History

v0.5.0 - 2021-01-24

This release introduces conditional sampling for the GaussianMultivariate modeling. The new conditioning feature allows passing a dictionary with the values to use to condition the rest of the columns.

It also fixes a bug that prevented constant distributions to be restored from a dictionary and updates some dependencies.

New Features

  • Conditional sampling from Gaussian copula - Issue #154 by @csala

Bug Fixes

  • ScipyModel subclasses fail to restore constant values when using from_dict - Issue #212 by @csala

v0.4.0 - 2021-01-27

This release introduces a few changes to optimize processing speed by re-implementing the Gaussian KDE pdf to use vectorized root finding methods and also adding the option to subsample the data during univariate selection.

General Improvements

  • Make gaussian_kde faster - Issue #200 by @k15z and @fealho

  • Use sub-sampling in select_univariate - Issue #183 by @csala

v0.3.3 - 2020-09-18

General Improvements

  • Use corr instead of cov in the GaussianMultivariate - Issue #195 by @rollervan

  • Add arguments to GaussianKDE - Issue #181 by @rollervan

New Features

  • Log Laplace Distribution - Issue #188 by @rollervan

v0.3.2 - 2020-08-08

General Improvements

  • Support Python 3.8 - Issue #185 by @csala

  • Support scipy >1.3 - Issue #180 by @csala

New Features

  • Add Uniform Univariate - Issue #179 by @rollervan

v0.3.1 - 2020-07-09

General Improvements

  • Raise numpy version upper bound to 2 - Issue #178 by @csala

New Features

  • Add Student T Univariate - Issue #172 by @gbonomib

Bug Fixes

  • Error in Quickstarts : Unknown projection ‘3d’ - Issue #174 by @csala

v0.3.0 - 2020-03-27

Important revamp of the internal implementation of the project, the testing infrastructure and the documentation by Kevin Alex Zhang @k15z, Carles Sala @csala and Kalyan Veeramachaneni @kveerama

Enhancements

  • Reimplementation of the existing Univariate distributions.

  • Addition of new Beta and Gamma Univariates.

  • New Univariate API with automatic selection of the optimal distribution.

  • Several improvements and fixes on the Bivariate and Multivariate Copulas implementation.

  • New visualization module with simple plotting patterns to visualize probability distributions.

  • New datasets module with toy datasets sampling functions.

  • New testing infrastructure with end-to-end, numerical and large scale testing.

  • Improved tutorials and documentation.

v0.2.5 - 2020-01-17

General Improvements

  • Convert import_object to get_instance - Issue #114 by @JDTheRipperPC

v0.2.4 - 2019-12-23

New Features

  • Allow creating copula classes directly - Issue #117 by @csala

General Improvements

  • Remove select_copula from Bivariate - Issue #118 by @csala

  • Rename TruncNorm to TruncGaussian and make it non standard - Issue #102 by @csala @JDTheRipperPC

Bugs fixed

  • Error on Frank and Gumble sampling - Issue #112 by @csala

v0.2.3 - 2019-09-17

New Features

  • Add support to Python 3.7 - Issue #53 by @JDTheRipperPC

General Improvements

  • Document RELEASE workflow - Issue #105 by @JDTheRipperPC

  • Improve serialization of univariate distributions - Issue #99 by @ManuelAlvarezC and @JDTheRipperPC

Bugs fixed

  • The method ‘select_copula’ of Bivariate return wrong CopulaType - Issue #101 by @JDTheRipperPC

v0.2.2 - 2019-07-31

New Features

  • truncnorm distribution and a generic wrapper for scipy.rv_continous distributions - Issue #27 by @amontanez, @csala and @ManuelAlvarezC

  • Independence bivariate copulas - Issue #46 by @aliciasun, @csala and @ManuelAlvarezC

  • Option to select seed on random number generator - Issue #63 by @echo66 and @ManuelAlvarezC

  • Option on Vine copulas to select number of rows to sample - Issue #77 by @ManuelAlvarezC

  • Make copulas accept both scalars and arrays as arguments - Issues #85 and #90 by @ManuelAlvarezC

General Improvements

  • Ability to properly handle constant data - Issues #57 and #82 by @csala and @ManuelAlvarezC

  • Tests for analytics properties of copulas - Issue #61 by @ManuelAlvarezC

  • Improved documentation - Issue #96 by @ManuelAlvarezC

Bugs fixed

  • Fix bug on Vine copulas, that made it crash during the bivariate copula selection - Issue #64 by @echo66 and @ManuelAlvarezC

v0.2.1 - Vine serialization

  • Add serialization to Vine copulas.

  • Add distribution as argument for the Gaussian Copula.

  • Improve Bivariate Copulas code structure to remove code duplication.

  • Fix bug in Vine Copulas sampling: ‘Edge’ object has no attribute ‘index’

  • Improve code documentation.

  • Improve code style and linting tools configuration.

v0.2.0 - Unified API

  • New API for stats methods.

  • Standarize input and output to numpy.ndarray.

  • Increase unittest coverage to 90%.

  • Add methods to load/save copulas.

  • Improve Gaussian copula sampling accuracy.

v0.1.1 - Minor Improvements

  • Different Copula types separated in subclasses

  • Extensive Unit Testing

  • More pythonic names in the public API.

  • Stop using third party elements that will be deprected soon.

  • Add methods to sample new data on bivariate copulas.

  • New KDE Univariate copula

  • Improved examples with additional demo data.

v0.1.0 - First Release

  • First release on PyPI.