Merge branch 'submodulev2' of https://github.com/neurodata/scikit-learn into submodulev2

Author: adam2392

SECURITY.md

@@ -4,8 +4,8 @@
 
 | Version   | Supported          |
 | --------- | ------------------ |
-| 1.2.2     | :white_check_mark: |
-| < 1.2.2   | :x:                |
+| 1.3.0     | :white_check_mark: |
+| < 1.3.0   | :x:                |
 
 ## Reporting a Vulnerability
 

build_tools/circle/doc_min_dependencies_environment.yml

@@ -23,7 +23,7 @@ dependencies:
   - memory_profiler
   - compilers
   - sphinx=6.0.0  # min
-  - sphinx-gallery=0.7.0  # min
+  - sphinx-gallery=0.10.1  # min
   - sphinx-copybutton=0.5.2  # min
   - numpydoc=1.2.0  # min
   - sphinx-prompt=1.3.0  # min

build_tools/circle/doc_min_dependencies_linux-64_conda.lock

@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: bd03405f744d4d5d0c59edd290d1e4245873b8593fcd3bbc3efdf8654a283161
+# input_hash: d465abb23248872aed411e2f2f7293a661f0b783f1a84420ffa5431229814cab
 @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-2023.5.7-hbcca054_0.conda#f5c65075fc34438d5b456c7f3f5ab695
@@ -100,7 +100,7 @@ https://conda.anaconda.org/conda-forge/linux-64/markupsafe-2.1.3-py38h01eb140_0.
 https://conda.anaconda.org/conda-forge/noarch/networkx-3.1-pyhd8ed1ab_0.conda#254f787d5068bc89f578bf63893ce8b4
 https://conda.anaconda.org/conda-forge/noarch/packaging-23.1-pyhd8ed1ab_0.conda#91cda59e66e1e4afe9476f8ef98f5c30
 https://conda.anaconda.org/conda-forge/linux-64/pillow-9.4.0-py38hde6dc18_1.conda#3de5619d3f556f966189e5251a266125
-https://conda.anaconda.org/conda-forge/noarch/pluggy-1.0.0-pyhd8ed1ab_5.tar.bz2#7d301a0d25f424d96175f810935f0da9
+https://conda.anaconda.org/conda-forge/noarch/pluggy-1.2.0-pyhd8ed1ab_0.conda#7263924c642d22e311d9e59b839f1b33
 https://conda.anaconda.org/conda-forge/linux-64/psutil-5.9.5-py38h1de0b5d_0.conda#92e899e7b0ed27c793014d1fa54f9b7b
 https://conda.anaconda.org/conda-forge/noarch/py-1.11.0-pyh6c4a22f_0.tar.bz2#b4613d7e7a493916d867842a6a148054
 https://conda.anaconda.org/conda-forge/noarch/pygments-2.15.1-pyhd8ed1ab_0.conda#d316679235612869eba305aa7d41d9bf
@@ -138,15 +138,15 @@ https://conda.anaconda.org/conda-forge/noarch/memory_profiler-0.61.0-pyhd8ed1ab_
 https://conda.anaconda.org/conda-forge/noarch/partd-1.4.0-pyhd8ed1ab_0.conda#721dab5803ea92ce02ddc4ee50aa0c48
 https://conda.anaconda.org/conda-forge/noarch/pip-23.1.2-pyhd8ed1ab_0.conda#7288da0d36821349cf1126e8670292df
 https://conda.anaconda.org/conda-forge/noarch/plotly-5.14.0-pyhd8ed1ab_0.conda#6a7bcc42ef58dd6cf3da9333ea102433
