%global _empty_manifest_terminate_build 0
Name: python-copulas
Version: 0.8.0
Release: 1
Summary: Create tabular synthetic data using copulas-based modeling.
License: BSL-1.1
URL: https://github.com/sdv-dev/Copulas
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/0d/0c/f93eb9a65764ab2000cf3fad591ef85200d2b06e88fc5020b4d945147532/copulas-0.8.0.tar.gz
BuildArch: noarch
Requires: python3-numpy
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Requires: python3-scikit-learn
Requires: python3-jupyter
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%description
[The Synthetic Data Vault Project](https://sdv.dev) was first created at MIT's [Data to AI Lab](
https://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we
created [DataCebo](https://datacebo.com) in 2020 with the goal of growing the project.
Today, DataCebo is the proud developer of SDV, the largest ecosystem for
synthetic data generation & evaluation. It is home to multiple libraries that support synthetic
data, including:
* 🔄 Data discovery & transformation. Reverse the transforms to reproduce realistic data.
* 🧠Multiple machine learning models -- ranging from Copulas to Deep Learning -- to create tabular,
multi table and time series data.
* 📊 Measuring quality and privacy of synthetic data, and comparing different synthetic data
generation models.
[Get started using the SDV package](https://sdv.dev/SDV/getting_started/install.html) -- a fully
integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
for specific needs.
# History
## 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.
### Maintenance
* Support python 3.10 and above - PR[#338](https://github.com/sdv-dev/Copulas/pull/338) by @pvk-developer
* Copulas Package Maintenance Updates - Issue[#336](https://github.com/sdv-dev/Copulas/issues/336) by @pvk-developer
* Add support for python 3.10 - PR[#329](https://github.com/sdv-dev/Copulas/pull/329) by @katxiao
## 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 estimatig the `loc` and `scale` parameters.
### General Improvements
* Add gaussian as fallback - Issue[#320](https://github.com/sdv-dev/Copulas/issues/320) by @fealho
* Improve the fit of the Beta distribution: Use the new loc and scale - Issue[#317](https://github.com/sdv-dev/Copulas/issues/317) by @pvk-developer
## v0.6.1 - 2022-02-25
This release improves the `random_state` functionality by taking in RandomState objects in addition to
random seeds.
### General Improvements
* Use random_state instead of random_seed - Issue[#113](https://github.com/sdv-dev/Copulas/issues/113) by @katxiao
## 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.
### General Improvements
* Add support for Python 3.9 - Issue[#282](https://github.com/sdv-dev/Copulas/issues/282) by @amontanez24
* Remove entry point in setup.py - Issue[#280](https://github.com/sdv-dev/Copulas/issues/280) by @amontanez24
* Update pandas dependency range - Issue[#266](https://github.com/sdv-dev/Copulas/issues/266) by @katxiao
* Fix repository language - Issue[#272](https://github.com/sdv-dev/Copulas/issues/272) by @pvk-developer
* Add pip check to CI workflows - Issue[#274](https://github.com/sdv-dev/Copulas/issues/274) by @pvk-developer
* Reorganize workflows and add codecov - PR[#267](https://github.com/sdv-dev/Copulas/pull/267) by @csala
* Constrain jinja2 versions - PR[#269](https://github.com/sdv-dev/Copulas/pull/269/files) 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.
