Pgmpy

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.

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

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.

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.

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.