-https://conda.anaconda.org/conda-forge/noarch/pytest-7.3.2-pyhd8ed1ab_1.conda#f2465696f4396245eca4613f6e924796
+https://conda.anaconda.org/conda-forge/noarch/pytest-7.4.0-pyhd8ed1ab_0.conda#3cfe9b9e958e7238a386933c75d190db
 https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.8.2-pyhd8ed1ab_0.tar.bz2#dd999d1cc9f79e67dbb855c8924c7984
 https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.6.3-hd8ed1ab_0.conda#3876f650ed7d0f95d70fa4b647621909
 https://conda.anaconda.org/conda-forge/noarch/urllib3-2.0.3-pyhd8ed1ab_0.conda#ae465d0fbf9f1979cb2d8d4043d885e2
 https://conda.anaconda.org/conda-forge/linux-64/gst-plugins-base-1.14.5-h0935bb2_2.tar.bz2#eb125ee86480e00a4a1ed45a577c3311
 https://conda.anaconda.org/conda-forge/noarch/importlib_metadata-6.7.0-hd8ed1ab_0.conda#27a4cec373ec84d1c1aa02a1e37f8eaf
 https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.8.0-20_mkl.tar.bz2#8274dc30518af9df1de47f5d9e73165c
 https://conda.anaconda.org/conda-forge/linux-64/numpy-1.17.3-py38h95a1406_0.tar.bz2#bc0cbf611fe2f86eab29b98e51404f5e
-https://conda.anaconda.org/conda-forge/noarch/platformdirs-3.6.0-pyhd8ed1ab_0.conda#741384b21c1b512617f4ee4ea8457c5d
+https://conda.anaconda.org/conda-forge/noarch/platformdirs-3.8.0-pyhd8ed1ab_0.conda#3e4aca765371893ad848397794600632
 https://conda.anaconda.org/conda-forge/noarch/pytest-forked-1.6.0-pyhd8ed1ab_0.conda#a46947638b6e005b63d2d6271da529b0
 https://conda.anaconda.org/conda-forge/noarch/requests-2.31.0-pyhd8ed1ab_0.conda#a30144e4156cdbb236f99ebb49828f8b
 https://conda.anaconda.org/conda-forge/linux-64/blas-2.20-mkl.tar.bz2#e7d09a07f5413e53dca5282b8fa50bed
@@ -167,7 +167,7 @@ https://conda.anaconda.org/conda-forge/linux-64/pyqt-5.12.3-py38ha8c2ead_3.tar.b
 https://conda.anaconda.org/conda-forge/linux-64/scikit-image-0.16.2-py38hb3f55d8_0.tar.bz2#468b398fefac8884cd6e6513af66549b
 https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.12.2-pyhd8ed1ab_0.conda#cf88f3a1c11536bc3c10c14ad00ccc42
 https://conda.anaconda.org/conda-forge/noarch/sphinx-copybutton-0.5.2-pyhd8ed1ab_0.conda#ac832cc43adc79118cf6e23f1f9b8995
-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-gallery-0.10.1-pyhd8ed1ab_0.tar.bz2#4918585fe5e5341740f7e63c61743efb
 https://conda.anaconda.org/conda-forge/noarch/sphinx-prompt-1.3.0-py_0.tar.bz2#9363002e2a134a287af4e32ff0f26cdc
 https://conda.anaconda.org/conda-forge/linux-64/matplotlib-3.1.3-py38_0.tar.bz2#1992ab91bbff86ded8d99d1f488d8e8b
 https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.12.2-py38h5c078b8_0.tar.bz2#33787719ad03d33cffc4e2e3ea82bc9e