### Issues Closed
* Exception: Optimization converged to parameters that are outside the range allowed by the distribution. - Issue [#264](https://github.com/sdv-dev/Copulas/issues/264) by @csala
* Use scipy stats models directly without creating instances - Issue [#261](https://github.com/sdv-dev/Copulas/issues/261) by @csala
## 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](https://github.com/sdv-dev/Copulas/issues/154) by @csala
### Bug Fixes
* ScipyModel subclasses fail to restore constant values when using `from_dict` - Issue [#212](https://github.com/sdv-dev/Copulas/issues/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](https://github.com/sdv-dev/Copulas/issues/200) by @k15z and @fealho
* Use sub-sampling in `select_univariate` - Issue [#183](https://github.com/sdv-dev/Copulas/issues/183) by @csala
## v0.3.3 - 2020-09-18
### General Improvements
* Use `corr` instead of `cov` in the GaussianMultivariate - Issue [#195](https://github.com/sdv-dev/Copulas/issues/195) by @rollervan
* Add arguments to GaussianKDE - Issue [#181](https://github.com/sdv-dev/Copulas/issues/181) by @rollervan
### New Features
* Log Laplace Distribution - Issue [#188](https://github.com/sdv-dev/Copulas/issues/188) by @rollervan
## v0.3.2 - 2020-08-08
### General Improvements
* Support Python 3.8 - Issue [#185](https://github.com/sdv-dev/Copulas/issues/185) by @csala
* Support scipy >1.3 - Issue [#180](https://github.com/sdv-dev/Copulas/issues/180) by @csala
### New Features
* Add Uniform Univariate - Issue [#179](https://github.com/sdv-dev/Copulas/issues/179) by @rollervan
## v0.3.1 - 2020-07-09
### General Improvements
* Raise numpy version upper bound to 2 - Issue [#178](https://github.com/sdv-dev/Copulas/issues/178) by @csala
### New Features
* Add Student T Univariate - Issue [#172](https://github.com/sdv-dev/Copulas/issues/172) by @gbonomib
### Bug Fixes
* Error in Quickstarts : Unknown projection '3d' - Issue [#174](https://github.com/sdv-dev/Copulas/issues/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](https://github.com/sdv-dev/Copulas/issues/114) by @JDTheRipperPC
## v0.2.4 - 2019-12-23
### New Features
* Allow creating copula classes directly - Issue [#117](https://github.com/sdv-dev/Copulas/issues/117) by @csala
### General Improvements
* Remove `select_copula` from `Bivariate` - Issue [#118](https://github.com/sdv-dev/Copulas/issues/118) by @csala
* Rename TruncNorm to TruncGaussian and make it non standard - Issue [#102](https://github.com/sdv-dev/Copulas/issues/102) by @csala @JDTheRipperPC
### Bugs fixed
* Error on Frank and Gumble sampling - Issue [#112](https://github.com/sdv-dev/Copulas/issues/112) by @csala
## v0.2.3 - 2019-09-17
### New Features
* Add support to Python 3.7 - Issue [#53](https://github.com/sdv-dev/Copulas/issues/53) by @JDTheRipperPC
### General Improvements
* Document RELEASE workflow - Issue [#105](https://github.com/sdv-dev/Copulas/issues/105) by @JDTheRipperPC
* Improve serialization of univariate distributions - Issue [#99](https://github.com/sdv-dev/Copulas/issues/99) by @ManuelAlvarezC and @JDTheRipperPC
### Bugs fixed
* The method 'select_copula' of Bivariate return wrong CopulaType - Issue [#101](https://github.com/sdv-dev/Copulas/issues/101) by @JDTheRipperPC
## v0.2.2 - 2019-07-31
### New Features
* `truncnorm` distribution and a generic wrapper for `scipy.rv_continous` distributions - Issue [#27](https://github.com/sdv-dev/Copulas/issues/27) by @amontanez, @csala and @ManuelAlvarezC
* `Independence` bivariate copulas - Issue [#46](https://github.com/sdv-dev/Copulas/issues/46) by @aliciasun, @csala and @ManuelAlvarezC
* Option to select seed on random number generator - Issue [#63](https://github.com/sdv-dev/Copulas/issues/63) by @echo66 and @ManuelAlvarezC
* Option on Vine copulas to select number of rows to sample - Issue [#77](https://github.com/sdv-dev/Copulas/issues/77) by @ManuelAlvarezC
* Make copulas accept both scalars and arrays as arguments - Issues [#85](https://github.com/sdv-dev/Copulas/issues/85) and [#90](https://github.com/sdv-dev/Copulas/issues/90) by @ManuelAlvarezC
### General Improvements
* Ability to properly handle constant data - Issues [#57](https://github.com/sdv-dev/Copulas/issues/57) and [#82](https://github.com/sdv-dev/Copulas/issues/82) by @csala and @ManuelAlvarezC
* Tests for analytics properties of copulas - Issue [#61](https://github.com/sdv-dev/Copulas/issues/61) by @ManuelAlvarezC
* Improved documentation - Issue [#96](https://github.com/sdv-dev/Copulas/issues/96) by @ManuelAlvarezC
### Bugs fixed
* Fix bug on Vine copulas, that made it crash during the bivariate copula selection - Issue [#64](https://github.com/sdv-dev/Copulas/issues/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.
