5950% N=400 Mono-modal Volume: ~exp(-6.10) * Expected Volume: exp(-1.57) Quality: correlation length: 189 (+) param0: +0.00| **************************************************| +1.00 param1: +0.00| *********************************************** | +1.00 param2: +0.00| ************************************************ | +1.00 Z=-6.9(3.66%) | Like=-4.30..-0.02 [-30.6766..-0.5047] | it/evals=630/4784 eff=14.3704% N=400 Z=-6.8(4.08%) | Like=-4.18..-0.02 [-30.6766..-0.5047] | it/evals=650/4969 eff=14.2263% N=400 Z=-6.5(5.59%) | Like=-3.86..-0.02 [-30.6766..-0.5047] | it/evals=700/5464 eff=13.8231% N=400 Mono-modal Volume: ~exp(-6.10) Expected Volume: exp(-1.80) Quality: correlation length: 189 (+) param0: +0.00| ********************************************** | +1.00 param1: +0.00| ******************************************** * | +1.00 param2: +0.00| *********************************************** | +1.00 Z=-6.2(7.12%) | Like=-3.52..-0.02 [-30.6766..-0.5047] | it/evals=750/5948 eff=13.5184% N=400 Z=-5.9(9.07%) | Like=-3.25..-0.02 [-30.6766..-0.5047] | it/evals=800/6425 eff=13.2780% N=400 Have 2 modes Volume: ~exp(-6.15) * Expected Volume: exp(-2.02) Quality: correlation length: 189 (+) param0: +0.00| 11111111111111111111122222222222222222222222 | +1.00 param1: +0.00| 1 111111111111111111112122222222222222222222 | +1.00 param2: +0.00| 111111111111111111111211222222222222222222222 | +1.00 Z=-5.9(9.49%) | Like=-3.20..-0.02 [-30.6766..-0.5047] | it/evals=810/6537 eff=13.1986% N=400 Z=-5.7(11.19%) | Like=-2.98..-0.02 [-30.6766..-0.5047] | it/evals=850/6951 eff=12.9751% N=400 Have 2 modes Volume: ~exp(-6.32) * Expected Volume: exp(-2.25) Quality: correlation length: 189 (+) positive degeneracy between param2 and param1: rho=0.76 param0: +0.00| 11111111111111111111112222222222222222222222 | +1.00 param1: +0.00| 111111111111111111112122222222222222222222 | +1.00 param2: +0.0| 111111111111111111111222222222222222222222 | +1.0 Z=-5.5(13.81%) | Like=-2.75..-0.02 [-30.6766..-0.5047] | it/evals=900/7450 eff=12.7660% N=400 Z=-5.3(16.87%) | Like=-2.55..-0.02 [-30.6766..-0.5047] | it/evals=950/7970 eff=12.5495% N=400 Have 2 modes Volume: ~exp(-6.77) * Expected Volume: exp(-2.47) Quality: correlation length: 189 (+) positive degeneracy between param2 and param1: rho=0.76 param0: +0.00| 111111111111111111111222222222222222222222 | +1.00 param1: +0.00| 1111111111111111111122222222222222222222 | +1.00 param2: +0.0| 11111111111111111111222222222222222222222 | +1.0 Z=-5.1(19.50%) | Like=-2.37..-0.02 [-30.6766..-0.5047] | it/evals=990/8396 eff=12.3812% N=400 Z=-5.1(20.29%) | Like=-2.32..-0.02 [-30.6766..-0.5047] | it/evals=1000/8495 eff=12.3533% N=400 Z=-5.0(23.45%) | Like=-2.16..-0.02 [-30.6766..-0.5047] | it/evals=1050/9040 eff=12.1528% N=400 Have 2 modes Volume: ~exp(-6.77) Expected Volume: exp(-2.70) Quality: correlation length: 189 (+) param0: +0.0| 111111111111111111 22222222222222222222 | +1.0 param1: +0.0| 1111111111111111111112222222222222222222 | +1.0 param2: +0.0| 1111111111111111111 20222222222222222222 | +1.0 Z=-4.8(27.34%) | Like=-1.96..-0.02 [-30.6766..-0.5047] | it/evals=1100/9580 eff=11.9826% N=400 Z=-4.7(30.73%) | Like=-1.82..-0.02 [-30.6766..-0.5047] | it/evals=1150/10105 eff=11.8496% N=400 Have 2 modes Volume: ~exp(-6.77) Expected Volume: exp(-2.92) Quality: correlation length: 189 (+) param0: +0.0| 11111111111111111 222222222222222222 | +1.0 param1: +0.0| 111111111111111111 022222222222222222 | +1.0 param2: +0.0| 111111111111111111 2022222222222222222 | +1.0 Z=-4.6(34.61%) | Like=-1.64..-0.02 [-30.6766..-0.5047] | it/evals=1200/10678 eff=11.6754% N=400 Z=-4.5(38.46%) | Like=-1.53..-0.02 [-30.6766..-0.5047] | it/evals=1250/11268 eff=11.5017% N=400 Have 2 modes Volume: ~exp(-7.11) * Expected Volume: exp(-3.15) Quality: correlation length: 189 (+) param0: +0.0| 11111111111111111 222222222222222222 | +1.0 param1: +0.0| 11111111111111111 2222222222222222 | +1.0 param2: +0.0| 11111111111111111 22222222222222222 | +1.0 Z=-4.4(39.23%) | Like=-1.51..-0.02 [-30.6766..-0.5047] | it/evals=1260/11377 eff=11.4785% N=400 Z=-4.4(42.26%) | Like=-1.43..-0.02 [-30.6766..-0.5047] | it/evals=1300/11843 eff=11.3607% N=400 Have 2 modes Volume: ~exp(-7.17) * Expected Volume: exp(-3.37) Quality: correlation length: 189 (+) param0: +0.0| 1111111111111111 22222222222222222 | +1.0 param1: +0.0| 11111111111111111 2222222222222222 | +1.0 param2: +0.0| 11111111111111111 22222222222222222 | +1.0 Z=-4.3(45.94%) | Like=-1.32..-0.02 [-30.6766..-0.5047] | it/evals=1350/12407 eff=11.2434% N=400 Z=-4.2(49.61%) | Like=-1.22..-0.02 [-30.6766..-0.5047] | it/evals=1400/12993 eff=11.1173% N=400 Have 2 modes Volume: ~exp(-7.67) * Expected Volume: exp(-3.60) Quality: correlation length: 189 (+) positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 111111111111111 222222222222222 | +1.0 param1: +0.0| 111111111111111 222222222222222 | +1.0 param2: +0.0| 111111111111111 222222222222222 | +1.0 Z=-4.1(52.55%) | Like=-1.13..-0.02 [-30.6766..-0.5047] | it/evals=1440/13482 eff=11.0075% N=400 Z=-4.1(53.35%) | Like=-1.12..-0.02 [-30.6766..-0.5047] | it/evals=1450/13614 eff=10.9732% N=400 Z=-4.1(56.74%) | Like=-1.02..-0.02 [-30.6766..-0.5047] | it/evals=1500/14232 eff=10.8444% N=400 Have 2 modes Volume: ~exp(-8.09) * Expected Volume: exp(-3.82) Quality: correlation length: 189 (+) positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 111111111111111 22222222222222 | +1.0 param1: +0.0| 11111111111111 222222222222222 | +1.0 param2: +0.0| 1111111111111 222222222222222 | +1.0 Z=-4.0(58.69%) | Like=-0.97..-0.02 [-30.6766..-0.5047] | it/evals=1530/14593 eff=10.7800% N=400 Z=-4.0(59.96%) | Like=-0.93..-0.02 [-30.6766..-0.5047] | it/evals=1550/14834 eff=10.7385% N=400 Z=-3.9(63.33%) | Like=-0.86..-0.02 [-30.6766..-0.5047] | it/evals=1600/15468 eff=10.6185% N=400 Have 2 modes Volume: ~exp(-8.09) Expected Volume: exp(-4.05) Quality: correlation length: 189 (+) param0: +0.0| 11111111111111 22222222222220 | +1.0 param1: +0.0| 1111111111111 22222222222222 | +1.0 param2: +0.0| 11111111111 2222222222222 | +1.0 Z=-3.9(66.58%) | Like=-0.80..-0.02 [-30.6766..-0.5047] | it/evals=1650/16093 eff=10.5142% N=400 Z=-3.9(69.47%) | Like=-0.74..-0.02 [-30.6766..-0.5047] | it/evals=1700/16732 eff=10.4090% N=400 Have 2 modes Volume: ~exp(-8.09) Expected Volume: exp(-4.27) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 011111111111 0222222222222 | +1.0 param1: +0.0| 011111111111 2222222222222 | +1.0 param2: +0.0| 11111111111 222222222222 | +1.0 Z=-3.8(72.08%) | Like=-0.67..-0.02 [-30.6766..-0.5047] | it/evals=1750/17351 eff=10.3239% N=400 Have 2 modes Volume: ~exp(-8.47) * Expected Volume: exp(-4.50) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.76 param0: +0.0| 11111111111 2222222222 +0.8 | +1.0 param1: +0.0| 111111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 222222222222 | +1.0 Z=-3.8(74.55%) | Like=-0.62..-0.01 [-30.6766..-0.5047] | it/evals=1800/17968 eff=10.2459% N=400 Z=-3.8(76.94%) | Like=-0.57..-0.01 [-30.6766..-0.5047] | it/evals=1850/18578 eff=10.1771% N=400 Have 2 modes Volume: ~exp(-8.91) * Expected Volume: exp(-4.73) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 11111111111 2222222222 +0.8 | +1.0 param1: +0.0| 11111111111 22222222222 +0.8 | +1.0 param2: +0.0| 1111111111 22222222222 +0.8 | +1.0 Z=-3.7(78.71%) | Like=-0.54..-0.01 [-30.6766..-0.5047] | it/evals=1890/19099 eff=10.1075% N=400 Z=-3.7(79.12%) | Like=-0.53..-0.01 [-30.6766..-0.5047] | it/evals=1900/19225 eff=10.0930% N=400 Z=-3.7(81.19%) | Like=-0.49..-0.01 [-0.4867..-0.4864]*| it/evals=1950/19868 eff=10.0164% N=400 Have 2 modes Volume: ~exp(-8.91) Expected Volume: exp(-4.95) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 1111111111 2222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 param2: +0.0| 1111111111 22222222222 +0.8 | +1.0 Z=-3.7(83.05%) | Like=-0.45..-0.01 [-0.4502..-0.4499]*| it/evals=2000/20495 eff=9.9527% N=400 Z=-3.7(84.71%) | Like=-0.42..-0.01 [-0.4167..-0.4167]*| it/evals=2050/21100 eff=9.9034% N=400 Have 2 modes Volume: ~exp(-9.07) * Expected Volume: exp(-5.18) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 2222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.7(85.32%) | Like=-0.40..-0.01 [-0.3999..-0.3998]*| it/evals=2070/21356 eff=9.8778% N=400 Z=-3.6(86.24%) | Like=-0.38..-0.01 [-0.3845..-0.3836]*| it/evals=2100/21727 eff=9.8467% N=400 Z=-3.6(87.63%) | Like=-0.35..-0.01 [-0.3542..-0.3539]*| it/evals=2150/22339 eff=9.7999% N=400 Have 2 modes Volume: ~exp(-9.81) * Expected Volume: exp(-5.40) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.77 param0: +0.0| +0.2 111111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.6(87.88%) | Like=-0.35..-0.01 [-0.3475..-0.3473]*| it/evals=2160/22477 eff=9.7839% N=400 Z=-3.6(88.87%) | Like=-0.33..-0.01 [-0.3264..-0.3257]*| it/evals=2200/22984 eff=9.7414% N=400 Have 2 modes Volume: ~exp(-9.81) Expected Volume: exp(-5.63) Quality: correlation length: 189 (+) positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 Z=-3.6(90.04%) | Like=-0.29..-0.01 [-0.2932..-0.2929]*| it/evals=2250/23621 eff=9.6895% N=400 Z=-3.6(91.07%) | Like=-0.27..-0.01 [-0.2680..-0.2680]*| it/evals=2300/24275 eff=9.6335% N=400 Have 2 modes Volume: ~exp(-9.94) * Expected Volume: exp(-5.85) Quality: correlation length: 189 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 22222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.6(91.85%) | Like=-0.25..-0.01 [-0.2525..-0.2517]*| it/evals=2340/24781 eff=9.5976% N=400 Z=-3.6(92.03%) | Like=-0.25..-0.01 [-0.2490..-0.2487]*| it/evals=2350/24904 eff=9.5903% N=400 Z=-3.6(92.88%) | Like=-0.23..-0.00 [-0.2261..-0.2258]*| it/evals=2400/25544 eff=9.5450% N=400 Have 2 modes Volume: ~exp(-10.17) * Expected Volume: exp(-6.08) Quality: correlation length: 189 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.6(93.36%) | Like=-0.22..-0.00 [-0.2162..-0.2162]*| it/evals=2430/25933 eff=9.5171% N=400 Z=-3.6(93.66%) | Like=-0.21..-0.00 [-0.2078..-0.2077]*| it/evals=2450/26182 eff=8.0321% N=400 Z=-3.5(94.34%) | Like=-0.19..-0.00 [-0.1915..-0.1915]*| it/evals=2500/26836 eff=7.6453% N=400 Have 2 modes Volume: ~exp(-10.54) * Expected Volume: exp(-6.30) Quality: correlation length: 189 (+) param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.5(94.60%) | Like=-0.18..-0.00 [-0.1833..-0.1832]*| it/evals=2520/27087 eff=7.9681% N=400 Z=-3.5(94.96%) | Like=-0.18..-0.00 [-0.1760..-0.1757]*| it/evals=2550/27459 eff=8.0645% N=400 Z=-3.5(95.52%) | Like=-0.16..-0.00 [-0.1638..-0.1637]*| it/evals=2600/28092 eff=7.8989% N=400 Have 2 modes Volume: ~exp(-10.59) * Expected Volume: exp(-6.53) Quality: correlation length: 189 (+) param0: +0.0| +0.3 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.3 1111111 2222222 +0.8 | +1.0 Z=-3.5(95.62%) | Like=-0.16..-0.00 [-0.1628..-0.1627]*| it/evals=2610/28211 eff=8.4034% N=400 Z=-3.5(96.02%) | Like=-0.15..-0.00 [-0.1520..-0.1519]*| it/evals=2650/28705 eff=8.0972% N=400 Have 2 modes Volume: ~exp(-11.06) * Expected Volume: exp(-6.75) Quality: correlation length: 189 (+) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| +0.3 111111 222222 +0.7 | +1.0 param1: +0.0| +0.3 11111 222222 +0.7 | +1.0 param2: +0.0| +0.3 111111 222222 +0.7 | +1.0 Z=-3.5(96.46%) | Like=-0.14..-0.00 [-0.1398..-0.1396]*| it/evals=2700/29308 eff=8.2919% N=400 Z=-3.5(96.86%) | Like=-0.13..-0.00 [-0.1294..-0.1292]*| it/evals=2750/29960 eff=7.6687% N=400 Have 2 modes Volume: ~exp(-11.27) * Expected Volume: exp(-6.98) Quality: correlation length: 189 (+) param0: +0.0| +0.3 111111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.14%) | Like=-0.12..-0.00 [-0.1201..-0.1200]*| it/evals=2790/30433 eff=8.4567% N=400 Z=-3.5(97.21%) | Like=-0.12..-0.00 [-0.1183..-0.1183]*| it/evals=2800/30572 eff=7.1942% N=400 Z=-3.5(97.53%) | Like=-0.11..-0.00 [-0.1081..-0.1080]*| it/evals=2850/31197 eff=8.0000% N=400 Have 2 modes Volume: ~exp(-11.43) * Expected Volume: exp(-7.20) Quality: correlation length: 189 (+) positive degeneracy between param2 and param0: rho=0.75 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(97.70%) | Like=-0.11..-0.00 [-0.1050..-0.1048]*| it/evals=2880/31574 eff=7.9576% N=400 Z=-3.5(97.81%) | Like=-0.10..-0.00 [-0.1015..-0.1013]*| it/evals=2900/31830 eff=7.8125% N=400 Z=-3.5(98.05%) | Like=-0.09..-0.00 [-0.0939..-0.0937]*| it/evals=2950/32444 eff=8.1433% N=400 Have 2 modes Volume: ~exp(-11.43) Expected Volume: exp(-7.43) Quality: correlation length: 189 (+) positive degeneracy between param2 and param0: rho=0.75 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.27%) | Like=-0.09..-0.00 [-0.0861..-0.0861]*| it/evals=3000/33081 eff=7.8493% N=400 Z=-3.5(98.47%) | Like=-0.08..-0.00 [-0.0779..-0.0779]*| it/evals=3050/33726 eff=7.7519% N=400 Have 2 modes Volume: ~exp(-12.12) * Expected Volume: exp(-7.65) Quality: correlation length: 189 (+) positive degeneracy between param2 and param0: rho=0.76 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.51%) | Like=-0.08..-0.00 [-0.0768..-0.0767]*| it/evals=3060/33856 eff=7.6923% N=400 Z=-3.5(98.64%) | Like=-0.07..-0.00 [-0.0726..-0.0723]*| it/evals=3100/34355 eff=8.0160% N=400 Have 2 modes Volume: ~exp(-12.12) Expected Volume: exp(-7.88) Quality: correlation length: 189 (+) positive degeneracy between param2 and param0: rho=0.76 param0: +0.0| +0.3 1111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.5(98.80%) | Like=-0.07..-0.00 [-0.0663..-0.0660]*| it/evals=3150/34994 eff=7.8247% N=400 Z=-3.5(98.94%) | Like=-0.06..-0.00 [-0.0615..-0.0614]*| it/evals=3200/35603 eff=8.2102% N=400 [ultranest] Explored until L=-0.0002 [ultranest] Likelihood function evaluations: 35907 [ultranest] logZ = -3.481 +- 0.05091 [ultranest] Effective samples strategy satisfied (ESS = 1879.0, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.14, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [ultranest] done iterating. logZ = -3.491 +- 0.136 single instance: logZ = -3.491 +- 0.071 bootstrapped : logZ = -3.481 +- 0.135 tail : logZ = +- 0.010 insert order U test : converged: False correlation: 16.0 iterations param0 0.52 +- 0.22 param1 0.53 +- 0.22 param2 0.53 +- 0.22 