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

• 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 function watex.datasets.load_edis().

• Upload the possibility to generate the synthetic ERP and VES data thanks to watex.make_erp() and watex.make_ves() respectively.

• 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.

• Generated Hydrogeology module watex.methods.hydro from hydrogeological parameters computation from the watex.utils.hydroutils utility

• Many other utilities have been added in watex.utils.funcutils and watex.utils.plotutils for computation.

• Document all the watex.exceptions module and reformat the WATex API documentation

• Add a profiling report in the gallery examples. See Plot Report Profiling.

Bug fixes

• Fix the typos in README.txt by changing the Analysis by Analyses since many analyses are performed with many scripts in the watex.analysis module.

• Fix the bug in watex.view.biPlot(). Rename the xlabel and ylabel.

• Fixed bug in watex.show_versions() to output the hard dependencies and update the public API in watex.__init__.

• Fixed bug in ERP and VES table for formatting the ERP and VES data sets documentation.

• Replace the shorthand of fa with factor in the new version of factor analysis watex.analysis.factor.

• Fix the bug in watex.analysis.decomposition.linear_discriminant_analysis() mathematical formula in the docstrings. Henceforth the function linear_discriminant_analysis() returns weight factor of X transformed as :

  >>> def linear_discriminant_analysis(X,y, ...):
          ...
          return X.dot(W) if return_X else W
  

• Fixed bug in watex.base.Data.profilingReport(). Exception henceforth occurs if the optional dependency pandas-profiling is not installed yet for report generation.

• Delete the module hua from datasets and replace by watex.datasets.sets for fast loading the inner datasets.

• Move tensor exceptions ZError to the exceptions module watex.exceptions and revised the EM exceptions errors in the whole watex.externals module.

• Many other bugs were fixed in watex.utils.plotutils after several tests.