update to 0.1.16

3 files changed, 207 insertions, 19 deletions

diff --git a/.SRCINFO b/.SRCINFO
index 1c493570d445..a6e0f898e3f8 100644
--- a/.SRCINFO
+++ b/.SRCINFO
@@ -1,21 +1,27 @@
 pkgbase = python-pgmpy
-	pkgdesc = A library for Probabilistic Graphical Models
-	pkgver = 0.1.12
+	pkgdesc = Probabilistic Graphical Model library
+	pkgver = 0.1.16
 	pkgrel = 1
 	url = https://github.com/pgmpy/pgmpy
+	changelog = CHANGELOG.md
 	arch = any
 	license = MIT
 	makedepends = python-setuptools
+	makedepends = python-sphinx
+	makedepends = python-nbsphinx
+	makedepends = python-sphinx_rtd_theme
+	depends = python>=3.7
+	depends = python-joblib
 	depends = python-networkx
+	depends = python-numpy
 	depends = python-pandas
-	depends = python-scikit-learn
 	depends = python-pyparsing
+	depends = python-scipy
+	depends = python-scikit-learn
 	depends = python-statsmodels
-	depends = python-tqdm
-	depends = python-pyparsing
 	depends = python-pytorch
-	source = https://pypi.io/packages/source/p/pgmpy/pgmpy-0.1.12.tar.gz
-	sha256sums = ff5b8b8ef3c22642a499d6b1633035800185de4628fb380f9fb78db08f71b7e4
+	depends = python-tqdm
+	source = python-pgmpy-0.1.16.tar.gz::https://github.com/pgmpy/pgmpy/archive/v0.1.16.tar.gz
+	sha256sums = 4bd3b82a65a406e24f82ecffa5eda6ab8133220272a7e5471a134fcb0ec33ee5
 
