Merge pull request #378 from BCG-X-Official/dev/2.1.1

BUILD: Release FACET 2.1.1
BCG-X-Official · Nov 15, 2023 · 66bea15 · 66bea15
2 parents 70f757f + 290864b
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diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -5,7 +5,7 @@ repos:
       - id: isort
 
   - repo: https://github.com/psf/black
-    rev: 22.8.0
+    rev: 23.10.1
     hooks:
       - id: black
         language: python
@@ -41,6 +41,6 @@ repos:
         language: python
         language_version: python39
         additional_dependencies:
-          - numpy~=1.22
+          - numpy~=1.24
           - gamma-pytools~=2.1
           - sklearndf~=2.2
diff --git a/README.rst b/README.rst
@@ -1,18 +1,5 @@
 .. image:: sphinx/source/_images/Gamma_Facet_Logo_RGB_LB.svg
 
-.. note:: **FACET 2.0 now available!**
-
-    FACET 2.0 brings numerous API enhancements and improvements, accelerates model
-    inspection by up to a factor of 50 in many practical applications, introduces a new,
-    more flexible and user-friendly API for hyperparameter tuning – with support for
-    `scikit-learn`'s native hyperparameter searchers – and improves the styling of all
-    visualizations.
-
-    See the `release notes <https://bcg-gamma.github.io/facet/docs-version/2-0/_generated/release_notes.html>`__
-    for more details.
-
-
-
 FACET is an open source library for human-explainable AI.
 It combines sophisticated model inspection and model-based simulation to enable better 
 explanations of your supervised machine learning models.
@@ -49,8 +36,8 @@ FACET is composed of the following key components:
 |                 | tried and tested pipelining paradigm with new capabilities for model  |
 |                 | selection, inspection, and simulation.                                |
 |                 | FACET also introduces                                                 |
-|                 | `sklearndf <https://github.com/BCG-Gamma/sklearndf>`__                |
-|                 | [`documentation <https://bcg-gamma.github.io/sklearndf/index.html>`__]|
+|                 | `sklearndf <https://github.com/BCG-X-Official/sklearndf>`__                |
+|                 | [`documentation <https://bcg-x-official.github.io/sklearndf/index.html>`__]|
 |                 | an augmented version of *scikit-learn* with enhanced support for      |
 |                 | *pandas* data frames that ensures end-to-end traceability of features.|
 +-----------------+-----------------------------------------------------------------------+
@@ -107,10 +94,10 @@ Quickstart
 The following quickstart guide provides a minimal example workflow to get you
 up and running with FACET.
 For additional tutorials and the API reference,
-see the `FACET documentation <https://bcg-gamma.github.io/facet/docs-version/2-0>`__.
+see the `FACET documentation <https://bcg-x-official.github.io/facet/docs-version/2-0>`__.
 
 Changes and additions to new versions are summarized in the
-`release notes <https://bcg-gamma.github.io/facet/docs-version/2-0/release_notes.html>`__.
+`release notes <https://bcg-x-official.github.io/facet/docs-version/2-0/release_notes.html>`__.
 
 
 Enhanced Machine Learning Workflow
@@ -349,7 +336,7 @@ removing `TCH`, and one of `TC` or `LDL` to further simplify the model and obtai
 reduced set of independent features.
 
 Please see the
-`API reference <https://bcg-gamma.github.io/facet/apidoc/facet.html>`__
+`API reference <https://bcg-x-official.github.io/facet/apidoc/facet.html>`__
 for more detail.
 
 
@@ -412,21 +399,21 @@ FACET is stable and is being supported long-term.
 
 Contributions to FACET are welcome and appreciated.
 For any bug reports or feature requests/enhancements please use the appropriate
-`GitHub form <https://github.com/BCG-Gamma/facet/issues>`_, and if you wish to do so,
+`GitHub form <https://github.com/BCG-X-Official/facet/issues>`_, and if you wish to do so,
 please open a PR addressing the issue.
 
 We do ask that for any major changes please discuss these with us first via an issue or
 using our team email: FacetTeam@bcg.com.
 
 For further information on contributing please see our
-`contribution guide <https://bcg-gamma.github.io/facet/contribution_guide.html>`__.
+`contribution guide <https://bcg-x-official.github.io/facet/contribution_guide.html>`__.
 