doc/conf.py

@@ -66,19 +66,22 @@
 ]
 
 # Specify how to identify the prompt when copying code snippets
-copybutton_prompt_text = ">>> "
+copybutton_prompt_text = r">>> |\.\.\. "
+copybutton_prompt_is_regexp = True
 
 try:
     import jupyterlite_sphinx  # noqa: F401
 
     extensions.append("jupyterlite_sphinx")
+    with_jupyterlite = True
 except ImportError:
     # In some cases we don't want to require jupyterlite_sphinx to be installed,
     # e.g. the doc-min-dependencies build
     warnings.warn(
         "jupyterlite_sphinx is not installed, you need to install it "
         "if you want JupyterLite links to appear in each example"
     )
+    with_jupyterlite = False
 
 # Produce `plot::` directives for examples that contain `import matplotlib` or
 # `from matplotlib import`.
@@ -526,13 +529,16 @@ def reset_sklearn_config(gallery_conf, fname):
         "dependencies": "./binder/requirements.txt",
         "use_jupyter_lab": True,
     },
-    "jupyterlite": {"notebook_modification_function": notebook_modification_function},
     # avoid generating too many cross links
     "inspect_global_variables": False,
     "remove_config_comments": True,
     "plot_gallery": "True",
     "reset_modules": ("matplotlib", "seaborn", reset_sklearn_config),
 }
+if with_jupyterlite:
+    sphinx_gallery_conf["jupyterlite"] = {
+        "notebook_modification_function": notebook_modification_function
+    }
 
 
 # The following dictionary contains the information used to create the

doc/developers/advanced_installation.rst

@@ -90,7 +90,7 @@ feature, code or documentation improvement).
 
    .. prompt:: bash $
 
-     pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+     pip install -v --no-use-pep517 --no-build-isolation -e .
 
 #. Check that the installed scikit-learn has a version number ending with
    `.dev0`:
@@ -109,7 +109,9 @@ feature, code or documentation improvement).
     (ending in `.pyx` or `.pxd`). This can happen when you edit them or when you
     use certain git commands such as `git pull`. Use the ``--no-build-isolation`` flag
     to avoid compiling the whole project each time, only the files you have
-    modified.
+    modified. Include the ``--no-use-pep517`` flag because the ``--no-build-isolation``
+    option might not work otherwise (this is due to a bug which will be fixed in the
+    future).
 
 Dependencies
 ------------
@@ -242,7 +244,7 @@ Finally, build scikit-learn from this command prompt:
 
 .. prompt:: bash $
 
-    pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+    pip install -v --no-use-pep517 --no-build-isolation -e .
 
 .. _compiler_macos:
 
@@ -284,7 +286,7 @@ scikit-learn from source:
         joblib threadpoolctl pytest compilers llvm-openmp
     conda activate sklearn-dev
     make clean
-    pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+    pip install -v --no-use-pep517 --no-build-isolation -e .
 
 .. note::
 
@@ -364,7 +366,7 @@ Finally, build scikit-learn in verbose mode (to check for the presence of the
 .. prompt:: bash $
 
     make clean
-    pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+    pip install -v --no-use-pep517 --no-build-isolation -e .
 
 .. _compiler_linux:
 
@@ -424,7 +426,7 @@ in the user folder using conda:
     conda create -n sklearn-dev -c conda-forge python numpy scipy cython \
         joblib threadpoolctl pytest compilers
     conda activate sklearn-dev
-    pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+    pip install -v --no-use-pep517 --no-build-isolation -e .
 
 .. _compiler_freebsd:
 
@@ -453,7 +455,7 @@ Finally, build the package using the standard command:
 
 .. prompt:: bash $
 
-    pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+    pip install -v --no-use-pep517 --no-build-isolation -e .
 
 For the upcoming FreeBSD 12.1 and 11.3 versions, OpenMP will be included in
 the base system and these steps will not be necessary.
@@ -514,7 +516,7 @@ and environment variable as follows before calling the ``pip install`` or
 ``python setup.py build_ext`` commands::
 
     export SKLEARN_BUILD_PARALLEL=3
-    pip install --verbose --no-use-pep517 --no-build-isolation --editable .
+    pip install -v --no-use-pep517 --no-build-isolation -e .
 
 On a machine with 2 CPU cores, it can be beneficial to use a parallelism level
 of 3 to overlap IO bound tasks (reading and writing files on disk) with CPU

doc/developers/contributing.rst

@@ -920,7 +920,7 @@ Building the documentation requires installing some additional packages:
 
     pip install sphinx sphinx-gallery numpydoc matplotlib Pillow pandas \
                 scikit-image packaging seaborn sphinx-prompt \
-                sphinxext-opengraph plotly pooch
+                sphinxext-opengraph sphinx-copybutton plotly pooch
 
