From 7ab4cb3afa13d5d352c09ffcf77bdb9199d6d6df Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Mon, 25 Jul 2022 11:16:52 +0200
Subject: [PATCH 01/10] MAINT Make PairwiseDistancesReduction usable only for
 C-contiguous arrays

---
 sklearn/cluster/tests/test_birch.py               | 15 +++++++++++++++
 .../_pairwise_distances_reduction/_dispatcher.py  |  7 +++++++
 .../tests/test_pairwise_distances_reduction.py    |  3 +++
 3 files changed, 25 insertions(+)

diff --git a/sklearn/cluster/tests/test_birch.py b/sklearn/cluster/tests/test_birch.py
index 5de87136e367b..2ed482c6cd70d 100644
--- a/sklearn/cluster/tests/test_birch.py
+++ b/sklearn/cluster/tests/test_birch.py
@@ -248,3 +248,18 @@ def test_both_subclusters_updated():
 
     # no error
     Birch(branching_factor=5, threshold=1e-5, n_clusters=None).fit(X)
+
+
+def test_f_ordered_array():
+    """
+    Non-regression test for:
+    https://github.com/scikit-learn/scikit-learn/issues/23988
+    """
+    from sklearn.datasets import load_iris
+    from sklearn.cluster import Birch
+
+    X, y = load_iris(return_X_y=True, as_frame=True)
+    birch = Birch(n_clusters=3)
+
+    # Must not err.
+    birch.fit_predict(X)
diff --git a/sklearn/metrics/_pairwise_distances_reduction/_dispatcher.py b/sklearn/metrics/_pairwise_distances_reduction/_dispatcher.py
index a79fde694a9ed..1cf670ed35dec 100644
--- a/sklearn/metrics/_pairwise_distances_reduction/_dispatcher.py
+++ b/sklearn/metrics/_pairwise_distances_reduction/_dispatcher.py
@@ -80,11 +80,18 @@ def is_usable_for(cls, X, Y, metric) -> bool:
         True if the PairwiseDistancesReduction can be used, else False.
         """
         dtypes_validity = X.dtype == Y.dtype == np.float64
+        c_contiguity = (
+            hasattr(X, "flags")
+            and X.flags.c_contiguous
+            and hasattr(Y, "flags")
+            and Y.flags.c_contiguous
+        )
         return (
             get_config().get("enable_cython_pairwise_dist", True)
             and not issparse(X)
             and not issparse(Y)
             and dtypes_validity
+            and c_contiguity
             and metric in cls.valid_metrics()
         )
 
diff --git a/sklearn/metrics/tests/test_pairwise_distances_reduction.py b/sklearn/metrics/tests/test_pairwise_distances_reduction.py
index 0b9c6e6aad196..9bb55aedf4dd0 100644
--- a/sklearn/metrics/tests/test_pairwise_distances_reduction.py
+++ b/sklearn/metrics/tests/test_pairwise_distances_reduction.py
@@ -530,6 +530,9 @@ def test_pairwise_distances_reduction_is_usable_for():
     assert not PairwiseDistancesReduction.is_usable_for(csr_matrix(X), Y, metric)
     assert not PairwiseDistancesReduction.is_usable_for(X, csr_matrix(Y), metric)
 
+    # F-ordered arrays are not supported
+    assert not PairwiseDistancesReduction.is_usable_for(np.asfortranarray(X), Y, metric)
+
 
 def test_argkmin_factory_method_wrong_usages():
     rng = np.random.RandomState(1)

From 42b00cb56ca652c37af18bf75fc9aab10618df28 Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Mon, 25 Jul 2022 11:38:57 +0200
Subject: [PATCH 02/10] TST Adapt test to be pandas-independent