 
 License
 -------
 
 FACET is licensed under Apache 2.0 as described in the
-`LICENSE <https://github.com/BCG-Gamma/facet/blob/develop/LICENSE>`_ file.
+`LICENSE <https://github.com/BCG-X-Official/facet/blob/develop/LICENSE>`_ file.
 
 
 Acknowledgements
@@ -446,7 +433,7 @@ BCG GAMMA
 ---------
 
 If you would like to know more about the team behind FACET please see the
-`about us <https://bcg-gamma.github.io/facet/about_us.html>`__ page.
+`about us <https://bcg-x-official.github.io/facet/about_us.html>`__ page.
 
 We are always on the lookout for passionate and talented data scientists to join the
 BCG GAMMA team. If you would like to know more you can find out about
@@ -476,7 +463,7 @@ or have a look at
 .. |pypi| image:: https://badge.fury.io/py/gamma-facet.svg
     :target: https://pypi.org/project/gamma-facet/
 
-.. |azure_build| image:: https://dev.azure.com/gamma-facet/facet/_apis/build/status/BCG-Gamma.facet?repoName=BCG-Gamma%2Ffacet&branchName=develop
+.. |azure_build| image:: https://dev.azure.com/gamma-facet/facet/_apis/build/status/BCG-X-Official.facet?repoName=BCG-X-Official%2Ffacet&branchName=develop
    :target: https://dev.azure.com/gamma-facet/facet/_build?definitionId=7&_a=summary
 
 .. |azure_code_cov| image:: https://img.shields.io/azure-devops/coverage/gamma-facet/facet/7/2.0.x
@@ -489,7 +476,7 @@ or have a look at
    :target: https://github.com/psf/black
 
 .. |made_with_sphinx_doc| image:: https://img.shields.io/badge/Made%20with-Sphinx-1f425f.svg
-   :target: https://bcg-gamma.github.io/facet/index.html
+   :target: https://bcg-x-official.github.io/facet/index.html
 
 .. |license_badge| image:: https://img.shields.io/badge/License-Apache%202.0-olivegreen.svg
    :target: https://opensource.org/licenses/Apache-2.0

diff --git a/RELEASE_NOTES.rst b/RELEASE_NOTES.rst
@@ -17,6 +17,12 @@ We still recommend using :mod:`sklearndf` models and learner pipelines along wit
 :class:`.NativeLearnerInspector` can be useful for inspecting models that have been
 trained using *scikit-learn* directly.
 