 To build the documentation, you need to be in the ``doc`` folder:
 

doc/templates/index.html

@@ -169,6 +169,8 @@ <h4 class="sk-landing-call-header">News</h4>
         <li><strong>On-going development:</strong>
         <a href="https://scikit-learn.org/dev/whats_new.html"><strong>What's new</strong> (Changelog)</a>
         </li>
+        <li><strong>June 2023.</strong> scikit-learn 1.3.0 is available for download (<a href="whats_new/v1.3.html#version-1-3-0">Changelog</a>).
+        </li>
         <li><strong>March 2023.</strong> scikit-learn 1.2.2 is available for download (<a href="whats_new/v1.2.html#version-1-2-2">Changelog</a>).
         </li>
         <li><strong>January 2023.</strong> scikit-learn 1.2.1 is available for download (<a href="whats_new/v1.2.html#version-1-2-1">Changelog</a>).

doc/themes/scikit-learn-modern/static/css/theme.css

@@ -1019,13 +1019,12 @@ div.sphx-glr-thumbcontainer {
   padding: 0;
 }
 
-
 @media screen and (min-width: 1540px) {
-  .sphx-glr-download-link-note {
-    position: absolute;
+  div.sphx-glr-download-link-note.admonition.note {
     position: absolute;
     left: 98%;
     width: 20ex;
+    margin-top: calc(max(5.75rem, 1vh));
   }
 }
 

doc/whats_new/v1.3.rst

@@ -7,7 +7,10 @@
 Version 1.3.0
 =============
 
-**In Development**
+**June 2023**
+
+For a short description of the main highlights of the release, please refer to
+:ref:`sphx_glr_auto_examples_release_highlights_plot_release_highlights_1_3_0.py`.
 
 .. include:: changelog_legend.inc
 
@@ -231,6 +234,11 @@ Changelog
   :user:`Jérémie du Boisberranger <jeremiedbb>`,
   :user:`Guillaume Lemaitre <glemaitre>`.
 
+- |Fix| :class:`cluster.KMeans`, :class:`cluster.MiniBatchKMeans` and
+  :func:`cluster.k_means` now correctly handle the combination of `n_init="auto"`
+  and `init` being an array-like, running one initialization in that case.
+  :pr:`26657` by :user:`Binesh Bannerjee <bnsh>`.
+
 - |API| The `sample_weight` parameter in `predict` for
   :meth:`cluster.KMeans.predict` and :meth:`cluster.MiniBatchKMeans.predict`
   is now deprecated and will be removed in v1.5.
@@ -455,6 +463,11 @@ Changelog
   on linearly separable problems.
   :pr:`25214` by `Tom Dupre la Tour`_.
 
+- |Fix| Fix a crash when calling `fit` on
+  :class:`linear_model.LogisticRegression(solver="newton-cholesky", max_iter=0)`
+  which failed to inspect the state of the model prior to the first parameter update.
+  :pr:`26653` by :user:`Olivier Grisel <ogrisel>`.
+
 - |API| Deprecates `n_iter` in favor of `max_iter` in
   :class:`linear_model.BayesianRidge` and :class:`linear_model.ARDRegression`.
   `n_iter` will be removed in scikit-learn 1.5. This change makes those
@@ -760,4 +773,40 @@ Code and Documentation Contributors
 Thanks to everyone who has contributed to the maintenance and improvement of
 the project since version 1.2, including:
 
