Updates with issue #21088

puhuk · puhuk · commit fa7327b94ca9 · 2021-10-07T01:37:37.000+09:00
diff --git a/doc/about.rst b/doc/about.rst
@@ -85,8 +85,8 @@ citations to the following paper:
 If you want to cite scikit-learn for its API or design, you may also want to consider the
 following paper:
 
-  `API design for machine learning software: experiences from the scikit-learn
-  project <:arxiv:`1309.0238`>`_, Buitinck *et al.*, 2013.
+  API design for machine learning software: experiences from the scikit-learn
+  project, Buitinck *et al.*, 2013. :arxiv:`1309.0238`
 
   Bibtex entry::
 
diff --git a/doc/conf.py b/doc/conf.py
@@ -48,6 +48,7 @@
     "add_toctree_functions",
     "sphinx-prompt",
     "sphinxext.opengraph",
+    "doi_role",
 ]
 
 # Support for `plot::` directives in sphinx 3.2 requires matplotlib 3.1.0 or newer
diff --git a/doc/modules/clustering.rst b/doc/modules/clustering.rst
@@ -544,10 +544,9 @@ graph, and SpectralClustering is initialized with `affinity='precomputed'`::
    <http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.19.8100>`_
    Andrew Y. Ng, Michael I. Jordan, Yair Weiss, 2001
 
- * `"Preconditioned Spectral Clustering for Stochastic
+ * "Preconditioned Spectral Clustering for Stochastic
    Block Partition Streaming Graph Challenge"
-   <:arxiv:`1708.07481`>`_
-   David Zhuzhunashvili, Andrew Knyazev
+   David Zhuzhunashvili, Andrew Knyazev :arxiv:`1708.07481`
 
 .. _hierarchical_clustering:
 
@@ -1705,7 +1704,7 @@ cluster analysis.
  * Peter J. Rousseeuw (1987). "Silhouettes: a Graphical Aid to the
    Interpretation and Validation of Cluster Analysis". Computational
    and Applied Mathematics 20: 53–65.
-   `doi:10.1016/0377-0427(87)90125-7 <:doi:`10.1016/0377-0427(87)90125-7`>`_.
+   :doi:`10.1016/0377-0427(87)90125-7`
 
 
 Advantages
@@ -1805,7 +1804,7 @@ number of points in cluster :math:`q`.
    `"A Dendrite Method for Cluster Analysis"
    <https://www.researchgate.net/publication/233096619_A_Dendrite_Method_for_Cluster_Analysis>`_.
    Communications in Statistics-theory and Methods 3: 1-27.
-   `doi:10.1080/03610927408827101 <:doi:`10.1080/03610927408827101`>`_.
+   :doi:`10.1080/03610927408827101`
 
 
 .. _davies-bouldin_index:
@@ -1882,12 +1881,12 @@ Then the Davies-Bouldin index is defined as:
    "A Cluster Separation Measure"
    IEEE Transactions on Pattern Analysis and Machine Intelligence.
    PAMI-1 (2): 224-227.
-   `doi:10.1109/TPAMI.1979.4766909 <:doi:`10.1109/TPAMI.1979.4766909`>`_.
+   :doi:`10.1109/TPAMI.1979.4766909`
 
  * Halkidi, Maria; Batistakis, Yannis; Vazirgiannis, Michalis (2001).
    "On Clustering Validation Techniques"
    Journal of Intelligent Information Systems, 17(2-3), 107-145.
-   `doi:10.1023/A:1012801612483 <:doi:`10.1023/A:1012801612483`>`_.
+   :doi:`10.1023/A:1012801612483`
 
  * `Wikipedia entry for Davies-Bouldin index
    <https://en.wikipedia.org/wiki/Davies–Bouldin_index>`_.
diff --git a/doc/modules/decomposition.rst b/doc/modules/decomposition.rst
@@ -341,13 +341,13 @@ components is less than 10 (strict) and the number of samples is more than 200
 
     * *randomized* solver:
 
-        - Algorithm 4.3 in
+        * Algorithm 4.3 in
           `"Finding structure with randomness: Stochastic algorithms for
           constructing approximate matrix decompositions"
-          <:arxiv:`0909.4061`>`_
+          <https://arxiv.org/abs/0909.4061>`_
           Halko, et al., 2009
 
