cpmr 0.1.1
Enhancements
- Renamed internal constant
networks and
includes to corr_types and
inc_edges, respectively, to better reflect their purpose.
In addition, the documentation which mentioned networks has
been updated to use correlation types to better reflect their
meaning.
- Reorganized
R/cpm.R so cpm() remains the
entry-point function at the top, followed by print.cpm(),
with internal helpers grouped below.
- Improved test architecture with explicit internal-helper coverage
and complete-case fold invariants.
Maintenance
- Refactored the internal
cpm() workflow into smaller
helpers (normalize_inputs,
resolve_include_cases,
apply_confounds_regression, etc.) while preserving
user-facing behavior.
- Removed the obsolete internal alias
regress_counfounds().
- Removed broad
Rfast namespace import in favor of
explicit Rfast:: calls.
- Updated
summary.cpm() edge summarization path to avoid
mutating local object fields.
cpmr 0.1.0
New features
- Added
summary() method to summarize the results of the
CPM analysis (#8).
- Added
tidy() method to tidy the results of the CPM
analysis (#10).
- Support
na_action argument in cpm()
function to handle missing values in the input data (#2).
Enhancements
- Added
params to cpm() output to store the
input arguments (#14).
- Let
"sum" be the default value for
return_edges argument.
- Let the first two dimensions of
edges in the output be
edges and networks, respectively.
- Polish the print method of the
cpm class.
cpmr 0.0.9
New features
- Added support for row/column matrix as input for behavior and
confounds data.
Maintenance
- Added more data checks to ensure the input data are in the correct
format.
cpmr 0.0.8
- Added
return_edges argument to optionally set how to
return edges in the output.
cpmr 0.0.7
- Convert back to older version of confounds treating.
cpmr 0.0.6
- Ensure confounds regression are now only used in feature
selection.
cpmr 0.0.5
- Fixed confounds treatment. Now confounds are used in feature
selection but not in model fitting.
cpmr 0.0.4
- Ensure sparsity threshold method work as expect.
- Some other improvements in code quality.
cpmr 0.0.3
- Keep observation names in the output.
- Check if observation names match between neural data and behavioral
data.
cpmr 0.0.2
- Added support for confounding variables.
cpmr 0.0.1
- Initial commit to r-universe.