%package -n python3-copulas
Summary: Create tabular synthetic data using copulas-based modeling.
Provides: python-copulas
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-copulas
[The Synthetic Data Vault Project](https://sdv.dev) was first created at MIT's [Data to AI Lab](
https://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we
created [DataCebo](https://datacebo.com) in 2020 with the goal of growing the project.
Today, DataCebo is the proud developer of SDV, the largest ecosystem for
synthetic data generation & evaluation. It is home to multiple libraries that support synthetic
data, including:
* 🔄 Data discovery & transformation. Reverse the transforms to reproduce realistic data.
* 🧠Multiple machine learning models -- ranging from Copulas to Deep Learning -- to create tabular,
multi table and time series data.
* 📊 Measuring quality and privacy of synthetic data, and comparing different synthetic data
generation models.
[Get started using the SDV package](https://sdv.dev/SDV/getting_started/install.html) -- a fully
integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
for specific needs.
# History
## 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.
### Maintenance
* Support python 3.10 and above - PR[#338](https://github.com/sdv-dev/Copulas/pull/338) by @pvk-developer
* Copulas Package Maintenance Updates - Issue[#336](https://github.com/sdv-dev/Copulas/issues/336) by @pvk-developer
* Add support for python 3.10 - PR[#329](https://github.com/sdv-dev/Copulas/pull/329) by @katxiao
## 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 estimatig the `loc` and `scale` parameters.
### General Improvements
* Add gaussian as fallback - Issue[#320](https://github.com/sdv-dev/Copulas/issues/320) by @fealho
* Improve the fit of the Beta distribution: Use the new loc and scale - Issue[#317](https://github.com/sdv-dev/Copulas/issues/317) by @pvk-developer
## v0.6.1 - 2022-02-25
This release improves the `random_state` functionality by taking in RandomState objects in addition to
random seeds.
### General Improvements
* Use random_state instead of random_seed - Issue[#113](https://github.com/sdv-dev/Copulas/issues/113) by @katxiao
## 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.
### General Improvements
* Add support for Python 3.9 - Issue[#282](https://github.com/sdv-dev/Copulas/issues/282) by @amontanez24
* Remove entry point in setup.py - Issue[#280](https://github.com/sdv-dev/Copulas/issues/280) by @amontanez24
* Update pandas dependency range - Issue[#266](https://github.com/sdv-dev/Copulas/issues/266) by @katxiao
* Fix repository language - Issue[#272](https://github.com/sdv-dev/Copulas/issues/272) by @pvk-developer
* Add pip check to CI workflows - Issue[#274](https://github.com/sdv-dev/Copulas/issues/274) by @pvk-developer
* Reorganize workflows and add codecov - PR[#267](https://github.com/sdv-dev/Copulas/pull/267) by @csala
* Constrain jinja2 versions - PR[#269](https://github.com/sdv-dev/Copulas/pull/269/files) 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.