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=403, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.68, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=622, logz=-24.15, remainder_fraction=100.0000%, Lmin=-20.28, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=803, logz=-20.21, remainder_fraction=100.0000%, Lmin=-16.37, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=854, logz=-19.41, remainder_fraction=100.0000%, Lmin=-15.82, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=1116, logz=-16.57, remainder_fraction=99.9998%, Lmin=-13.17, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=180, ncalls=1281, logz=-15.03, remainder_fraction=99.9989%, Lmin=-11.69, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=1389, logz=-14.29, remainder_fraction=99.9978%, Lmin=-11.29, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=1683, logz=-12.78, remainder_fraction=99.9903%, Lmin=-9.82, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=1808, logz=-12.26, remainder_fraction=99.9839%, Lmin=-9.25, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=2003, logz=-11.45, remainder_fraction=99.9650%, Lmin=-8.31, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=2363, logz=-10.21, remainder_fraction=99.8793%, Lmin=-7.15, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=360, ncalls=2449, logz=-10.00, remainder_fraction=99.8532%, Lmin=-7.01, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=2761, logz=-9.30, remainder_fraction=99.6998%, Lmin=-6.50, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=3183, logz=-8.59, remainder_fraction=99.3699%, Lmin=-5.80, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=3594, logz=-8.00, remainder_fraction=98.8077%, Lmin=-5.29, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=3966, logz=-7.61, remainder_fraction=98.2320%, Lmin=-5.00, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=4058, logz=-7.53, remainder_fraction=98.0840%, Lmin=-4.88, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=4511, logz=-7.11, remainder_fraction=97.1040%, Lmin=-4.46, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=630, ncalls=4784, logz=-6.89, remainder_fraction=96.3421%, Lmin=-4.30, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=4969, logz=-6.76, remainder_fraction=95.9189%, Lmin=-4.18, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=5464, logz=-6.45, remainder_fraction=94.4093%, Lmin=-3.86, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=5948, logz=-6.18, remainder_fraction=92.8818%, Lmin=-3.52, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=6425, logz=-5.91, remainder_fraction=90.9290%, Lmin=-3.25, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=6537, logz=-5.87, remainder_fraction=90.5066%, Lmin=-3.20, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=6951, logz=-5.68, remainder_fraction=88.8135%, Lmin=-2.98, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=7450, logz=-5.47, remainder_fraction=86.1933%, Lmin=-2.75, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=7970, logz=-5.28, remainder_fraction=83.1275%, Lmin=-2.55, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=8396, logz=-5.15, remainder_fraction=80.4972%, Lmin=-2.37, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=8495, logz=-5.11, remainder_fraction=79.7125%, Lmin=-2.32, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=9040, logz=-4.95, remainder_fraction=76.5531%, Lmin=-2.16, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=9580, logz=-4.81, remainder_fraction=72.6550%, Lmin=-1.96, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=10105, logz=-4.68, remainder_fraction=69.2740%, Lmin=-1.82, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=10678, logz=-4.56, remainder_fraction=65.3864%, Lmin=-1.64, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=11268, logz=-4.46, remainder_fraction=61.5360%, Lmin=-1.53, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=11377, logz=-4.43, remainder_fraction=60.7666%, Lmin=-1.51, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=11843, logz=-4.36, remainder_fraction=57.7427%, Lmin=-1.43, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=12407, logz=-4.27, remainder_fraction=54.0592%, Lmin=-1.32, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=12993, logz=-4.19, remainder_fraction=50.3890%, Lmin=-1.22, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1440, ncalls=13482, logz=-4.14, remainder_fraction=47.4482%, Lmin=-1.13, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=13614, logz=-4.12, remainder_fraction=46.6489%, Lmin=-1.12, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=14232, logz=-4.06, remainder_fraction=43.2553%, Lmin=-1.02, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=14593, logz=-4.02, remainder_fraction=41.3082%, Lmin=-0.97, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=14834, logz=-4.00, remainder_fraction=40.0430%, Lmin=-0.93, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=15468, logz=-3.95, remainder_fraction=36.6692%, Lmin=-0.86, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=16093, logz=-3.90, remainder_fraction=33.4180%, Lmin=-0.80, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=16732, logz=-3.86, remainder_fraction=30.5296%, Lmin=-0.74, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=17351, logz=-3.82, remainder_fraction=27.9218%, Lmin=-0.67, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=17968, logz=-3.78, remainder_fraction=25.4504%, Lmin=-0.62, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=18578, logz=-3.75, remainder_fraction=23.0607%, Lmin=-0.57, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=19099, logz=-3.73, remainder_fraction=21.2894%, Lmin=-0.54, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=19225, logz=-3.73, remainder_fraction=20.8844%, Lmin=-0.53, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=19868, logz=-3.70, remainder_fraction=18.8074%, Lmin=-0.49, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=20495, logz=-3.68, remainder_fraction=16.9469%, Lmin=-0.45, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=21100, logz=-3.66, remainder_fraction=15.2851%, Lmin=-0.42, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=21356, logz=-3.65, remainder_fraction=14.6759%, Lmin=-0.40, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=21727, logz=-3.64, remainder_fraction=13.7644%, Lmin=-0.38, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=22339, logz=-3.62, remainder_fraction=12.3743%, Lmin=-0.35, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=22477, logz=-3.62, remainder_fraction=12.1191%, Lmin=-0.35, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=22984, logz=-3.61, remainder_fraction=11.1265%, Lmin=-0.33, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=23621, logz=-3.60, remainder_fraction=9.9644%, Lmin=-0.29, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=24275, logz=-3.58, remainder_fraction=8.9265%, Lmin=-0.27, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2340, ncalls=24781, logz=-3.58, remainder_fraction=8.1515%, Lmin=-0.25, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=24904, logz=-3.57, remainder_fraction=7.9653%, Lmin=-0.25, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=25544, logz=-3.57, remainder_fraction=7.1158%, Lmin=-0.23, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=25933, logz=-3.56, remainder_fraction=6.6411%, Lmin=-0.22, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=26182, logz=-3.56, remainder_fraction=6.3405%, Lmin=-0.21, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=26836, logz=-3.55, remainder_fraction=5.6599%, Lmin=-0.19, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=27087, logz=-3.55, remainder_fraction=5.4011%, Lmin=-0.18, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=27459, logz=-3.54, remainder_fraction=5.0372%, Lmin=-0.18, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=28092, logz=-3.54, remainder_fraction=4.4813%, Lmin=-0.16, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=28211, logz=-3.54, remainder_fraction=4.3780%, Lmin=-0.16, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=28705, logz=-3.53, remainder_fraction=3.9814%, Lmin=-0.15, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=29308, logz=-3.53, remainder_fraction=3.5412%, Lmin=-0.14, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=29960, logz=-3.52, remainder_fraction=3.1418%, Lmin=-0.13, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=30433, logz=-3.52, remainder_fraction=2.8565%, Lmin=-0.12, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=30572, logz=-3.52, remainder_fraction=2.7888%, Lmin=-0.12, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=31197, logz=-3.52, remainder_fraction=2.4744%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2880, ncalls=31574, logz=-3.51, remainder_fraction=2.3021%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2900, ncalls=31830, logz=-3.51, remainder_fraction=2.1940%, Lmin=-0.10, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2950, ncalls=32444, logz=-3.51, remainder_fraction=1.9472%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3000, ncalls=33081, logz=-3.51, remainder_fraction=1.7255%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3050, ncalls=33726, logz=-3.51, remainder_fraction=1.5299%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3060, ncalls=33856, logz=-3.51, remainder_fraction=1.4933%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3100, ncalls=34355, logz=-3.51, remainder_fraction=1.3559%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3150, ncalls=34994, logz=-3.50, remainder_fraction=1.2008%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3200, ncalls=35603, logz=-3.50, remainder_fraction=1.0623%, Lmin=-0.06, Lmax=-0.00 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=-0.0002 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 35907 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -3.481 +- 0.05091 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1879.0, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.14, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.07 bs:0.05 tail:0.01 total:0.05 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_stepsampling.py::test_stepsampler_regionslice | 5.21 | |
------------------------------Captured stdout call------------------------------ [ultranest] Sampling 400 live points from prior ... Mono-modal Volume: ~exp(-4.16) * Expected Volume: exp(0.00) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.0000|***************************************************| +1.0000 param2: +0.000|***************************************************| +1.000 Z=-inf(0.00%) | Like=-30.68..-0.33 [-30.6766..-0.5047] | it/evals=0/405 eff=0.0000% N=400 Z=-24.1(0.00%) | Like=-20.28..-0.33 [-30.6766..-0.5047] | it/evals=50/616 eff=23.1481% N=400 Mono-modal Volume: ~exp(-4.64) * Expected Volume: exp(-0.23) Quality: ok param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-20.3(0.00%) | Like=-16.37..-0.04 [-30.6766..-0.5047] | it/evals=90/795 eff=22.7848% N=400 Z=-19.4(0.00%) | Like=-15.80..-0.04 [-30.6766..-0.5047] | it/evals=100/834 eff=23.0415% N=400 Z=-16.6(0.00%) | Like=-13.24..-0.04 [-30.6766..-0.5047] | it/evals=150/1068 eff=22.4551% N=400 Mono-modal Volume: ~exp(-4.64) Expected Volume: exp(-0.45) Quality: ok param0: +0.00|***************************************************| +1.00 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-14.4(0.00%) | Like=-11.25..-0.04 [-30.6766..-0.5047] | it/evals=200/1317 eff=21.8103% N=400 Z=-12.8(0.01%) | Like=-9.64..-0.04 [-30.6766..-0.5047] | it/evals=250/1592 eff=20.9732% N=400 Mono-modal Volume: ~exp(-4.83) * Expected Volume: exp(-0.67) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.0000|***************************************************| +1.0000 Z=-12.2(0.02%) | Like=-9.11..-0.04 [-30.6766..-0.5047] | it/evals=270/1701 eff=20.7533% N=400 Z=-11.4(0.05%) | Like=-8.37..-0.04 [-30.6766..-0.5047] | it/evals=300/1859 eff=20.5620% N=400 Z=-10.3(0.12%) | Like=-7.50..-0.04 [-30.6766..-0.5047] | it/evals=350/2144 eff=20.0688% N=400 Mono-modal Volume: ~exp(-4.83) Expected Volume: exp(-0.90) Quality: ok param0: +0.000|**************** **********************************| +1.000 param1: +0.000|***************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-9.5(0.29%) | Like=-6.71..-0.04 [-30.6766..-0.5047] | it/evals=400/2480 eff=19.2308% N=400 Mono-modal Volume: ~exp(-5.11) * Expected Volume: exp(-1.12) Quality: ok param0: +0.000|***************************************************| +1.000 param1: +0.00|***************************************************| +1.00 param2: +0.000|***************************************************| +1.000 Z=-8.8(0.60%) | Like=-6.01..-0.04 [-30.6766..-0.5047] | it/evals=450/2808 eff=18.6877% N=400 Z=-8.2(1.13%) | Like=-5.54..-0.04 [-30.6766..-0.5047] | it/evals=500/3139 eff=18.2548% N=400 Mono-modal Volume: ~exp(-5.65) * Expected Volume: exp(-1.35) Quality: ok param0: +0.00|***************************************************| +1.00 param1: +0.000|* *************************************************| +1.000 param2: +0.000|***************************************************| +1.000 Z=-7.8(1.68%) | Like=-5.23..-0.04 [-30.6766..-0.5047] | it/evals=540/3447 eff=17.7223% N=400 Z=-7.7(1.81%) | Like=-5.18..-0.04 [-30.6766..-0.5047] | it/evals=550/3510 eff=17.6849% N=400 Z=-7.3(2.73%) | Like=-4.77..-0.04 [-30.6766..-0.5047] | it/evals=600/3895 eff=17.1674% N=400 Mono-modal Volume: ~exp(-5.65) Expected Volume: exp(-1.57) Quality: ok param0: +0.00|***************************************************| +1.00 param1: +0.00|* *************************************************| +1.00 param2: +0.000|***************************************************| +1.000 Z=-7.0(3.73%) | Like=-4.40..-0.04 [-30.6766..-0.5047] | it/evals=650/4253 eff=16.8700% N=400 Z=-6.7(4.97%) | Like=-4.14..-0.04 [-30.6766..-0.5047] | it/evals=700/4624 eff=16.5720% N=400 Mono-modal Volume: ~exp(-5.66) * Expected Volume: exp(-1.80) Quality: ok param0: +0.00| ************************************************ | +1.00 param1: +0.00| *********************************************** | +1.00 param2: +0.00| ************************************************* | +1.00 Z=-6.6(5.53%) | Like=-4.02..-0.04 [-30.6766..-0.5047] | it/evals=720/4784 eff=16.4234% N=400 Z=-6.4(6.53%) | Like=-3.86..-0.04 [-30.6766..-0.5047] | it/evals=750/5026 eff=16.2127% N=400 Z=-6.2(8.47%) | Like=-3.50..-0.04 [-30.6766..-0.5047] | it/evals=800/5418 eff=15.9426% N=400 Mono-modal Volume: ~exp(-6.05) * Expected Volume: exp(-2.02) Quality: ok param0: +0.00| ********************************************* * | +1.00 param1: +0.00| *********************************************** | +1.00 param2: +0.00| *********************************************** | +1.00 Z=-6.1(8.80%) | Like=-3.42..-0.04 [-30.6766..-0.5047] | it/evals=810/5489 eff=15.9167% N=400 Z=-5.9(10.55%) | Like=-3.22..-0.04 [-30.6766..-0.5047] | it/evals=850/5840 eff=15.6250% N=400 Mono-modal Volume: ~exp(-6.10) * Expected Volume: exp(-2.25) Quality: ok param0: +0.00| ******************************************* | +1.00 param1: +0.00| ********************************************* | +1.00 param2: +0.00| ******************************************** | +1.00 Z=-5.7(13.22%) | Like=-2.99..-0.03 [-30.6766..-0.5047] | it/evals=900/6318 eff=15.2078% N=400 Z=-5.5(15.68%) | Like=-2.79..-0.03 [-30.6766..-0.5047] | it/evals=950/6763 eff=14.9301% N=400 Have 2 modes Volume: ~exp(-6.59) * Expected Volume: exp(-2.47) Quality: ok positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 param0: +0.0| 111111111111111111111222222222222222222222 | +1.0 param1: +0.00| 11111111111111111111112222222222222222222222 | +1.00 param2: +0.00| 11111111111111111111111222222222222222222222 | +1.00 Z=-5.4(17.94%) | Like=-2.63..-0.03 [-30.6766..-0.5047] | it/evals=990/7181 eff=14.5996% N=400 Z=-5.4(18.44%) | Like=-2.60..-0.03 [-30.6766..-0.5047] | it/evals=1000/7298 eff=14.4970% N=400 Z=-5.2(21.39%) | Like=-2.41..-0.03 [-30.6766..-0.5047] | it/evals=1050/7840 eff=14.1129% N=400 Have 2 modes Volume: ~exp(-7.02) * Expected Volume: exp(-2.70) Quality: correlation length: 1074 (+) positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 11111111111111111111122222222222222222222 | +1.0 param1: +0.0| 11111111111111111111122222222222222222222 | +1.0 param2: +0.00| 111111111111111111111122222222222222222222 | +1.00 Z=-5.1(23.16%) | Like=-2.28..-0.03 [-30.6766..-0.5047] | it/evals=1080/8164 eff=13.9104% N=400 Z=-5.1(24.25%) | Like=-2.19..-0.03 [-30.6766..-0.5047] | it/evals=1100/8365 eff=13.8104% N=400 Z=-4.9(27.46%) | Like=-2.05..-0.03 [-30.6766..-0.5047] | it/evals=1150/8907 eff=13.5183% N=400 Have 2 modes Volume: ~exp(-7.09) * Expected Volume: exp(-2.92) Quality: correlation length: 48 (+) positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 11111111111111111111122222222222222222222 | +1.0 param1: +0.0| 1111111111111111111 2222222222222222222 | +1.0 param2: +0.0| 11111111111111111111222222222222222222222 | +1.0 Z=-4.9(28.99%) | Like=-1.99..-0.03 [-30.6766..-0.5047] | it/evals=1170/9135 eff=13.3944% N=400 Z=-4.8(31.14%) | Like=-1.93..-0.03 [-30.6766..-0.5047] | it/evals=1200/9445 eff=13.2670% N=400 Z=-4.7(34.73%) | Like=-1.79..-0.02 [-30.6766..-0.5047] | it/evals=1250/10035 eff=12.9735% N=400 Have 2 modes Volume: ~exp(-7.35) * Expected Volume: exp(-3.15) Quality: correlation length: 135 (-) positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 1111111111111111111 22222222222222222222 | +1.0 param1: +0.0| 1111111111111111111 2222222222222222222 | +1.0 param2: +0.0| 1111111111111111111 2222222222222222222 | +1.0 Z=-4.7(35.66%) | Like=-1.74..-0.02 [-30.6766..-0.5047] | it/evals=1260/10167 eff=12.9006% N=400 Z=-4.6(38.60%) | Like=-1.64..-0.02 [-30.6766..-0.5047] | it/evals=1300/10646 eff=12.6879% N=400 Have 2 modes Volume: ~exp(-7.44) * Expected Volume: exp(-3.37) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.77 param0: +0.0| 111111111111111111 222222222222222222 | +1.0 param1: +0.0| 11111111111111111 22222222222222222 | +1.0 param2: +0.0| 11111111111111111 222222222222222222 | +1.0 Z=-4.5(42.02%) | Like=-1.52..-0.02 [-30.6766..-0.5047] | it/evals=1350/11212 eff=12.4861% N=400 Z=-4.4(45.82%) | Like=-1.43..-0.02 [-30.6766..