---
 sklearn/cluster/tests/test_birch.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/sklearn/cluster/tests/test_birch.py b/sklearn/cluster/tests/test_birch.py
index 2ed482c6cd70d..d0b3ae03b3c93 100644
--- a/sklearn/cluster/tests/test_birch.py
+++ b/sklearn/cluster/tests/test_birch.py
@@ -255,10 +255,9 @@ def test_f_ordered_array():
     Non-regression test for:
     https://github.com/scikit-learn/scikit-learn/issues/23988
     """
-    from sklearn.datasets import load_iris
-    from sklearn.cluster import Birch
+    X, _ = make_blobs(n_samples=80, n_features=4, random_state=0)
+    X = np.asfortranarray(X)
 
-    X, y = load_iris(return_X_y=True, as_frame=True)
     birch = Birch(n_clusters=3)
 
     # Must not err.

From 4505c39d1a9bebab7b3ba4766e8617d2a73fa5ea Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 10:44:32 +0200
Subject: [PATCH 03/10] TST Add tests for f-contiguous arrays support

and remove the old one
---
 sklearn/cluster/tests/test_birch.py | 14 -------
 sklearn/tests/test_common.py        | 57 +++++++++++++++++++++++++++++
 2 files changed, 57 insertions(+), 14 deletions(-)

diff --git a/sklearn/cluster/tests/test_birch.py b/sklearn/cluster/tests/test_birch.py
index d0b3ae03b3c93..5de87136e367b 100644
--- a/sklearn/cluster/tests/test_birch.py
+++ b/sklearn/cluster/tests/test_birch.py
@@ -248,17 +248,3 @@ def test_both_subclusters_updated():
 
     # no error
     Birch(branching_factor=5, threshold=1e-5, n_clusters=None).fit(X)
-
-
-def test_f_ordered_array():
-    """
-    Non-regression test for:
-    https://github.com/scikit-learn/scikit-learn/issues/23988
-    """
-    X, _ = make_blobs(n_samples=80, n_features=4, random_state=0)
-    X = np.asfortranarray(X)
-
-    birch = Birch(n_clusters=3)
-
-    # Must not err.
-    birch.fit_predict(X)
diff --git a/sklearn/tests/test_common.py b/sklearn/tests/test_common.py
index 17d22f78b7e12..cc87ba401ccc7 100644
--- a/sklearn/tests/test_common.py
+++ b/sklearn/tests/test_common.py
@@ -18,6 +18,24 @@
 import pytest
 import numpy as np
 
+from sklearn.cluster import (
+    AffinityPropagation,
+    Birch,
+    MeanShift,
+    OPTICS,
+    SpectralClustering,
+)
+from sklearn.datasets import make_blobs
+from sklearn.manifold import Isomap, TSNE, LocallyLinearEmbedding
+from sklearn.neighbors import (
+    LocalOutlierFactor,
+    KNeighborsClassifier,
+    KNeighborsRegressor,
+    RadiusNeighborsClassifier,
+    RadiusNeighborsRegressor,
+)
+from sklearn.semi_supervised import LabelPropagation, LabelSpreading
+
 from sklearn.utils import all_estimators
 from sklearn.utils._testing import ignore_warnings
 from sklearn.exceptions import ConvergenceWarning
@@ -541,3 +559,42 @@ def test_check_param_validation(estimator):
         )
     _set_checking_parameters(estimator)
     check_param_validation(name, estimator)
+
+
+@pytest.mark.parametrize(
+    "Estimator",
+    [
+        AffinityPropagation,
+        Birch,
+        MeanShift,
+        KNeighborsClassifier,
+        KNeighborsRegressor,
+        RadiusNeighborsClassifier,
+        RadiusNeighborsRegressor,
+        LabelPropagation,
+        LabelSpreading,
+        OPTICS,
+        SpectralClustering,
+        LocalOutlierFactor,
+        LocallyLinearEmbedding,
+        Isomap,
+        TSNE,
+    ],
+)
+def test_f_contiguous_array_estimator(Estimator):
+    # Non-regression test for:
+    # https://github.com/scikit-learn/scikit-learn/issues/23988
+    # https://github.com/scikit-learn/scikit-learn/issues/24013
+
+    X, _ = make_blobs(n_samples=80, n_features=4, random_state=0)
+    X = np.asfortranarray(X)
+    y = np.round(X[:, 0])
+
+    est = Estimator()
+    est.fit(X, y)
+
+    if hasattr(est, "transform"):
+        est.transform(X)
+
+    if hasattr(est, "predict"):
+        est.predict(X)