-TODO: update at the time of the release.
+2357juan, Abhishek Singh Kushwah, Adam Handke, Adam Kania, Adam Li, adienes,
+Admir Demiraj, adoublet, Adrin Jalali, A.H.Mansouri, Ahmedbgh, Ala-Na, Alex
+Buzenet, AlexL, Ali H. El-Kassas, amay, András Simon, André Pedersen, Andrew
+Wang, Ankur Singh, annegnx, Ansam Zedan, Anthony22-dev, Artur Hermano, Arturo
+Amor, as-90, ashah002, Ashish Dutt, Ashwin Mathur, AymericBasset, Azaria
+Gebremichael, Barata Tripramudya Onggo, Benedek Harsanyi, Benjamin Bossan,
+Bharat Raghunathan, Binesh Bannerjee, Boris Feld, Brendan Lu, Brevin Kunde,
+cache-missing, Camille Troillard, Carla J, carlo, Carlo Lemos, c-git, Changyao
+Chen, Chiara Marmo, Christian Lorentzen, Christian Veenhuis, Christine P. Chai,
+crispinlogan, Da-Lan, DanGonite57, Dave Berenbaum, davidblnc, david-cortes,
+Dayne, Dea María Léon, Denis, Dimitri Papadopoulos Orfanos, Dimitris
+Litsidis, Dmitry Nesterov, Dominic Fox, Dominik Prodinger, Edern, Ekaterina
+Butyugina, Elabonga Atuo, Emir, farhan khan, Felipe Siola, futurewarning, Gael
+Varoquaux, genvalen, Gleb Levitski, Guillaume Lemaitre, gunesbayir, Haesun
+Park, hujiahong726, i-aki-y, Ian Thompson, Ido M, Ily, Irene, Jack McIvor,
+jakirkham, James Dean, JanFidor, Jarrod Millman, JB Mountford, Jérémie du
+Boisberranger, Jessicakk0711, Jiawei Zhang, Joey Ortiz, JohnathanPi, John
+Pangas, Joshua Choo Yun Keat, Joshua Hedlund, JuliaSchoepp, Julien Jerphanion,
+jygerardy, ka00ri, Kaushik Amar Das, Kento Nozawa, Kian Eliasi, Kilian Kluge,
+Lene Preuss, Linus, Logan Thomas, Loic Esteve, Louis Fouquet, Lucy Liu, Madhura
+Jayaratne, Marc Torrellas Socastro, Maren Westermann, Mario Kostelac, Mark
+Harfouche, Marko Toplak, Marvin Krawutschke, Masanori Kanazu, mathurinm, Matt
+Haberland, Max Halford, maximeSaur, Maxwell Liu, m. bou, mdarii, Meekail Zain,
+Mikhail Iljin, murezzda, Nawazish Alam, Nicola Fanelli, Nightwalkx, Nikolay
+Petrov, Nishu Choudhary, NNLNR, npache, Olivier Grisel, Omar Salman, ouss1508,
+PAB, Pandata, partev, Peter Piontek, Phil, pnucci, Pooja M, Pooja Subramaniam,
+precondition, Quentin Barthélemy, Rafal Wojdyla, Raghuveer Bhat, Rahil Parikh,
+Ralf Gommers, ram vikram singh, Rushil Desai, Sadra Barikbin, SANJAI_3, Sashka
+Warner, Scott Gigante, Scott Gustafson, searchforpassion, Seoeun
+Hong, Shady el Gewily, Shiva chauhan, Shogo Hida, Shreesha Kumar Bhat, sonnivs,
+Sortofamudkip, Stanislav (Stanley) Modrak, Stefanie Senger, Steven Van
+Vaerenbergh, Tabea Kossen, Théophile Baranger, Thijs van Weezel, Thomas A
+Caswell, Thomas Germer, Thomas J. Fan, Tim Head, Tim P, Tom Dupré la Tour,
+tomiock, tspeng, Valentin Laurent, Veghit, VIGNESH D, Vijeth Moudgalya, Vinayak
+Mehta, Vincent M, Vincent-violet, Vyom Pathak, William M, windiana42, Xiao
+Yuan, Yao Xiao, Yaroslav Halchenko, Yotam Avidar-Constantini, Yuchen Zhou,
+Yusuf Raji, zeeshan lone

doc/whats_new/v1.4.rst

@@ -58,3 +58,13 @@ TODO: update at the time of the release.
   :meth:`base.OutlierMixin.fit_predict` now accept ``**kwargs`` which are
   passed to the ``fit`` method of the the estimator. :pr:`26506` by `Adrin
   Jalali`_.
+
+:mod:`sklearn.decomposition`
+............................
+
+- |Enhancement| An "auto" option was added to the `n_components` parameter of
+  :func:`decomposition.non_negative_factorization`, :class:`decomposition.NMF` and
+  :class:`decomposition.MiniBatchNMF` to automatically infer the number of components from W or H shapes
+  when using a custom initialization. The default value of this parameter will change
+  from `None` to `auto` in version 1.6.
+  :pr:`26634` by :user:`Alexandre Landeau <AlexL>` and :user:`Alexandre Vigny <avigny>`.