scikit-learn · glemaitre · Sep 15, 2022 · Jun 23, 2022 · Jun 23, 2022 · Jun 23, 2022
diff --git a/README.rst b/README.rst
@@ -42,6 +42,7 @@
 .. |PandasMinVersion| replace:: 1.0.5
 .. |SeabornMinVersion| replace:: 0.9.0
 .. |PytestMinVersion| replace:: 5.0.1
+.. |PlotlyMinVersion| replace:: 5.9.0
 
 .. image:: https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/scikit-learn-logo.png
   :target: https://scikit-learn.org/
@@ -83,7 +84,7 @@ classes end with "Display") require Matplotlib (>= |MatplotlibMinVersion|).
 For running the examples Matplotlib >= |MatplotlibMinVersion| is required.
 A few examples require scikit-image >= |Scikit-ImageMinVersion|, a few examples
 require pandas >= |PandasMinVersion|, some examples require seaborn >=
-|SeabornMinVersion|.
+|SeabornMinVersion| and plotly >= |PlotlyMinVersion|.
 
 User installation
 ~~~~~~~~~~~~~~~~~

diff --git a/build_tools/github/doc_environment.yml b/build_tools/github/doc_environment.yml
@@ -25,6 +25,7 @@ dependencies:
   - sphinx-gallery
   - numpydoc
   - sphinx-prompt
+  - plotly
   - pip
   - pip:
     - sphinxext-opengraph
diff --git a/build_tools/github/doc_linux-64_conda.lock b/build_tools/github/doc_linux-64_conda.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: eb6f446eaacd58fbff84b6520503d14519011e67e0f6ce3d39a9a2922fb781cb
+# input_hash: 51824060cd657aa08f97c645d9c3c1efd6eec66aedaf8949d8d7cb5d9d8e69e6
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
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@@ -83,7 +83,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.10-h9b69904_4.tar.b
 https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-he0ac6c6_0.tar.bz2#f5759f0c80708fbf9c4836c0cb46d0fe
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 https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.37-h753d276_4.tar.bz2#6b611734b73d639c084ac4be2fcd996a
-https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.39.2-h753d276_1.tar.bz2#90136dc0a305db4e1df24945d431457b
+https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.39.3-h753d276_0.tar.bz2#ccb2457c73609f2622b8a4b3e42e5d8b
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@@ -112,7 +112,7 @@ https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-16_linux64_openb
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 https://conda.anaconda.org/conda-forge/linux-64/mysql-libs-8.0.30-h28c427c_1.tar.bz2#0bd292db365c83624316efc2764d9f16
-https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.39.2-h4ff8645_1.tar.bz2#2676ec698ce91567fca50654ac1b18ba
+https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.39.3-h4ff8645_0.tar.bz2#f03cf4ec974e32b6c5d349f62637e36e
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@@ -175,10 +175,12 @@ https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.0-pyhd8
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-jsmath-1.0.1-py_0.tar.bz2#67cd9d9c0382d37479b4d306c369a2d4
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+https://conda.anaconda.org/conda-forge/noarch/tenacity-8.0.1-pyhd8ed1ab_0.tar.bz2#8b29b2c12cb21dbd057755e5fd22d005
 https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.1.0-pyh8a188c0_0.tar.bz2#a2995ee828f65687ac5b1e71a2ab1e0c
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 https://conda.anaconda.org/conda-forge/noarch/toolz-0.12.0-pyhd8ed1ab_0.tar.bz2#92facfec94bc02d6ccf42e7173831a36
+https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.3.0-pyha770c72_0.tar.bz2#a9d85960bc62d53cc4ea0d1d27f73c98
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@@ -198,6 +200,7 @@ https://conda.anaconda.org/conda-forge/noarch/packaging-21.3-pyhd8ed1ab_0.tar.bz
 https://conda.anaconda.org/conda-forge/noarch/partd-1.3.0-pyhd8ed1ab_0.tar.bz2#af8c82d121e63082926062d61d9abb54
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 https://conda.anaconda.org/conda-forge/noarch/pip-22.2.2-pyhd8ed1ab_0.tar.bz2#0b43abe4d3ee93e82742d37def53a836
+https://conda.anaconda.org/conda-forge/noarch/plotly-5.10.0-pyhd8ed1ab_0.tar.bz2#e95502aa0f8e3db05d198214472575de