### Issues Closed
* Exception: Optimization converged to parameters that are outside the range allowed by the distribution. - Issue [#264](https://github.com/sdv-dev/Copulas/issues/264) by @csala
* Use scipy stats models directly without creating instances - Issue [#261](https://github.com/sdv-dev/Copulas/issues/261) by @csala
## 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](https://github.com/sdv-dev/Copulas/issues/154) by @csala
### Bug Fixes
* ScipyModel subclasses fail to restore constant values when using `from_dict` - Issue [#212](https://github.com/sdv-dev/Copulas/issues/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](https://github.com/sdv-dev/Copulas/issues/200) by @k15z and @fealho
* Use sub-sampling in `select_univariate` - Issue [#183](https://github.com/sdv-dev/Copulas/issues/183) by @csala
## v0.3.3 - 2020-09-18
### General Improvements
* Use `corr` instead of `cov` in the GaussianMultivariate - Issue [#195](https://github.com/sdv-dev/Copulas/issues/195) by @rollervan
* Add arguments to GaussianKDE - Issue [#181](https://github.com/sdv-dev/Copulas/issues/181) by @rollervan
### New Features
* Log Laplace Distribution - Issue [#188](https://github.com/sdv-dev/Copulas/issues/188) by @rollervan
## v0.3.2 - 2020-08-08
### General Improvements
* Support Python 3.8 - Issue [#185](https://github.com/sdv-dev/Copulas/issues/185) by @csala
* Support scipy >1.3 - Issue [#180](https://github.com/sdv-dev/Copulas/issues/180) by @csala
### New Features
* Add Uniform Univariate - Issue [#179](https://github.com/sdv-dev/Copulas/issues/179) by @rollervan
## v0.3.1 - 2020-07-09
### General Improvements
* Raise numpy version upper bound to 2 - Issue [#178](https://github.com/sdv-dev/Copulas/issues/178) by @csala
### New Features
* Add Student T Univariate - Issue [#172](https://github.com/sdv-dev/Copulas/issues/172) by @gbonomib
### Bug Fixes
* Error in Quickstarts : Unknown projection '3d' - Issue [#174](https://github.com/sdv-dev/Copulas/issues/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](https://github.com/sdv-dev/Copulas/issues/114) by @JDTheRipperPC
## v0.2.4 - 2019-12-23
### New Features
* Allow creating copula classes directly - Issue [#117](https://github.com/sdv-dev/Copulas/issues/117) by @csala
### General Improvements
* Remove `select_copula` from `Bivariate` - Issue [#118](https://github.com/sdv-dev/Copulas/issues/118) by @csala
* Rename TruncNorm to TruncGaussian and make it non standard - Issue [#102](https://github.com/sdv-dev/Copulas/issues/102) by @csala @JDTheRipperPC
### Bugs fixed
* Error on Frank and Gumble sampling - Issue [#112](https://github.com/sdv-dev/Copulas/issues/112) by @csala
## v0.2.3 - 2019-09-17
### New Features
* Add support to Python 3.7 - Issue [#53](https://github.com/sdv-dev/Copulas/issues/53) by @JDTheRipperPC
### General Improvements
* Document RELEASE workflow - Issue [#105](https://github.com/sdv-dev/Copulas/issues/105) by @JDTheRipperPC
* Improve serialization of univariate distributions - Issue [#99](https://github.com/sdv-dev/Copulas/issues/99) by @ManuelAlvarezC and @JDTheRipperPC
### Bugs fixed
* The method 'select_copula' of Bivariate return wrong CopulaType - Issue [#101](https://github.com/sdv-dev/Copulas/issues/101) by @JDTheRipperPC
## v0.2.2 - 2019-07-31
### New Features
* `truncnorm` distribution and a generic wrapper for `scipy.rv_continous` distributions - Issue [#27](https://github.com/sdv-dev/Copulas/issues/27) by @amontanez, @csala and @ManuelAlvarezC
* `Independence` bivariate copulas - Issue [#46](https://github.com/sdv-dev/Copulas/issues/46) by @aliciasun, @csala and @ManuelAlvarezC
* Option to select seed on random number generator - Issue [#63](https://github.com/sdv-dev/Copulas/issues/63) by @echo66 and @ManuelAlvarezC
* Option on Vine copulas to select number of rows to sample - Issue [#77](https://github.com/sdv-dev/Copulas/issues/77) by @ManuelAlvarezC
* Make copulas accept both scalars and arrays as arguments - Issues [#85](https://github.com/sdv-dev/Copulas/issues/85) and [#90](https://github.com/sdv-dev/Copulas/issues/90) by @ManuelAlvarezC
### General Improvements
* Ability to properly handle constant data - Issues [#57](https://github.com/sdv-dev/Copulas/issues/57) and [#82](https://github.com/sdv-dev/Copulas/issues/82) by @csala and @ManuelAlvarezC
* Tests for analytics properties of copulas - Issue [#61](https://github.com/sdv-dev/Copulas/issues/61) by @ManuelAlvarezC
* Improved documentation - Issue [#96](https://github.com/sdv-dev/Copulas/issues/96) by @ManuelAlvarezC
### Bugs fixed
* Fix bug on Vine copulas, that made it crash during the bivariate copula selection - Issue [#64](https://github.com/sdv-dev/Copulas/issues/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.