-0.5047] | it/evals=1400/11812 eff=12.2678% N=400 Have 2 modes Volume: ~exp(-7.44) Expected Volume: exp(-3.60) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 1111111111111111 02222222222222222 | +1.0 param1: +0.0| 11111111111111111 22222222222222222 | +1.0 param2: +0.0| 111111111111111 222222222222222 | +1.0 Z=-4.4(49.43%) | Like=-1.33..-0.02 [-30.6766..-0.5047] | it/evals=1450/12453 eff=12.0302% N=400 Z=-4.3(52.98%) | Like=-1.22..-0.02 [-30.6766..-0.5047] | it/evals=1500/13074 eff=11.8353% N=400 Have 2 modes Volume: ~exp(-7.71) * Expected Volume: exp(-3.82) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 1111111111111111 2222222222222222 | +1.0 param1: +0.0| 111111111111111 222222222222222 | +1.0 param2: +0.0| 111111111111111 222222222222222 | +1.0 Z=-4.3(54.74%) | Like=-1.17..-0.01 [-30.6766..-0.5047] | it/evals=1530/13459 eff=11.7161% N=400 Z=-4.2(56.18%) | Like=-1.12..-0.01 [-30.6766..-0.5047] | it/evals=1550/13686 eff=11.6664% N=400 Z=-4.2(59.50%) | Like=-1.03..-0.01 [-30.6766..-0.5047] | it/evals=1600/14331 eff=11.4852% N=400 Have 2 modes Volume: ~exp(-8.07) * Expected Volume: exp(-4.05) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 param0: +0.0| 111111111111111 222222222222222 | +1.0 param1: +0.0| 1111111111111 22222222222222 | +1.0 param2: +0.0| 1111111111111 222222222222222 | +1.0 Z=-4.2(60.74%) | Like=-0.99..-0.01 [-30.6766..-0.5047] | it/evals=1620/14589 eff=11.4173% N=400 Z=-4.1(62.59%) | Like=-0.93..-0.01 [-30.6766..-0.5047] | it/evals=1650/14955 eff=11.3363% N=400 Z=-4.1(65.55%) | Like=-0.86..-0.01 [-30.6766..-0.5047] | it/evals=1700/15607 eff=11.1791% N=400 Have 2 modes Volume: ~exp(-8.27) * Expected Volume: exp(-4.27) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.77 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 11111111111111 2222222222222 | +1.0 param1: +0.0| 1111111111111 2222222222222 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-4.1(66.14%) | Like=-0.85..-0.01 [-30.6766..-0.5047] | it/evals=1710/15724 eff=11.1590% N=400 Z=-4.0(68.40%) | Like=-0.80..-0.01 [-30.6766..-0.5047] | it/evals=1750/16217 eff=11.0640% N=400 Have 2 modes Volume: ~exp(-8.62) * Expected Volume: exp(-4.50) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.78 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| 1111111111111 222222222222 | +1.0 param1: +0.0| 1111111111111 222222222222 | +1.0 param2: +0.0| 1111111111111 2222222222222 | +1.0 Z=-4.0(71.29%) | Like=-0.72..-0.01 [-30.6766..-0.5047] | it/evals=1800/16837 eff=10.9509% N=400 Z=-4.0(73.93%) | Like=-0.68..-0.01 [-30.6766..-0.5047] | it/evals=1850/17456 eff=10.8466% N=400 Have 2 modes Volume: ~exp(-8.66) * Expected Volume: exp(-4.73) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.77 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 11111111111 22222222222 +0.8 | +1.0 param1: +0.0| 111111111111 22222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.9(75.76%) | Like=-0.62..-0.01 [-30.6766..-0.5047] | it/evals=1890/17958 eff=10.7643% N=400 Z=-3.9(76.24%) | Like=-0.61..-0.01 [-30.6766..-0.5047] | it/evals=1900/18097 eff=10.7363% N=400 Z=-3.9(78.48%) | Like=-0.56..-0.01 [-30.6766..-0.5047] | it/evals=1950/18738 eff=10.6337% N=400 Have 2 modes Volume: ~exp(-9.05) * Expected Volume: exp(-4.95) Quality: correlation length: 8 (-) positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 11111111111 2222222222 +0.8 | +1.0 param1: +0.0| 11111111111 2222222222 +0.8 | +1.0 param2: +0.0| 11111111111 22222222222 +0.8 | +1.0 Z=-3.9(79.71%) | Like=-0.53..-0.01 [-30.6766..-0.5047] | it/evals=1980/19119 eff=10.5775% N=400 Z=-3.9(80.48%) | Like=-0.52..-0.01 [-30.6766..-0.5047] | it/evals=2000/19373 eff=10.5413% N=400 Z=-3.9(82.33%) | Like=-0.48..-0.01 [-0.4752..-0.4746]*| it/evals=2050/19999 eff=10.4597% N=400 Have 2 modes Volume: ~exp(-9.24) * Expected Volume: exp(-5.18) Quality: correlation length: 8 (-) positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| 1111111111 222222222 +0.8 | +1.0 param1: +0.0| 1111111111 222222222 +0.8 | +1.0 param2: +0.0| 1111111111 222222222 +0.8 | +1.0 Z=-3.8(83.03%) | Like=-0.46..-0.01 [-0.4596..-0.4565]*| it/evals=2070/20256 eff=10.4251% N=400 Z=-3.8(84.08%) | Like=-0.42..-0.01 [-0.4189..-0.4183]*| it/evals=2100/20629 eff=10.3811% N=400 Z=-3.8(85.69%) | Like=-0.39..-0.01 [-0.3921..-0.3908]*| it/evals=2150/21265 eff=10.3043% N=400 Have 2 modes Volume: ~exp(-9.72) * Expected Volume: exp(-5.40) Quality: correlation length: 8 (-) positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| 1111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.8(86.00%) | Like=-0.39..-0.01 [-0.3866..-0.3848]*| it/evals=2160/21380 eff=10.2955% N=400 Z=-3.8(87.16%) | Like=-0.36..-0.01 [-0.3608..-0.3607]*| it/evals=2200/21905 eff=10.2302% N=400 Have 2 modes Volume: ~exp(-9.78) * Expected Volume: exp(-5.63) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.77 param0: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param1: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 222222222 +0.8 | +1.0 Z=-3.8(88.50%) | Like=-0.33..-0.01 [-0.3335..-0.3322]*| it/evals=2250/22558 eff=10.1543% N=400 Z=-3.8(89.69%) | Like=-0.31..-0.01 [-0.3097..-0.3091]*| it/evals=2300/23168 eff=10.1019% N=400 Have 2 modes Volume: ~exp(-9.78) Expected Volume: exp(-5.85) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.77 positive degeneracy between param2 and param1: rho=0.78 param0: +0.0| +0.2 111111110 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 111111111 22222222 +0.8 | +1.0 Z=-3.8(90.77%) | Like=-0.28..-0.01 [-0.2834..-0.2832]*| it/evals=2350/23818 eff=10.0350% N=400 Z=-3.7(91.75%) | Like=-0.26..-0.01 [-0.2587..-0.2581]*| it/evals=2400/24467 eff=9.9722% N=400 Have 2 modes Volume: ~exp(-10.17) * Expected Volume: exp(-6.08) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.77 param0: +0.0| +0.2 11111111 22222222 +0.8 | +1.0 param1: +0.0| +0.2 11111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.7(92.29%) | Like=-0.25..-0.01 [-0.2484..-0.2484]*| it/evals=2430/24841 eff=9.9423% N=400 Z=-3.7(92.63%) | Like=-0.24..-0.01 [-0.2400..-0.2397]*| it/evals=2450/25079 eff=9.9275% N=400 Z=-3.7(93.42%) | Like=-0.22..-0.01 [-0.2192..-0.2186]*| it/evals=2500/25714 eff=9.8760% N=400 Have 2 modes Volume: ~exp(-10.30) * Expected Volume: exp(-6.30) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.7(93.71%) | Like=-0.21..-0.01 [-0.2146..-0.2144]*| it/evals=2520/25973 eff=9.8541% N=400 Z=-3.7(94.12%) | Like=-0.20..-0.01 [-0.2019..-0.2019]*| it/evals=2550/26358 eff=9.8236% N=400 Z=-3.7(94.77%) | Like=-0.19..-0.01 [-0.1918..-0.1917]*| it/evals=2600/27022 eff=9.7664% N=400 Have 2 modes Volume: ~exp(-10.58) * Expected Volume: exp(-6.53) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.77 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param1: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.7(94.89%) | Like=-0.19..-0.01 [-0.1903..-0.1903]*| it/evals=2610/27150 eff=9.7570% N=400 Z=-3.7(95.34%) | Like=-0.18..-0.01 [-0.1772..-0.1771]*| it/evals=2650/27643 eff=9.7273% N=400 Have 2 modes Volume: ~exp(-10.81) * Expected Volume: exp(-6.75) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| +0.2 1111111 2222222 +0.7 | +1.0 param1: +0.0| +0.2 1111111 222222 +0.8 | +1.0 param2: +0.0| +0.2 1111111 2222222 +0.8 | +1.0 Z=-3.7(95.86%) | Like=-0.16..-0.00 [-0.1648..-0.1647]*| it/evals=2700/28286 eff=7.7760% N=400 Z=-3.7(96.31%) | Like=-0.15..-0.00 [-0.1512..-0.1511]*| it/evals=2750/28925 eff=7.8247% N=400 Have 2 modes Volume: ~exp(-10.92) * Expected Volume: exp(-6.98) Quality: correlation length: 8 (-) positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| +0.2 111111 22222 +0.7 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 1111111 222222 +0.7 | +1.0 Z=-3.7(96.65%) | Like=-0.14..-0.00 [-0.1416..-0.1414]*| it/evals=2790/29423 eff=8.0321% N=400 Z=-3.7(96.72%) | Like=-0.14..-0.00 [-0.1395..-0.1393]*| it/evals=2800/29544 eff=8.2645% N=400 Z=-3.7(97.09%) | Like=-0.13..-0.00 [-0.1293..-0.1292]*| it/evals=2850/30160 eff=8.1169% N=400 Have 2 modes Volume: ~exp(-11.15) * Expected Volume: exp(-7.20) Quality: correlation length: 8 (-) positive degeneracy between param2 and param1: rho=0.75 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 111111 222222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.7(97.29%) | Like=-0.12..-0.00 [-0.1208..-0.1206]*| it/evals=2880/30554 eff=7.6142% N=400 Z=-3.7(97.42%) | Like=-0.12..-0.00 [-0.1160..-0.1160]*| it/evals=2900/30811 eff=7.7821% N=400 Z=-3.7(97.71%) | Like=-0.11..-0.00 [-0.1074..-0.1074]*| it/evals=2950/31427 eff=8.1169% N=400 Have 2 modes Volume: ~exp(-11.23) * Expected Volume: exp(-7.43) Quality: correlation length: 8 (-) positive degeneracy between param2 and param1: rho=0.77 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.7(97.82%) | Like=-0.10..-0.00 [-0.1043..-0.1039]*| it/evals=2970/31688 eff=7.6628% N=400 Z=-3.7(97.97%) | Like=-0.10..-0.00 [-0.0986..-0.0986]*| it/evals=3000/32079 eff=7.6726% N=400 Z=-3.7(98.20%) | Like=-0.09..-0.00 [-0.0918..-0.0917]*| it/evals=3050/32694 eff=8.1301% N=400 Have 2 modes Volume: ~exp(-11.53) * Expected Volume: exp(-7.65) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.3 11111 22222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.7(98.24%) | Like=-0.09..-0.00 [-0.0893..-0.0893]*| it/evals=3060/32822 eff=7.8125% N=400 Z=-3.7(98.40%) | Like=-0.08..-0.00 [-0.0827..-0.0821]*| it/evals=3100/33345 eff=7.6482% N=400 Have 2 modes Volume: ~exp(-11.53) Expected Volume: exp(-7.88) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.75 positive degeneracy between param2 and param0: rho=0.75 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.3 11111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.7(98.58%) | Like=-0.08..-0.00 [-0.0763..-0.0762]*| it/evals=3150/33971 eff=7.9872% N=400 Z=-3.7(98.75%) | Like=-0.07..-0.00 [-0.0695..-0.0694]*| it/evals=3200/34611 eff=7.8125% N=400 Have 2 modes Volume: ~exp(-12.12) * Expected Volume: exp(-8.10) Quality: correlation length: 8 (-) positive degeneracy between param1 and param0: rho=0.77 positive degeneracy between param2 and param0: rho=0.76 positive degeneracy between param2 and param1: rho=0.76 param0: +0.0| +0.3 11111 2222 +0.7 | +1.0 param1: +0.0| +0.3 11111 22222 +0.7 | +1.0 param2: +0.0| +0.3 11111 22222 +0.7 | +1.0 Z=-3.7(98.86%) | Like=-0.07..-0.00 [-0.0653..-0.0653]*| it/evals=3240/35099 eff=8.1967% N=400 Z=-3.7(98.89%) | Like=-0.06..-0.00 [-0.0642..-0.0641]*| it/evals=3250/35220 eff=8.2645% N=400 [ultranest] Explored until L=-0.0003 [ultranest] Likelihood function evaluations: 35775 [ultranest] logZ = -3.659 +- 0.0619 [ultranest] Effective samples strategy satisfied (ESS = 1962.9, need >400) [ultranest] Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [ultranest] Evidency uncertainty strategy is satisfied (dlogz=0.13, need <0.5) [ultranest] logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [ultranest] done iterating. logZ = -3.663 +- 0.134 single instance: logZ = -3.663 +- 0.072 bootstrapped : logZ = -3.659 +- 0.133 tail : logZ = +- 0.010 insert order U test : converged: False correlation: 8.0 iterations param0 0.51 +- 0.22 param1 0.50 +- 0.22 param2 0.50 +- 0.22 -------------------------------Captured log call-------------------------------- [35mDEBUG [0m ultranest:integrator.py:1016 ReactiveNestedSampler: dims=3+0, resume=False, log_dir=None, backend=hdf5, vectorized=True, nbootstraps=30, ndraw=128..65536 [32mINFO [0m ultranest:integrator.py:1288 Sampling 400 live points from prior ... [35mDEBUG [0m ultranest:integrator.py:2194 run_iter dlogz=0.5, dKL=0.5, frac_remain=0.01, Lepsilon=0.0010, min_ess=400 [35mDEBUG [0m ultranest:integrator.py:2198 max_iters=-1, max_ncalls=-1, max_num_improvement_loops=-1, min_num_live_points=400, cluster_num_live_points=40 [35mDEBUG [0m ultranest:integrator.py:2255 minimal_widths_sequence: [(-inf, 400.0), (inf, 400.0)] [35mDEBUG [0m ultranest:integrator.py:2406 iteration=0, ncalls=405, logz=-inf, remainder_fraction=100.0000%, Lmin=-30.68, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=50, ncalls=616, logz=-24.15, remainder_fraction=100.0000%, Lmin=-20.28, Lmax=-0.33 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=90, ncalls=795, logz=-20.27, remainder_fraction=100.0000%, Lmin=-16.37, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=100, ncalls=834, logz=-19.39, remainder_fraction=100.0000%, Lmin=-15.80, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=150, ncalls=1068, logz=-16.62, remainder_fraction=99.9997%, Lmin=-13.24, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=200, ncalls=1317, logz=-14.35, remainder_fraction=99.9975%, Lmin=-11.25, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=250, ncalls=1592, logz=-12.80, remainder_fraction=99.9880%, Lmin=-9.64, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=270, ncalls=1701, logz=-12.20, remainder_fraction=99.9784%, Lmin=-9.11, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=300, ncalls=1859, logz=-11.40, remainder_fraction=99.9541%, Lmin=-8.37, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=350, ncalls=2144, logz=-10.34, remainder_fraction=99.8753%, Lmin=-7.50, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=400, ncalls=2480, logz=-9.51, remainder_fraction=99.7074%, Lmin=-6.71, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=450, ncalls=2808, logz=-8.79, remainder_fraction=99.4041%, Lmin=-6.01, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=500, ncalls=3139, logz=-8.20, remainder_fraction=98.8728%, Lmin=-5.54, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=540, ncalls=3447, logz=-7.82, remainder_fraction=98.3214%, Lmin=-5.23, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=550, ncalls=3510, logz=-7.74, remainder_fraction=98.1867%, Lmin=-5.18, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=600, ncalls=3895, logz=-7.34, remainder_fraction=97.2706%, Lmin=-4.77, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=650, ncalls=4253, logz=-7.00, remainder_fraction=96.2743%, Lmin=-4.40, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=700, ncalls=4624, logz=-6.69, remainder_fraction=95.0292%, Lmin=-4.14, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=720, ncalls=4784, logz=-6.58, remainder_fraction=94.4742%, Lmin=-4.02, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=750, ncalls=5026, logz=-6.43, remainder_fraction=93.4680%, Lmin=-3.86, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=800, ncalls=5418, logz=-6.18, remainder_fraction=91.5253%, Lmin=-3.50, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=810, ncalls=5489, logz=-6.13, remainder_fraction=91.1969%, Lmin=-3.42, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=850, ncalls=5840, logz=-5.94, remainder_fraction=89.4468%, Lmin=-3.22, Lmax=-0.04 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=900, ncalls=6318, logz=-5.72, remainder_fraction=86.7809%, Lmin=-2.99, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=950, ncalls=6763, logz=-5.53, remainder_fraction=84.3241%, Lmin=-2.79, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=990, ncalls=7181, logz=-5.39, remainder_fraction=82.0584%, Lmin=-2.63, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1000, ncalls=7298, logz=-5.36, remainder_fraction=81.5576%, Lmin=-2.60, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1050, ncalls=7840, logz=-5.21, remainder_fraction=78.6083%, Lmin=-2.41, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1080, ncalls=8164, logz=-5.12, remainder_fraction=76.8432%, Lmin=-2.28, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1100, ncalls=8365, logz=-5.06, remainder_fraction=75.7518%, Lmin=-2.19, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1150, ncalls=8907, logz=-4.93, remainder_fraction=72.5433%, Lmin=-2.05, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1170, ncalls=9135, logz=-4.88, remainder_fraction=71.0098%, Lmin=-1.99, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1200, ncalls=9445, logz=-4.81, remainder_fraction=68.8642%, Lmin=-1.93, Lmax=-0.03 