 pkgname = python-pgmpy
-
diff --git a/CHANGELOG.md b/CHANGELOG.md
new file mode 100644
index 000000000000..8277d6ea9fed
--- /dev/null
+++ b/CHANGELOG.md
@@ -0,0 +1,154 @@
+# Changelog
+All notable changes to this project will be documented in this file.
+
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
+and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
+
+## [0.1.16] - 2021-09-30
+### Added
+1. Adds a `fit_update` method to `BayesianNetwork` for updating model using new data.
+2. Adds `simulate` method to `BayesianNetwork` and `DynamicBayesianNetwork` to simulated data under different conditions.
+3. Adds `DynamicBayesianNetwork.fit` method to learn model paramters from data.
+4. `ApproxInference` class to do approximate inference on models using sampling.
+5. Robust tests for all sampling methods.
+6. Adds `BayesianNetwork.load` and `BayesianNetwork.save` to quickly read and write files.
+
+### Changed
+1. `BayesianModel` and `MarkovModel` renamed to `BayesianNetwork` and `MarkovNetwork` respectively.
+2. The default value of node position in `DAG.to_daft` method.
+3. Documentation updated on the website.
+
+### Fixed
+1. Fixes bug in `DAG.is_iequivalent` method.
+2. Automatically truncate table when CPD is too large.
+3. Auto-adjustment of probability values when they don't exactly sum to 1.
+4. tqdm works both in notebooks and terminal.
+5. Fixes bug in `CausalInference.query` method.
+
+## [0.1.15] - 2021-06-30
+### Added
+1. Adds network pruning for inference algrithms to reduce the size of network before
+   running inference.
+2. Adds support for latent variables in DAG and BayesianModel.
+3. Parallel implementation for parameter estimation algorithms.
+4. Adds `DAG.get_random` and `BayesianModel.get_random` methods to be able to generate random models.
+5. Adds `CausalInference.query` method for doing do operation inference with or without adjustment sets.
+6. Adds functionality to treesearch to do auto root and class node selection (#1418)
+7. Adds option to specify virtual evidence in bayesian network inference.
+8. Adds Expectation-Maximization (EM) algorithm for parameter estimation in latent variable models.
+9. Add `BDeuScore` as another option for structure score when using HillClimbSearch.
+10. Adds CausalInference.get_minimal_adjustment_set` for finding adjustment sets.
+
+### Changed
+1. Renames `DAG.is_active_trail` to `is_dconnected`.
+2. `DAG.do` can accept multiple variables in the argument.
+3. Optimizes sampling methods.
+4. CI moved from travis and appveyor to github actions.
+5. Drops support for python 3.6. Requires 3.7+.
+
+### Fixed
+1. Example model files were not getting included in the pypi and conda packages.
+2. The order of values returned by CI tests was wrong. #1403
+3. Adjusted and normalized MI wasn't working properly in TreeSearch.
+4. #1423: Value error in bayesian estimation.
+5. Fixes bug in `DiscreteFactor.__eq__` to also consider the state names order.
+
+## [0.1.14] - 2021-03-31
+### Added
+1. Adds support for python 3.9.
+2. `BayesianModelProbability` class for calculating pmf for BNs.
+3. BayesianModel.predict has a new argument `stochastic` which returns stochastic results instead of MAP.
+4. Adds new method pgmpy.base.DAG.to_daft to easily convert models into publishable plots.
+
+### Changed
+1. `pgmpy.utils.get_example_model` now doesn't need internet connection to work. Files moved locally.
+
+### Fixed
+1. Latex output of `pgmpy.DAG.get_independencies`.
+2. Bug fix in PC algorithm as it was skipping some combinations.
+3. Error in sampling because of seed not correctly set.
+
+## [0.1.13] - 2020-12-30
+### Added
+1. New conditional independence tests for discrete variables
+
+### Changed
+1. Adds warning in BayesianEstimator when using dirichlet prior.
+
+### Fixed
+1. Bug in `PC.skeleton_to_pdag`.
+2. Bug in `HillClimbSearch` when no legal operations.
+
+### Removed
+
+## [0.1.12] - 2020-09-30
+### Added
+1. PC estimator with original, stable, and parallel variants.
+2. PDAG class to represent partially directed DAGs.
+3. `pgmpy.utils.get_example_model` function to fetch models from bnlearn repository.
+4. Refactor HillClimbSearch with a new feature to specify fixed edges in the model.
+5. Adds a global `SHOW_PROGRESS` variable.
+6. Adds Chow-Liu structure learning algorithm.