 https://conda.anaconda.org/conda-forge/linux-64/pluggy-1.0.0-py39hf3d152e_3.tar.bz2#c375c89340e563053f3656c7f134d265
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@@ -231,14 +234,14 @@ https://conda.anaconda.org/conda-forge/noarch/tifffile-2022.8.12-pyhd8ed1ab_0.ta
 https://conda.anaconda.org/conda-forge/linux-64/pyqt-5.15.7-py39h18e9c17_0.tar.bz2#5ed8f83afff3b64fa91f7a6af8d7ff04
 https://conda.anaconda.org/conda-forge/noarch/pytest-xdist-2.5.0-pyhd8ed1ab_0.tar.bz2#1fdd1f3baccf0deb647385c677a1a48e
 https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.19.3-py39h1832856_1.tar.bz2#472bb5b9d9eb26ac697902da265ee551
-https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.11.2-pyhd8ed1ab_0.tar.bz2#fe2303dc8f1febeb82d927ce8ad153ed
+https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.12.0-pyhd8ed1ab_0.tar.bz2#05ee2fb22c1eca4309c06d11aff049f3
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-https://conda.anaconda.org/conda-forge/noarch/seaborn-0.11.2-hd8ed1ab_0.tar.bz2#e56b6a19f4b717eca7c68ad78196b075
+https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.0-hd8ed1ab_0.tar.bz2#c22474d96fa1725ae47def82b5668686
 https://conda.anaconda.org/conda-forge/noarch/sphinx-5.1.1-pyhd8ed1ab_1.tar.bz2#cd1129e88f6278787212624e1b7a8001
 https://conda.anaconda.org/conda-forge/noarch/numpydoc-1.4.0-pyhd8ed1ab_1.tar.bz2#0aac89c61a466b0f9c4fd0ec44d81f1d
 https://conda.anaconda.org/conda-forge/noarch/sphinx-gallery-0.11.1-pyhd8ed1ab_0.tar.bz2#729254314a5d178eefca50acbc2687b8
 https://conda.anaconda.org/conda-forge/noarch/sphinx-prompt-1.4.0-pyhd8ed1ab_0.tar.bz2#88ee91e8679603f2a5bd036d52919cc2
-# pip sphinxext-opengraph @ https://files.pythonhosted.org/packages/58/ed/59df64b8400caf736f38bd3725ab9b1d9e50874f629980973aea090c1a8b/sphinxext_opengraph-0.6.3-py3-none-any.whl#sha256=bf76017c105856b07edea6caf4942b6ae9bb168585dccfd6dbdb6e4161f6b03a
+# pip sphinxext-opengraph @ https://files.pythonhosted.org/packages/58/ed/59df64b8400caf736f38bd3725ab9b1d9e50874f629980973aea090c1a8b/sphinxext_opengraph-0.6.3-py3-none-any.whl#md5=None
diff --git a/build_tools/github/doc_min_dependencies_environment.yml b/build_tools/github/doc_min_dependencies_environment.yml
@@ -25,6 +25,7 @@ dependencies:
   - sphinx-gallery=0.7.0  # min
   - numpydoc=1.2.0  # min
   - sphinx-prompt=1.3.0  # min
+  - plotly=5.9.0  # min
   - pip
   - pip:
     - sphinxext-opengraph==0.4.2  # min
diff --git a/build_tools/github/doc_min_dependencies_linux-64_conda.lock b/build_tools/github/doc_min_dependencies_linux-64_conda.lock
@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: d7c5b73a8e5033accbbf23734674ee617f6e77fbc98fe96e654c88b245458829
+# input_hash: 53d568af487a4ac9a260bfa1bcd5263594b6a4aef53e17e7ccf17e2e2165ab96
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
 https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2022.6.15-ha878542_0.tar.bz2#c320890f77fd1d617fa876e0982002c2
@@ -45,7 +45,7 @@ https://conda.anaconda.org/conda-forge/linux-64/gfortran_impl_linux-64-7.5.0-h56
 https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-7.5.0-hd0bb8aa_20.tar.bz2#dbe78fc5fb9c339f8e55426559e12f7b
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 https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.37-h753d276_4.tar.bz2#6b611734b73d639c084ac4be2fcd996a
-https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.39.2-h753d276_1.tar.bz2#90136dc0a305db4e1df24945d431457b
+https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.39.3-h753d276_0.tar.bz2#ccb2457c73609f2622b8a4b3e42e5d8b
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@@ -61,7 +61,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libglib-2.66.3-hbe7bbb4_0.tar.bz
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 https://conda.anaconda.org/conda-forge/linux-64/mkl-2020.4-h726a3e6_304.tar.bz2#b9b35a50e5377b19da6ec0709ae77fc3
-https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.39.2-h4ff8645_1.tar.bz2#2676ec698ce91567fca50654ac1b18ba