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1250, ncalls=10035, logz=-4.71, remainder_fraction=65.2730%, Lmin=-1.79, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1260, ncalls=10167, logz=-4.68, remainder_fraction=64.3421%, Lmin=-1.74, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1300, ncalls=10646, logz=-4.61, remainder_fraction=61.3984%, Lmin=-1.64, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1350, ncalls=11212, logz=-4.52, remainder_fraction=57.9774%, Lmin=-1.52, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1400, ncalls=11812, logz=-4.44, remainder_fraction=54.1787%, Lmin=-1.43, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1450, ncalls=12453, logz=-4.36, remainder_fraction=50.5724%, Lmin=-1.33, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1500, ncalls=13074, logz=-4.30, remainder_fraction=47.0192%, Lmin=-1.22, Lmax=-0.02 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1530, ncalls=13459, logz=-4.26, remainder_fraction=45.2560%, Lmin=-1.17, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1550, ncalls=13686, logz=-4.24, remainder_fraction=43.8209%, Lmin=-1.12, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1600, ncalls=14331, logz=-4.18, remainder_fraction=40.5046%, Lmin=-1.03, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1620, ncalls=14589, logz=-4.16, remainder_fraction=39.2642%, Lmin=-0.99, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1650, ncalls=14955, logz=-4.13, remainder_fraction=37.4087%, Lmin=-0.93, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1700, ncalls=15607, logz=-4.08, remainder_fraction=34.4490%, Lmin=-0.86, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1710, ncalls=15724, logz=-4.07, remainder_fraction=33.8563%, Lmin=-0.85, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1750, ncalls=16217, logz=-4.04, remainder_fraction=31.6042%, Lmin=-0.80, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1800, ncalls=16837, logz=-4.00, remainder_fraction=28.7050%, Lmin=-0.72, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1850, ncalls=17456, logz=-3.97, remainder_fraction=26.0728%, Lmin=-0.68, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1890, ncalls=17958, logz=-3.94, remainder_fraction=24.2425%, Lmin=-0.62, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1900, ncalls=18097, logz=-3.93, remainder_fraction=23.7622%, Lmin=-0.61, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1950, ncalls=18738, logz=-3.91, remainder_fraction=21.5184%, Lmin=-0.56, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=1980, ncalls=19119, logz=-3.89, remainder_fraction=20.2941%, Lmin=-0.53, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2000, ncalls=19373, logz=-3.88, remainder_fraction=19.5207%, Lmin=-0.52, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2050, ncalls=19999, logz=-3.86, remainder_fraction=17.6664%, Lmin=-0.48, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2070, ncalls=20256, logz=-3.85, remainder_fraction=16.9683%, Lmin=-0.46, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2100, ncalls=20629, logz=-3.84, remainder_fraction=15.9248%, Lmin=-0.42, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2150, ncalls=21265, logz=-3.82, remainder_fraction=14.3089%, Lmin=-0.39, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2160, ncalls=21380, logz=-3.81, remainder_fraction=13.9960%, Lmin=-0.39, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2200, ncalls=21905, logz=-3.80, remainder_fraction=12.8435%, Lmin=-0.36, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2250, ncalls=22558, logz=-3.79, remainder_fraction=11.5027%, Lmin=-0.33, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2300, ncalls=23168, logz=-3.77, remainder_fraction=10.3147%, Lmin=-0.31, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2350, ncalls=23818, logz=-3.76, remainder_fraction=9.2264%, Lmin=-0.28, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2400, ncalls=24467, logz=-3.75, remainder_fraction=8.2458%, Lmin=-0.26, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2430, ncalls=24841, logz=-3.74, remainder_fraction=7.7093%, Lmin=-0.25, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2450, ncalls=25079, logz=-3.74, remainder_fraction=7.3695%, Lmin=-0.24, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2500, ncalls=25714, logz=-3.73, remainder_fraction=6.5837%, Lmin=-0.22, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2520, ncalls=25973, logz=-3.73, remainder_fraction=6.2910%, Lmin=-0.21, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2550, ncalls=26358, logz=-3.72, remainder_fraction=5.8762%, Lmin=-0.20, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2600, ncalls=27022, logz=-3.72, remainder_fraction=5.2296%, Lmin=-0.19, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2610, ncalls=27150, logz=-3.72, remainder_fraction=5.1096%, Lmin=-0.19, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2650, ncalls=27643, logz=-3.71, remainder_fraction=4.6555%, Lmin=-0.18, Lmax=-0.01 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2700, ncalls=28286, logz=-3.71, remainder_fraction=4.1411%, Lmin=-0.16, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2750, ncalls=28925, logz=-3.70, remainder_fraction=3.6862%, Lmin=-0.15, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2790, ncalls=29423, logz=-3.70, remainder_fraction=3.3539%, Lmin=-0.14, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2800, ncalls=29544, logz=-3.70, remainder_fraction=3.2759%, Lmin=-0.14, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2850, ncalls=30160, logz=-3.69, remainder_fraction=2.9114%, Lmin=-0.13, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2880, ncalls=30554, logz=-3.69, remainder_fraction=2.7098%, Lmin=-0.12, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2900, ncalls=30811, logz=-3.69, remainder_fraction=2.5837%, Lmin=-0.12, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2950, ncalls=31427, logz=-3.69, remainder_fraction=2.2920%, Lmin=-0.11, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=2970, ncalls=31688, logz=-3.69, remainder_fraction=2.1845%, Lmin=-0.10, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3000, ncalls=32079, logz=-3.68, remainder_fraction=2.0329%, Lmin=-0.10, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3050, ncalls=32694, logz=-3.68, remainder_fraction=1.8041%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3060, ncalls=32822, logz=-3.68, remainder_fraction=1.7613%, Lmin=-0.09, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3100, ncalls=33345, logz=-3.68, remainder_fraction=1.5980%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3150, ncalls=33971, logz=-3.68, remainder_fraction=1.4160%, Lmin=-0.08, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3200, ncalls=34611, logz=-3.68, remainder_fraction=1.2549%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3240, ncalls=35099, logz=-3.67, remainder_fraction=1.1386%, Lmin=-0.07, Lmax=-0.00 [35mDEBUG [0m ultranest:integrator.py:2406 iteration=3250, ncalls=35220, logz=-3.67, remainder_fraction=1.1111%, Lmin=-0.06, Lmax=-0.00 [32mINFO [0m ultranest:integrator.py:2450 Explored until L=-0.0003 [32mINFO [0m ultranest:integrator.py:2536 Likelihood function evaluations: 35775 [35mDEBUG [0m ultranest:integrator.py:2118 did a run_iter pass! [32mINFO [0m ultranest:integrator.py:2493 logZ = -3.659 +- 0.0619 [32mINFO [0m ultranest:integrator.py:1434 Effective samples strategy satisfied (ESS = 1962.9, need >400) [32mINFO [0m ultranest:integrator.py:1465 Posterior uncertainty strategy is satisfied (KL: 0.46+-0.07 nat, need <0.50 nat) [32mINFO [0m ultranest:integrator.py:1493 Evidency uncertainty strategy is satisfied (dlogz=0.13, need <0.5) [32mINFO [0m ultranest:integrator.py:1497 logZ error budget: single: 0.07 bs:0.06 tail:0.01 total:0.06 required:<0.50 [32mINFO [0m ultranest:integrator.py:2121 done iterating. | |||
Passed | tests/test_stepsampling.py::test_stepsampler | 0.03 | |
------------------------------Captured stdout call------------------------------ ineffective proposal scale (1). shrinking... [0.50145819 0.88258894 0.72125693] -3.6832317726231345 [0.13901781 0.7619484 0.2501404 ] -12.053904626865283 | |||
Passed | tests/test_stepsampling.py::test_stepsampler_adapt_when_stuck | 0.06 | |
------------------------------Captured stdout call------------------------------ CubeMHSampler rejected by region ineffective proposal scale (1). shrinking... rejected by region ineffective proposal scale (0.385543). shrinking... rejected by region ineffective proposal scale (0.148644). shrinking... rejected by region ineffective proposal scale (0.0573086). shrinking... rejected by region ineffective proposal scale (0.0220949). shrinking... rejected by region ineffective proposal scale (0.00851855). shrinking... CubeSliceSampler | |||
Passed | tests/test_stepsampling.py::test_stepsampler_regionmh_adapt | 0.14 | |
------------------------------Captured stdout call------------------------------ RegionMHSampler(nsteps=3) ineffective proposal scale (1.1). shrinking... ineffective proposal scale (0.880663). shrinking... RegionMHSampler(adaptive_nsteps=move-distance) ineffective proposal scale (1.1). shrinking... ineffective proposal scale (1). shrinking... RegionMHSampler(adaptive_nsteps=proposal-total-distances) ineffective proposal scale (1.1). shrinking... RegionMHSampler(adaptive_nsteps=proposal-summed-distances) ineffective proposal scale (1.1). shrinking... CubeMHSampler(nsteps=3) ineffective proposal scale (1). shrinking... ineffective proposal scale (0.800603). shrinking... CubeMHSampler(adaptive_nsteps=move-distance) ineffective proposal scale (1). shrinking... ineffective proposal scale (0.800603). shrinking... CubeMHSampler(adaptive_nsteps=proposal-total-distances) ineffective proposal scale (1). shrinking... ineffective proposal scale (0.800603). shrinking... CubeMHSampler(adaptive_nsteps=proposal-summed-distances) ineffective proposal scale (1). shrinking... ineffective proposal scale (0.800603). shrinking... CubeSliceSampler(nsteps=3) CubeSliceSampler(adaptive_nsteps=move-distance) CubeSliceSampler(adaptive_nsteps=proposal-total-distances) CubeSliceSampler(adaptive_nsteps=proposal-summed-distances) RegionSliceSampler(nsteps=3) RegionSliceSampler(adaptive_nsteps=move-distance) RegionSliceSampler(adaptive_nsteps=proposal-total-distances) RegionSliceSampler(adaptive_nsteps=proposal-summed-distances) | |||
Passed | tests/test_stepsampling.py::test_pathsampler | 0.03 | |
------------------------------Captured stdout call------------------------------ reset 1 set gradient function to nocall starting at [0.5 0.5] starting new direction [0.01 0.01] from [0.5 0.5] i: 0->1 (step 0) suggested point: [0.51 0.51] -> inside. i: 1->2 (step 1) suggested point: [0.52 0.52] -> inside. i: 2->3 (step 2) suggested point: [0.53 0.53] -> inside. i: 3->4 (step 3) suggested point: [0.54 0.54] -> inside. triggering re-orientation reset 1 walked 1 paths; returning sample adjusting scale 1.000000 up: istep=5 inside=4 outside=0 region=0 nstuck=0 make reflect set gradient function to gradient starting at [0.5 0.5] starting new direction [0.01 0.01] from [0.5 0.5] i: 0->1 (step 0) suggested point: [0.51 0.51] -> outside. trying to reflect at [0.51 0.51] trying [0.5 0.52] successful reflect! i: 1->2 (step 1) suggested point: [0.49 0.53] -> inside. i: 2->3 (step 2) suggested point: [0.48 0.54] -> inside. i: 3->4 (step 3) suggested point: [0.47 0.55] -> inside. triggering re-orientation reset 1 walked 1 paths; returning sample adjusting scale 1.100000 up: istep=5 inside=4 outside=0 region=0 nstuck=0 make stuck starting at [0.5 0.5] starting new direction [0.01 0.01] from [0.5 0.5] i: 0->1 (step 0) suggested point: [0.51 0.51] -> outside. trying to reflect at [0.51 0.51] trying [0.5 0.52] unsuccessful reflect i: 0->-1 (step 1) suggested point: [0.49 0.49] -> outside. trying to reflect at [0.49 0.49] trying [0.5 0.48] unsuccessful reflect i: 0->0 (step 2) i: 0->0 (step 3) triggering re-orientation reset 1 walked 1 paths; returning sample adjusting scale 1.210000 down: istep=5 inside=0 outside=4 region=0 nstuck=3 | |||
Passed | tests/test_stepsampling.py::test_ellipsoid_bracket | 0.18 | |
------------------------------Captured stdout call------------------------------ seed: 0 [0.50992628 0.49615106] 0.8846954103224107 [[0.01926479 0.00029866] [0.00029866 0.02059322]] [[51.91984507 -0.75298154] [-0.75298154 48.57059161]] [[-0.03014079 -0.13548551] [-0.14053046 0.02905876]] [[-7.05626717 1.45908831] [ 1.51341904 6.80295189]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.017174902905080985 0.23786423427151487 seed: 1 [0.50159445 0.47100674] 1.8743099471353246 [[ 0.33611853 -0.03266527] [-0.03266527 0.34105515]] [[3.00309364 0.28762753] [0.28762753 2.95962525]] [[ 0.41434574 -0.40550726] [-0.44683648 -0.37602169]] [[-1.32593047 -1.11579659] [-1.22951834 1.20329128]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6917900617926906 0.8846363293094491 seed: 2 [0.48812653 0.53575766] 20.38450684976214 [[ 0.02882855 -0.00164512] [-0.00164512 0.01039618]] [[35.00392418 5.53912476] [ 5.53912476 97.06571607]] [[-0.16955471 0.00893047] [ 0.01501439 0.10085012]] [[-0.87122291 -5.85191377] [-9.83855613 0.51819813]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6730808254214168 0.8527385288859411 seed: 3 [0.47230407 0.50830476] 2.0192802558538405 [[0.30519242 0.02950729] [0.02950729 0.30154492]] [[ 3.30791723 -0.32369199] [-0.32369199 3.34792997]] [[-0.42039895 -0.35840918] [-0.39521765 0.38124524]] [[ 1.30899395 -1.26271615] [-1.39239654 -1.18708124]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.7071890735938766 0.855064597755619 seed: 4 [0.50099605 0.49480303] 1.0789338425112094 [[ 0.02212739 -0.00207538] [-0.00207538 0.01904731]] [[45.65946589 4.9750119 ] [ 4.9750119 53.04291745]] [[-0.1359778 0.06031112] [ 0.06842332 0.11985642]] [[-3.35006084 -5.86826706] [-6.65758288 2.95288126]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.052565699606072866 0.24797734092031085 seed: 5 [0.49104398 0.55215679] 2.0230339684412333 [[0.37506221 0.01679208] [0.01679208 0.33671203]] [[ 2.67219079 -0.13326413] [-0.13326413 2.97654281]] [[-0.57805143 -0.20228385] [-0.21732937 0.53803344]] [[ 0.61224159 -1.5157015 ] [-1.62843674 -0.56985664]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.7799365812711072 0.9593158783831075 seed: 6 [0.52418964 0.50030038] 2.1457304801032278 [[ 0.018437 -0.00089551] [-0.00089551 0.0204369 ]] [[54.35445482 2.38173058] [ 2.38173058 49.03546901]] [[ 0.05147825 -0.12564627] [-0.13464496 -0.04803782]] [[-6.94384782 -2.47738415] [-2.65481249 6.47977157]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.07419300769210857 0.3204076821837687 seed: 7 [0.484248 0.51819016] 1.8539629878442634 [[0.3042633 0.01242581] [0.01242581 0.34076343]] [[ 3.29152877 -0.12002437] [-0.12002437 2.93896385]] [[-0.17284996 -0.52381885] [-0.56099455 0.16139563]] [[-1.74353623 0.5016076 ] [ 0.53720694 1.62799648]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6659778758876831 0.8349705094435842 seed: 8 [0.50408499 0.49428346] 0.9655037157675875 [[ 0.02323618 -0.00217529] [-0.00217529 0.01719814]] [[43.55202481 5.50863067] [ 5.50863067 58.8425811 ]] [[-0.14724143 0.03944802] [ 0.04752047 0.12222906]] [[-2.39135596 -6.15088949] [-7.40957792 1.98512876]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.044400678705535615 0.2448003575805587 seed: 9 [0.48904592 0.48752116] 1.5384778143104043 [[ 0.35830766 -0.02034459] [-0.02034459 0.3526576 ]] [[2.80006946 0.16153418] [0.16153418 2.84493043]] [[-0.46246098 0.38004934] [ 0.40268134 0.43646917]] [[-1.13466924 -1.22987608] [-1.3031154 1.07089714]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6534001039705724 0.8271676775022705 seed: 10 [0.48019733 0.48916557] 2.9213240856230063 [[ 0.02687924 -0.00160957] [-0.00160957 0.01361342]] [[37.46870819 4.43008875] [ 4.43008875 73.98069138]] [[-0.1633707 0.01375712] [ 0.01953864 0.11502898]] [[-1.02505008 -6.03473119] [-8.57086863 0.72173568]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.19872037150428723 0.3506413010364053 seed: 11 [0.59345747 0.50405991] 3.7306863239940204 [[ 0.44726794 -0.04617036] [-0.04617036 0.39179286]] [[2.26332908 0.26671929] [0.26671929 2.58380033]] [[-0.59882319 0.29778974] [ 0.33882562 0.52629845]] [[-0.81437012 -1.2649626 ] [-1.43927639 0.71574004]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -1.092686015122924 1.4746656432581782 seed: 12 [0.50346304 0.49828554] 0.7215776662713073 [[ 0.02197582 -0.00051243] [-0.00051243 0.01859843]] [[45.53382294 1.25457289] [ 1.25457289 53.80254874]] [[-0.14689036 0.01997595] [ 0.02179624 0.134623 ]] [[-1.07847582 -6.6611345 ] [-7.26812202 0.98840835]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.019765258396075982 0.22521924489885897 seed: 13 [0.52739261 0.49636814] 3.3812808083835133 [[0.15850363 0.01102533] [0.01102533 0.38344053]] [[ 6.32164766 -0.18177065] [-0.18177065 2.61319295]] [[-0.03026402 -0.39697319] [-0.61892143 0.0194112 ]] [[-2.51305304 0.07881674] [ 0.12288328 1.61186 ]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6029032189790895 0.8593349879630028 seed: 14 [0.49578687 0.49107959] 0.985344450508965 [[0.0229603 0.00218594] [0.00218594 0.01727914]] [[44.08438795 -5.57700003] [-5.57700003 58.57878206]] [[-0.14575598 -0.0414186 ] [-0.04959054 0.12173709]] [[ 2.50484132 -6.1489965 ] [-7.36220173 -2.0920726 ]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.04428553210487171 0.244441630592295 seed: 15 seed: 16 [0.49343334 0.47906169] 29.470736305310133 [[0.02519435 0.00144764] [0.00144764 0.01541777]] [[39.90673801 -3.74700043] [-3.74700043 65.21203037]] [[-0.15773825 -0.01769165] [-0.02286578 0.12204478]] [[ 1.16331785 -6.20914081] [-8.02507871 -0.90007894]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.7596099227288234 0.9551032647005249 seed: 17 [0.45822053 0.45620346] 3.867101221747955 [[ 0.31747032 -0.11633444] [-0.11633444 0.32983302]] [[3.61744326 1.27589782] [1.27589782 3.48185534]] [[ 0.45650634 -0.33026093] [-0.48140645 -0.31317861]] [[-1.59428407 -1.03716033] [-1.51182183 1.09373219]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.9980562454409576 1.065967262438615 seed: 18 [0.50867005 0.48928539] 1.987131194992184 [[ 0.01875748 -0.00245339] [-0.00245339 0.02174844]] [[54.11045954 6.10407145] [ 6.10407145 46.66888943]] [[ 0.0744627 -0.11494687] [-0.13259532 -0.06455171]] [[-6.61385603 -3.21983974] [-3.71420034 5.73355084]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.08414368416027168 0.29342603298305664 seed: 19 [0.51301403 0.48323565] 1.6197886971538265 [[ 0.36663328 -0.01367268] [-0.01367268 0.30642217]] [[2.73206723 0.12190594] [0.12190594 3.26891089]] [[-0.59418281 0.11653355] [ 0.12860559 0.53840763]] [[-0.38401258 -1.60766961] [-1.77421269 0.34796581]] from [0.4 0.525] in direction [1. 0.] ellipsoid bracket: -0.6574825285771522 0.8797835081854678 | |||