+2.1.1
+~~~~~
+
+This is a maintenance release to catch up with FACET |nbsp| 2.0.1.
+
+
 2.1.0
 ~~~~~
 
@@ -44,6 +50,8 @@ fully type-checked by |mypy|.
   and classifiers; it is no longer necessary to wrap them into a
   :class:`.RegressorPipelineDF` or :class:`.ClassifierPipelineDF` instance with empty
   preprocessing
+- FIX: replace a call to method ``get_text_heights()`` of :class:`matplotlib.axes.Axes`,
+  which is deprecated as of :mod:`matplotlib` |nbsp| 3.6
 
 
 2.0.0

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
@@ -24,8 +24,8 @@ resources:
   repositories:
     - repository: pytools
       type: github
-      endpoint: BCG-Gamma
-      name: BCG-Gamma/pytools
+      endpoint: BCG-X-Official
+      name: BCG-X-Official/pytools
       ref: 2.1.x
 
 variables:
@@ -65,7 +65,7 @@ stages:
               versionSpec: '3.9'
             displayName: 'use Python 3.9'
           - script: |
-              python -m pip install black~=22.8
+              python -m pip install black~=23.10.1
               python -m black --check .
             displayName: 'Run black'
       - job:
@@ -655,6 +655,7 @@ stages:
 
                 cd $(System.DefaultWorkingDirectory)
                 echo "Checking out github-pages"
+                git fetch origin github-pages --depth=1
                 git checkout --track origin/github-pages
 
                 # make sure we have a docs directory
@@ -676,6 +677,7 @@ stages:
 
                 cd $(System.DefaultWorkingDirectory)
                 echo "Checking out $(branchName)"
+                git fetch origin $(branchName) --depth=1
                 git checkout $(branchName)
 
                 # install micromamba

diff --git a/condabuild/meta.yaml b/condabuild/meta.yaml
@@ -58,13 +58,13 @@ test:
     - pytest -vs test
 
 about:
-  home: https://github.com/BCG-Gamma/facet
+  home: https://github.com/BCG-X-Official/facet
   license: Apache Software License v2.0
   license_file: LICENSE
   description: |
     FACET is an open source library for human-explainable AI. It combines sophisticated
     model inspection and model-based simulation to enable better explanations of
     your supervised machine learning models.
-  dev_url: https://github.com/BCG-Gamma/facet
-  doc_url: https://bcg-gamma.github.io/facet/
-  doc_source_url: https://github.com/BCG-Gamma/facet/blob/develop/README.rst
+  dev_url: https://github.com/BCG-X-Official/facet
+  doc_url: https://bcg-x-official.github.io/facet/
+  doc_source_url: https://github.com/BCG-X-Official/facet/blob/develop/README.rst
diff --git a/environment.yml b/environment.yml
@@ -5,17 +5,18 @@ channels:
 dependencies:
   # run
   - gamma-pytools     ~= 2.1
-  - joblib            ~= 1.2
+  - joblib            ~= 1.3
   - lightgbm          ~= 3.3
-  - matplotlib        ~= 3.7
-  - numpy             ~= 1.24
+  - matplotlib        ~= 3.8
+  - numpy             ~= 1.26
   - pandas            ~= 2.0
-  - python            ~= 3.9
-  - scikit-learn      ~= 1.2.0
-  - scipy             ~= 1.10
-  - shap              ~= 0.41
+  - python            ~= 3.11
+  - scikit-learn      ~= 1.2.2
+  - scipy             ~= 1.11
+  - shap              ~= 0.43
   - sklearndf         ~= 2.2
-  - typing_extensions ~= 4.3
+  - typing_extensions ~= 4.6
+  - xlrd              ~= 2.0
   # additional packages for notebooks etc.
   - pip     ~= 23.0
   - pip:
@@ -30,7 +31,7 @@ dependencies:
   - pydata-sphinx-theme      ~= 0.8.1
   # notebooks
   - ipywidgets ~= 8.0
-  - jupyterlab ~= 3.5
+  - jupyterlab ~= 4.0
   - openpyxl   ~= 3.0
   - seaborn    ~= 0.12
-  - tableone   ~= 0.7
+  - tableone   ~= 0.8
diff --git a/pypi_description.rst b/pypi_description.rst
@@ -36,7 +36,7 @@ workflow, enhancing
 tried and tested pipelining paradigm with new capabilities for model
 selection, inspection, and simulation.
 FACET also introduces
-`sklearndf <https://github.com/BCG-Gamma/sklearndf>`__, an augmented
+`sklearndf <https://github.com/BCG-X-Official/sklearndf>`__, an augmented
 version of *scikit-learn* with enhanced support for *pandas* data
 frames that ensures end-to-end traceability of features.
 
@@ -51,7 +51,7 @@ License
 ---------------------------
 
 FACET is licensed under Apache 2.0 as described in the
-`LICENSE <https://github.com/BCG-Gamma/facet/blob/develop/LICENSE>`_ file.
+`LICENSE <https://github.com/BCG-X-Official/facet/blob/develop/LICENSE>`_ file.
 
 .. Begin-Badges
 
@@ -68,7 +68,7 @@ FACET is licensed under Apache 2.0 as described in the
    :target: https://github.com/psf/black
 
 .. |made_with_sphinx_doc| image:: https://img.shields.io/badge/Made%20with-Sphinx-1f425f.svg
-   :target: https://bcg-gamma.github.io/facet/index.html