+https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.39.3-h4ff8645_0.tar.bz2#f03cf4ec974e32b6c5d349f62637e36e
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@@ -102,9 +102,11 @@ https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.0-pyhd8
 https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-jsmath-1.0.1-py_0.tar.bz2#67cd9d9c0382d37479b4d306c369a2d4
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+https://conda.anaconda.org/conda-forge/noarch/tenacity-8.0.1-pyhd8ed1ab_0.tar.bz2#8b29b2c12cb21dbd057755e5fd22d005
 https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.1.0-pyh8a188c0_0.tar.bz2#a2995ee828f65687ac5b1e71a2ab1e0c
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 https://conda.anaconda.org/conda-forge/noarch/toolz-0.12.0-pyhd8ed1ab_0.tar.bz2#92facfec94bc02d6ccf42e7173831a36
+https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.3.0-pyha770c72_0.tar.bz2#a9d85960bc62d53cc4ea0d1d27f73c98
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@@ -120,6 +122,7 @@ https://conda.anaconda.org/conda-forge/linux-64/numpy-1.17.3-py38h95a1406_0.tar.
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+https://conda.anaconda.org/conda-forge/noarch/plotly-5.9.0-pyhd8ed1ab_0.tar.bz2#00a668931d448ce0ce42d1b02005d636
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@@ -148,16 +151,16 @@ https://conda.anaconda.org/conda-forge/noarch/pyopenssl-22.0.0-pyhd8ed1ab_0.tar.
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-https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.11.2-pyhd8ed1ab_0.tar.bz2#fe2303dc8f1febeb82d927ce8ad153ed
+https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.12.0-pyhd8ed1ab_0.tar.bz2#05ee2fb22c1eca4309c06d11aff049f3
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-https://conda.anaconda.org/conda-forge/noarch/seaborn-0.11.2-hd8ed1ab_0.tar.bz2#e56b6a19f4b717eca7c68ad78196b075
+https://conda.anaconda.org/conda-forge/noarch/seaborn-0.12.0-hd8ed1ab_0.tar.bz2#c22474d96fa1725ae47def82b5668686
 https://conda.anaconda.org/conda-forge/noarch/sphinx-4.0.1-pyh6c4a22f_2.tar.bz2#c203dcc46f262853ecbb9552c50d664e
 https://conda.anaconda.org/conda-forge/noarch/numpydoc-1.2-pyhd8ed1ab_0.tar.bz2#025ad7ca2c7f65007ab6b6f5d93a56eb
 https://conda.anaconda.org/conda-forge/noarch/sphinx-gallery-0.7.0-py_0.tar.bz2#80bad3f857ecc86a4ab73f3e57addd13
 https://conda.anaconda.org/conda-forge/noarch/sphinx-prompt-1.3.0-py_0.tar.bz2#9363002e2a134a287af4e32ff0f26cdc
-# pip sphinxext-opengraph @ https://files.pythonhosted.org/packages/50/ac/c105ed3e0a00b14b28c0aa630935af858fd8a32affeff19574b16e2c6ae8/sphinxext_opengraph-0.4.2-py3-none-any.whl#sha256=a51f2604f9a5b6c0d25d3a88e694d5c02e20812dc0e482adf96c8628f9109357
+# pip sphinxext-opengraph @ https://files.pythonhosted.org/packages/50/ac/c105ed3e0a00b14b28c0aa630935af858fd8a32affeff19574b16e2c6ae8/sphinxext_opengraph-0.4.2-py3-none-any.whl#md5=None
diff --git a/build_tools/update_environments_and_lock_files.py b/build_tools/update_environments_and_lock_files.py
@@ -242,6 +242,7 @@ def remove_from(alist, to_remove):
            "sphinx-gallery",
             "numpydoc",
             "sphinx-prompt",
+            "plotly",
         ],
         "pip_dependencies": ["sphinxext-opengraph"],
         "package_constraints": {
@@ -257,6 +258,7 @@ def remove_from(alist, to_remove):
             "numpydoc": "min",
             "sphinx-prompt": "min",
             "sphinxext-opengraph": "min",
+            "plotly": "min",
         },
     },
     {
@@ -274,6 +276,7 @@ def remove_from(alist, to_remove):
             "sphinx-gallery",
             "numpydoc",
             "sphinx-prompt",
+            "plotly",
         ],
         "pip_dependencies": ["sphinxext-opengraph"],
         "package_constraints": {

diff --git a/doc/conf.py b/doc/conf.py
@@ -29,6 +29,17 @@
 import sphinx_gallery
 from sphinx_gallery.sorting import ExampleTitleSortKey
 
+try:
+    # Configure plotly to integrate its output into the HTML pages generated by
+    # sphinx-gallery.
