MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` #26068

BabaYaga1221 · 2023-04-03T19:19:40Z

What does this implement/fix? Explain your changes.

Implements memoryviews instead of cnp.ndarray (as intended in #25484);

Any other comments?

Review the code for cnp.ndarray[dtype=floating] X to floating[::1] X. If declare const in change code, the variable cannot update the values afterward which could raise an error as the X need to be updated.

…rs.py

thomasjpfan

Thank you for the PR!

With the removal of cnp, we can remove cnp import and it's usage:

scikit-learn/sklearn/_isotonic.pyx

Lines 8 to 11 in 3d26e28

    
           cimport numpy as cnp 
        
           from cython cimport floating 
        
           cnp.import_array()

Also "include_np" is no longer required in the setup.py:

scikit-learn/setup.py

Line 199 in 3d26e28

{"sources": ["_isotonic.pyx"], "include_np": True},

thomasjpfan · 2023-04-04T18:18:33Z

sklearn/_isotonic.pyx

+def _make_unique(floating[::1] X,
+                 floating[::1] y,
+                 floating[::1] sample_weights):


From looking at the code, I do not think the input: X, y, and sample_weights are changed. They can be made const.

thomasjpfan · 2023-04-04T18:19:13Z

sklearn/preprocessing/_encoders.py

@@ -739,7 +741,7 @@ def __init__(
        drop=None,
        sparse="deprecated",
        sparse_output=True,
-        dtype=np.float64,
+        dtype=np.uint8,


Can you revert all the changes in _encoders.py? The change is not related to the title of this PR. (memoryviews + cnp.ndarray)

thomasjpfan · 2023-04-04T18:32:30Z

sklearn/_isotonic.pyx

@@ -75,10 +75,10 @@ def _make_unique(cnp.ndarray[dtype=floating] X,
    """
    unique_values = len(np.unique(X))

-    cdef cnp.ndarray[dtype=floating] y_out = np.empty(unique_values,
+    cdef floating[::1] y_out = np.empty(unique_values,


X.dtype is not avalible if X is a memoryview. One needs to get the dtype directly:

if floating is float: dtype = np.float32 else: dtype = np.float64 cdef floating[::1] y_out = np.empty(unique_values, dtype=dtype)

We also need to change the following:

scikit-learn/sklearn/_isotonic.pyx

Line 91 in 3d26e28

cdef floating eps = np.finfo(X.dtype).resolution

cdef floating eps = np.finfo(X.dtype).resolution
can you suggest what I need to change?
can I change to this - cdef floating eps = 1e-6

Use the newly defined dtype

cdef floating eps = np.finfo(dtype).resolution

thomasjpfan

Also the output of _make_unique needs to be NumPy arrays:

diff --git a/sklearn/_isotonic.pyx b/sklearn/_isotonic.pyx
index 7c2e974881..fa34042350 100644
--- a/sklearn/_isotonic.pyx
+++ b/sklearn/_isotonic.pyx
@@ -108,4 +108,8 @@ def _make_unique(floating[::1] X,
     x_out[i] = current_x
     weights_out[i] = current_weight
     y_out[i] = current_y / current_weight
-    return x_out[:i+1], y_out[:i+1], weights_out[:i+1]
+    return (
+        np.asarray(x_out[:i+1]),
+        np.asarray(y_out[:i+1]),
+        np.asarray(weights_out[:i+1])
+    )

BabaYaga1221 · 2023-04-04T19:04:25Z

@thomasjpfan update the changes as per suggested, Sir.

thomasjpfan · 2023-04-04T19:16:52Z

sklearn/preprocessing/_encoders.py

-                "Found unknown categories in columns "
-                f"{columns_with_unknown} during transform. These "
-                "unknown categories will be encoded as all zeros",
+                (


Can you revert this change too?

thomasjpfan · 2023-04-04T19:17:04Z

sklearn/preprocessing/_encoders.py

-                "`sparse` was renamed to `sparse_output` in version 1.2 and "
-                "will be removed in 1.4. `sparse_output` is ignored unless you "
-                "leave `sparse` to its default value.",
+                (


Same here regarding reverting.

okay sir , just a minute.

jjerphan

Thank you for finishing this series, @BabaYaga1221.

Here are a few comments. Let us know if you need to understand CI failures.

jjerphan · 2023-04-04T21:32:55Z

sklearn/_isotonic.pyx

+    return(
+        np.asarray(x_out[:i+1])
+        np.asarray(y_out[:i+1])
+        np.asarray(weights_out[:i+1]))


We need commas here.

Suggested change

return(

np.asarray(x_out[:i+1])

np.asarray(y_out[:i+1])

np.asarray(weights_out[:i+1]))

return (

np.asarray(x_out[:i+1]),

np.asarray(y_out[:i+1]),

np.asarray(weights_out[:i+1]),

)

sklearn/_isotonic.pyx

BabaYaga1221 · 2023-04-04T22:03:04Z

@jjerphan I change the code as per your suggestion. And, can you help me to understand CI failures.

thomasjpfan · 2023-04-05T14:58:36Z

sklearn/_isotonic.pyx

-def _make_unique(cnp.ndarray[dtype=floating] X,
-                 cnp.ndarray[dtype=floating] y,
-                 cnp.ndarray[dtype=floating] sample_weights):
+def _make_unique(const floating[:, ::1] X,


The input is 1d for _make_unique.