From f0dc170a4ca1f6794fe908020c398c28c386d330 Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 10:45:18 +0200
Subject: [PATCH 04/10] Convert f-contiguous array into c-contiguous arrays
 where appropriate

---
 sklearn/cluster/_affinity_propagation.py |  2 +-
 sklearn/cluster/_birch.py                |  3 ++-
 sklearn/cluster/_mean_shift.py           |  2 +-
 sklearn/metrics/pairwise.py              | 17 +++++++++++++++--
 sklearn/metrics/tests/test_pairwise.py   |  9 +++++++++
 5 files changed, 28 insertions(+), 5 deletions(-)

diff --git a/sklearn/cluster/_affinity_propagation.py b/sklearn/cluster/_affinity_propagation.py
index f0274b113a341..8030bee119c6f 100644
--- a/sklearn/cluster/_affinity_propagation.py
+++ b/sklearn/cluster/_affinity_propagation.py
@@ -516,7 +516,7 @@ def predict(self, X):
             Cluster labels.
         """
         check_is_fitted(self)
-        X = self._validate_data(X, reset=False, accept_sparse="csr")
+        X = self._validate_data(X, reset=False, accept_sparse="csr", order="C")
         if not hasattr(self, "cluster_centers_"):
             raise ValueError(
                 "Predict method is not supported when affinity='precomputed'."
diff --git a/sklearn/cluster/_birch.py b/sklearn/cluster/_birch.py
index 20a414d1ac56e..fd5be63144dec 100644
--- a/sklearn/cluster/_birch.py
+++ b/sklearn/cluster/_birch.py
@@ -554,6 +554,7 @@ def _fit(self, X, partial):
             copy=self.copy,
             reset=first_call,
             dtype=[np.float64, np.float32],
+            order="C",
         )
         threshold = self.threshold
         branching_factor = self.branching_factor
@@ -689,7 +690,7 @@ def predict(self, X):
             Labelled data.
         """
         check_is_fitted(self)
-        X = self._validate_data(X, accept_sparse="csr", reset=False)
+        X = self._validate_data(X, accept_sparse="csr", reset=False, order="C")
         return self._predict(X)
 
     def _predict(self, X):
diff --git a/sklearn/cluster/_mean_shift.py b/sklearn/cluster/_mean_shift.py
index 356386eef3db7..f080bb05d51dd 100644
--- a/sklearn/cluster/_mean_shift.py
+++ b/sklearn/cluster/_mean_shift.py
@@ -518,6 +518,6 @@ def predict(self, X):
             Index of the cluster each sample belongs to.
         """
         check_is_fitted(self)
-        X = self._validate_data(X, reset=False)
+        X = self._validate_data(X, reset=False, order="C")
         with config_context(assume_finite=True):
             return pairwise_distances_argmin(X, self.cluster_centers_)
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
index bcf01bc2925a3..d50e18b57ec34 100644
--- a/sklearn/metrics/pairwise.py
+++ b/sklearn/metrics/pairwise.py
@@ -69,6 +69,7 @@ def check_pairwise_arrays(
     accept_sparse="csr",
     force_all_finite=True,
     copy=False,
+    order=None,
 ):
     """Set X and Y appropriately and checks inputs.
 