-        - `"An implementation of a randomized algorithm for principal component
+        * `"An implementation of a randomized algorithm for principal component
           analysis"
           <https://arxiv.org/pdf/1412.3510.pdf>`_
           A. Szlam et al. 2014
diff --git a/doc/modules/ensemble.rst b/doc/modules/ensemble.rst
@@ -1210,8 +1210,8 @@ Finally, many parts of the implementation of
      <https://statweb.stanford.edu/~jhf/ftp/stobst.pdf>`_
   .. [R2007] G. Ridgeway, "Generalized Boosted Models: A guide to the gbm
      package", 2007
-  .. [XGBoost] Tianqi Chen, Carlos Guestrin, `"XGBoost: A Scalable Tree
-     Boosting System" <:arxiv:`1603.02754`>`_
+  .. [XGBoost] Tianqi Chen, Carlos Guestrin, "XGBoost: A Scalable Tree
+     Boosting System" :arxiv:`1603.02754`
   .. [LightGBM] Ke et. al. `"LightGBM: A Highly Efficient Gradient
      BoostingDecision Tree" <https://papers.nips.cc/paper/
      6907-lightgbm-a-highly-efficient-gradient-boosting-decision-tree>`_
diff --git a/doc/modules/grid_search.rst b/doc/modules/grid_search.rst
@@ -538,9 +538,8 @@ since it has reached the last iteration (3) with the highest score:
        Optimization <http://proceedings.mlr.press/v51/jamieson16.html>`_, in
        proc. of Machine Learning Research, 2016.
     .. [2] L. Li, K. Jamieson, G. DeSalvo, A. Rostamizadeh, A. Talwalkar,
-       `Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
-       <:arxiv:`1603.06560`>`_, in Machine Learning Research
-       18, 2018.
+       Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
+       , in Machine Learning Research 18, 2018. :arxiv:`1603.06560`
 
 .. _grid_search_tips:
 
diff --git a/doc/modules/kernel_approximation.rst b/doc/modules/kernel_approximation.rst
@@ -246,8 +246,8 @@ or store training examples.
     .. [VVZ2010] `"Generalized RBF feature maps for Efficient Detection"
       <https://www.robots.ox.ac.uk/~vgg/publications/2010/Sreekanth10/sreekanth10.pdf>`_
       Vempati, S. and Vedaldi, A. and Zisserman, A. and Jawahar, CV - 2010
-    .. [PP2013] `"Fast and scalable polynomial kernels via explicit feature maps"
-      <:doi:`10.1145/2487575.2487591>`_
+    .. [PP2013] "Fast and scalable polynomial kernels via explicit feature maps"
+      :doi:`10.1145/2487575.2487591`
       Pham, N., & Pagh, R. - 2013
     .. [CCF2002] `"Finding frequent items in data streams"
       <http://www.cs.princeton.edu/courses/archive/spring04/cos598B/bib/CharikarCF.pdf>`_
diff --git a/doc/modules/linear_model.rst b/doc/modules/linear_model.rst
@@ -934,7 +934,7 @@ to warm-starting (see :term:`Glossary <warm_start>`).
 
     .. [6] Mark Schmidt, Nicolas Le Roux, and Francis Bach: `Minimizing Finite Sums with the Stochastic Average Gradient. <https://hal.inria.fr/hal-00860051/document>`_
 
-    .. [7] Aaron Defazio, Francis Bach, Simon Lacoste-Julien: `SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. <:arxiv:`1407.0202`>`_
+    .. [7] Aaron Defazio, Francis Bach, Simon Lacoste-Julien: SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. :arxiv:`1407.0202`
 
     .. [8] https://en.wikipedia.org/wiki/Broyden%E2%80%93Fletcher%E2%80%93Goldfarb%E2%80%93Shanno_algorithm
 
diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
@@ -563,8 +563,8 @@ or *informedness*.
      Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples,
      and Case Studies <https://mitpress.mit.edu/books/fundamentals-machine-learning-predictive-data-analytics>`_,
      2015.
-  .. [Urbanowicz2015] Urbanowicz R.J.,  Moore, J.H. `ExSTraCS 2.0: description and evaluation of a scalable learning
-     classifier system <:doi:`10.1007/s12065-015-0128-8`>`_, Evol. Intel. (2015) 8: 89.
+  .. [Urbanowicz2015] Urbanowicz R.J.,  Moore, J.H. ExSTraCS 2.0: description and evaluation of a scalable learning
+     classifier system :doi:`10.1007/s12065-015-0128-8`, Evol. Intel. (2015) 8: 89.
 