Passed | tests/test_stepsampling.py::test_crop_bracket | 0.00 | |
------------------------------Captured stdout call------------------------------ left: -1.9354937665716845 [1.93780732 1.70985572] right: 2.3302374240517256 [-1.45856722 -0.87105549] | |||
Passed | tests/test_stepsampling.py::test_aharm_sampler | 0.01 | |
------------------------------Captured stdout call------------------------------ calling likelihood with 7 prepared points, accepted: ====== calling likelihood with 7 prepared points, accepted: == calling likelihood with 3 prepared points, accepted: = calling likelihood with 3 prepared points, accepted: = calling likelihood with 1 prepared points, accepted: = done in 5 function calls, 19 likelihood evals | |||
Passed | tests/test_store.py::test_text_store | 0.00 | |
------------------------------Captured stdout call------------------------------ [(1, [101.0, 155.0, 413.0, 213.0]), (2, [99.0, 156.0, 413.0, 213.0])] | |||
Passed | tests/test_store.py::test_hdf5_store | 0.01 | |
------------------------------Captured stdout call------------------------------ [(1, array([101., 155., 413., 213.])), (2, array([ 99., 156., 413., 213.]))] | |||
Passed | tests/test_store.py::test_nullstore | 0.00 | |
No log output captured. | |||
Passed | tests/test_store.py::test_storemany | 0.30 | |
------------------------------Captured stdout call------------------------------ ======== <class 'ultranest.store.TextPointStore'> N=1 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.5, 1.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [0.0, 1.0, 1.0]), (2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] stack[1]: [(1, [0.0, 1.0, 1.0]), (2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] 0 0.1 reading: [0.0, 1.0, 1.0] stack[2]: [(2, [-inf, -0.1, -0.1]), (3, [1.0, 1.5, 1.5])] stack[3]: [(3, [1.0, 1.5, 1.5])] 1 1.1 reading: [1.0, 1.5, 1.5] ======== <class 'ultranest.store.TextPointStore'> N=2 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [0.0, 1.0, 1.0]), (3, [1.0, 2.0, 2.0]), (4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] stack[1]: [(2, [0.0, 1.0, 1.0]), (3, [1.0, 2.0, 2.0]), (4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] stack[2]: [(4, [-inf, -0.1, -0.1]), (5, [-inf, 0.9, 0.9]), (6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] stack[3]: [(6, [1.0, 1.5, 1.5]), (7, [2.0, 2.5, 2.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] ======== <class 'ultranest.store.TextPointStore'> N=10 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [-inf, 1.9, 1.9]), (3, [-inf, 2.9, 2.9]), (4, [-inf, 3.9, 3.9]), (5, [-inf, 4.9, 4.9]), (6, [-inf, 5.9, 5.9]), (7, [-inf, 6.9, 6.9]), (8, [-inf, 7.9, 7.9]), (9, [-inf, 8.9, 8.9]), (10, [0.0, 1.0, 1.0]), (11, [1.0, 2.0, 2.0]), (12, [2.0, 3.0, 3.0]), (13, [3.0, 4.0, 4.0]), (14, [4.0, 5.0, 5.0]), (15, [5.0, 6.0, 6.0]), (16, [6.0, 7.0, 7.0]), (17, [7.0, 8.0, 8.0]), (18, [8.0, 9.0, 9.0]), (19, [9.0, 10.0, 10.0]), (20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] stack[1]: [(10, [0.0, 1.0, 1.0]), (11, [1.0, 2.0, 2.0]), (12, [2.0, 3.0, 3.0]), (13, [3.0, 4.0, 4.0]), (14, [4.0, 5.0, 5.0]), (15, [5.0, 6.0, 6.0]), (16, [6.0, 7.0, 7.0]), (17, [7.0, 8.0, 8.0]), (18, [8.0, 9.0, 9.0]), (19, [9.0, 10.0, 10.0]), (20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] 2 2.1 reading: [2.0, 3.0, 3.0] 3 3.1 reading: [3.0, 4.0, 4.0] 4 4.1 reading: [4.0, 5.0, 5.0] 5 5.1 reading: [5.0, 6.0, 6.0] 6 6.1 reading: [6.0, 7.0, 7.0] 7 7.1 reading: [7.0, 8.0, 8.0] 8 8.1 reading: [8.0, 9.0, 9.0] 9 9.1 reading: [9.0, 10.0, 10.0] stack[2]: [(20, [-inf, -0.1, -0.1]), (21, [-inf, 0.9, 0.9]), (22, [-inf, 1.9, 1.9]), (23, [-inf, 2.9, 2.9]), (24, [-inf, 3.9, 3.9]), (25, [-inf, 4.9, 4.9]), (26, [-inf, 5.9, 5.9]), (27, [-inf, 6.9, 6.9]), (28, [-inf, 7.9, 7.9]), (29, [-inf, 8.9, 8.9]), (30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] stack[3]: [(30, [1.0, 1.5, 1.5]), (31, [2.0, 2.5, 2.5]), (32, [3.0, 3.5, 3.5]), (33, [4.0, 4.5, 4.5]), (34, [5.0, 5.5, 5.5]), (35, [6.0, 6.5, 6.5]), (36, [7.0, 7.5, 7.5]), (37, [8.0, 8.5, 8.5]), (38, [9.0, 9.5, 9.5]), (39, [10.0, 10.5, 10.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] 3 3.1 reading: [3.0, 3.5, 3.5] 4 4.1 reading: [4.0, 4.5, 4.5] 5 5.1 reading: [5.0, 5.5, 5.5] 6 6.1 reading: [6.0, 6.5, 6.5] 7 7.1 reading: [7.0, 7.5, 7.5] 8 8.1 reading: [8.0, 8.5, 8.5] 9 9.1 reading: [9.0, 9.5, 9.5] 10 10.1 reading: [10.0, 10.5, 10.5] ======== <class 'ultranest.store.TextPointStore'> N=100 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 10 11 storing: [10, 10.1, 10.1] 11 12 storing: [11, 11.1, 11.1] 12 13 storing: [12, 12.1, 12.1] 13 14 storing: [13, 13.1, 13.1] 14 15 storing: [14, 14.1, 14.1] 15 16 storing: [15, 15.1, 15.1] 16 17 storing: [16, 16.1, 16.1] 17 18 storing: [17, 17.1, 17.1] 18 19 storing: [18, 18.1, 18.1] 19 20 storing: [19, 19.1, 19.1] 20 21 storing: [20, 20.1, 20.1] 21 22 storing: [21, 21.1, 21.1] 22 23 storing: [22, 22.1, 22.1] 23 24 storing: [23, 23.1, 23.1] 24 25 storing: [24, 24.1, 24.1] 25 26 storing: [25, 25.1, 25.1] 26 27 storing: [26, 26.1, 26.1] 27 28 storing: [27, 27.1, 27.1] 28 29 storing: [28, 28.1, 28.1] 29 30 storing: [29, 29.1, 29.1] 30 31 storing: [30, 30.1, 30.1] 31 32 storing: [31, 31.1, 31.1] 32 33 storing: [32, 32.1, 32.1] 33 34 storing: [33, 33.1, 33.1] 34 35 storing: [34, 34.1, 34.1] 35 36 storing: [35, 35.1, 35.1] 36 37 storing: [36, 36.1, 36.1] 37 38 storing: [37, 37.1, 37.1] 38 39 storing: [38, 38.1, 38.1] 39 40 storing: [39, 39.1, 39.1] 40 41 storing: [40, 40.1, 40.1] 41 42 storing: [41, 41.1, 41.1] 42 43 storing: [42, 42.1, 42.1] 43 44 storing: [43, 43.1, 43.1] 44 45 storing: [44, 44.1, 44.1] 45 46 storing: [45, 45.1, 45.1] 46 47 storing: [46, 46.1, 46.1] 47 48 storing: [47, 47.1, 47.1] 48 49 storing: [48, 48.1, 48.1] 49 50 storing: [49, 49.1, 49.1] 50 51 storing: [50, 50.1, 50.1] 51 52 storing: [51, 51.1, 51.1] 52 53 storing: [52, 52.1, 52.1] 53 54 storing: [53, 53.1, 53.1] 54 55 storing: [54, 54.1, 54.1] 55 56 storing: [55, 55.1, 55.1] 56 57 storing: [56, 56.1, 56.1] 57 58 storing: [57, 57.1, 57.1] 58 59 storing: [58, 58.1, 58.1] 59 60 storing: [59, 59.1, 59.1] 60 61 storing: [60, 60.1, 60.1] 61 62 storing: [61, 61.1, 61.1] 62 63 storing: [62, 62.1, 62.1] 63 64 storing: [63, 63.1, 63.1] 64 65 storing: [64, 64.1, 64.1] 65 66 storing: [65, 65.1, 65.1] 66 67 storing: [66, 66.1, 66.1] 67 68 storing: [67, 67.1, 67.1] 68 69 storing: [68, 68.1, 68.1] 69 70 storing: [69, 69.1, 69.1] 70 71 storing: [70, 70.1, 70.1] 71 72 storing: [71, 71.1, 71.1] 72 73 storing: [72, 72.1, 72.1] 73 74 storing: [73, 73.1, 73.1] 74 75 storing: [74, 74.1, 74.1] 75 76 storing: [75, 75.1, 75.1] 76 77 storing: [76, 76.1, 76.1] 77 78 storing: [77, 77.1, 77.1] 78 79 storing: [78, 78.1, 78.1] 79 80 storing: [79, 79.1, 79.1] 80 81 storing: [80, 80.1, 80.1] 81 82 storing: [81, 81.1, 81.1] 82 83 storing: [82, 82.1, 82.1] 83 84 storing: [83, 83.1, 83.1] 84 85 storing: [84, 84.1, 84.1] 85 86 storing: [85, 85.1, 85.1] 86 87 storing: [86, 86.1, 86.1] 87 88 storing: [87, 87.1, 87.1] 88 89 storing: [88, 88.1, 88.1] 89 90 storing: [89, 89.1, 89.1] 90 91 storing: [90, 90.1, 90.1] 91 92 storing: [91, 91.1, 91.1] 92 93 storing: [92, 92.1, 92.1] 93 94 storing: [93, 93.1, 93.1] 94 95 storing: [94, 94.1, 94.1] 95 96 storing: [95, 95.1, 95.1] 96 97 storing: [96, 96.1, 96.1] 97 98 storing: [97, 97.1, 97.1] 98 99 storing: [98, 98.1, 98.1] 99 100 storing: [99, 99.1, 99.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] 11 12 storing: [11, 11.5, 11.5] 12 13 storing: [12, 12.5, 12.5] 13 14 storing: [13, 13.5, 13.5] 14 15 storing: [14, 14.5, 14.5] 15 16 storing: [15, 15.5, 15.5] 16 17 storing: [16, 16.5, 16.5] 17 18 storing: [17, 17.5, 17.5] 18 19 storing: [18, 18.5, 18.5] 19 20 storing: [19, 19.5, 19.5] 20 21 storing: [20, 20.5, 20.5] 21 22 storing: [21, 21.5, 21.5] 22 23 storing: [22, 22.5, 22.5] 23 24 storing: [23, 23.5, 23.5] 24 25 storing: [24, 24.5, 24.5] 25 26 storing: [25, 25.5, 25.5] 26 27 storing: [26, 26.5, 26.5] 27 28 storing: [27, 27.5, 27.5] 28 29 storing: [28, 28.5, 28.5] 29 30 storing: [29, 29.5, 29.5] 30 31 storing: [30, 30.5, 30.5] 31 32 storing: [31, 31.5, 31.5] 32 33 storing: [32, 32.5, 32.5] 33 34 storing: [33, 33.5, 33.5] 34 35 storing: [34, 34.5, 34.5] 35 36 storing: [35, 35.5, 35.5] 36 37 storing: [36, 36.5, 36.5] 37 38 storing: [37, 37.5, 37.5] 38 39 storing: [38, 38.5, 38.5] 39 40 storing: [39, 39.5, 39.5] 40 41 storing: [40, 40.5, 40.5] 41 42 storing: [41, 41.5, 41.5] 42 43 storing: [42, 42.5, 42.5] 43 44 storing: [43, 43.5, 43.5] 44 45 storing: [44, 44.5, 44.5] 45 46 storing: [45, 45.5, 45.5] 46 47 storing: [46, 46.5, 46.5] 47 48 storing: [47, 47.5, 47.5] 48 49 storing: [48, 48.5, 48.5] 49 50 storing: [49, 49.5, 49.5] 50 51 storing: [50, 50.5, 50.5] 51 52 storing: [51, 51.5, 51.5] 52 53 storing: [52, 52.5, 52.5] 53 54 storing: [53, 53.5, 53.5] 54 55 storing: [54, 54.5, 54.5] 55 56 storing: [55, 55.5, 55.5] 56 57 storing: [56, 56.5, 56.5] 57 58 storing: [57, 57.5, 57.5] 58 59 storing: [58, 58.5, 58.5] 59 60 storing: [59, 59.5, 59.5] 60 61 storing: [60, 60.5, 60.5] 61 62 storing: [61, 61.5, 61.5] 62 63 storing: [62, 62.5, 62.5] 63 64 storing: [63, 63.5, 63.5] 64 65 storing: [64, 64.5, 64.5] 65 66 storing: [65, 65.5, 65.5] 66 67 storing: [66, 66.5, 66.5] 67 68 storing: [67, 67.5, 67.5] 68 69 storing: [68, 68.5, 68.5] 69 70 storing: [69, 69.5, 69.5] 70 71 storing: [70, 70.5, 70.5] 71 72 storing: [71, 71.5, 71.5] 72 73 storing: [72, 72.5, 72.5] 73 74 storing: [73, 73.5, 73.5] 74 75 storing: [74, 74.5, 74.5] 75 76 storing: [75, 75.5, 75.5] 76 77 storing: [76, 76.5, 76.5] 77 78 storing: [77, 77.5, 77.5] 78 79 storing: [78, 78.5, 78.5] 79 80 storing: [79, 79.5, 79.5] 80 81 storing: [80, 80.5, 80.5] 81 82 storing: [81, 81.5, 81.5] 82 83 storing: [82, 82.5, 82.5] 83 84 storing: [83, 83.5, 83.5] 84 85 storing: [84, 84.5, 84.5] 85 86 storing: [85, 85.5, 85.5] 86 87 storing: [86, 86.5, 86.5] 87 88 storing: [87, 87.5, 87.5] 88 89 storing: [88, 88.5, 88.5] 89 90 storing: [89, 89.5, 89.5] 90 91 storing: [90, 90.5, 90.5] 91 92 storing: [91, 91.5, 91.5] 92 93 storing: [92, 92.5, 92.5] 93 94 storing: [93, 93.5, 93.5] 94 95 storing: [94, 94.5, 94.5] 95 96 storing: [95, 95.5, 95.5] 96 97 storing: [96, 96.5, 96.5] 97 98 storing: [97, 97.5, 97.5] 98 99 storing: [98, 98.5, 98.5] 99 100 storing: [99, 99.5, 99.5] 100 101 storing: [100, 100.5, 100.5] reading... stack[0]: [(0, [-inf, -0.1, -0.1]), (1, [-inf, 0.9, 0.9]), (2, [-inf, 1.9, 1.9]), (3, [-inf, 2.9, 2.9]), (4, [-inf, 3.9, 3.9]), (5, [-inf, 4.9, 4.9]), (6, [-inf, 5.9, 5.9]), (7, [-inf, 6.9, 6.9]), (8, [-inf, 7.9, 7.9]), (9, [-inf, 8.9, 8.9]), (10, [-inf, 9.9, 9.9]), (11, [-inf, 10.9, 10.9]), (12, [-inf, 11.9, 11.9]), (13, [-inf, 12.9, 12.9]), (14, [-inf, 13.9, 13.9]), (15, [-inf, 14.9, 14.9]), (16, [-inf, 15.9, 15.9]), (17, [-inf, 16.9, 16.9]), (18, [-inf, 17.9, 17.9]), (19, [-inf, 18.9, 18.9]), (20, [-inf, 19.9, 19.9]), (21, [-inf, 20.9, 20.9]), (22, [-inf, 21.9, 21.9]), (23, [-inf, 22.9, 22.9]), (24, [-inf, 23.9, 23.9]), (25, [-inf, 24.9, 24.9]), (26, [-inf, 25.9, 25.9]), (27, [-inf, 26.9, 26.9]), (28, [-inf, 27.9, 27.9]), (29, [-inf, 28.9, 28.9]), (30, [-inf, 29.9, 29.9]), (31, [-inf, 30.9, 30.9]), (32, [-inf, 31.9, 31.9]), (33, [-inf, 32.9, 32.9]), (34, [-inf, 33.9, 33.9]), (35, [-inf, 34.9, 34.9]), (36, [-inf, 35.9, 35.9]), (37, [-inf, 36.9, 36.9]), (38, [-inf, 37.9, 37.9]), (39, [-inf, 38.9, 38.9]), (40, [-inf, 39.9, 39.9]), (41, [-inf, 40.9, 40.9]), (42, [-inf, 41.9, 41.9]), (43, [-inf, 42.9, 42.9]), (44, [-inf, 43.9, 43.9]), (45, [-inf, 44.9, 44.9]), (46, [-inf, 45.9, 45.9]), (47, [-inf, 46.9, 46.9]), (48, [-inf, 47.9, 47.9]), (49, [-inf, 48.9, 48.9]), (50, [-inf, 49.9, 49.9]), (51, [-inf, 50.9, 50.9]), (52, [-inf, 51.9, 51.9]), (53, [-inf, 52.9, 52.9]), (54, [-inf, 53.9, 53.9]), (55, [-inf, 54.9, 54.9]), (56, [-inf, 55.9, 55.9]), (57, [-inf, 56.9, 56.9]), (58, [-inf, 57.9, 57.9]), (59, [-inf, 58.9, 58.9]), (60, [-inf, 59.9, 59.9]), (61, [-inf, 60.9, 60.9]), (62, [-inf, 61.9, 61.9]), (63, [-inf, 62.9, 62.9]), (64, [-inf, 63.9, 63.9]), (65, [-inf, 64.9, 64.9]), (66, [-inf, 65.9, 65.9]), (67, [-inf, 66.9, 66.9]), (68, [-inf, 67.9, 67.9]), (69, [-inf, 68.9, 68.9]), (70, [-inf, 69.9, 69.9]), (71, [-inf, 70.9, 70.9]), (72, [-inf, 71.9, 71.9]), (73, [-inf, 72.9, 72.9]), (74, [-inf, 73.9, 73.9]), (75, [-inf, 74.9, 74.9]), (76, [-inf, 75.9, 75.9]), (77, [-inf, 76.9, 76.9]), (78, [-inf, 77.9, 77.9]), (79, [-inf, 78.9, 78.9]), (80, [-inf, 79.9, 79.9]), (81, [-inf, 80.9, 80.9]), (82, [-inf, 81.9, 81.9]), (83, [-inf, 82.9, 82.9]), (84, [-inf, 83.9, 83.9]), (85, [-inf, 84.9, 84.9]), (86, [-inf, 85.9, 85.9]), (87, [-inf, 86.9, 86.9]), (88, [-inf, 87.9, 87.9]), (89, [-inf, 88.9, 88.9]), (90, [-inf, 89.9, 89.9]), (91, [-inf, 90.9, 90.9]), (92, [-inf, 91.9, 91.9]), (93, [-inf, 92.9, 92.9]), (94, [-inf, 93.9, 93.9]), (95, [-inf, 94.9, 94.9]), (96, [-inf, 95.9, 95.9]), (97, [-inf, 96.9, 96.9]), (98, [-inf, 97.9, 97.9]), (99, [-inf, 98.9, 98.9]), (100, [0.0, 1.0, 1.0]), (101, [1.0, 2.0, 2.0]), (102, [2.0, 3.0, 3.0]), (103, [3.0, 4.0, 4.0]), (104, [4.0, 5.0, 5.0]), (105, [5.0, 6.0, 6.0]), (106, [6.0, 7.0, 7.0]), (107, [7.0, 8.0, 8.0]), (108, [8.0, 9.0, 9.0]), (109, [9.0, 10.0, 10.0]), (110, [10.0, 11.0, 11.0]), (111, [11.0, 12.0, 12.0]), (112, [12.0, 13.0, 13.0]), (113, [13.0, 14.0, 14.0]), (114, [14.0, 15.0, 15.0]), (115, [15.0, 16.0, 16.0]), (116, [16.0, 17.0, 17.0]), (117, [17.0, 18.0, 18.0]), (118, [18.0, 19.0, 19.0]), (119, [19.0, 20.0, 20.0]), (120, [20.0, 21.0, 21.0]), (121, [21.0, 22.0, 22.0]), (122, [22.0, 23.0, 23.0]), (123, [23.0, 24.0, 24.0]), (124, [24.0, 25.0, 25.0]), (125, [25.0, 26.0, 26.0]), (126, [26.0, 27.0, 27.0]), (127, [27.0, 28.0, 28.0]), (128, [28.0, 29.0, 29.0]), (129, [29.0, 30.0, 30.0]), (130, [30.0, 31.0, 31.0]), (131, [31.0, 32.0, 32.0]), (132, [32.0, 33.0, 33.0]), (133, [33.0, 