@@ -127,6 +128,15 @@ def check_pairwise_arrays(
 
         .. versionadded:: 0.22
 
+    order : {'F', 'C'} or None, default=None
+        Whether the arrays will be forced to be fortran or c-style.
+        When order is None (default), then if copy=False, nothing is ensured
+        about the memory layout of the output array; otherwise (copy=True)
+        the memory layout of the returned array is kept as close as possible
+        to the original array.
+
+        ..versionadded:: 1.1.2
+
     Returns
     -------
     safe_X : {array-like, sparse matrix} of shape (n_samples_X, n_features)
@@ -150,6 +160,7 @@ def check_pairwise_arrays(
             copy=copy,
             force_all_finite=force_all_finite,
             estimator=estimator,
+            order=order,
         )
     else:
         X = check_array(
@@ -159,6 +170,7 @@ def check_pairwise_arrays(
             copy=copy,
             force_all_finite=force_all_finite,
             estimator=estimator,
+            order=order,
         )
         Y = check_array(
             Y,
@@ -167,6 +179,7 @@ def check_pairwise_arrays(
             copy=copy,
             force_all_finite=force_all_finite,
             estimator=estimator,
+            order=order,
         )
 
     if precomputed:
@@ -661,7 +674,7 @@ def pairwise_distances_argmin_min(
     pairwise_distances_argmin : Same as `pairwise_distances_argmin_min` but only
         returns the argmins.
     """
-    X, Y = check_pairwise_arrays(X, Y)
+    X, Y = check_pairwise_arrays(X, Y, order="C")
 
     if axis == 0:
         X, Y = Y, X
@@ -773,7 +786,7 @@ def pairwise_distances_argmin(X, Y, *, axis=1, metric="euclidean", metric_kwargs
     if metric_kwargs is None:
         metric_kwargs = {}
 
-    X, Y = check_pairwise_arrays(X, Y)
+    X, Y = check_pairwise_arrays(X, Y, order="C")
 
     if axis == 0:
         X, Y = Y, X
diff --git a/sklearn/metrics/tests/test_pairwise.py b/sklearn/metrics/tests/test_pairwise.py
index f14c558d5a3c1..a74db9a2fc316 100644
--- a/sklearn/metrics/tests/test_pairwise.py
+++ b/sklearn/metrics/tests/test_pairwise.py
@@ -534,6 +534,15 @@ def test_pairwise_distances_argmin_min(dtype):
 
     assert_array_equal(argmin_0, argmin_1)
 
+    # F-contiguous arrays must be supported and must return identical
+    # C-contiguous results.
+    argmin_C_contiguous = pairwise_distances_argmin(X, Y)
+    argmin_F_contiguous = pairwise_distances_argmin(
+        np.asfortranarray(X), np.asfortranarray(Y)
+    )
+
+    assert_array_equal(argmin_C_contiguous, argmin_F_contiguous)
+
 
 def _reduce_func(dist, start):
     return dist[:, :100]

From 4d88ed5fb5a28a254c5355d64b83a6168dd9d4d5 Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 10:48:30 +0200
Subject: [PATCH 05/10] DOC Add whats_new entry

---
 doc/whats_new/v1.1.rst | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/doc/whats_new/v1.1.rst b/doc/whats_new/v1.1.rst
index 4c46c0d631f76..adfb71eac065b 100644
--- a/doc/whats_new/v1.1.rst
+++ b/doc/whats_new/v1.1.rst
@@ -12,6 +12,10 @@ Version 1.1.2
 Changelog
 ---------
 
+- |Fix| Add support for F-contiguous arrays for estimators and functions whose back-end
+  have been changed in 1.1.
+  :pr:`23990` by :user:`Julien Jerphanion <jjerphan>`.
+
 :mod:`sklearn.cluster`
 ......................
 

