:orphan:

.. include:: _contributors.rst

.. _changes_0_1:

What's new?
===========

Here we list a changelog of dodiscover.

.. contents:: Contents
   :local:
   :depth: 3

.. currentmodule:: dodiscover

.. _current:

Version 0.1
===========

**In Development**


Changelog
---------


- |Feature| Implement continuous integration and repository docs, by `Adam Li`_ (:pr:`15`)
- |Feature| Implement conditional independence tests under the ``dodiscover.ci`` submodule, by `Adam Li`_ (:pr:`16`)
- |Feature| Implement skeleton learning method, :class:`dodiscover.constraint.LearnSkeleton` under the ``dodiscover.constraint`` submodule, by `Adam Li`_ (:pr:`20`)
- |Feature| Add ContextBuilder class and make_context factory function for creating context objects. by `Chris Trevino`_ (:pr:`42`)
- |Feature| Implement confusion matrix method for comparing networkx-like graphs, :func:`dodiscover.metrics.confusion_matrix_networks`, by `Adam Li`_ (:pr:`48`)
- |Feature| Implement classification-based CI test (CCIT), :class:`dodiscover.ci.ClassifierCITest` under the ``dodiscover.ci`` submodule, by `Adam Li`_ (:pr:`28`)
- |Feature| Implement PC algorithm, :class:`dodiscover.constraint.PC` for learning causal structure from observational data under the ``dodiscover.constraint`` submodule, by `Adam Li`_ (:pr:`30`)
- |Feature| Implement algorithm to learn skeleton using potentially d-separated sets (PDS), :class:`dodiscover.constraint.LearnSemiMarkovianSkeleton` for learning causal structure from observational data with latent confounders, by `Adam Li`_ (:pr:`50`)
- |Feature| Implement FCI algorithm, :class:`dodiscover.constraint.FCI` for learning causal structure from observational data with latent confounders under the ``dodiscover.constraint`` submodule, by `Adam Li`_ (:pr:`52`)
- |Feature| Implement Structural Hamming Distance metric to compare directed graphs, :func:`dodiscover.metrics.structure_hamming_dist`, by `Adam Li`_ (:pr:`55`)
- |Fix| Update dependency on networkx, which removes a PR branch dependency with pywhy-graphs having the MixedEdgeGraph class that was causing a dependency conflict, by `Adam Li`_ (:pr:`74`)
- |Enhancement| Add tutorial for PC algorithm with Asia data, by `Robert Osazuwa Ness`_ (:pr:`67`)
- |Enhancement| Add wrapper for GIN algorithm from causal-learn, by `Robert Osazuwa Ness`_ (:pr:`94`)
- |Feature| Add conditional k-sample (discrepancy) test, :class:`dodiscover.cd.KernelCDTest`, by `Adam Li`_ (:pr:`81`)
- |Feature| Add conditional k-sample (discrepancy) test, :class:`dodiscover.cd.BregmanCDTest`, by `Adam Li`_ (:pr:`82`)
- |Feature| Add conditional mutual information test, :class:`dodiscover.ci.CMITest`, by `Adam Li`_ (:pr:`83`)
- |Feature| Add classifier conditional mutual information test, :class:`dodiscover.ci.ClassifierCMITest`, by `Adam Li`_ (:pr:`85`)
- |Feature| Add rules for orientation under selection bias in FCI algorithm, :class:`dodiscover.constraint.FCI`, by `Jaron Lee`_ (:pr:`106`)
- |Feature| Add pre-commit hooks for linting, type-checking, and code formatting, by `Jaron Lee`_ (:pr:`117`)
- |Feature| Adds parallelization via joblib to the skeleton learners, by `Adam Li`_ (:pr:`127`)
- |Feature| Add a suite of general categorical data CI tests, by `Adam Li`_ (:pr:`128`)
- |Feature| Implement CAM, SCORE, DAS, NoGAM algorithms in ``dodiscover.toporder`` submodule (:pr:`129`)
- |Feature| Add Psi-FCI and I-FCI algorithm for handling soft-interventional data, :class:`dodiscover.constraint.PsiFCI` by `Adam Li`_ (:pr:`111`)

Code and Documentation Contributors
-----------------------------------

Thanks to everyone who has contributed to the maintenance and improvement of
the project since version inception, including:

* `Adam Li`_
* `Chris Trevino`_
* `Robert Osazuwa Ness`_
* `Jaron Lee`_