34.0, 34.0]), (134, [34.0, 35.0, 35.0]), (135, [35.0, 36.0, 36.0]), (136, [36.0, 37.0, 37.0]), (137, [37.0, 38.0, 38.0]), (138, [38.0, 39.0, 39.0]), (139, [39.0, 40.0, 40.0]), (140, [40.0, 41.0, 41.0]), (141, [41.0, 42.0, 42.0]), (142, [42.0, 43.0, 43.0]), (143, [43.0, 44.0, 44.0]), (144, [44.0, 45.0, 45.0]), (145, [45.0, 46.0, 46.0]), (146, [46.0, 47.0, 47.0]), (147, [47.0, 48.0, 48.0]), (148, [48.0, 49.0, 49.0]), (149, [49.0, 50.0, 50.0]), (150, [50.0, 51.0, 51.0]), (151, [51.0, 52.0, 52.0]), (152, [52.0, 53.0, 53.0]), (153, [53.0, 54.0, 54.0]), (154, [54.0, 55.0, 55.0]), (155, [55.0, 56.0, 56.0]), (156, [56.0, 57.0, 57.0]), (157, [57.0, 58.0, 58.0]), (158, [58.0, 59.0, 59.0]), (159, [59.0, 60.0, 60.0]), (160, [60.0, 61.0, 61.0]), (161, [61.0, 62.0, 62.0]), (162, [62.0, 63.0, 63.0]), (163, [63.0, 64.0, 64.0]), (164, [64.0, 65.0, 65.0]), (165, [65.0, 66.0, 66.0]), (166, [66.0, 67.0, 67.0]), (167, [67.0, 68.0, 68.0]), (168, [68.0, 69.0, 69.0]), (169, [69.0, 70.0, 70.0]), (170, [70.0, 71.0, 71.0]), (171, [71.0, 72.0, 72.0]), (172, [72.0, 73.0, 73.0]), (173, [73.0, 74.0, 74.0]), (174, [74.0, 75.0, 75.0]), (175, [75.0, 76.0, 76.0]), (176, [76.0, 77.0, 77.0]), (177, [77.0, 78.0, 78.0]), (178, [78.0, 79.0, 79.0]), (179, [79.0, 80.0, 80.0]), (180, [80.0, 81.0, 81.0]), (181, [81.0, 82.0, 82.0]), (182, [82.0, 83.0, 83.0]), (183, [83.0, 84.0, 84.0]), (184, [84.0, 85.0, 85.0]), (185, [85.0, 86.0, 86.0]), (186, [86.0, 87.0, 87.0]), (187, [87.0, 88.0, 88.0]), (188, [88.0, 89.0, 89.0]), (189, [89.0, 90.0, 90.0]), (190, [90.0, 91.0, 91.0]), (191, [91.0, 92.0, 92.0]), (192, [92.0, 93.0, 93.0]), (193, [93.0, 94.0, 94.0]), (194, [94.0, 95.0, 95.0]), (195, [95.0, 96.0, 96.0]), (196, [96.0, 97.0, 97.0]), (197, [97.0, 98.0, 98.0]), (198, [98.0, 99.0, 99.0]), (199, [99.0, 100.0, 100.0]), (200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] stack[1]: [(100, [0.0, 1.0, 1.0]), (101, [1.0, 2.0, 2.0]), (102, [2.0, 3.0, 3.0]), (103, [3.0, 4.0, 4.0]), (104, [4.0, 5.0, 5.0]), (105, [5.0, 6.0, 6.0]), (106, [6.0, 7.0, 7.0]), (107, [7.0, 8.0, 8.0]), (108, [8.0, 9.0, 9.0]), (109, [9.0, 10.0, 10.0]), (110, [10.0, 11.0, 11.0]), (111, [11.0, 12.0, 12.0]), (112, [12.0, 13.0, 13.0]), (113, [13.0, 14.0, 14.0]), (114, [14.0, 15.0, 15.0]), (115, [15.0, 16.0, 16.0]), (116, [16.0, 17.0, 17.0]), (117, [17.0, 18.0, 18.0]), (118, [18.0, 19.0, 19.0]), (119, [19.0, 20.0, 20.0]), (120, [20.0, 21.0, 21.0]), (121, [21.0, 22.0, 22.0]), (122, [22.0, 23.0, 23.0]), (123, [23.0, 24.0, 24.0]), (124, [24.0, 25.0, 25.0]), (125, [25.0, 26.0, 26.0]), (126, [26.0, 27.0, 27.0]), (127, [27.0, 28.0, 28.0]), (128, [28.0, 29.0, 29.0]), (129, [29.0, 30.0, 30.0]), (130, [30.0, 31.0, 31.0]), (131, [31.0, 32.0, 32.0]), (132, [32.0, 33.0, 33.0]), (133, [33.0, 34.0, 34.0]), (134, [34.0, 35.0, 35.0]), (135, [35.0, 36.0, 36.0]), (136, [36.0, 37.0, 37.0]), (137, [37.0, 38.0, 38.0]), (138, [38.0, 39.0, 39.0]), (139, [39.0, 40.0, 40.0]), (140, [40.0, 41.0, 41.0]), (141, [41.0, 42.0, 42.0]), (142, [42.0, 43.0, 43.0]), (143, [43.0, 44.0, 44.0]), (144, [44.0, 45.0, 45.0]), (145, [45.0, 46.0, 46.0]), (146, [46.0, 47.0, 47.0]), (147, [47.0, 48.0, 48.0]), (148, [48.0, 49.0, 49.0]), (149, [49.0, 50.0, 50.0]), (150, [50.0, 51.0, 51.0]), (151, [51.0, 52.0, 52.0]), (152, [52.0, 53.0, 53.0]), (153, [53.0, 54.0, 54.0]), (154, [54.0, 55.0, 55.0]), (155, [55.0, 56.0, 56.0]), (156, [56.0, 57.0, 57.0]), (157, [57.0, 58.0, 58.0]), (158, [58.0, 59.0, 59.0]), (159, [59.0, 60.0, 60.0]), (160, [60.0, 61.0, 61.0]), (161, [61.0, 62.0, 62.0]), (162, [62.0, 63.0, 63.0]), (163, [63.0, 64.0, 64.0]), (164, [64.0, 65.0, 65.0]), (165, [65.0, 66.0, 66.0]), (166, [66.0, 67.0, 67.0]), (167, [67.0, 68.0, 68.0]), (168, [68.0, 69.0, 69.0]), (169, [69.0, 70.0, 70.0]), (170, [70.0, 71.0, 71.0]), (171, [71.0, 72.0, 72.0]), (172, [72.0, 73.0, 73.0]), (173, [73.0, 74.0, 74.0]), (174, [74.0, 75.0, 75.0]), (175, [75.0, 76.0, 76.0]), (176, [76.0, 77.0, 77.0]), (177, [77.0, 78.0, 78.0]), (178, [78.0, 79.0, 79.0]), (179, [79.0, 80.0, 80.0]), (180, [80.0, 81.0, 81.0]), (181, [81.0, 82.0, 82.0]), (182, [82.0, 83.0, 83.0]), (183, [83.0, 84.0, 84.0]), (184, [84.0, 85.0, 85.0]), (185, [85.0, 86.0, 86.0]), (186, [86.0, 87.0, 87.0]), (187, [87.0, 88.0, 88.0]), (188, [88.0, 89.0, 89.0]), (189, [89.0, 90.0, 90.0]), (190, [90.0, 91.0, 91.0]), (191, [91.0, 92.0, 92.0]), (192, [92.0, 93.0, 93.0]), (193, [93.0, 94.0, 94.0]), (194, [94.0, 95.0, 95.0]), (195, [95.0, 96.0, 96.0]), (196, [96.0, 97.0, 97.0]), (197, [97.0, 98.0, 98.0]), (198, [98.0, 99.0, 99.0]), (199, [99.0, 100.0, 100.0]), (200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] 0 0.1 reading: [0.0, 1.0, 1.0] 1 1.1 reading: [1.0, 2.0, 2.0] 2 2.1 reading: [2.0, 3.0, 3.0] 3 3.1 reading: [3.0, 4.0, 4.0] 4 4.1 reading: [4.0, 5.0, 5.0] 5 5.1 reading: [5.0, 6.0, 6.0] 6 6.1 reading: [6.0, 7.0, 7.0] 7 7.1 reading: [7.0, 8.0, 8.0] 8 8.1 reading: [8.0, 9.0, 9.0] 9 9.1 reading: [9.0, 10.0, 10.0] 10 10.1 reading: [10.0, 11.0, 11.0] 11 11.1 reading: [11.0, 12.0, 12.0] 12 12.1 reading: [12.0, 13.0, 13.0] 13 13.1 reading: [13.0, 14.0, 14.0] 14 14.1 reading: [14.0, 15.0, 15.0] 15 15.1 reading: [15.0, 16.0, 16.0] 16 16.1 reading: [16.0, 17.0, 17.0] 17 17.1 reading: [17.0, 18.0, 18.0] 18 18.1 reading: [18.0, 19.0, 19.0] 19 19.1 reading: [19.0, 20.0, 20.0] 20 20.1 reading: [20.0, 21.0, 21.0] 21 21.1 reading: [21.0, 22.0, 22.0] 22 22.1 reading: [22.0, 23.0, 23.0] 23 23.1 reading: [23.0, 24.0, 24.0] 24 24.1 reading: [24.0, 25.0, 25.0] 25 25.1 reading: [25.0, 26.0, 26.0] 26 26.1 reading: [26.0, 27.0, 27.0] 27 27.1 reading: [27.0, 28.0, 28.0] 28 28.1 reading: [28.0, 29.0, 29.0] 29 29.1 reading: [29.0, 30.0, 30.0] 30 30.1 reading: [30.0, 31.0, 31.0] 31 31.1 reading: [31.0, 32.0, 32.0] 32 32.1 reading: [32.0, 33.0, 33.0] 33 33.1 reading: [33.0, 34.0, 34.0] 34 34.1 reading: [34.0, 35.0, 35.0] 35 35.1 reading: [35.0, 36.0, 36.0] 36 36.1 reading: [36.0, 37.0, 37.0] 37 37.1 reading: [37.0, 38.0, 38.0] 38 38.1 reading: [38.0, 39.0, 39.0] 39 39.1 reading: [39.0, 40.0, 40.0] 40 40.1 reading: [40.0, 41.0, 41.0] 41 41.1 reading: [41.0, 42.0, 42.0] 42 42.1 reading: [42.0, 43.0, 43.0] 43 43.1 reading: [43.0, 44.0, 44.0] 44 44.1 reading: [44.0, 45.0, 45.0] 45 45.1 reading: [45.0, 46.0, 46.0] 46 46.1 reading: [46.0, 47.0, 47.0] 47 47.1 reading: [47.0, 48.0, 48.0] 48 48.1 reading: [48.0, 49.0, 49.0] 49 49.1 reading: [49.0, 50.0, 50.0] 50 50.1 reading: [50.0, 51.0, 51.0] 51 51.1 reading: [51.0, 52.0, 52.0] 52 52.1 reading: [52.0, 53.0, 53.0] 53 53.1 reading: [53.0, 54.0, 54.0] 54 54.1 reading: [54.0, 55.0, 55.0] 55 55.1 reading: [55.0, 56.0, 56.0] 56 56.1 reading: [56.0, 57.0, 57.0] 57 57.1 reading: [57.0, 58.0, 58.0] 58 58.1 reading: [58.0, 59.0, 59.0] 59 59.1 reading: [59.0, 60.0, 60.0] 60 60.1 reading: [60.0, 61.0, 61.0] 61 61.1 reading: [61.0, 62.0, 62.0] 62 62.1 reading: [62.0, 63.0, 63.0] 63 63.1 reading: [63.0, 64.0, 64.0] 64 64.1 reading: [64.0, 65.0, 65.0] 65 65.1 reading: [65.0, 66.0, 66.0] 66 66.1 reading: [66.0, 67.0, 67.0] 67 67.1 reading: [67.0, 68.0, 68.0] 68 68.1 reading: [68.0, 69.0, 69.0] 69 69.1 reading: [69.0, 70.0, 70.0] 70 70.1 reading: [70.0, 71.0, 71.0] 71 71.1 reading: [71.0, 72.0, 72.0] 72 72.1 reading: [72.0, 73.0, 73.0] 73 73.1 reading: [73.0, 74.0, 74.0] 74 74.1 reading: [74.0, 75.0, 75.0] 75 75.1 reading: [75.0, 76.0, 76.0] 76 76.1 reading: [76.0, 77.0, 77.0] 77 77.1 reading: [77.0, 78.0, 78.0] 78 78.1 reading: [78.0, 79.0, 79.0] 79 79.1 reading: [79.0, 80.0, 80.0] 80 80.1 reading: [80.0, 81.0, 81.0] 81 81.1 reading: [81.0, 82.0, 82.0] 82 82.1 reading: [82.0, 83.0, 83.0] 83 83.1 reading: [83.0, 84.0, 84.0] 84 84.1 reading: [84.0, 85.0, 85.0] 85 85.1 reading: [85.0, 86.0, 86.0] 86 86.1 reading: [86.0, 87.0, 87.0] 87 87.1 reading: [87.0, 88.0, 88.0] 88 88.1 reading: [88.0, 89.0, 89.0] 89 89.1 reading: [89.0, 90.0, 90.0] 90 90.1 reading: [90.0, 91.0, 91.0] 91 91.1 reading: [91.0, 92.0, 92.0] 92 92.1 reading: [92.0, 93.0, 93.0] 93 93.1 reading: [93.0, 94.0, 94.0] 94 94.1 reading: [94.0, 95.0, 95.0] 95 95.1 reading: [95.0, 96.0, 96.0] 96 96.1 reading: [96.0, 97.0, 97.0] 97 97.1 reading: [97.0, 98.0, 98.0] 98 98.1 reading: [98.0, 99.0, 99.0] 99 99.1 reading: [99.0, 100.0, 100.0] stack[2]: [(200, [-inf, -0.1, -0.1]), (201, [-inf, 0.9, 0.9]), (202, [-inf, 1.9, 1.9]), (203, [-inf, 2.9, 2.9]), (204, [-inf, 3.9, 3.9]), (205, [-inf, 4.9, 4.9]), (206, [-inf, 5.9, 5.9]), (207, [-inf, 6.9, 6.9]), (208, [-inf, 7.9, 7.9]), (209, [-inf, 8.9, 8.9]), (210, [-inf, 9.9, 9.9]), (211, [-inf, 10.9, 10.9]), (212, [-inf, 11.9, 11.9]), (213, [-inf, 12.9, 12.9]), (214, [-inf, 13.9, 13.9]), (215, [-inf, 14.9, 14.9]), (216, [-inf, 15.9, 15.9]), (217, [-inf, 16.9, 16.9]), (218, [-inf, 17.9, 17.9]), (219, [-inf, 18.9, 18.9]), (220, [-inf, 19.9, 19.9]), (221, [-inf, 20.9, 20.9]), (222, [-inf, 21.9, 21.9]), (223, [-inf, 22.9, 22.9]), (224, [-inf, 23.9, 23.9]), (225, [-inf, 24.9, 24.9]), (226, [-inf, 25.9, 25.9]), (227, [-inf, 26.9, 26.9]), (228, [-inf, 27.9, 27.9]), (229, [-inf, 28.9, 28.9]), (230, [-inf, 29.9, 29.9]), (231, [-inf, 30.9, 30.9]), (232, [-inf, 31.9, 31.9]), (233, [-inf, 32.9, 32.9]), (234, [-inf, 33.9, 33.9]), (235, [-inf, 34.9, 34.9]), (236, [-inf, 35.9, 35.9]), (237, [-inf, 36.9, 36.9]), (238, [-inf, 37.9, 37.9]), (239, [-inf, 38.9, 38.9]), (240, [-inf, 39.9, 39.9]), (241, [-inf, 40.9, 40.9]), (242, [-inf, 41.9, 41.9]), (243, [-inf, 42.9, 42.9]), (244, [-inf, 43.9, 43.9]), (245, [-inf, 44.9, 44.9]), (246, [-inf, 45.9, 45.9]), (247, [-inf, 46.9, 46.9]), (248, [-inf, 47.9, 47.9]), (249, [-inf, 48.9, 48.9]), (250, [-inf, 49.9, 49.9]), (251, [-inf, 50.9, 50.9]), (252, [-inf, 51.9, 51.9]), (253, [-inf, 52.9, 52.9]), (254, [-inf, 53.9, 53.9]), (255, [-inf, 54.9, 54.9]), (256, [-inf, 55.9, 55.9]), (257, [-inf, 56.9, 56.9]), (258, [-inf, 57.9, 57.9]), (259, [-inf, 58.9, 58.9]), (260, [-inf, 59.9, 59.9]), (261, [-inf, 60.9, 60.9]), (262, [-inf, 61.9, 61.9]), (263, [-inf, 62.9, 62.9]), (264, [-inf, 63.9, 63.9]), (265, [-inf, 64.9, 64.9]), (266, [-inf, 65.9, 65.9]), (267, [-inf, 66.9, 66.9]), (268, [-inf, 67.9, 67.9]), (269, [-inf, 68.9, 68.9]), (270, [-inf, 69.9, 69.9]), (271, [-inf, 70.9, 70.9]), (272, [-inf, 71.9, 71.9]), (273, [-inf, 72.9, 72.9]), (274, [-inf, 73.9, 73.9]), (275, [-inf, 74.9, 74.9]), (276, [-inf, 75.9, 75.9]), (277, [-inf, 76.9, 76.9]), (278, [-inf, 77.9, 77.9]), (279, [-inf, 78.9, 78.9]), (280, [-inf, 79.9, 79.9]), (281, [-inf, 80.9, 80.9]), (282, [-inf, 81.9, 81.9]), (283, [-inf, 82.9, 82.9]), (284, [-inf, 83.9, 83.9]), (285, [-inf, 84.9, 84.9]), (286, [-inf, 85.9, 85.9]), (287, [-inf, 86.9, 86.9]), (288, [-inf, 87.9, 87.9]), (289, [-inf, 88.9, 88.9]), (290, [-inf, 89.9, 89.9]), (291, [-inf, 90.9, 90.9]), (292, [-inf, 91.9, 91.9]), (293, [-inf, 92.9, 92.9]), (294, [-inf, 93.9, 93.9]), (295, [-inf, 94.9, 94.9]), (296, [-inf, 95.9, 95.9]), (297, [-inf, 96.9, 96.9]), (298, [-inf, 97.9, 97.9]), (299, [-inf, 98.9, 98.9]), (300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] stack[3]: [(300, [1.0, 1.5, 1.5]), (301, [2.0, 2.5, 2.5]), (302, [3.0, 3.5, 3.5]), (303, [4.0, 4.5, 4.5]), (304, [5.0, 5.5, 5.5]), (305, [6.0, 6.5, 6.5]), (306, [7.0, 7.5, 7.5]), (307, [8.0, 8.5, 8.5]), (308, [9.0, 9.5, 9.5]), (309, [10.0, 10.5, 10.5]), (310, [11.0, 11.5, 11.5]), (311, [12.0, 12.5, 12.5]), (312, [13.0, 13.5, 13.5]), (313, [14.0, 14.5, 14.5]), (314, [15.0, 15.5, 15.5]), (315, [16.0, 16.5, 16.5]), (316, [17.0, 17.5, 17.5]), (317, [18.0, 18.5, 18.5]), (318, [19.0, 19.5, 19.5]), (319, [20.0, 20.5, 20.5]), (320, [21.0, 21.5, 21.5]), (321, [22.0, 22.5, 22.5]), (322, [23.0, 23.5, 23.5]), (323, [24.0, 24.5, 24.5]), (324, [25.0, 25.5, 25.5]), (325, [26.0, 26.5, 26.5]), (326, [27.0, 27.5, 27.5]), (327, [28.0, 28.5, 28.5]), (328, [29.0, 29.5, 29.5]), (329, [30.0, 30.5, 30.5]), (330, [31.0, 31.5, 31.5]), (331, [32.0, 32.5, 32.5]), (332, [33.0, 33.5, 33.5]), (333, [34.0, 34.5, 34.5]), (334, [35.0, 35.5, 35.5]), (335, [36.0, 36.5, 36.5]), (336, [37.0, 37.5, 37.5]), (337, [38.0, 38.5, 38.5]), (338, [39.0, 39.5, 39.5]), (339, [40.0, 40.5, 40.5]), (340, [41.0, 41.5, 41.5]), (341, [42.0, 42.5, 42.5]), (342, [43.0, 43.5, 43.5]), (343, [44.0, 44.5, 44.5]), (344, [45.0, 45.5, 45.5]), (345, [46.0, 46.5, 46.5]), (346, [47.0, 47.5, 47.5]), (347, [48.0, 48.5, 48.5]), (348, [49.0, 49.5, 49.5]), (349, [50.0, 50.5, 50.5]), (350, [51.0, 51.5, 51.5]), (351, [52.0, 52.5, 52.5]), (352, [53.0, 53.5, 53.5]), (353, [54.0, 54.5, 54.5]), (354, [55.0, 55.5, 55.5]), (355, [56.0, 56.5, 56.5]), (356, [57.0, 57.5, 57.5]), (357, [58.0, 58.5, 58.5]), (358, [59.0, 59.5, 59.5]), (359, [60.0, 60.5, 60.5]), (360, [61.0, 61.5, 61.5]), (361, [62.0, 62.5, 62.5]), (362, [63.0, 63.5, 63.5]), (363, [64.0, 64.5, 64.5]), (364, [65.0, 65.5, 65.5]), (365, [66.0, 66.5, 66.5]), (366, [67.0, 67.5, 67.5]), (367, [68.0, 68.5, 68.5]), (368, [69.0, 69.5, 69.5]), (369, [70.0, 70.5, 70.5]), (370, [71.0, 71.5, 71.5]), (371, [72.0, 72.5, 72.5]), (372, [73.0, 73.5, 73.5]), (373, [74.0, 74.5, 74.5]), (374, [75.0, 75.5, 75.5]), (375, [76.0, 76.5, 76.5]), (376, [77.0, 77.5, 77.5]), (377, [78.0, 78.5, 78.5]), (378, [79.0, 79.5, 79.5]), (379, [80.0, 80.5, 80.5]), (380, [81.0, 81.5, 81.5]), (381, [82.0, 82.5, 82.5]), (382, [83.0, 83.5, 83.5]), (383, [84.0, 84.5, 84.5]), (384, [85.0, 85.5, 85.5]), (385, [86.0, 86.5, 86.5]), (386, [87.0, 87.5, 87.5]), (387, [88.0, 88.5, 88.5]), (388, [89.0, 89.5, 89.5]), (389, [90.0, 90.5, 90.5]), (390, [91.0, 91.5, 91.5]), (391, [92.0, 92.5, 92.5]), (392, [93.0, 93.5, 93.5]), (393, [94.0, 94.5, 94.5]), (394, [95.0, 95.5, 95.5]), (395, [96.0, 96.5, 96.5]), (396, [97.0, 97.5, 97.5]), (397, [98.0, 98.5, 98.5]), (398, [99.0, 99.5, 99.5]), (399, [100.0, 100.5, 100.5])] 1 1.1 reading: [1.0, 1.5, 1.5] 2 2.1 reading: [2.0, 2.5, 2.5] 3 3.1 reading: [3.0, 3.5, 3.5] 4 4.1 reading: [4.0, 4.5, 4.5] 5 5.1 reading: [5.0, 5.5, 5.5] 6 6.1 reading: [6.0, 6.5, 6.5] 7 7.1 reading: [7.0, 7.5, 7.5] 8 8.1 reading: [8.0, 8.5, 8.5] 9 9.1 reading: [9.0, 9.5, 9.5] 10 10.1 reading: [10.0, 10.5, 10.5] 11 11.1 reading: [11.0, 11.5, 11.5] 12 12.1 reading: [12.0, 12.5, 12.5] 13 13.1 reading: [13.0, 13.5, 13.5] 14 14.1 reading: [14.0, 14.5, 14.5] 15 15.1 reading: [15.0, 15.5, 15.5] 16 16.1 reading: [16.0, 16.5, 16.5] 17 17.1 reading: [17.0, 17.5, 17.5] 18 18.1 reading: [18.0, 18.5, 18.5] 19 19.1 reading: [19.0, 19.5, 19.5] 20 20.1 reading: [20.0, 20.5, 20.5] 21 21.1 reading: [21.0, 21.5, 21.5] 22 22.1 reading: [22.0, 22.5, 22.5] 23 23.1 reading: [23.0, 23.5, 23.5] 24 24.1 reading: [24.0, 24.5, 24.5] 25 25.1 reading: [25.0, 25.5, 25.5] 26 26.1 reading: [26.0, 26.5, 26.5] 27 27.1 reading: [27.0, 27.5, 27.5] 28 28.1 reading: [28.0, 28.5, 28.5] 29 29.1 reading: [29.0, 29.5, 29.5] 30 30.1 reading: [30.0, 30.5, 30.5] 31 31.1 reading: [31.0, 31.5, 31.5] 32 32.1 reading: [32.0, 32.5, 32.5] 33 33.1 reading: [33.0, 33.5, 33.5] 34 34.1 reading: [34.0, 34.5, 34.5] 35 35.1 reading: [35.0, 35.5, 35.5] 36 36.1 reading: [36.0, 36.5, 36.5] 37 37.1 reading: [37.0, 37.5, 37.5] 38 38.1 reading: [38.0, 38.5, 38.5] 39 39.1 reading: [39.0, 39.5, 39.5] 40 40.1 reading: [40.0, 40.5, 40.5] 41 41.1 reading: [41.0, 41.5, 41.5] 42 42.1 reading: [42.0, 42.5, 42.5] 43 43.1 reading: [43.0, 43.5, 43.5] 44 44.1 reading: [44.0, 44.5, 44.5] 45 45.1 reading: [45.0, 45.5, 45.5] 46 46.1 reading: [46.0, 46.5, 46.5] 47 47.1 reading: [47.0, 47.5, 47.5] 48 48.1 reading: [48.0, 48.5, 48.5] 49 49.1 reading: [49.0, 49.5, 49.5] 50 50.1 reading: [50.0, 50.5, 50.5] 51 51.1 reading: [51.0, 51.5, 51.5] 52 52.1 reading: [52.0, 52.5, 52.5] 53 53.1 reading: [53.0, 53.5, 53.5] 54 54.1 reading: [54.0, 54.5, 54.5] 55 55.1 reading: [55.0, 55.5, 55.5] 56 56.1 reading: [56.0, 56.5, 56.5] 57 57.1 reading: [57.0, 57.5, 57.5] 58 58.1 reading: [58.0, 58.5, 58.5] 59 59.1 reading: [59.0, 59.5, 59.5] 60 60.1 reading: [60.0, 60.5, 60.5] 61 61.1 reading: [61.0, 61.5, 61.5] 62 62.1 reading: [62.0, 62.5, 62.5] 63 63.1 reading: [63.0, 63.5, 63.5] 64 64.1 reading: [64.0, 64.5, 64.5] 65 65.1 reading: [65.0, 65.5, 65.5] 66 66.1 reading: [66.0, 66.5, 66.5] 67 67.1 reading: [67.0, 67.5, 67.5] 68 68.1 reading: [68.0, 68.5, 68.5] 69 69.1 reading: [69.0, 69.5, 69.5] 70 70.1 reading: [70.0, 70.5, 70.5] 71 71.1 reading: [71.0, 71.5, 71.5] 72 72.1 reading: [72.0, 72.5, 72.5] 73 73.1 reading: [73.0, 73.5, 73.5] 74 74.1 reading: [74.0, 74.5, 74.5] 75 75.1 reading: [75.0, 75.5, 75.5] 76 76.1 reading: [76.0, 76.5, 76.5] 77 77.1 reading: [77.0, 77.5, 77.5] 78 78.1 reading: [78.0, 78.5, 78.5] 79 79.1 reading: [79.0, 79.5, 79.5] 80 80.1 reading: [80.0, 80.5, 80.5] 81 81.1 reading: [81.0, 81.5, 81.5] 82 82.1 reading: [82.0, 82.5, 82.5] 83 83.1 reading: [83.0, 83.5, 83.5] 84 84.1 reading: [84.0, 84.5, 84.5] 85 85.1 reading: [85.0, 85.5, 85.5] 86 86.1 reading: [86.0, 86.5, 86.5] 87 87.1 reading: [87.0, 87.5, 87.5] 88 88.1 reading: [88.0, 88.5, 88.5] 89 89.1 reading: [89.0, 89.5, 89.5] 90 90.1 reading: [90.0, 90.5, 90.5] 91 91.1 reading: [91.0, 91.5, 91.5] 92 92.1 reading: [92.0, 92.5, 92.5] 93 93.1 reading: [93.0, 93.5, 93.5] 94 94.1 reading: [94.0, 94.5, 94.5] 95 95.1 reading: [95.0, 95.5, 95.5] 96 96.1 reading: [96.0, 96.5, 96.5] 97 97.1 reading: [97.0, 97.5, 97.5] 98 98.1 reading: [98.0, 98.5, 98.5] 99 99.1 reading: [99.0, 99.5, 99.5] 100 100.1 reading: [100.0, 100.5, 100.5] ======== <class 'ultranest.store.HDF5PointStore'> N=1 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.5, 1.