From 819c4e5464928ba3b4ac95f5f8fae0a04fe573f6 Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 10:53:32 +0200
Subject: [PATCH 06/10] Trigger CI


From e65fbe9b26d0e83b24a7fbb042fe794fb21b4f2f Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 10:57:41 +0200
Subject: [PATCH 07/10] fixup! TST Add tests for f-contiguous arrays support

---
 sklearn/metrics/tests/test_pairwise.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/sklearn/metrics/tests/test_pairwise.py b/sklearn/metrics/tests/test_pairwise.py
index a74db9a2fc316..31964e2d182dd 100644
--- a/sklearn/metrics/tests/test_pairwise.py
+++ b/sklearn/metrics/tests/test_pairwise.py
@@ -534,8 +534,7 @@ def test_pairwise_distances_argmin_min(dtype):
 
     assert_array_equal(argmin_0, argmin_1)
 
-    # F-contiguous arrays must be supported and must return identical
-    # C-contiguous results.
+    # F-contiguous arrays must be supported and must return identical results.
     argmin_C_contiguous = pairwise_distances_argmin(X, Y)
     argmin_F_contiguous = pairwise_distances_argmin(
         np.asfortranarray(X), np.asfortranarray(Y)

From c77814d953f8860566cae6029cb4a537cada5069 Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 20:30:38 +0200
Subject: [PATCH 08/10] FIX Correct multitasking-mess

---
 doc/whats_new/v1.1.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/doc/whats_new/v1.1.rst b/doc/whats_new/v1.1.rst
index 56b470db0b45b..0cb0233fef038 100644
--- a/doc/whats_new/v1.1.rst
+++ b/doc/whats_new/v1.1.rst
@@ -13,7 +13,7 @@ Changelog
 ---------
 
 - |Fix| A default HTML representation is shown for meta-estimators with invalid
-  parameters. :pr:`24015` by `Thomas Fan`
+  parameters. :pr:`24015` by `Thomas Fan`_.
 
 - |Fix| Add support for F-contiguous arrays for estimators and functions whose back-end
   have been changed in 1.1.

From 83e33e0a0d65659235506454036a44b878a304cc Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Wed, 27 Jul 2022 20:51:20 +0200
Subject: [PATCH 09/10] TST Ignore FutureWarning

---
 sklearn/tests/test_common.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/sklearn/tests/test_common.py b/sklearn/tests/test_common.py
index ba127cc8a9b43..3cac700c73d69 100644
--- a/sklearn/tests/test_common.py
+++ b/sklearn/tests/test_common.py
@@ -548,6 +548,8 @@ def test_check_param_validation(estimator):
     check_param_validation(name, estimator)
 
 
+# TODO: remove this filter in 1.2
+@pytest.mark.filterwarnings("ignore::FutureWarning:sklearn")
 @pytest.mark.parametrize(
     "Estimator",
     [

From 576cc05b202871b9cb398da2bb2af53c9de951bc Mon Sep 17 00:00:00 2001
From: Julien Jerphanion <git@jjerphan.xyz>
Date: Thu, 28 Jul 2022 10:00:20 +0200
Subject: [PATCH 10/10] MAINT Fallback on previous backend for F-contiguous
 array

---
 sklearn/cluster/_affinity_propagation.py |  2 +-
 sklearn/cluster/_birch.py                |  3 +--
 sklearn/cluster/_mean_shift.py           |  2 +-
 sklearn/metrics/pairwise.py              | 17 ++---------------
 4 files changed, 5 insertions(+), 19 deletions(-)

