Pybnesian

- Adds support for pyarrow 5.0.0 in the PyPi wheels.
- Added `Arguments.args()` to access the `args` and `kwargs` for a node.
- Added `BayesianNetworkBase.underlying_node_type()` to get the underlying node type of a node given some data.
- Improves the fitting of hybrid factors. Now, an specific discrete configuration can be left unfitted if the base continuous factor raises `SingularCovarianceData`.
- Improves the `LinearGaussianCPD` fit when the covariance matrix of the data is singular.
- Improves the `NormalReferenceRule`, `ScottsBandwidth`, and `UCV` estimation when the covariance of the data is singular.
- Fixes a bug loading an heterogeneous Bayesian network from a file.
- Introduces a check that a needed category exists in discrete data.
- `Assignment` now supports integer numbers converting them automatically to float.
- Fix a bug in `GreedyHillClimbing` that caused the return of Bayesian networks with `UnknownFactorType`.
- Reduces memory usage when fitting and printing an hybrid `Factor`.
- Fixes a precision bug in `GreedyHillClimbing`.
- Improves `CrossValidation` parameter checking.

- Fixed a bug in the `UCV` bandwidth selector that may cause segmentation fault.
- Added some checks to ensure that the categorical data is of type string.
- Fixed the `GreedyHillClimbing` iteration counter, which was begin increased twice per iteration.
- Added a default parameter value for `include_cpd` in `BayesianNetworkBase:save()` and
`DynamicBayesianNetworkBase::save()`.
- Added more checks to detect ill-conditioned regression problems. The `BIC` score returns `-infinity` for
ill-conditioned regression problems.

- Fixed the build process to support CMake versions older than 3.13.
- Fixed a bug that might raise an error with a call to `FactorType::new_factor()`
with `*args` and `**kwargs` arguments . This bug was only reproducible if the library was compiled with gcc.
- Added CMake as prerequisite to compile the library in the docs.

- Removed all the submodules to simplify the imports. Now, all the classes are accessible directly from the pybnesian
root module.
- Added a `ProductKDE` class that implements `KDE` with diagonal bandwidth matrix.
- Added an abstract class `BandwidthSelector` to implement bandwidth selection for `KDE` and `ProductKDE`. Three
concrete implementations of bandwidth selection are included: `ScottsBandwidth`, `NormalReferenceRule` and `UCV`.
- Added `Arguments`, `Args` and `Kwargs` to store a set of arguments to be used to create new factors through
`FactorType::new_factor()`. The `Arguments` are accepted by `BayesianNetworkBase::fit()` and the constructors of
`CVLikelihood`, `HoldoutLikelihood` and `ValidatedLikelihood`.

- An error related to the processing of categorical data with too many categories has been corrected.
- Removed `-march=native` flag in the build script to avoid the use of instruction sets not available on some CPUs.

- Added conditional linear Gaussian networks (`CLGNetworkType`, `CLGNetwork`, `ConditionalCLGNetwork` and `DynamicCLGNetwork`).
- Implemented `ChiSquare` (and `DynamicChiSquare`) indepencence test.
- Implemented `MutualInformation` (and `DynamicMutualInformation`) indepencence test. This is valid for hybrid data.
- Implemented `BDe` (Bayesian Dirichlet equivalent) score (and `DynamicBDe`).
- Added `UnknownFactorType` as default `FactorType` for Bayesian networks when the node type could not be deduced.
- Added `Assignment` class to represent the assignment of values to variables.

API changes:

- Added method `Score::data()`.
- Added `BayesianNetworkType::data_default_node_type()` for non-homogeneous `BayesianNetworkType`.
- Added constructor for `HeterogeneousBN` to specify a default `FactorType` for each data type. Also, it adds
`HeterogeneousBN::default_node_types()` and `HeterogeneousBN::single_default()`.
- Added `BayesianNetworkBase::has_unknown_node_types()` and `BayesianNetworkBase::set_unknown_node_types()`.
- Changed signature of `BayesianNetworkType::compatible_node_type()` to include the new node type as argument.
- Removed `FactorType::opposite_semiparametric()`. This functionality has been replaced by
`BayesianNetworkType::alternative_node_type()`.
- Included model as parameter of `Operator::opposite()`.
- Added method `OperatorSet::set_type_blacklist()`. Added a type blacklist argument to `ChangeNodeTypeSet` constructor.