chore: Release v1.2.0 #91
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Checks were hard coded to ensure dimensions of e.g. sample-feature. However, we want to allow more general data, with sample and feature names provided by the user.
Dimensions were hard coded but we want Hilbert transform to be performed over any general 2D Arrays
Added three methods for creating synthetic DataArray, Dataset and list of DataArrays. These methods will slowly replace mock data currently used.
Support generation of test cases (resolve #55)
Other actions like converting multiindices or removing NaNs is present in separate classes
In Complex MCA, PCA preprocessing must happen before Hilbert transform (fix #85)
Move actual implementation of method into algorithm methods, while fit, transform, inverse_transform take care of pre and post-processing
Move Hilbert transform related methods into own file (resolve refactor: complex utilties #54)
Instead of individual classes that store different model results use a single DataContainer class that structures results in a dictionary (resolve #88).
Returned scores were always (L2) normalized which can lead to confusion when compared to the scores of other packages like sklearn or eofs. Now users can decide whether to return normalized or "raw" scores.
New parameter allows to choose whether dask models will be computed immediately after decomposition or not. Before, all dask objects were delayed until the end resulting in redundant dask computations.
scores aren't (yet) supported by GWPCA
Boolean or None values cannot be serialized by xarray which required manual conversion of attributes before to_netcdf can be used. Now model attributes are streamlined internally by converting any boolean or None values to strings (resolves #89 )
Conflict between poetry and torch version that cannot be resolved. Therefore remove cca-zoo dependency and associated tests.
Adds Self in python3.10
This was referenced Oct 24, 2023
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