+   :target: https://bcg-x-official.github.io/facet/index.html
 
 .. |license_badge| image:: https://img.shields.io/badge/License-Apache%202.0-olivegreen.svg
    :target: https://opensource.org/licenses/Apache-2.0

diff --git a/pyproject.toml b/pyproject.toml
@@ -8,7 +8,7 @@ exclude = [".idea", "tmp", "dist", ".tox", ".pytest_cache"]
 [tool.flit.metadata]
 module = "facet"
 author = "Boston Consulting Group (BCG)"
-home-page = "https://github.com/BCG-Gamma/facet"
+home-page = "https://github.com/BCG-X-Official/facet"
 description-file = "pypi_description.rst"
 dist-name = "gamma-facet"
 license = "Apache Software License v2.0"
@@ -64,8 +64,8 @@ docs = [
 ]
 
 [tool.flit.metadata.urls]
-Documentation = "https://bcg-gamma.github.io/facet/"
-Repository = "https://github.com/BCG-Gamma/facet"
+Documentation = "https://bcg-x-official.github.io/facet/"
+Repository = "https://github.com/BCG-X-Official/facet"
 
 [build]
 # comma-separated list of packages to be built from source in pip min builds

diff --git a/sphinx/auxiliary/Diabetes_getting_started_example.ipynb b/sphinx/auxiliary/Diabetes_getting_started_example.ipynb
@@ -25,7 +25,7 @@
     "    \n",
     "- **Enhanced Machine Learning Workflow**  \n",
     "\n",
-    "    FACET offers an efficient and transparent machine learning workflow, enhancing [scikit-learn]( https://scikit-learn.org/stable/index.html)'s tried and tested pipelining paradigm with new capabilities for model selection, inspection, and simulation. FACET also introduces [sklearndf](https://github.com/BCG-Gamma/sklearndf), an augmented version of *scikit-learn* with enhanced support for *pandas* dataframes that ensures end-to-end traceability of features.       "
+    "    FACET offers an efficient and transparent machine learning workflow, enhancing [scikit-learn]( https://scikit-learn.org/stable/index.html)'s tried and tested pipelining paradigm with new capabilities for model selection, inspection, and simulation. FACET also introduces [sklearndf](https://github.com/BCG-X-Official/sklearndf), an augmented version of *scikit-learn* with enhanced support for *pandas* dataframes that ensures end-to-end traceability of features.       "
    ]
   },
   {

diff --git a/sphinx/auxiliary/Facet_sphinx_tutorial_template.ipynb b/sphinx/auxiliary/Facet_sphinx_tutorial_template.ipynb
@@ -43,7 +43,7 @@
     "    \n",
     "- **Enhanced Machine Learning Workflow**  \n",
     "\n",
-    "    FACET offers an efficient and transparent machine learning workflow, enhancing [scikit-learn]( https://scikit-learn.org/stable/index.html)'s tried and tested pipelining paradigm with new capabilities for model selection, inspection, and simulation. FACET also introduces [sklearndf](https://github.com/BCG-Gamma/sklearndf), an augmented version of *scikit-learn* with enhanced support for *pandas* dataframes that ensures end-to-end traceability of features.     \n",
+    "    FACET offers an efficient and transparent machine learning workflow, enhancing [scikit-learn]( https://scikit-learn.org/stable/index.html)'s tried and tested pipelining paradigm with new capabilities for model selection, inspection, and simulation. FACET also introduces [sklearndf](https://github.com/BCG-X-Official/sklearndf), an augmented version of *scikit-learn* with enhanced support for *pandas* dataframes that ensures end-to-end traceability of features.     \n",
     "\n",
     "***\n",
     "\n",
@@ -86,7 +86,7 @@
     "\n",
     "1. Common packages (pandas, matplotlib, etc.)\n",
     "2. Required FACET classes (inspection, selection, validation, simulation, etc.)\n",
-    "3. Other BCG Gamma packages which simplify pipelining (sklearndf, see on [GitHub](https://github.com/orgs/BCG-Gamma/sklearndf/)) and support visualization (pytools, see on [GitHub](https://github.com/BCG-Gamma/pytools)) when using FACET"
+    "3. Other BCG Gamma packages which simplify pipelining (sklearndf, see on [GitHub](https://github.com/orgs/BCG-X-Official/sklearndf/)) and support visualization (pytools, see on [GitHub](https://github.com/BCG-X-Official/pytools)) when using FACET"
    ]
   },
   {
@@ -128,7 +128,7 @@
    "source": [
     "**sklearndf imports**\n",
     "\n",
-    "Instead of using the \"regular\" scikit-learn package, we are going to use sklearndf (see on [GitHub](https://github.com/orgs/BCG-Gamma/sklearndf/)). sklearndf is an open source library designed to address a common issue with scikit-learn: the outputs of transformers are numpy arrays, even when the input is a data frame. However, to inspect a model it is essential to keep track of the feature names. sklearndf retains all the functionality available through scikit-learn plus the feature traceability and usability associated with Pandas data frames. Additionally, the names of all your favourite scikit-learn functions are the same except for `DF` on the end. For example, the standard scikit-learn import:\n",
