v0.1.2 (July 15, 2022)#

This is a minor release with bug fixes for issues identified since v0.1.1. In this release, most of the classes are renamed and constructed following referring to Python PEP8.

  • Fixed a bug that appeared within the bootstrapping algorithm on 32-bit systems.

  • Fixed a bug where watex.cases.features.FeatureInspection would crash on mixed categorical and numerical inputs. Now a crash is avoided and both data types.

  • Revised the whole module watex.erp as well as the detection of the conductive zone.

  • Fixed a bug where the auto-detection shape of anomaly “H” is confused with “U”. See the DC -method.

  • Fixed a bug where the term:sfi is wrong computed when the value of resistivity is relatively higher.

  • Fixed a bug where despine() would cause an error when trying to trim spines on a matplotlib categorical axis.

  • Adapted to a change in the auto-selection of the best anomaly that caused problems with multiple reading excel sheets.

  • Developed a watex.utils.funcutils.read_from_excelsheets() to parse multiple excel data from different localities at once.

  • Deprecated several utility functions that are no longer used internally (select_anomaly, getminVal, compute_lower_anomaly, and define_conductive_zone, compute_sfi). compute_sfi is henceforth replace by watex.sfi()

  • Fixed bugs in watex.cases.processing.Preprocessing and watex.cases.processing.Processing and adapted to rearranged to accept other datasets whose objective is for predicting the groundwater flow rate.

  • Fixed bugs watex.cases.modeling.BaseModel especially in the method watex.cases.modeling.BaseModel.get_learning_curve() decoratored by watex.decorators.visualize_valearn_curve. Henceforth returns the keyword arguments and are systematically used to customize the validation curve from the base learning curve.