 .. _cohen_kappa:
 
diff --git a/doc/modules/neural_networks_supervised.rst b/doc/modules/neural_networks_supervised.rst
@@ -184,7 +184,7 @@ Algorithms
 
 MLP trains using `Stochastic Gradient Descent
 <https://en.wikipedia.org/wiki/Stochastic_gradient_descent>`_,
-`Adam <:arxiv:`1412.6980`>`_, or
+Adam :arxiv:`1412.6980`, or
 `L-BFGS <https://en.wikipedia.org/wiki/Limited-memory_BFGS>`__.
 Stochastic Gradient Descent (SGD) updates parameters using the gradient of the
 loss function with respect to a parameter that needs adaptation, i.e.
diff --git a/doc/modules/partial_dependence.rst b/doc/modules/partial_dependence.rst
@@ -262,8 +262,8 @@ estimators that support it, and 'brute' is used for the rest.
     C. Molnar, `Interpretable Machine Learning
     <https://christophm.github.io/interpretable-ml-book/>`_, Section 5.1, 2019.
 
-    A. Goldstein, A. Kapelner, J. Bleich, and E. Pitkin, `Peeking Inside the
+    A. Goldstein, A. Kapelner, J. Bleich, and E. Pitkin, Peeking Inside the
     Black Box: Visualizing Statistical Learning With Plots of Individual
-    Conditional Expectation <:arxiv:`1309.6392`>`_,
+    Conditional Expectation :arxiv:`1309.6392`,
     Journal of Computational and Graphical Statistics, 24(1): 44-65, Springer,
     2015.
diff --git a/doc/modules/preprocessing.rst b/doc/modules/preprocessing.rst
@@ -979,12 +979,11 @@ Interestingly, a :class:`SplineTransformer` of ``degree=0`` is the same as
 
     * Eilers, P., & Marx, B. (1996). Flexible Smoothing with B-splines and
       Penalties. Statist. Sci. 11 (1996), no. 2, 89--121.
-      `doi:10.1214/ss/1038425655 <:doi:`10.1214/ss/1038425655`>`_
+      :doi:`10.1214/ss/1038425655`
 
     * Perperoglou, A., Sauerbrei, W., Abrahamowicz, M. et al. A review of
       spline function procedures in R. BMC Med Res Methodol 19, 46 (2019).
-      `doi:10.1186/s12874-019-0666-3
-      <:doi:`10.1186/s12874-019-0666-3`>`_
+      :doi:`10.1186/s12874-019-0666-3`
 
 .. _function_transformer:
 
diff --git a/doc/sphinxext/doi_role.py b/doc/sphinxext/doi_role.py
@@ -0,0 +1,52 @@
+# -*- coding: utf-8 -*-
+"""
+    doilinks
+    ~~~~~~~~
+    Extension to add links to DOIs. With this extension you can use e.g.
+    :doi:`10.1016/S0022-2836(05)80360-2` in your documents. This will
+    create a link to a DOI resolver
+    (``https://doi.org/10.1016/S0022-2836(05)80360-2``).
+    The link caption will be the raw DOI.
+    You can also give an explicit caption, e.g.
+    :doi:`Basic local alignment search tool <10.1016/S0022-2836(05)80360-2>`.
+
+    :copyright: Copyright 2015  Jon Lund Steffensen. Based on extlinks by
+        the Sphinx team.
+    :license: BSD.
+"""
+
+from docutils import nodes, utils
+
+from sphinx.util.nodes import split_explicit_title
+
+
+def doi_role(typ, rawtext, text, lineno, inliner, options={}, content=[]):
+    text = utils.unescape(text)
+    has_explicit_title, title, part = split_explicit_title(text)
+    full_url = 'https://doi.org/' + part
+    if not has_explicit_title:
+        title = 'DOI:' + part
+    pnode = nodes.reference(title, title, internal=False, refuri=full_url)
+    return [pnode], []
+
+
+def arxiv_role(typ, rawtext, text, lineno, inliner, options={}, content=[]):
+    text = utils.unescape(text)
+    has_explicit_title, title, part = split_explicit_title(text)
+    full_url = 'https://arxiv.org/abs/' + part
+    if not has_explicit_title:
+        title = 'arXiv:' + part
+    pnode = nodes.reference(title, title, internal=False, refuri=full_url)
+    return [pnode], []
+
+
+def setup_link_role(app):
+    app.add_role('doi', doi_role, override=True)
+    app.add_role('DOI', doi_role, override=True)
+    app.add_role('arXiv', arxiv_role, override=True)
+    app.add_role('arxiv', arxiv_role, override=True)
+
+
+def setup(app):
+    app.connect('builder-inited', setup_link_role)
+    return {'version': '0.1', 'parallel_read_safe': True}

Original file line number	Diff line number	Diff line change
`@@ -48,6 +48,7 @@`
`48`	`48`	`"add_toctree_functions",`
`49`	`49`	`"sphinx-prompt",`
`50`	`50`	`"sphinxext.opengraph",`
	`51`	`+ "doi_role",`
`51`	`52`	`]`
`52`	`53`
`53`	`54`	# Support for `plot::` directives in sphinx 3.2 requires matplotlib 3.1.0 or newer