diff --git a/sklearn/cluster/_affinity_propagation.py b/sklearn/cluster/_affinity_propagation.py
index d2089bb4bcd65..c577b2856d470 100644
--- a/sklearn/cluster/_affinity_propagation.py
+++ b/sklearn/cluster/_affinity_propagation.py
@@ -512,7 +512,7 @@ def predict(self, X):
             Cluster labels.
         """
         check_is_fitted(self)
-        X = self._validate_data(X, reset=False, accept_sparse="csr", order="C")
+        X = self._validate_data(X, reset=False, accept_sparse="csr")
         if not hasattr(self, "cluster_centers_"):
             raise ValueError(
                 "Predict method is not supported when affinity='precomputed'."
diff --git a/sklearn/cluster/_birch.py b/sklearn/cluster/_birch.py
index fd5be63144dec..20a414d1ac56e 100644
--- a/sklearn/cluster/_birch.py
+++ b/sklearn/cluster/_birch.py
@@ -554,7 +554,6 @@ def _fit(self, X, partial):
             copy=self.copy,
             reset=first_call,
             dtype=[np.float64, np.float32],
-            order="C",
         )
         threshold = self.threshold
         branching_factor = self.branching_factor
@@ -690,7 +689,7 @@ def predict(self, X):
             Labelled data.
         """
         check_is_fitted(self)
-        X = self._validate_data(X, accept_sparse="csr", reset=False, order="C")
+        X = self._validate_data(X, accept_sparse="csr", reset=False)
         return self._predict(X)
 
     def _predict(self, X):
diff --git a/sklearn/cluster/_mean_shift.py b/sklearn/cluster/_mean_shift.py
index f080bb05d51dd..356386eef3db7 100644
--- a/sklearn/cluster/_mean_shift.py
+++ b/sklearn/cluster/_mean_shift.py
@@ -518,6 +518,6 @@ def predict(self, X):
             Index of the cluster each sample belongs to.
         """
         check_is_fitted(self)
-        X = self._validate_data(X, reset=False, order="C")
+        X = self._validate_data(X, reset=False)
         with config_context(assume_finite=True):
             return pairwise_distances_argmin(X, self.cluster_centers_)
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
index d50e18b57ec34..bcf01bc2925a3 100644
--- a/sklearn/metrics/pairwise.py
+++ b/sklearn/metrics/pairwise.py
@@ -69,7 +69,6 @@ def check_pairwise_arrays(
     accept_sparse="csr",
     force_all_finite=True,
     copy=False,
-    order=None,
 ):
     """Set X and Y appropriately and checks inputs.
 
@@ -128,15 +127,6 @@ def check_pairwise_arrays(
 
         .. versionadded:: 0.22
 
-    order : {'F', 'C'} or None, default=None
-        Whether the arrays will be forced to be fortran or c-style.
-        When order is None (default), then if copy=False, nothing is ensured
-        about the memory layout of the output array; otherwise (copy=True)
-        the memory layout of the returned array is kept as close as possible
-        to the original array.
-
-        ..versionadded:: 1.1.2
-
     Returns
     -------
     safe_X : {array-like, sparse matrix} of shape (n_samples_X, n_features)
@@ -160,7 +150,6 @@ def check_pairwise_arrays(
             copy=copy,
             force_all_finite=force_all_finite,
             estimator=estimator,
-            order=order,
         )
     else:
         X = check_array(
@@ -170,7 +159,6 @@ def check_pairwise_arrays(
             copy=copy,
             force_all_finite=force_all_finite,
             estimator=estimator,
-            order=order,
         )
         Y = check_array(
             Y,
@@ -179,7 +167,6 @@ def check_pairwise_arrays(
             copy=copy,
             force_all_finite=force_all_finite,
             estimator=estimator,
-            order=order,
         )
 
     if precomputed:
@@ -674,7 +661,7 @@ def pairwise_distances_argmin_min(
     pairwise_distances_argmin : Same as `pairwise_distances_argmin_min` but only
         returns the argmins.
     """
-    X, Y = check_pairwise_arrays(X, Y, order="C")
+    X, Y = check_pairwise_arrays(X, Y)
 
     if axis == 0:
         X, Y = Y, X
@@ -786,7 +773,7 @@ def pairwise_distances_argmin(X, Y, *, axis=1, metric="euclidean", metric_kwargs
     if metric_kwargs is None:
         metric_kwargs = {}
 
-    X, Y = check_pairwise_arrays(X, Y, order="C")
+    X, Y = check_pairwise_arrays(X, Y)
 
     if axis == 0:
         X, Y = Y, X