+    import plotly.io as pio
+
+    pio.renderers.default = "sphinx_gallery"
+except ImportError:
+    # Make it possible to render the doc when not running the examples
+    # that need plotly.
+    pass
+
 # -- General configuration ---------------------------------------------------
 
 # Add any Sphinx extension module names here, as strings. They can be
@@ -257,6 +268,9 @@
     "auto_examples/linear_model/plot_bayesian_ridge": (
         "auto_examples/linear_model/plot_ard"
     ),
+    "examples/model_selection/grid_search_text_feature_extraction.py": (
+        "examples/model_selection/plot_grid_search_text_feature_extraction.py"
+    ),
 }
 html_context["redirects"] = redirects
 for old_link in redirects:

diff --git a/doc/modules/compose.rst b/doc/modules/compose.rst
@@ -163,7 +163,7 @@ You can also provide custom feature names for the input data using
 .. topic:: Examples:
 
  * :ref:`sphx_glr_auto_examples_feature_selection_plot_feature_selection_pipeline.py`
- * :ref:`sphx_glr_auto_examples_model_selection_grid_search_text_feature_extraction.py`
+ * :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_text_feature_extraction.py`
  * :ref:`sphx_glr_auto_examples_compose_plot_digits_pipe.py`
  * :ref:`sphx_glr_auto_examples_miscellaneous_plot_kernel_approximation.py`
  * :ref:`sphx_glr_auto_examples_svm_plot_svm_anova.py`

diff --git a/doc/modules/cross_validation.rst b/doc/modules/cross_validation.rst
@@ -295,7 +295,7 @@ section.
     * :ref:`sphx_glr_auto_examples_model_selection_plot_roc_crossval.py`,
     * :ref:`sphx_glr_auto_examples_feature_selection_plot_rfe_with_cross_validation.py`,
     * :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_digits.py`,
-    * :ref:`sphx_glr_auto_examples_model_selection_grid_search_text_feature_extraction.py`,
+    * :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_text_feature_extraction.py`,
     * :ref:`sphx_glr_auto_examples_model_selection_plot_cv_predict.py`,
     * :ref:`sphx_glr_auto_examples_model_selection_plot_nested_cross_validation_iris.py`.
 

diff --git a/doc/modules/feature_extraction.rst b/doc/modules/feature_extraction.rst
@@ -607,7 +607,7 @@ As usual the best way to adjust the feature extraction parameters
 is to use a cross-validated grid search, for instance by pipelining the
 feature extractor with a classifier:
 
- * :ref:`sphx_glr_auto_examples_model_selection_grid_search_text_feature_extraction.py`
+ * :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_text_feature_extraction.py`
 
 
 Decoding text files

diff --git a/doc/modules/grid_search.rst b/doc/modules/grid_search.rst
@@ -77,7 +77,7 @@ evaluated and the best combination is retained.
     - See :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_digits.py` for an example of
       Grid Search computation on the digits dataset.
 
-    - See :ref:`sphx_glr_auto_examples_model_selection_grid_search_text_feature_extraction.py` for an example
+    - See :ref:`sphx_glr_auto_examples_model_selection_plot_grid_search_text_feature_extraction.py` for an example
       of Grid Search coupling parameters from a text documents feature
       extractor (n-gram count vectorizer and TF-IDF transformer) with a
       classifier (here a linear SVM trained with SGD with either elastic