v0.1.4 (October 7, 2022)#
This is a minor release with a change in objective and bug fixes for issues identified since v0.1.3. This version is the first
uploaded using the PyData-sphinx-Theme. The new documentation
is built after fixing many minor bugs and improving the docstring documentation.
New features#
Major change Upload the SEG- EDI datasets. Henceforth, a sample of EDI data can be called for demonstration rather than using the data in
data/directory. Retrieving a sample of EDI is possible through the functionwatex.datasets.load_edis().Feature Upload the possibility to generate the synthetic ERP and VES data thanks to
watex.make_erp()andwatex.make_ves()respectively.Enhancement Revised the EM module by implementing the
watex.methods.em.Processing.skew()methods for computing the geological structures dimensionality. This function is useful to determine which type of inversion to use for modeling NSAMT data.Enhancement Generated Hydrogeology module
watex.methods.hydrofrom hydrogeological parameters computation from thewatex.utils.hydroutilsutilityMajor change Many other utilities have been added in
watex.utils.funcutilsandwatex.utils.plotutilsfor computation.Enhancement Document all the
watex.exceptionsmodule and reformat theWATexAPI documentationFeature Add a profiling report in the gallery examples. See sphx_glr_glr_examples_base_plot_profiling_report.py.
Major change Replace the shorthand of
fawithfactorin the new version of factor analysiswatex.analysis.factor.
Bug fixes#
Fix Fix the typos in
README.txtby changing theAnalysisbyAnalysessince many analyses are performed with many scripts in thewatex.analysismodule.Fix Fix the bug in
watex.view.biPlot(). Rename thexlabelandylabel.Fix Fixed bug in
watex.show_versions()to output the hard dependencies and update the public API inwatex.__init__.Fix Fixed bug in ERP and VES table for formatting the ERP and VES data sets documentation.
Fix Fix the bug in
watex.analysis.decomposition.linear_discriminant_analysis()mathematical formula in the docstrings. Henceforth the functionlinear_discriminant_analysis()returns weight factor of X transformed as :>>> def linear_discriminant_analysis(X,y, ...): ... return X.dot(W) if return_X else W
Fix Fixed bug in
watex.base.Data.profilingReport(). Exception henceforth occurs if the optional dependencypandas-profilingis not installed yet for report generation.Deprecated Delete the module
huafrom datasets and replace bywatex.datasets.setsfor fast loading the inner datasets.Major change Move tensor exceptions
ZErrorto the exceptions modulewatex.exceptionsand revised the EM exceptions errors in the wholewatex.externalsmodule.Fix Many other bugs were fixed in
watex.utils.plotutilsafter several tests.