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([0., 1., 1.])), (2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] stack[1]: [(1, array([0., 1., 1.])), (2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] 0 0.1 reading: [0. 1. 1.] stack[2]: [(2, array([-inf, -0.1, -0.1])), (3, array([1. , 1.5, 1.5]))] stack[3]: [(3, array([1. , 1.5, 1.5]))] 1 1.1 reading: [1. 1.5 1.5] ======== <class 'ultranest.store.HDF5PointStore'> N=2 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([0., 1., 1.])), (3, array([1., 2., 2.])), (4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] stack[1]: [(2, array([0., 1., 1.])), (3, array([1., 2., 2.])), (4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] stack[2]: [(4, array([-inf, -0.1, -0.1])), (5, array([-inf, 0.9, 0.9])), (6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] stack[3]: [(6, array([1. , 1.5, 1.5])), (7, array([2. , 2.5, 2.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] ======== <class 'ultranest.store.HDF5PointStore'> N=10 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([-inf, 1.9, 1.9])), (3, array([-inf, 2.9, 2.9])), (4, array([-inf, 3.9, 3.9])), (5, array([-inf, 4.9, 4.9])), (6, array([-inf, 5.9, 5.9])), (7, array([-inf, 6.9, 6.9])), (8, array([-inf, 7.9, 7.9])), (9, array([-inf, 8.9, 8.9])), (10, array([0., 1., 1.])), (11, array([1., 2., 2.])), (12, array([2., 3., 3.])), (13, array([3., 4., 4.])), (14, array([4., 5., 5.])), (15, array([5., 6., 6.])), (16, array([6., 7., 7.])), (17, array([7., 8., 8.])), (18, array([8., 9., 9.])), (19, array([ 9., 10., 10.])), (20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] stack[1]: [(10, array([0., 1., 1.])), (11, array([1., 2., 2.])), (12, array([2., 3., 3.])), (13, array([3., 4., 4.])), (14, array([4., 5., 5.])), (15, array([5., 6., 6.])), (16, array([6., 7., 7.])), (17, array([7., 8., 8.])), (18, array([8., 9., 9.])), (19, array([ 9., 10., 10.])), (20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] 2 2.1 reading: [2. 3. 3.] 3 3.1 reading: [3. 4. 4.] 4 4.1 reading: [4. 5. 5.] 5 5.1 reading: [5. 6. 6.] 6 6.1 reading: [6. 7. 7.] 7 7.1 reading: [7. 8. 8.] 8 8.1 reading: [8. 9. 9.] 9 9.1 reading: [ 9. 10. 10.] stack[2]: [(20, array([-inf, -0.1, -0.1])), (21, array([-inf, 0.9, 0.9])), (22, array([-inf, 1.9, 1.9])), (23, array([-inf, 2.9, 2.9])), (24, array([-inf, 3.9, 3.9])), (25, array([-inf, 4.9, 4.9])), (26, array([-inf, 5.9, 5.9])), (27, array([-inf, 6.9, 6.9])), (28, array([-inf, 7.9, 7.9])), (29, array([-inf, 8.9, 8.9])), (30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] stack[3]: [(30, array([1. , 1.5, 1.5])), (31, array([2. , 2.5, 2.5])), (32, array([3. , 3.5, 3.5])), (33, array([4. , 4.5, 4.5])), (34, array([5. , 5.5, 5.5])), (35, array([6. , 6.5, 6.5])), (36, array([7. , 7.5, 7.5])), (37, array([8. , 8.5, 8.5])), (38, array([9. , 9.5, 9.5])), (39, array([10. , 10.5, 10.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] 3 3.1 reading: [3. 3.5 3.5] 4 4.1 reading: [4. 4.5 4.5] 5 5.1 reading: [5. 5.5 5.5] 6 6.1 reading: [6. 6.5 6.5] 7 7.1 reading: [7. 7.5 7.5] 8 8.1 reading: [8. 8.5 8.5] 9 9.1 reading: [9. 9.5 9.5] 10 10.1 reading: [10. 10.5 10.5] ======== <class 'ultranest.store.HDF5PointStore'> N=100 ======== writing... 0 1 storing: [0, 0.1, 0.1] 1 2 storing: [1, 1.1, 1.1] 2 3 storing: [2, 2.1, 2.1] 3 4 storing: [3, 3.1, 3.1] 4 5 storing: [4, 4.1, 4.1] 5 6 storing: [5, 5.1, 5.1] 6 7 storing: [6, 6.1, 6.1] 7 8 storing: [7, 7.1, 7.1] 8 9 storing: [8, 8.1, 8.1] 9 10 storing: [9, 9.1, 9.1] 10 11 storing: [10, 10.1, 10.1] 11 12 storing: [11, 11.1, 11.1] 12 13 storing: [12, 12.1, 12.1] 13 14 storing: [13, 13.1, 13.1] 14 15 storing: [14, 14.1, 14.1] 15 16 storing: [15, 15.1, 15.1] 16 17 storing: [16, 16.1, 16.1] 17 18 storing: [17, 17.1, 17.1] 18 19 storing: [18, 18.1, 18.1] 19 20 storing: [19, 19.1, 19.1] 20 21 storing: [20, 20.1, 20.1] 21 22 storing: [21, 21.1, 21.1] 22 23 storing: [22, 22.1, 22.1] 23 24 storing: [23, 23.1, 23.1] 24 25 storing: [24, 24.1, 24.1] 25 26 storing: [25, 25.1, 25.1] 26 27 storing: [26, 26.1, 26.1] 27 28 storing: [27, 27.1, 27.1] 28 29 storing: [28, 28.1, 28.1] 29 30 storing: [29, 29.1, 29.1] 30 31 storing: [30, 30.1, 30.1] 31 32 storing: [31, 31.1, 31.1] 32 33 storing: [32, 32.1, 32.1] 33 34 storing: [33, 33.1, 33.1] 34 35 storing: [34, 34.1, 34.1] 35 36 storing: [35, 35.1, 35.1] 36 37 storing: [36, 36.1, 36.1] 37 38 storing: [37, 37.1, 37.1] 38 39 storing: [38, 38.1, 38.1] 39 40 storing: [39, 39.1, 39.1] 40 41 storing: [40, 40.1, 40.1] 41 42 storing: [41, 41.1, 41.1] 42 43 storing: [42, 42.1, 42.1] 43 44 storing: [43, 43.1, 43.1] 44 45 storing: [44, 44.1, 44.1] 45 46 storing: [45, 45.1, 45.1] 46 47 storing: [46, 46.1, 46.1] 47 48 storing: [47, 47.1, 47.1] 48 49 storing: [48, 48.1, 48.1] 49 50 storing: [49, 49.1, 49.1] 50 51 storing: [50, 50.1, 50.1] 51 52 storing: [51, 51.1, 51.1] 52 53 storing: [52, 52.1, 52.1] 53 54 storing: [53, 53.1, 53.1] 54 55 storing: [54, 54.1, 54.1] 55 56 storing: [55, 55.1, 55.1] 56 57 storing: [56, 56.1, 56.1] 57 58 storing: [57, 57.1, 57.1] 58 59 storing: [58, 58.1, 58.1] 59 60 storing: [59, 59.1, 59.1] 60 61 storing: [60, 60.1, 60.1] 61 62 storing: [61, 61.1, 61.1] 62 63 storing: [62, 62.1, 62.1] 63 64 storing: [63, 63.1, 63.1] 64 65 storing: [64, 64.1, 64.1] 65 66 storing: [65, 65.1, 65.1] 66 67 storing: [66, 66.1, 66.1] 67 68 storing: [67, 67.1, 67.1] 68 69 storing: [68, 68.1, 68.1] 69 70 storing: [69, 69.1, 69.1] 70 71 storing: [70, 70.1, 70.1] 71 72 storing: [71, 71.1, 71.1] 72 73 storing: [72, 72.1, 72.1] 73 74 storing: [73, 73.1, 73.1] 74 75 storing: [74, 74.1, 74.1] 75 76 storing: [75, 75.1, 75.1] 76 77 storing: [76, 76.1, 76.1] 77 78 storing: [77, 77.1, 77.1] 78 79 storing: [78, 78.1, 78.1] 79 80 storing: [79, 79.1, 79.1] 80 81 storing: [80, 80.1, 80.1] 81 82 storing: [81, 81.1, 81.1] 82 83 storing: [82, 82.1, 82.1] 83 84 storing: [83, 83.1, 83.1] 84 85 storing: [84, 84.1, 84.1] 85 86 storing: [85, 85.1, 85.1] 86 87 storing: [86, 86.1, 86.1] 87 88 storing: [87, 87.1, 87.1] 88 89 storing: [88, 88.1, 88.1] 89 90 storing: [89, 89.1, 89.1] 90 91 storing: [90, 90.1, 90.1] 91 92 storing: [91, 91.1, 91.1] 92 93 storing: [92, 92.1, 92.1] 93 94 storing: [93, 93.1, 93.1] 94 95 storing: [94, 94.1, 94.1] 95 96 storing: [95, 95.1, 95.1] 96 97 storing: [96, 96.1, 96.1] 97 98 storing: [97, 97.1, 97.1] 98 99 storing: [98, 98.1, 98.1] 99 100 storing: [99, 99.1, 99.1] 1 2 storing: [1, 1.5, 1.5] 2 3 storing: [2, 2.5, 2.5] 3 4 storing: [3, 3.5, 3.5] 4 5 storing: [4, 4.5, 4.5] 5 6 storing: [5, 5.5, 5.5] 6 7 storing: [6, 6.5, 6.5] 7 8 storing: [7, 7.5, 7.5] 8 9 storing: [8, 8.5, 8.5] 9 10 storing: [9, 9.5, 9.5] 10 11 storing: [10, 10.5, 10.5] 11 12 storing: [11, 11.5, 11.5] 12 13 storing: [12, 12.5, 12.5] 13 14 storing: [13, 13.5, 13.5] 14 15 storing: [14, 14.5, 14.5] 15 16 storing: [15, 15.5, 15.5] 16 17 storing: [16, 16.5, 16.5] 17 18 storing: [17, 17.5, 17.5] 18 19 storing: [18, 18.5, 18.5] 19 20 storing: [19, 19.5, 19.5] 20 21 storing: [20, 20.5, 20.5] 21 22 storing: [21, 21.5, 21.5] 22 23 storing: [22, 22.5, 22.5] 23 24 storing: [23, 23.5, 23.5] 24 25 storing: [24, 24.5, 24.5] 25 26 storing: [25, 25.5, 25.5] 26 27 storing: [26, 26.5, 26.5] 27 28 storing: [27, 27.5, 27.5] 28 29 storing: [28, 28.5, 28.5] 29 30 storing: [29, 29.5, 29.5] 30 31 storing: [30, 30.5, 30.5] 31 32 storing: [31, 31.5, 31.5] 32 33 storing: [32, 32.5, 32.5] 33 34 storing: [33, 33.5, 33.5] 34 35 storing: [34, 34.5, 34.5] 35 36 storing: [35, 35.5, 35.5] 36 37 storing: [36, 36.5, 36.5] 37 38 storing: [37, 37.5, 37.5] 38 39 storing: [38, 38.5, 38.5] 39 40 storing: [39, 39.5, 39.5] 40 41 storing: [40, 40.5, 40.5] 41 42 storing: [41, 41.5, 41.5] 42 43 storing: [42, 42.5, 42.5] 43 44 storing: [43, 43.5, 43.5] 44 45 storing: [44, 44.5, 44.5] 45 46 storing: [45, 45.5, 45.5] 46 47 storing: [46, 46.5, 46.5] 47 48 storing: [47, 47.5, 47.5] 48 49 storing: [48, 48.5, 48.5] 49 50 storing: [49, 49.5, 49.5] 50 51 storing: [50, 50.5, 50.5] 51 52 storing: [51, 51.5, 51.5] 52 53 storing: [52, 52.5, 52.5] 53 54 storing: [53, 53.5, 53.5] 54 55 storing: [54, 54.5, 54.5] 55 56 storing: [55, 55.5, 55.5] 56 57 storing: [56, 56.5, 56.5] 57 58 storing: [57, 57.5, 57.5] 58 59 storing: [58, 58.5, 58.5] 59 60 storing: [59, 59.5, 59.5] 60 61 storing: [60, 60.5, 60.5] 61 62 storing: [61, 61.5, 61.5] 62 63 storing: [62, 62.5, 62.5] 63 64 storing: [63, 63.5, 63.5] 64 65 storing: [64, 64.5, 64.5] 65 66 storing: [65, 65.5, 65.5] 66 67 storing: [66, 66.5, 66.5] 67 68 storing: [67, 67.5, 67.5] 68 69 storing: [68, 68.5, 68.5] 69 70 storing: [69, 69.5, 69.5] 70 71 storing: [70, 70.5, 70.5] 71 72 storing: [71, 71.5, 71.5] 72 73 storing: [72, 72.5, 72.5] 73 74 storing: [73, 73.5, 73.5] 74 75 storing: [74, 74.5, 74.5] 75 76 storing: [75, 75.5, 75.5] 76 77 storing: [76, 76.5, 76.5] 77 78 storing: [77, 77.5, 77.5] 78 79 storing: [78, 78.5, 78.5] 79 80 storing: [79, 79.5, 79.5] 80 81 storing: [80, 80.5, 80.5] 81 82 storing: [81, 81.5, 81.5] 82 83 storing: [82, 82.5, 82.5] 83 84 storing: [83, 83.5, 83.5] 84 85 storing: [84, 84.5, 84.5] 85 86 storing: [85, 85.5, 85.5] 86 87 storing: [86, 86.5, 86.5] 87 88 storing: [87, 87.5, 87.5] 88 89 storing: [88, 88.5, 88.5] 89 90 storing: [89, 89.5, 89.5] 90 91 storing: [90, 90.5, 90.5] 91 92 storing: [91, 91.5, 91.5] 92 93 storing: [92, 92.5, 92.5] 93 94 storing: [93, 93.5, 93.5] 94 95 storing: [94, 94.5, 94.5] 95 96 storing: [95, 95.5, 95.5] 96 97 storing: [96, 96.5, 96.5] 97 98 storing: [97, 97.5, 97.5] 98 99 storing: [98, 98.5, 98.5] 99 100 storing: [99, 99.5, 99.5] 100 101 storing: [100, 100.5, 100.5] reading... stack[0]: [(0, array([-inf, -0.1, -0.1])), (1, array([-inf, 0.9, 0.9])), (2, array([-inf, 1.9, 1.9])), (3, array([-inf, 2.9, 2.9])), (4, array([-inf, 3.9, 3.9])), (5, array([-inf, 4.9, 4.9])), (6, array([-inf, 5.9, 5.9])), (7, array([-inf, 6.9, 6.9])), (8, array([-inf, 7.9, 7.9])), (9, array([-inf, 8.9, 8.9])), (10, array([-inf, 9.9, 9.9])), (11, array([-inf, 10.9, 10.9])), (12, array([-inf, 11.9, 11.9])), (13, array([-inf, 12.9, 12.9])), (14, array([-inf, 13.9, 13.9])), (15, array([-inf, 14.9, 14.9])), (16, array([-inf, 15.9, 15.9])), (17, array([-inf, 16.9, 16.9])), (18, array([-inf, 17.9, 17.9])), (19, array([-inf, 18.9, 18.9])), (20, array([-inf, 19.9, 19.9])), (21, array([-inf, 20.9, 20.9])), (22, array([-inf, 21.9, 21.9])), (23, array([-inf, 22.9, 22.9])), (24, array([-inf, 23.9, 23.9])), (25, array([-inf, 24.9, 24.9])), (26, array([-inf, 25.9, 25.9])), (27, array([-inf, 26.9, 26.9])), (28, array([-inf, 27.9, 27.9])), (29, array([-inf, 28.9, 28.9])), (30, array([-inf, 29.9, 29.9])), (31, array([-inf, 30.9, 30.9])), (32, array([-inf, 31.9, 31.9])), (33, array([-inf, 32.9, 32.9])), (34, array([-inf, 33.9, 33.9])), (35, array([-inf, 34.9, 34.9])), (36, array([-inf, 35.9, 35.9])), (37, array([-inf, 36.9, 36.9])), (38, array([-inf, 37.9, 37.9])), (39, array([-inf, 38.9, 38.9])), (40, array([-inf, 39.9, 39.9])), (41, array([-inf, 40.9, 40.9])), (42, array([-inf, 41.9, 41.9])), (43, array([-inf, 42.9, 42.9])), (44, array([-inf, 43.9, 43.9])), (45, array([-inf, 44.9, 44.9])), (46, array([-inf, 45.9, 45.9])), (47, array([-inf, 46.9, 46.9])), (48, array([-inf, 47.9, 47.9])), (49, array([-inf, 48.9, 48.9])), (50, array([-inf, 49.9, 49.9])), (51, array([-inf, 50.9, 50.9])), (52, array([-inf, 51.9, 51.9])), (53, array([-inf, 52.9, 52.9])), (54, array([-inf, 53.9, 53.9])), (55, array([-inf, 54.9, 54.9])), (56, array([-inf, 55.9, 55.9])), (57, array([-inf, 56.9, 56.9])), (58, array([-inf, 57.9, 57.9])), (59, array([-inf, 58.9, 58.9])), (60, array([-inf, 59.9, 59.9])), (61, array([-inf, 60.9, 60.9])), (62, array([-inf, 61.9, 61.9])), (63, array([-inf, 62.9, 62.9])), (64, array([-inf, 63.9, 63.9])), (65, array([-inf, 64.9, 64.9])), (66, array([-inf, 65.9, 65.9])), (67, array([-inf, 66.9, 66.9])), (68, array([-inf, 67.9, 67.9])), (69, array([-inf, 68.9, 68.9])), (70, array([-inf, 69.9, 69.9])), (71, array([-inf, 70.9, 70.9])), (72, array([-inf, 71.9, 71.9])), (73, array([-inf, 72.9, 72.9])), (74, array([-inf, 73.9, 73.9])), (75, array([-inf, 74.9, 74.9])), (76, array([-inf, 75.9, 75.9])), (77, array([-inf, 76.9, 76.9])), (78, array([-inf, 77.9, 77.9])), (79, array([-inf, 78.9, 78.9])), (80, array([-inf, 79.9, 79.9])), (81, array([-inf, 80.9, 80.9])), (82, array([-inf, 81.9, 81.9])), (83, array([-inf, 82.9, 82.9])), (84, array([-inf, 83.9, 83.9])), (85, array([-inf, 84.9, 84.9])), (86, array([-inf, 85.9, 85.9])), (87, array([-inf, 86.9, 86.9])), (88, array([-inf, 87.9, 87.9])), (89, array([-inf, 88.9, 88.9])), (90, array([-inf, 89.9, 89.9])), (91, array([-inf, 90.9, 90.9])), (92, array([-inf, 91.9, 91.9])), (93, array([-inf, 92.9, 92.9])), (94, array([-inf, 93.9, 93.9])), (95, array([-inf, 94.9, 94.9])), (96, array([-inf, 95.9, 95.9])), (97, array([-inf, 96.9, 96.9])), (98, array([-inf, 97.9, 97.9])), (99, array([-inf, 98.9, 98.9])), (100, array([0., 1., 1.])), (101, array([1., 2., 2.])), (102, array([2., 3., 3.])), (103, array([3., 4., 4.])), (104, array([4., 5., 5.])), (105, array([5., 6., 6.])), (106, array([6., 7., 7.])), (107, array([7., 8., 8.])), (108, array([8., 9., 9.])), (109, array([ 9., 10., 10.])), (110, array([10., 11., 11.])), (111, array([11., 12., 12.])), (112, array([12., 13., 13.])), (113, array([13., 14., 14.])), (114, array([14., 15., 15.])), (115, array([15., 16., 16.])), (116, array([16., 17., 17.])), (117, array([17., 18., 18.])), (118, array([18., 19., 19.])), (119, array([19., 20., 20.])), (120, array([20., 21., 21.])), (121, array([21., 22., 22.])), (122, array([22., 23., 23.])), (123, array([23., 24., 24.])), (124, array([24., 25., 25.])), (125, array([25., 26., 26.])), (126, array([26., 27., 27.])), (127, array([27., 28., 28.])), (128, array([28., 29., 29.])), (129, array([29., 30., 30.])), (130, array([30., 31., 31.])), (131, array([31., 32., 32.])), (132, array([32., 33., 33.])), (133, array([33., 34., 34.])), (134, array([34., 35., 35.])), (135, array([35., 36., 36.])), (136, array([36., 37., 37.])), (137, array([37., 38., 38.])), (138, array([38., 39., 39.])), (139, array([39., 40., 40.])), (140, array([40., 41., 41.])), (141, array([41., 42., 42.])), 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(299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] 0 0.1 reading: [0. 1. 1.] 1 1.1 reading: [1. 2. 2.] 2 2.1 reading: [2. 3. 3.] 3 3.1 reading: [3. 4. 4.] 4 4.1 reading: [4. 5. 5.] 5 5.1 reading: [5. 6. 6.] 6 6.1 reading: [6. 7. 7.] 7 7.1 reading: [7. 8. 8.] 8 8.1 reading: [8. 9. 9.] 9 9.1 reading: [ 9. 10. 10.] 10 10.1 reading: [10. 11. 11.] 11 11.1 reading: [11. 12. 12.] 12 12.1 reading: [12. 13. 13.] 13 13.1 reading: [13. 14. 14.] 14 14.1 reading: [14. 15. 15.] 15 15.1 reading: [15. 16. 16.] 16 16.1 reading: [16. 17. 17.] 17 17.1 reading: [17. 18. 18.] 18 18.1 reading: [18. 19. 19.] 19 19.1 reading: [19. 20. 20.] 20 20.1 reading: [20. 21. 21.] 21 21.1 reading: [21. 22. 22.] 22 22.1 reading: [22. 23. 23.] 23 23.1 reading: [23. 24. 24.] 24 24.1 reading: [24. 25. 25.] 25 25.1 reading: [25. 26. 26.] 26 26.1 reading: [26. 27. 27.] 27 27.1 reading: [27. 28. 28.] 28 28.1 reading: [28. 29. 29.] 29 29.1 reading: [29. 30. 30.] 30 30.1 reading: [30. 31. 31.] 31 31.1 reading: [31. 