%package help
Summary: Development documents and examples for copulas
Provides: python3-copulas-doc
%description help
[The Synthetic Data Vault Project](https://sdv.dev) was first created at MIT's [Data to AI Lab](
https://dai.lids.mit.edu/) in 2016. After 4 years of research and traction with enterprise, we
created [DataCebo](https://datacebo.com) in 2020 with the goal of growing the project.
Today, DataCebo is the proud developer of SDV, the largest ecosystem for
synthetic data generation & evaluation. It is home to multiple libraries that support synthetic
data, including:
* 🔄 Data discovery & transformation. Reverse the transforms to reproduce realistic data.
* 🧠Multiple machine learning models -- ranging from Copulas to Deep Learning -- to create tabular,
multi table and time series data.
* 📊 Measuring quality and privacy of synthetic data, and comparing different synthetic data
generation models.
[Get started using the SDV package](https://sdv.dev/SDV/getting_started/install.html) -- a fully
integrated solution and your one-stop shop for synthetic data. Or, use the standalone libraries
for specific needs.
# History
## 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.
### Maintenance
* Support python 3.10 and above - PR[#338](https://github.com/sdv-dev/Copulas/pull/338) by @pvk-developer
* Copulas Package Maintenance Updates - Issue[#336](https://github.com/sdv-dev/Copulas/issues/336) by @pvk-developer
* Add support for python 3.10 - PR[#329](https://github.com/sdv-dev/Copulas/pull/329) by @katxiao
## 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 estimatig the `loc` and `scale` parameters.
### General Improvements
* Add gaussian as fallback - Issue[#320](https://github.com/sdv-dev/Copulas/issues/320) by @fealho
* Improve the fit of the Beta distribution: Use the new loc and scale - Issue[#317](https://github.com/sdv-dev/Copulas/issues/317) by @pvk-developer
## v0.6.1 - 2022-02-25
This release improves the `random_state` functionality by taking in RandomState objects in addition to
random seeds.
### General Improvements
* Use random_state instead of random_seed - Issue[#113](https://github.com/sdv-dev/Copulas/issues/113) by @katxiao
## 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.
### General Improvements
* Add support for Python 3.9 - Issue[#282](https://github.com/sdv-dev/Copulas/issues/282) by @amontanez24
* Remove entry point in setup.py - Issue[#280](https://github.com/sdv-dev/Copulas/issues/280) by @amontanez24
* Update pandas dependency range - Issue[#266](https://github.com/sdv-dev/Copulas/issues/266) by @katxiao
* Fix repository language - Issue[#272](https://github.com/sdv-dev/Copulas/issues/272) by @pvk-developer
* Add pip check to CI workflows - Issue[#274](https://github.com/sdv-dev/Copulas/issues/274) by @pvk-developer
* Reorganize workflows and add codecov - PR[#267](https://github.com/sdv-dev/Copulas/pull/267) by @csala
* Constrain jinja2 versions - PR[#269](https://github.com/sdv-dev/Copulas/pull/269/files) 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.
