Change Log¶
Version 1.0.6¶
- Latest version of python black can now run. Linted tmle_core.py.
Version 1.0.5¶
- Removed master branch, replaced with main
- Removed all mention of master branch from documentation
Version 1.0.4¶
- Fixed TMLE plot and code errors in documentation
Version 1.0.3¶
- Fixed bug with random_seed functionality in all tools
Version 1.0.2¶
- Updated end-to-end example notebook in /examples folder
- Fixed various class docstrings if they still reference old v0.5.2 API
- Fixed bug where custom class input parameters weren’t being used
Version 1.0.1¶
- Added to TMLE overview in the docs (including plot)
Version 1.0.0: Major Update¶
- Overhaul of the TMLE tool to make it dramatically more accurate and user-friendly.
- Improved TMLE example documentation
- Much like with scikit-learn, there are now separate model classes used for predicting binary or continuous outcomes
- Updating documentation to reflect API changes
- Added more tests
- Linted with pylint (added .pylintrc file)
Version 0.5.2¶
- Fixed bug that prevented causal-curve modules from being shown in Sphinx documentation
- Augmented tests to capture more error states and improve code coverage
Version 0.5.1¶
- Removed working test file
Version 0.5.0¶
- Added new predict, predict_interval, and predict_log_odds methods to GPS tool
- Slight updates to doc to reflect new features
Version 0.4.1¶
- When using GPS tool with a treatment with negative values, only the normal GLM family can be picked
- Added ‘sphinx_rtd_theme’ to dependency list in .travis.yml and install.rst
- core.py base class now has __version__ attribute
Version 0.4.0¶
- Added support for binary outcomes in GPS tool
- Small changes to repo README
Version 0.3.8¶
- Added citation (yay!)
Version 0.3.7¶
- Bumped version for PyPi
Version 0.3.6¶
- Fixed bug in Mediation.calculate_mediation that would clip treatments < 0 or > 1
- Fixed incorrect horizontal axis labels in lead example
- Fixed typos in documentation
- Added links to resources so users could learn more about causal inference theory
Version 0.3.5¶
- Re-organized documentation
- Added Introduction section to explain purpose and need for the package
Version 0.3.4¶
- Removed XGBoost as dependency.
- Now using sklearn’s gradient boosting implementation.
Version 0.3.3¶
- Misc edits to paper and bibliography
Version 0.3.2¶
- Fixed random seed issue with Mediation tool
- Fixed Mediation bootstrap issue. Confidence interval bounded [0,1]
- Fixed issue with all classes not accepting non-sequential indicies in pandas Dataframes/Series
- Class init checks for all classes now print cleaner errors if bad input
Version 0.3.1¶
- Small fixes to end-to-end example documentation
- Enlarged image in paper
Version 0.3.0¶
- Added full, end-to-end example of package usage to documentation
- Cleaned up documentation
- Added example folder with end-to-end notebook
- Added manuscript to paper folder
Version 0.2.4¶
- Strengthened unit tests
Version 0.2.3¶
- codecov integration
Version 0.2.2¶
- Travis CI integration
Version 0.2.1¶
- Fixed Mediation tool error / removed tqdm from requirements
- Misc documentation cleanup / revisions
Version 0.2.0¶
- Added new Mediation class
- Updated documentation to reflect this
- Added unit and integration tests for Mediation methods
Version 0.1.3¶
- Simplifying unit and integration tests.
Version 0.1.2¶
- Added unit and integration tests
Version 0.1.1¶
- setup.py fix
Version 0.1.0¶
- Added new TMLE class
- Updated documentation to reflect new TMLE method
- Renamed CDRC method to more appropriate GPS method
- Small docstring corrections to GPS method
Version 0.0.10¶
- Bug fix in GPS estimation method
Version 0.0.9¶
- Project created