+    "Instead of using the \"regular\" scikit-learn package, we are going to use sklearndf (see on [GitHub](https://github.com/orgs/BCG-X-Official/sklearndf/)). sklearndf is an open source library designed to address a common issue with scikit-learn: the outputs of transformers are numpy arrays, even when the input is a data frame. However, to inspect a model it is essential to keep track of the feature names. sklearndf retains all the functionality available through scikit-learn plus the feature traceability and usability associated with Pandas data frames. Additionally, the names of all your favourite scikit-learn functions are the same except for `DF` on the end. For example, the standard scikit-learn import:\n",
     "\n",
     "`from sklearn.pipeline import Pipeline`\n",
     "\n",
@@ -152,7 +152,7 @@
    "source": [
     "**pytools imports**\n",
     "\n",
-    "pytools (see on [GitHub](https://github.com/BCG-Gamma/pytools)) is an open source library containing general machine learning and visualization utilities, some of which are useful for visualising the advanced model inspection capabilities of FACET."
+    "pytools (see on [GitHub](https://github.com/BCG-X-Official/pytools)) is an open source library containing general machine learning and visualization utilities, some of which are useful for visualising the advanced model inspection capabilities of FACET."
    ]
   },
   {

diff --git a/sphinx/make.py b/sphinx/make.py
@@ -9,14 +9,13 @@
 
 
 if __name__ == "__main__":
-
     # noinspection PyUnusedLocal
     def run_make(branch: str, working_directory: str) -> None:
         """Stub, overwritten by bootstrap.py"""
 
     # run the common make file available in the pytools repo
     with request.urlopen(
-        f"https://raw.githubusercontent.com/BCG-Gamma/pytools/{BRANCH}"
+        f"https://raw.githubusercontent.com/BCG-X-Official/pytools/{BRANCH}"
         f"/sphinx/base/bootstrap.py"
     ) as response:
         exec(response.read().decode("utf-8"), globals())

diff --git a/sphinx/source/conf.py b/sphinx/source/conf.py
@@ -19,9 +19,9 @@
     project="facet",
     html_logo=os.path.join("_images", "Gamma_Facet_Logo_RGB_LB.svg"),
     intersphinx_mapping={
-        "pytools": ("https://bcg-gamma.github.io/pytools/", None),
+        "pytools": ("https://bcg-x-official.github.io/pytools/", None),
         "shap": ("https://shap.readthedocs.io/en/stable", None),
         "sklearn": ("https://scikit-learn.org/stable", None),
-        "sklearndf": ("https://bcg-gamma.github.io/sklearndf/", None),
+        "sklearndf": ("https://bcg-x-official.github.io/sklearndf/", None),
     },
 )
diff --git a/sphinx/source/contribution_guide.rst b/sphinx/source/contribution_guide.rst
@@ -296,7 +296,7 @@ The ``sphinx/source`` folder contains:
 
 
 The two key scripts are ``make.py`` and ``conf.py``. The base configuration for the
-these scripts can be found in `pytools/sphinx <https://github.com/BCG-Gamma/pytools/tree/develop/sphinx/base>`_.
+these scripts can be found in `pytools/sphinx <https://github.com/BCG-X-Official/pytools/tree/develop/sphinx/base>`_.
 The reason for this is to minimise code given the standardization of the documentation
 build across multiple packages.
 
@@ -452,7 +452,7 @@ The build process for the PyPI and conda distributions uses the following key
 files:
 
 - ``make.py``: generic Python script for package builds. Most configuration is imported
-  from pytools `make.py <https://github.com/BCG-Gamma/pytools/blob/develop/make.py>`__
+  from pytools `make.py <https://github.com/BCG-X-Official/pytools/blob/develop/make.py>`__
   which is a build script that wraps the package build, as well as exposing the matrix
   dependency definitions specified in the ``pyproject.toml`` as environment variables
 - ``pyproject.toml``: metadata for PyPI, build settings and package dependencies

diff --git a/sphinx/source/faqs.rst b/sphinx/source/faqs.rst
@@ -14,7 +14,7 @@ on `stackoverflow <https://stackoverflow.com/>`_.
 1. **What if I find a bug or have an idea for a new feature?**
 
     For bug reports or feature requests please use our
-    `GitHub issue tracker <https://github.com/BCG-Gamma/facet/issues>`_.
+    `GitHub issue tracker <https://github.com/BCG-X-Official/facet/issues>`_.
     For any other enquiries please feel free to contact us at FacetTeam@bcg.com.
 
 2. **How does FACET's novel algorithm calculate pairwise feature redundancy and synergy?**