source
get_default_dataset_path
get_default_dataset_path ()
Create a directory in the user’s home directory for storing datasets
get_default_dataset_path()
Path('/Users/daniel/.tsfast/datasets')
source
get_dataset_path
get_dataset_path ()
Retrieves the tsfast dataset directory. Tries to read the path in the environment variable ‘TSFAST_PATH’, returns the default otherwise.
env_path = '/directory/.tsfast/'
os.environ['TSFAST_PATH'] = env_path
test_eq(get_dataset_path(),Path(env_path))
get_dataset_path()
Path('/directory/.tsfast')
os.environ['TSFAST_PATH'] = ''
get_dataset_path()
Path('/Users/daniel/.tsfast/datasets')
source
clean_default_dataset_path
clean_default_dataset_path ()
Removes the default directory where the datasets are stored
source
create_dls_downl
create_dls_downl (dataset=None, download_function=None, win_sz:int=100,
x:list=[], stp_sz:int=1, sub_seq_len:int=None,
bs:int=64, prediction:bool=False,
input_delay:bool=False, valid_stp_sz:int=None,
cached:bool=True, num_workers:int=5,
max_batches_training:int=300,
max_batches_valid:int=None, dls_id:str=None, **kwargs)
dataset |
NoneType |
None |
path to the dataset directory, if not provided uses default |
download_function |
NoneType |
None |
function |
win_sz |
int |
100 |
|
x |
list |
[] |
|
stp_sz |
int |
1 |
|
sub_seq_len |
int |
None |
|
bs |
int |
64 |
|
prediction |
bool |
False |
|
input_delay |
bool |
False |
|
valid_stp_sz |
int |
None |
|
cached |
bool |
True |
|
num_workers |
int |
5 |
|
max_batches_training |
int |
300 |
|
max_batches_valid |
int |
None |
|
dls_id |
str |
None |
|
kwargs |
VAR_KEYWORD |
|
|
# #| export
# @delegates(create_dls_downloadable,keep=True)
# def create_dls_wh(
# dataset,
# win_sz=100,
# **kwargs):
# 'Dataloader for Wienerhammerstein Benchmark'
# return create_dls_downloadable(dataset,
# download_function=wiener_hammerstein,
# u=['u0'],
# y=['y0'],
# **kwargs)
Wiener Hammerstein Benchmark Dataset
dls = create_dls_wh()
dls.show_batch(max_n=1)
dls = create_dls_wh_prediction()
dls.show_batch(max_n=1)
dls[-1].show_batch(max_n=1)
Silverbox Benchmark Dataset
dls = create_dls_silverbox()
dls.show_batch(max_n=1)
dls = create_dls_silverbox_prediction()
dls.show_batch(max_n=1)
Cascaded Tanks Benchmark Dataset
dls = create_dls_cascaded_tanks()
len(dls.items)
dls = create_dls_cascaded_tanks()
dls.show_batch(max_n=1)
dls = create_dls_cascaded_tanks_prediction()
dls.show_batch(max_n=1)
EMPS Benchmark Dataset
dls = create_dls_emps()
dls.show_batch(max_n=1)
dls = create_dls_emps_prediction()
dls.show_batch(max_n=1)
CED Benchmark Dataset
dls = create_dls_ced()
dls.show_batch(max_n=1)
dls = create_dls_ced_prediction()
dls.show_batch(max_n=1)
Wiener Hammerstein with Process Noise Benchmark Dataset
dls = create_dls_noisy_wh()
dls.show_batch(max_n=1)
dls = create_dls_noisy_wh_prediction()
dls.show_batch(max_n=1)
Industrial Robot Benchmark Dataset
dls = create_dls_robot_forward()
dls.show_batch(max_n=1)
dls = create_dls_robot_forward_prediction()
dls.show_batch(max_n=1)
dls = create_dls_robot_inverse()
dls.show_batch(max_n=1)
dls = create_dls_robot_inverse_prediction()
dls.show_batch(max_n=1)
Ship Benchmark Dataset
dls = create_dls_ship()
dls.show_batch(max_n=1)
dls = create_dls_ship_prediction()
dls.show_batch(max_n=1)
Quadrotor Pelican Dataset
dls = create_dls_quad_pelican()
dls.show_batch(max_n=1)
dls = create_dls_quad_pelican_prediction()
dls.show_batch(max_n=1)
Quadrotor PI Dataset
dls = create_dls_quad_pi()
dls.show_batch(max_n=1)
dls = create_dls_quad_pi_prediction()
dls.show_batch(max_n=1)
BROAD Dataset
dls = create_dls_broad()
dls.show_batch(max_n=1)
dls = create_dls_broad_prediction()
dls.show_batch(max_n=1)