- Revert back to original version handling. The flipping back and forth was
because I had problems with installing the package in NixOS through
fetchPypi. More specifically setuptools related checks were failing. Then I realized that I can disable checks.
- Refactor version handling
- Allow failure in importing plot module
__version__.pyfor handling versioning
- Readme: back to original form with good examples
- Documentation: Move good parts of new readme to Sphinx documentation
- Missing images in PyPi
- Absolute to relative image links so that images show in PyPi
- Covariance matrix visualization plot
- Polynomial formula
- Lift for
ronia.arraymapper.ArrayMapper
- Design matrix builder function
design_matrixto a method ofronia.Formula - Naming convention: "basis" -> "term"
- White noise GP
- Remove future annotations which break Py < 3.7 compatibility
- Numpy engine for fitting GAM models
- PyTest configuration file
conftest.py - Documentation with Sphinx
- Unit test coverage
- Truncated eigenvalue decomposition:
np.linalg.eigh->np.linalg.svd. Eigh is problematic since it may return negative eigenvalues (very close to zero). As a consequence, the truncated covariance decomposition never gives the full basis with sensible arguments. See also https://github.com/roniawz/ronia/issues/5.
- Bug in
setup.py
- Versioneer
- Redundant information in
setup.py
- Dependence from
attrspackage
- Common constructor for kernel based GP formulas
- Unit tests for GP kernels
- Numpy testing incompatibility issues
- Numpy deprecation warning
- Type hints for most functions
- Unit testing module for modules
formulae,utils - Unit tests for
BayesianGAM - Docstrings
- Parameter
verbosetoBayesianGAM.fitdefaulting toFalse
- Support serializing models to JSON
- Methods
predict_marginalandpredict_marginalstoBayesianGAM - Type hints to
BayesianGAM
BayesPyFormula=>Formula- Formulae package => module
__div__to__truediv__inArrayMapper
- Broken comparison methods in
ArrayMapper
- Unit tests for
ArrayMapper
BayesPyFormulainterface: Attributepriors=>prior. This gives more flexibility in defining priors. E.g., when summing up terms, sometimes one wants the final prior not to be block diagonal.- Naming
*partial*=>*marginal*inBayesianGAM
SumandFlattentransformations forBayesPyFormula- Smoke tests corresponding the README examples
- Dependence from Pandas
- Simplify
BayesPyFormula.__mul__so that all bases are just multiplied with the given input map - All references to
sigmanow correspond to variance
- Formulas for
BSpline1dandReLU
KeyFunctionis now calledArrayMapper
attrfrozen class feature fromBayesianGAMin order to be able to definethetaas the prior distribution by default in the initialization
- Create package basic structure
BayesPyFormulafor configuring and manipulating basis-function based GAM modelsBayesianGAMfor fitting predictive GAM models using Bayesian methods- Utilities for constructing Gaussian process covariances using suitable kernel functions
kronconstructing multi-dimensional Gaussian processes with Kronecker covariance structure- Various plotting tools for validating and inspecting model parameters and their posterior probability distributions
- Three illustrated examples to README.md