v0.10.0 - 2023-11-13¶
This release updates all visualizations to use plotly, and removes the matplotlib dependency.
v0.9.2 - 2023-10-12¶
This release removes a warning that was being raised when univariate distributions failed to fit and logs the message instead.
When Copulas univariate fit fails, produce a log instead of a warning - Issue #359 by @R-Palazzo
v0.9.1 - 2023-08-10¶
This release fixes problems with the documentation site and drops support for Python 3.7.
v0.9.0 - 2023-04-26¶
This release adds support for pandas 2.0 and above. Additionally adds a functionality to find
version add-ons and renames
v0.8.0 - 2023-01-06¶
This release adds support for python 3.10 and 3.11. Additionally, it drops support for python 3.6.
v0.7.0 - 2022-05-10¶
This release adds
gaussian as a fallback distribution in case the user specified one fails. It also improves the
fit of the
beta distribution by properly estimating the
v0.6.1 - 2022-02-25¶
This release improves the
random_state functionality by taking in RandomState objects in addition to
v0.6.0 - 2021-05-13¶
This release makes Copulas compatible with Python 3.9! It also improves library maintenance by updating dependencies, reorganizing the CI workflows, adding pip check to the workflows and removing unused files.
Add support for Python 3.9 - Issue#282 by @amontanez24
Remove entry point in setup.py - Issue#280 by @amontanez24
Update pandas dependency range - Issue#266 by @katxiao
Fix repository language - Issue#272 by @pvk-developer
Add pip check to CI workflows - Issue#274 by @pvk-developer
Reorganize workflows and add codecov - PR#267 by @csala
Constrain jinja2 versions - PR#269 by @fealho
v0.5.1 - 2021-08-13¶
This release improves performance by changing the way scipy stats is used, calling their methods directly without creating intermediate instances.
It also fixes a bug introduced by the scipy 1.7.0 release where some distributions fail to fit because scipy validates the learned parameters.
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.
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.
v0.3.3 - 2020-09-18¶
v0.3.2 - 2020-08-08¶
v0.3.1 - 2020-07-09¶
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
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¶
v0.2.4 - 2019-12-23¶
v0.2.3 - 2019-09-17¶
v0.2.2 - 2019-07-31¶
truncnormdistribution and a generic wrapper for
scipy.rv_continousdistributions - Issue #27 by @amontanez, @csala and @ManuelAlvarezC
Independencebivariate 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
v0.2.1 - Vine serialization¶
Add serialization to Vine copulas.
distributionas 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
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.