+7. Add `pgmpy.utils.get_example_model` to fetch models from bnlearn's repository.
+8. Adds `get_value` and `set_value` method to `DiscreteFactor` to get/set a single value.
+9. Adds `get_acestral_graph` to `DAG`.
+
+### Changed
+1. Refactors ConstraintBasedEstimators into PC with a lot of general improvements.
+2. Improved (faster, new arguments) indepenedence tests with changes in argument.
+3. Refactors `sample_discrete` method. Sampling algorithms much faster.
+4. Refactors `HillClimbSearch` to be faster.
+5. Sampling methods now return dataframe of type categorical.
+
+### Fixed
+
+### Removed
+1. `Data` class.
+
+## [0.1.11] - 2020-06-30
+### Added
+- New example notebook: Alarm.ipynb
+- Support for python 3.8
+- Score Caching support for scoring methods.
+
+### Changed
+- Code quality check moved to codacy from landscape
+- Additional parameter `max_ci_vars` for `ConstraintBasedEstimator`.
+- Additional parameter `pseudo_count` for K2 score.
+- Sampling methods return state names instead of number when available.
+- XMLBIFReader and BIFReader not accepts argument for specifying state name type.
+
+### Fixed
+- Additional checks for TabularCPD values shape.
+- `DiscreteFactor.reduce` accepts both state names and state numbers for variables.
+- `BeliefPropagation.query` fixed to return normalized CPDs.
+- Bug in flip operation in `HillClimbSearch`.
+- BIFWriter to write the state names to file if available.
+- `BayesianModel.to_markov_model` fixed to work with disconnected graphs.
+- VariableElimination fixed to not ignore identifical factors.
+- Fixes automatic sorting of state names in estimators.
+
+### Removed
+- No support for ProbModelXML file format.
+
+## [0.1.10] - 2020-01-22
+### Added
+- Documentation updated to include Structural Equation Models(SEM) and Causal Inference.
+- Adds Mmhc estimator.
+
+### Changed
+- BdeuScore is renamed to BDeuScore.
+- Refactoring of NaiveBayes
+- Overhaul of CI and setup infrastructure.
+- query methods check for common variabls in variable and evidence argument.
+
+### Fixed
+- Example notebooks for Inference.
+- DAG.moralize gives consistent results for disconnected graphs.
+- Fixes problems with XMLBIF and BIF reader and writer classes to be consistent.
+- Better integration of state names throughout the package.
+- Improves remove_factors and add_factors methods of FactorGraph
+- copy method of TabularCPD and DiscreteFactor now makes a copy of state names.
+
+### Removed
+- six not a dependency anymore.
diff --git a/PKGBUILD b/PKGBUILD
index 08b6aab1d936..980832f53e44 100644
--- a/PKGBUILD
+++ b/PKGBUILD
@@ -1,21 +1,49 @@
+# Maintainer: Luis Martinez <luis dot martinez at disroot dot org>
+
 pkgname=python-pgmpy
-pkgver=0.1.12
+pkgver=0.1.16
 pkgrel=1
-pkgdesc="A library for Probabilistic Graphical Models"
-arch=(any)
+pkgdesc="Probabilistic Graphical Model library"
+arch=('any')
 url="https://github.com/pgmpy/pgmpy"
 license=('MIT')
-makedepends=('python-setuptools')
-depends=('python-networkx' 'python-pandas' 'python-scikit-learn' 'python-pyparsing' 'python-statsmodels' 'python-tqdm' 'python-pyparsing' 'python-pytorch')
-source=("https://pypi.io/packages/source/p/pgmpy/pgmpy-$pkgver.tar.gz")
-sha256sums=('ff5b8b8ef3c22642a499d6b1633035800185de4628fb380f9fb78db08f71b7e4')
+depends=(
+	'python>=3.7'
+	'python-joblib'
+	'python-networkx'
+	'python-numpy'
+	'python-pandas'
+	'python-pyparsing'
+	'python-scipy'
+	'python-scikit-learn'
+	'python-statsmodels'
+	'python-pytorch'
+	'python-tqdm')
+makedepends=(
+	'python-setuptools'
+	'python-sphinx'
+	'python-nbsphinx'
+	'python-sphinx_rtd_theme')
+# checkdepends=('python-pytest' 'python-mock' 'python-daft')
+changelog=CHANGELOG.md
+source=("$pkgname-$pkgver.tar.gz::$url/archive/v$pkgver.tar.gz")
+sha256sums=('4bd3b82a65a406e24f82ecffa5eda6ab8133220272a7e5471a134fcb0ec33ee5')
 
 build() {
-  cd pgmpy-$pkgver
-  python setup.py build
+	cd "pgmpy-$pkgver"
+	python setup.py build
+	cd docs
+	make man BUILDDIR=_build
 }
 
+# check() {
+# 	cd "pgmpy-$pkgver"
+# 	pytest
+# }
+
 package() {
-  cd pgmpy-$pkgver
-  python setup.py install --root="$pkgdir/" --optimize=1
+	cd "pgmpy-$pkgver"
+	PYTHONHASHSEED=0 python setup.py install --root="$pkgdir/" --optimize=1 --skip-build
+	install -Dm 644 LICENSE -t "$pkgdir/usr/share/licenses/$pkgname/"
+	install -Dm 644 docs/_build/man/pgmpy.1 -t "$pkgdir/usr/share/man/man1/"
 }