32. 32.] 32 32.1 reading: [32. 33. 33.] 33 33.1 reading: [33. 34. 34.] 34 34.1 reading: [34. 35. 35.] 35 35.1 reading: [35. 36. 36.] 36 36.1 reading: [36. 37. 37.] 37 37.1 reading: [37. 38. 38.] 38 38.1 reading: [38. 39. 39.] 39 39.1 reading: [39. 40. 40.] 40 40.1 reading: [40. 41. 41.] 41 41.1 reading: [41. 42. 42.] 42 42.1 reading: [42. 43. 43.] 43 43.1 reading: [43. 44. 44.] 44 44.1 reading: [44. 45. 45.] 45 45.1 reading: [45. 46. 46.] 46 46.1 reading: [46. 47. 47.] 47 47.1 reading: [47. 48. 48.] 48 48.1 reading: [48. 49. 49.] 49 49.1 reading: [49. 50. 50.] 50 50.1 reading: [50. 51. 51.] 51 51.1 reading: [51. 52. 52.] 52 52.1 reading: [52. 53. 53.] 53 53.1 reading: [53. 54. 54.] 54 54.1 reading: [54. 55. 55.] 55 55.1 reading: [55. 56. 56.] 56 56.1 reading: [56. 57. 57.] 57 57.1 reading: [57. 58. 58.] 58 58.1 reading: [58. 59. 59.] 59 59.1 reading: [59. 60. 60.] 60 60.1 reading: [60. 61. 61.] 61 61.1 reading: [61. 62. 62.] 62 62.1 reading: [62. 63. 63.] 63 63.1 reading: [63. 64. 64.] 64 64.1 reading: [64. 65. 65.] 65 65.1 reading: [65. 66. 66.] 66 66.1 reading: [66. 67. 67.] 67 67.1 reading: [67. 68. 68.] 68 68.1 reading: [68. 69. 69.] 69 69.1 reading: [69. 70. 70.] 70 70.1 reading: [70. 71. 71.] 71 71.1 reading: [71. 72. 72.] 72 72.1 reading: [72. 73. 73.] 73 73.1 reading: [73. 74. 74.] 74 74.1 reading: [74. 75. 75.] 75 75.1 reading: [75. 76. 76.] 76 76.1 reading: [76. 77. 77.] 77 77.1 reading: [77. 78. 78.] 78 78.1 reading: [78. 79. 79.] 79 79.1 reading: [79. 80. 80.] 80 80.1 reading: [80. 81. 81.] 81 81.1 reading: [81. 82. 82.] 82 82.1 reading: [82. 83. 83.] 83 83.1 reading: [83. 84. 84.] 84 84.1 reading: [84. 85. 85.] 85 85.1 reading: [85. 86. 86.] 86 86.1 reading: [86. 87. 87.] 87 87.1 reading: [87. 88. 88.] 88 88.1 reading: [88. 89. 89.] 89 89.1 reading: [89. 90. 90.] 90 90.1 reading: [90. 91. 91.] 91 91.1 reading: [91. 92. 92.] 92 92.1 reading: [92. 93. 93.] 93 93.1 reading: [93. 94. 94.] 94 94.1 reading: [94. 95. 95.] 95 95.1 reading: [95. 96. 96.] 96 96.1 reading: [96. 97. 97.] 97 97.1 reading: [97. 98. 98.] 98 98.1 reading: [98. 99. 99.] 99 99.1 reading: [ 99. 100. 100.] stack[2]: [(200, array([-inf, -0.1, -0.1])), (201, array([-inf, 0.9, 0.9])), (202, array([-inf, 1.9, 1.9])), (203, array([-inf, 2.9, 2.9])), (204, array([-inf, 3.9, 3.9])), (205, array([-inf, 4.9, 4.9])), (206, array([-inf, 5.9, 5.9])), (207, array([-inf, 6.9, 6.9])), (208, array([-inf, 7.9, 7.9])), (209, array([-inf, 8.9, 8.9])), (210, array([-inf, 9.9, 9.9])), (211, array([-inf, 10.9, 10.9])), (212, array([-inf, 11.9, 11.9])), (213, array([-inf, 12.9, 12.9])), (214, array([-inf, 13.9, 13.9])), (215, array([-inf, 14.9, 14.9])), (216, array([-inf, 15.9, 15.9])), (217, array([-inf, 16.9, 16.9])), (218, array([-inf, 17.9, 17.9])), (219, array([-inf, 18.9, 18.9])), (220, array([-inf, 19.9, 19.9])), (221, array([-inf, 20.9, 20.9])), (222, array([-inf, 21.9, 21.9])), (223, array([-inf, 22.9, 22.9])), (224, array([-inf, 23.9, 23.9])), (225, array([-inf, 24.9, 24.9])), (226, array([-inf, 25.9, 25.9])), (227, array([-inf, 26.9, 26.9])), (228, array([-inf, 27.9, 27.9])), (229, array([-inf, 28.9, 28.9])), (230, array([-inf, 29.9, 29.9])), (231, array([-inf, 30.9, 30.9])), (232, array([-inf, 31.9, 31.9])), (233, array([-inf, 32.9, 32.9])), (234, array([-inf, 33.9, 33.9])), (235, array([-inf, 34.9, 34.9])), (236, array([-inf, 35.9, 35.9])), (237, array([-inf, 36.9, 36.9])), (238, array([-inf, 37.9, 37.9])), (239, array([-inf, 38.9, 38.9])), (240, array([-inf, 39.9, 39.9])), (241, array([-inf, 40.9, 40.9])), (242, array([-inf, 41.9, 41.9])), (243, array([-inf, 42.9, 42.9])), (244, array([-inf, 43.9, 43.9])), (245, array([-inf, 44.9, 44.9])), (246, array([-inf, 45.9, 45.9])), (247, array([-inf, 46.9, 46.9])), (248, array([-inf, 47.9, 47.9])), (249, array([-inf, 48.9, 48.9])), (250, array([-inf, 49.9, 49.9])), (251, array([-inf, 50.9, 50.9])), (252, array([-inf, 51.9, 51.9])), (253, array([-inf, 52.9, 52.9])), (254, array([-inf, 53.9, 53.9])), (255, array([-inf, 54.9, 54.9])), (256, array([-inf, 55.9, 55.9])), (257, array([-inf, 56.9, 56.9])), (258, array([-inf, 57.9, 57.9])), (259, array([-inf, 58.9, 58.9])), (260, array([-inf, 59.9, 59.9])), (261, array([-inf, 60.9, 60.9])), (262, array([-inf, 61.9, 61.9])), (263, array([-inf, 62.9, 62.9])), (264, array([-inf, 63.9, 63.9])), (265, array([-inf, 64.9, 64.9])), (266, array([-inf, 65.9, 65.9])), (267, array([-inf, 66.9, 66.9])), (268, array([-inf, 67.9, 67.9])), (269, array([-inf, 68.9, 68.9])), (270, array([-inf, 69.9, 69.9])), (271, array([-inf, 70.9, 70.9])), (272, array([-inf, 71.9, 71.9])), (273, array([-inf, 72.9, 72.9])), (274, array([-inf, 73.9, 73.9])), (275, array([-inf, 74.9, 74.9])), (276, array([-inf, 75.9, 75.9])), (277, array([-inf, 76.9, 76.9])), (278, array([-inf, 77.9, 77.9])), (279, array([-inf, 78.9, 78.9])), (280, array([-inf, 79.9, 79.9])), (281, array([-inf, 80.9, 80.9])), (282, array([-inf, 81.9, 81.9])), (283, array([-inf, 82.9, 82.9])), (284, array([-inf, 83.9, 83.9])), (285, array([-inf, 84.9, 84.9])), (286, array([-inf, 85.9, 85.9])), (287, array([-inf, 86.9, 86.9])), (288, array([-inf, 87.9, 87.9])), (289, array([-inf, 88.9, 88.9])), (290, array([-inf, 89.9, 89.9])), (291, array([-inf, 90.9, 90.9])), (292, array([-inf, 91.9, 91.9])), (293, array([-inf, 92.9, 92.9])), (294, array([-inf, 93.9, 93.9])), (295, array([-inf, 94.9, 94.9])), (296, array([-inf, 95.9, 95.9])), (297, array([-inf, 96.9, 96.9])), (298, array([-inf, 97.9, 97.9])), (299, array([-inf, 98.9, 98.9])), (300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] stack[3]: [(300, array([1. , 1.5, 1.5])), (301, array([2. , 2.5, 2.5])), (302, array([3. , 3.5, 3.5])), (303, array([4. , 4.5, 4.5])), (304, array([5. , 5.5, 5.5])), (305, array([6. , 6.5, 6.5])), (306, array([7. , 7.5, 7.5])), (307, array([8. , 8.5, 8.5])), (308, array([9. , 9.5, 9.5])), (309, array([10. , 10.5, 10.5])), (310, array([11. , 11.5, 11.5])), (311, array([12. , 12.5, 12.5])), (312, array([13. , 13.5, 13.5])), (313, array([14. , 14.5, 14.5])), (314, array([15. , 15.5, 15.5])), (315, array([16. , 16.5, 16.5])), (316, array([17. , 17.5, 17.5])), (317, array([18. , 18.5, 18.5])), (318, array([19. , 19.5, 19.5])), (319, array([20. , 20.5, 20.5])), (320, array([21. , 21.5, 21.5])), (321, array([22. , 22.5, 22.5])), (322, array([23. , 23.5, 23.5])), (323, array([24. , 24.5, 24.5])), (324, array([25. , 25.5, 25.5])), (325, array([26. , 26.5, 26.5])), (326, array([27. , 27.5, 27.5])), (327, array([28. , 28.5, 28.5])), (328, array([29. , 29.5, 29.5])), (329, array([30. , 30.5, 30.5])), (330, array([31. , 31.5, 31.5])), (331, array([32. , 32.5, 32.5])), (332, array([33. , 33.5, 33.5])), (333, array([34. , 34.5, 34.5])), (334, array([35. , 35.5, 35.5])), (335, array([36. , 36.5, 36.5])), (336, array([37. , 37.5, 37.5])), (337, array([38. , 38.5, 38.5])), (338, array([39. , 39.5, 39.5])), (339, array([40. , 40.5, 40.5])), (340, array([41. , 41.5, 41.5])), (341, array([42. , 42.5, 42.5])), (342, array([43. , 43.5, 43.5])), (343, array([44. , 44.5, 44.5])), (344, array([45. , 45.5, 45.5])), (345, array([46. , 46.5, 46.5])), (346, array([47. , 47.5, 47.5])), (347, array([48. , 48.5, 48.5])), (348, array([49. , 49.5, 49.5])), (349, array([50. , 50.5, 50.5])), (350, array([51. , 51.5, 51.5])), (351, array([52. , 52.5, 52.5])), (352, array([53. , 53.5, 53.5])), (353, array([54. , 54.5, 54.5])), (354, array([55. , 55.5, 55.5])), (355, array([56. , 56.5, 56.5])), (356, array([57. , 57.5, 57.5])), (357, array([58. , 58.5, 58.5])), (358, array([59. , 59.5, 59.5])), (359, array([60. , 60.5, 60.5])), (360, array([61. , 61.5, 61.5])), (361, array([62. , 62.5, 62.5])), (362, array([63. , 63.5, 63.5])), (363, array([64. , 64.5, 64.5])), (364, array([65. , 65.5, 65.5])), (365, array([66. , 66.5, 66.5])), (366, array([67. , 67.5, 67.5])), (367, array([68. , 68.5, 68.5])), (368, array([69. , 69.5, 69.5])), (369, array([70. , 70.5, 70.5])), (370, array([71. , 71.5, 71.5])), (371, array([72. , 72.5, 72.5])), (372, array([73. , 73.5, 73.5])), (373, array([74. , 74.5, 74.5])), (374, array([75. , 75.5, 75.5])), (375, array([76. , 76.5, 76.5])), (376, array([77. , 77.5, 77.5])), (377, array([78. , 78.5, 78.5])), (378, array([79. , 79.5, 79.5])), (379, array([80. , 80.5, 80.5])), (380, array([81. , 81.5, 81.5])), (381, array([82. , 82.5, 82.5])), (382, array([83. , 83.5, 83.5])), (383, array([84. , 84.5, 84.5])), (384, array([85. , 85.5, 85.5])), (385, array([86. , 86.5, 86.5])), (386, array([87. , 87.5, 87.5])), (387, array([88. , 88.5, 88.5])), (388, array([89. , 89.5, 89.5])), (389, array([90. , 90.5, 90.5])), (390, array([91. , 91.5, 91.5])), (391, array([92. , 92.5, 92.5])), (392, array([93. , 93.5, 93.5])), (393, array([94. , 94.5, 94.5])), (394, array([95. , 95.5, 95.5])), (395, array([96. , 96.5, 96.5])), (396, array([97. , 97.5, 97.5])), (397, array([98. , 98.5, 98.5])), (398, array([99. , 99.5, 99.5])), (399, array([100. , 100.5, 100.5]))] 1 1.1 reading: [1. 1.5 1.5] 2 2.1 reading: [2. 2.5 2.5] 3 3.1 reading: [3. 3.5 3.5] 4 4.1 reading: [4. 4.5 4.5] 5 5.1 reading: [5. 5.5 5.5] 6 6.1 reading: [6. 6.5 6.5] 7 7.1 reading: [7. 7.5 7.5] 8 8.1 reading: [8. 8.5 8.5] 9 9.1 reading: [9. 9.5 9.5] 10 10.1 reading: [10. 10.5 10.5] 11 11.1 reading: [11. 11.5 11.5] 12 12.1 reading: [12. 12.5 12.5] 13 13.1 reading: [13. 13.5 13.5] 14 14.1 reading: [14. 14.5 14.5] 15 15.1 reading: [15. 15.5 15.5] 16 16.1 reading: [16. 16.5 16.5] 17 17.1 reading: [17. 17.5 17.5] 18 18.1 reading: [18. 18.5 18.5] 19 19.1 reading: [19. 19.5 19.5] 20 20.1 reading: [20. 20.5 20.5] 21 21.1 reading: [21. 21.5 21.5] 22 22.1 reading: [22. 22.5 22.5] 23 23.1 reading: [23. 23.5 23.5] 24 24.1 reading: [24. 24.5 24.5] 25 25.1 reading: [25. 25.5 25.5] 26 26.1 reading: [26. 26.5 26.5] 27 27.1 reading: [27. 27.5 27.5] 28 28.1 reading: [28. 28.5 28.5] 29 29.1 reading: [29. 29.5 29.5] 30 30.1 reading: [30. 30.5 30.5] 31 31.1 reading: [31. 31.5 31.5] 32 32.1 reading: [32. 32.5 32.5] 33 33.1 reading: [33. 33.5 33.5] 34 34.1 reading: [34. 34.5 34.5] 35 35.1 reading: [35. 35.5 35.5] 36 36.1 reading: [36. 36.5 36.5] 37 37.1 reading: [37. 37.5 37.5] 38 38.1 reading: [38. 38.5 38.5] 39 39.1 reading: [39. 39.5 39.5] 40 40.1 reading: [40. 40.5 40.5] 41 41.1 reading: [41. 41.5 41.5] 42 42.1 reading: [42. 42.5 42.5] 43 43.1 reading: [43. 43.5 43.5] 44 44.1 reading: [44. 44.5 44.5] 45 45.1 reading: [45. 45.5 45.5] 46 46.1 reading: [46. 46.5 46.5] 47 47.1 reading: [47. 47.5 47.5] 48 48.1 reading: [48. 48.5 48.5] 49 49.1 reading: [49. 49.5 49.5] 50 50.1 reading: [50. 50.5 50.5] 51 51.1 reading: [51. 51.5 51.5] 52 52.1 reading: [52. 52.5 52.5] 53 53.1 reading: [53. 53.5 53.5] 54 54.1 reading: [54. 54.5 54.5] 55 55.1 reading: [55. 55.5 55.5] 56 56.1 reading: [56. 56.5 56.5] 57 57.1 reading: [57. 57.5 57.5] 58 58.1 reading: [58. 58.5 58.5] 59 59.1 reading: [59. 59.5 59.5] 60 60.1 reading: [60. 60.5 60.5] 61 61.1 reading: [61. 61.5 61.5] 62 62.1 reading: [62. 62.5 62.5] 63 63.1 reading: [63. 63.5 63.5] 64 64.1 reading: [64. 64.5 64.5] 65 65.1 reading: [65. 65.5 65.5] 66 66.1 reading: [66. 66.5 66.5] 67 67.1 reading: [67. 67.5 67.5] 68 68.1 reading: [68. 68.5 68.5] 69 69.1 reading: [69. 69.5 69.5] 70 70.1 reading: [70. 70.5 70.5] 71 71.1 reading: [71. 71.5 71.5] 72 72.1 reading: [72. 72.5 72.5] 73 73.1 reading: [73. 73.5 73.5] 74 74.1 reading: [74. 74.5 74.5] 75 75.1 reading: [75. 75.5 75.5] 76 76.1 reading: [76. 76.5 76.5] 77 77.1 reading: [77. 77.5 77.5] 78 78.1 reading: [78. 78.5 78.5] 79 79.1 reading: [79. 79.5 79.5] 80 80.1 reading: [80. 80.5 80.5] 81 81.1 reading: [81. 81.5 81.5] 82 82.1 reading: [82. 82.5 82.5] 83 83.1 reading: [83. 83.5 83.5] 84 84.1 reading: [84. 84.5 84.5] 85 85.1 reading: [85. 85.5 85.5] 86 86.1 reading: [86. 86.5 86.5] 87 87.1 reading: [87. 87.5 87.5] 88 88.1 reading: [88. 88.5 88.5] 89 89.1 reading: [89. 89.5 89.5] 90 90.1 reading: [90. 90.5 90.5] 91 91.1 reading: [91. 91.5 91.5] 92 92.1 reading: [92. 92.5 92.5] 93 93.1 reading: [93. 93.5 93.5] 94 94.1 reading: [94. 94.5 94.5] 95 95.1 reading: [95. 95.5 95.5] 96 96.1 reading: [96. 96.5 96.5] 97 97.1 reading: [97. 97.5 97.5] 98 98.1 reading: [98. 98.5 98.5] 99 99.1 reading: [99. 99.5 99.5] 100 100.1 reading: [100. 100.5 100.5] | |||
Passed | tests/test_transforms.py::test_transform | 0.02 | |
------------------------------Captured stdout call------------------------------ -0.999 1 [ 1. -0.999 -0.999 1. ] (1000, 2) -0.999 0.001 [ 1. -0.999 -0.999 1. ] (1000, 2) -0.8991 1 [ 1. -0.8991 -0.8991 1. ] (1000, 2) -0.8991 0.001 [ 1. -0.8991 -0.8991 1. ] (1000, 2) -0.7992 1 [ 1. -0.7992 -0.7992 1. ] (1000, 2) -0.7992 0.001 [ 1. -0.7992 -0.7992 1. ] (1000, 2) -0.6993 1 [ 1. -0.6993 -0.6993 1. ] (1000, 2) -0.6993 0.001 [ 1. -0.6993 -0.6993 1. ] (1000, 2) -0.5994 1 [ 1. -0.5994 -0.5994 1. ] (1000, 2) -0.5994 0.001 [ 1. -0.5994 -0.5994 1. ] (1000, 2) -0.4995000000000001 1 [ 1. -0.4995 -0.4995 1. ] (1000, 2) -0.4995000000000001 0.001 [ 1. -0.4995 -0.4995 1. ] (1000, 2) -0.3996000000000001 1 [ 1. -0.3996 -0.3996 1. ] (1000, 2) -0.3996000000000001 0.001 [ 1. -0.3996 -0.3996 1. ] (1000, 2) -0.29970000000000013 1 [ 1. -0.2997 -0.2997 1. ] (1000, 2) -0.29970000000000013 0.001 [ 1. -0.2997 -0.2997 1. ] (1000, 2) -0.19980000000000017 1 [ 1. -0.1998 -0.1998 1. ] (1000, 2) -0.19980000000000017 0.001 [ 1. -0.1998 -0.1998 1. ] (1000, 2) -0.0999000000000002 1 [ 1. -0.0999 -0.0999 1. ] (1000, 2) -0.0999000000000002 0.001 [ 1. -0.0999 -0.0999 1. ] (1000, 2) -2.2182256032010628e-16 1 [ 1.0000000e+00 -2.2182256e-16 -2.2182256e-16 1.0000000e+00] (1000, 2) -2.2182256032010628e-16 0.001 [ 1.0000000e+00 -2.2182256e-16 -2.2182256e-16 1.0000000e+00] (1000, 2) 0.09989999999999964 1 [1. 0.0999 0.0999 1. ] (1000, 2) 0.09989999999999964 0.001 [1. 0.0999 0.0999 1. ] (1000, 2) 0.19979999999999973 1 [1. 0.1998 0.1998 1. ] (1000, 2) 0.19979999999999973 0.001 [1. 0.1998 0.1998 1. ] (1000, 2) 0.2996999999999998 1 [1. 0.2997 0.2997 1. ] (1000, 2) 0.2996999999999998 0.001 [1. 0.2997 0.2997 1. ] (1000, 2) 0.3995999999999997 1 [1. 0.3996 0.3996 1. ] (1000, 2) 0.3995999999999997 0.001 [1. 0.3996 0.3996 1. ] (1000, 2) 0.49949999999999956 1 [1. 0.4995 0.4995 1. ] (1000, 2) 0.49949999999999956 0.001 [1. 0.4995 0.4995 1. ] (1000, 2) 0.5993999999999996 1 [1. 0.5994 0.5994 1. ] (1000, 2) 0.5993999999999996 0.001 [1. 0.5994 0.5994 1. ] (1000, 2) 0.6992999999999997 1 [1. 0.6993 0.6993 1. ] (1000, 2) 0.6992999999999997 0.001 [1. 0.6993 0.6993 1. ] (1000, 2) 0.7991999999999996 1 [1. 0.7992 0.7992 1. ] (1000, 2) 0.7991999999999996 0.001 [1. 0.7992 0.7992 1. ] (1000, 2) 0.8990999999999995 1 [1. 0.8991 0.8991 1. ] (1000, 2) 0.8990999999999995 0.001 [1. 0.8991 0.8991 1. ] (1000, 2) | |||
Passed | tests/test_transforms.py::test_affine_transform | 0.04 | |
------------------------------Captured stdout call------------------------------ settings: corr: 0 scaleratio: 1 covmatrix: [1. 0. 0. 1.] (400, 2) settings: corr: 0.6 scaleratio: 1 covmatrix: [1. 0.6 0.6 1. ] (400, 2) settings: corr: 0.95 scaleratio: 1 covmatrix: [1. 0.95 0.95 1. ] (400, 2) settings: corr: 0.999 scaleratio: 1 covmatrix: [1. 0.999 0.999 1. ] (400, 2) | |||
Passed | tests/test_transforms.py::test_wrap | 0.04 | |
------------------------------Captured stdout call------------------------------ Npoints=10 wrapped_dims=[] Npoints=10 wrapped_dims=[0] Npoints=10 wrapped_dims=[1] Npoints=10 wrapped_dims=[0, 1] Npoints=100 wrapped_dims=[] Npoints=100 wrapped_dims=[0] Npoints=100 wrapped_dims=[1] Npoints=100 wrapped_dims=[0, 1] Npoints=1000 wrapped_dims=[] Npoints=1000 wrapped_dims=[0] Npoints=1000 wrapped_dims=[1] Npoints=1000 wrapped_dims=[0, 1] | |||
Passed | tests/test_utils.py::test_vectorize | 0.00 | |
No log output captured. | |||
Passed | tests/test_utils.py::test_is_affine_transform | 0.00 | |
No log output captured. | |||
Passed | tests/test_viz.py::test_rounding_pos | 0.00 | |
No log output captured. | |||
Passed | tests/test_viz.py::test_rounding_u | 0.00 | |
No log output captured. | |||
Passed | tests/test_viz.py::test_rounding_negpos | 0.00 | |
No log output captured. | |||
Passed | tests/test_viz.py::test_rounding_withguess | 0.00 | |
No log output captured. | |||
Passed | tests/test_viz.py::test_fmt | 0.00 | |
No log output captured. |