### Issues Closed
* Exception: Optimization converged to parameters that are outside the range allowed by the distribution. - Issue [#264](https://github.com/sdv-dev/Copulas/issues/264) by @csala
* Use scipy stats models directly without creating instances - Issue [#261](https://github.com/sdv-dev/Copulas/issues/261) by @csala
## 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](https://github.com/sdv-dev/Copulas/issues/154) by @csala
### Bug Fixes
* ScipyModel subclasses fail to restore constant values when using `from_dict` - Issue [#212](https://github.com/sdv-dev/Copulas/issues/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](https://github.com/sdv-dev/Copulas/issues/200) by @k15z and @fealho
* Use sub-sampling in `select_univariate` - Issue [#183](https://github.com/sdv-dev/Copulas/issues/183) by @csala
## v0.3.3 - 2020-09-18
### General Improvements
* Use `corr` instead of `cov` in the GaussianMultivariate - Issue [#195](https://github.com/sdv-dev/Copulas/issues/195) by @rollervan
* Add arguments to GaussianKDE - Issue [#181](https://github.com/sdv-dev/Copulas/issues/181) by @rollervan
### New Features
* Log Laplace Distribution - Issue [#188](https://github.com/sdv-dev/Copulas/issues/188) by @rollervan
## v0.3.2 - 2020-08-08
### General Improvements
* Support Python 3.8 - Issue [#185](https://github.com/sdv-dev/Copulas/issues/185) by @csala
* Support scipy >1.3 - Issue [#180](https://github.com/sdv-dev/Copulas/issues/180) by @csala
### New Features
* Add Uniform Univariate - Issue [#179](https://github.com/sdv-dev/Copulas/issues/179) by @rollervan
## v0.3.1 - 2020-07-09
### General Improvements
* Raise numpy version upper bound to 2 - Issue [#178](https://github.com/sdv-dev/Copulas/issues/178) by @csala
### New Features
* Add Student T Univariate - Issue [#172](https://github.com/sdv-dev/Copulas/issues/172) by @gbonomib
### Bug Fixes
* Error in Quickstarts : Unknown projection '3d' - Issue [#174](https://github.com/sdv-dev/Copulas/issues/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](https://github.com/sdv-dev/Copulas/issues/114) by @JDTheRipperPC
## v0.2.4 - 2019-12-23
### New Features
* Allow creating copula classes directly - Issue [#117](https://github.com/sdv-dev/Copulas/issues/117) by @csala
### General Improvements
* Remove `select_copula` from `Bivariate` - Issue [#118](https://github.com/sdv-dev/Copulas/issues/118) by @csala
* Rename TruncNorm to TruncGaussian and make it non standard - Issue [#102](https://github.com/sdv-dev/Copulas/issues/102) by @csala @JDTheRipperPC
### Bugs fixed
* Error on Frank and Gumble sampling - Issue [#112](https://github.com/sdv-dev/Copulas/issues/112) by @csala
## v0.2.3 - 2019-09-17
### New Features
* Add support to Python 3.7 - Issue [#53](https://github.com/sdv-dev/Copulas/issues/53) by @JDTheRipperPC
### General Improvements
* Document RELEASE workflow - Issue [#105](https://github.com/sdv-dev/Copulas/issues/105) by @JDTheRipperPC
* Improve serialization of univariate distributions - Issue [#99](https://github.com/sdv-dev/Copulas/issues/99) by @ManuelAlvarezC and @JDTheRipperPC
### Bugs fixed
* The method 'select_copula' of Bivariate return wrong CopulaType - Issue [#101](https://github.com/sdv-dev/Copulas/issues/101) by @JDTheRipperPC
## v0.2.2 - 2019-07-31
### New Features
* `truncnorm` distribution and a generic wrapper for `scipy.rv_continous` distributions - Issue [#27](https://github.com/sdv-dev/Copulas/issues/27) by @amontanez, @csala and @ManuelAlvarezC
* `Independence` bivariate copulas - Issue [#46](https://github.com/sdv-dev/Copulas/issues/46) by @aliciasun, @csala and @ManuelAlvarezC
* Option to select seed on random number generator - Issue [#63](https://github.com/sdv-dev/Copulas/issues/63) by @echo66 and @ManuelAlvarezC
* Option on Vine copulas to select number of rows to sample - Issue [#77](https://github.com/sdv-dev/Copulas/issues/77) by @ManuelAlvarezC
* Make copulas accept both scalars and arrays as arguments - Issues [#85](https://github.com/sdv-dev/Copulas/issues/85) and [#90](https://github.com/sdv-dev/Copulas/issues/90) by @ManuelAlvarezC
### General Improvements
* Ability to properly handle constant data - Issues [#57](https://github.com/sdv-dev/Copulas/issues/57) and [#82](https://github.com/sdv-dev/Copulas/issues/82) by @csala and @ManuelAlvarezC
* Tests for analytics properties of copulas - Issue [#61](https://github.com/sdv-dev/Copulas/issues/61) by @ManuelAlvarezC
* Improved documentation - Issue [#96](https://github.com/sdv-dev/Copulas/issues/96) by @ManuelAlvarezC
### Bugs fixed
* Fix bug on Vine copulas, that made it crash during the bivariate copula selection - Issue [#64](https://github.com/sdv-dev/Copulas/issues/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.
%prep
%autosetup -n copulas-0.8.0
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-copulas -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue Apr 11 2023 Python_Bot - 0.8.0-1
- Package Spec generated
