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Version Bump: v0.7 (#355)
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‎MANIFEST.in

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include requirements.txt
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include requirements-plotting.txt
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include requirements-test.txt
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include CONTRIBUTING.md
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include LICENSE
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include dowhy/VERSION
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recursive-include docs *

‎docs/source/code_repo.rst

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You can browse the code in a html-friendly format `here
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<https://github.com/Microsoft/dowhy>`_.
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v0.7: Better Refuters for unobserved confounders and placebo treatment
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----------------------------------------------------------------------
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* **[Major]** Faster backdoor identification with support for minimal adjustment, maximal adjustment
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or exhaustive search. More test coverage for identification.
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* **[Major]** Added new functionality of causal discovery [Experimental].
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DoWhy now supports discovery algorithms from external libraries like CDT.
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`[Example notebook] <https://github.com/microsoft/dowhy/blob/master/docs/source/example_notebooks/dowhy_causal_discovery_example.ipynb>`_
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* **[Major]** Implemented ID algorithm for causal identification. [Experimental]
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* Added friendly text-based interpretation for DoWhy's effect estimate.
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* Added a new estimation method, distance matching that relies on a distance
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metrics between inputs.
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* Heuristics to infer default parameters for refuters.
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* Inferring default strata automatically for propensity score stratification.
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* Added support for custom propensity models in propensity-based estimation
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methods.
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* Bug fixes for confidence intervals for linear regression. Better version of
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bootstrap method.
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* Allow effect estimation without need to refit the model for econml estimators
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Big thanks to @AndrewC19, @ha2trinh, @siddhanthaldar, and @vojavocni
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v0.6: Better Refuters for unobserved confounders and placebo treatment
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----------------------------------------------------------------------
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‎docs/source/conf.py

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author = 'Amit Sharma, Emre Kiciman'
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# The short X.Y version
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version = '0.6'
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version = '0.7'
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# The full version, including alpha/beta/rc tags
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release = ''
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‎docs/source/dowhy.causal_estimators.rst

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:undoc-members:
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:show-inheritance:
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dowhy.causal\_estimators.distance\_matching\_estimator module
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-------------------------------------------------------------
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.. automodule:: dowhy.causal_estimators.distance_matching_estimator
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.causal\_estimators.econml module
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--------------------------------------
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‎docs/source/dowhy.causal_identifiers.rst

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dowhy.causal\_identifiers package
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=================================
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Submodules
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----------
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dowhy.causal\_identifiers.backdoor module
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-----------------------------------------
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.. automodule:: dowhy.causal_identifiers.backdoor
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.causal\_identifiers.id\_identifier module
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-----------------------------------------------
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.. automodule:: dowhy.causal_identifiers.id_identifier
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:members:
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:undoc-members:
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:show-inheritance:
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Module contents
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---------------
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.. automodule:: dowhy.causal_identifiers
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:members:
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:undoc-members:
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:show-inheritance:

‎docs/source/dowhy.graph_learners.rst

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dowhy.graph\_learners package
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=============================
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Submodules
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----------
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dowhy.graph\_learners.cdt module
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--------------------------------
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.. automodule:: dowhy.graph_learners.cdt
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.graph\_learners.ges module
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--------------------------------
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.. automodule:: dowhy.graph_learners.ges
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.graph\_learners.lingam module
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-----------------------------------
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.. automodule:: dowhy.graph_learners.lingam
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:members:
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:undoc-members:
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:show-inheritance:
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Module contents
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---------------
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.. automodule:: dowhy.graph_learners
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:members:
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:undoc-members:
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:show-inheritance:

‎docs/source/dowhy.rst

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dowhy.api
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dowhy.causal_estimators
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dowhy.causal_identifiers
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dowhy.causal_refuters
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dowhy.data_transformers
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dowhy.do_samplers
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dowhy.graph_learners
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dowhy.interpreters
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dowhy.utils
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:undoc-members:
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:show-inheritance:
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dowhy.graph\_learner module
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---------------------------
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.. automodule:: dowhy.graph_learner
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.interpreter module
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------------------------
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‎docs/source/dowhy.utils.rst

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:undoc-members:
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dowhy.utils.graph\_operations module
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------------------------------------
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.. automodule:: dowhy.utils.graph_operations
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.utils.ordered\_set module
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-------------------------------
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.. automodule:: dowhy.utils.ordered_set
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:members:
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:undoc-members:
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:show-inheritance:
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dowhy.utils.propensity\_score module
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------------------------------------
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‎dowhy/VERSION

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0.6
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0.7

‎setup.py

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license='MIT',
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long_description=long_description,
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url='https://github.com/microsoft/dowhy', # Optional
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download_url='https://github.com/microsoft/dowhy/archive/v0.6.tar.gz',
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download_url='https://github.com/microsoft/dowhy/archive/v0.7.tar.gz',
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author='Amit Sharma, Emre Kiciman',
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classifiers=[ # Optional
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'Development Status :: 4 - Beta',
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'License :: OSI Approved :: MIT License',
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'Programming Language :: Python :: 3.6',
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'Programming Language :: Python :: 3.7',
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'Programming Language :: Python :: 3.8',
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'Programming Language :: Python :: 3.9',
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],
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keywords='causality machine-learning causal-inference statistics graphical-model',
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packages=find_packages(exclude=['docs', 'tests']),
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python_requires='>=3.5',
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python_requires='>=3.6',
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install_requires=install_requires,
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extras_require=extras_require,
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include_package_data=True,

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