Suggested change

def _make_unique(const floating[:, ::1] X,

def _make_unique(const floating[:] X,

The input to _make_unique is reshape to be a 1d view:

scikit-learn/sklearn/isotonic.py

Lines 264 to 267 in de968ed

def _build_y(self, X, y, sample_weight, trim_duplicates=True):

"""Build the y_ IsotonicRegression."""

self._check_input_data_shape(X)

X = X.reshape(-1) # use 1d view

thomasjpfan · 2023-04-05T15:04:50Z

sklearn/_isotonic.pyx

+        dtype = np.float64
+
+    cdef floating[::1] y_out = np.empty(unique_values, dtype=dtype)
+


Suggested change

thomasjpfan · 2023-04-05T17:07:56Z

sklearn/_isotonic.pyx

-def _make_unique(cnp.ndarray[dtype=floating] X,
-                 cnp.ndarray[dtype=floating] y,
-                 cnp.ndarray[dtype=floating] sample_weights):
+def _make_unique(const floating[:] X,


I was a little too quick with the suggestion:

Suggested change

def _make_unique(const floating[:] X,

def _make_unique(const floating[::1] X,

The call-site uses integer indexing which makes a copy, which means X is contagious.

scikit-learn/sklearn/isotonic.py

Lines 279 to 281 in e2d1209

order = np.lexsort((y, X))

X, y, sample_weight = [array[order] for array in [X, y, sample_weight]]

unique_X, unique_y, unique_sample_weight = _make_unique(X, y, sample_weight)

…-learn

BabaYaga1221 · 2023-04-05T17:19:28Z

@thomasjpfan Change the code as per your suggestion, but, can you tell me about CI failuers.

thomasjpfan

Many of the previous CI errors can be reproduced locally. Please see the Contributing Guide about building scikit-learn and running the tests locally. This way you can test locally before pushing to GitHub.

That being said, with the latest commit in f547fd9 (#26068), the CI tests all passed.

LGTM

BabaYaga1221 · 2023-04-05T18:44:30Z

@thomasjpfan Thank you for your review. I will be very grateful if you merge my changes.

jjerphan

LGTM. Thank you, @BabaYaga1221!

BabaYaga1221 · 2023-04-06T08:55:17Z

@jjerphan @thomasjpfan I am glad to be a part of this project and I look forward to contributing more in the future. Please let me know if there are any tasks that I can help with.

…scikit-learn#26068)

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(scikit-learn#26029) * MAINT Parameters validation for sklearn.metrics.silhouette_score (scikit-learn#26054) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * FIX fix spelling mistake in _NumPyAPIWrapper (scikit-learn#26064) * CI ignore more non-library Python files in codecov (scikit-learn#26059) * MAINT Parameters validation for sklearn.metrics.pairwise.cosine_distances (scikit-learn#26046) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Introduce BinaryClassifierCurveDisplayMixin (scikit-learn#25969) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * ENH Forces shape to be tuple when using Array API's reshape (scikit-learn#26030) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Tim Head <betatim@gmail.com> * MAINT Parameters validation for sklearn.metrics.pairwise.paired_euclidean_distances (scikit-learn#26073) * MAINT Parameters 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jeremiedbb <jeremiedbb@yahoo.fr> * MAINT Parameters validation for sklearn.preprocessing.normalize (scikit-learn#26069) Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr> * MAINT Parameter validation for metrics.cluster.fowlkes_mallows_score (scikit-learn#26080) Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr> * MAINT Parameters validation for compose.make_column_transformer (scikit-learn#25897) Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr> * MAINT Parameters validation for sklearn.metrics.pairwise.polynomial_kernel (scikit-learn#26070) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.metrics.pairwise.rbf_kernel (scikit-learn#26071) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.metrics.pairwise.sigmoid_kernel (scikit-learn#26072) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Param validation: constraint for numeric missing values (scikit-learn#26085) * FIX Adds support for negative values in categorical features in gradient boosting (scikit-learn#25629) Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Tim Head <betatim@gmail.com> * MAINT Fix C warning in Cython module splitting.pyx (scikit-learn#26051) * MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` (scikit-learn#26068) * FIX Fixes memory regression for inspecting extension arrays (scikit-learn#26106) * PERF set openmp to use only physical cores by default (scikit-learn#26082) * MNT Update black to 23.3.0 (scikit-learn#26110) * MNT Adds black commit to git-blame-ignore-revs (scikit-learn#26111) * MAINT Parameters validation for sklearn.metrics.pair_confusion_matrix (scikit-learn#26107) * MAINT Parameters validation for sklearn.metrics.mean_poisson_deviance (scikit-learn#26104) * DOC Use notebook style in plot_lof_outlier_detection.py (scikit-learn#26017) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * MAINT utils._fast_dict uses types from utils._typedefs (scikit-learn#26025) * DOC remove sparse-matrix for `y` in ElasticNet (scikit-learn#26127) * ENH add exponential loss (scikit-learn#25965) * MAINT Parameters validation for sklearn.preprocessing.robust_scale (scikit-learn#26086) * MAINT Parameters validation for sklearn.datasets.fetch_rcv1 (scikit-learn#26126) * MAINT Parameters validation for sklearn.metrics.adjusted_rand_score (scikit-learn#26134) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.metrics.calinski_harabasz_score (scikit-learn#26135) * MAINT Parameters validation for sklearn.metrics.davies_bouldin_score (scikit-learn#26136) * MAINT: remove `from numpy.math cimport` statements (scikit-learn#26143) * MAINT Parameters validation for sklearn.inspection.permutation_importance (scikit-learn#26145) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.metrics.cluster.homogeneity_completeness_v_measure (scikit-learn#26137) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.metrics.rand_score (scikit-learn#26138) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * DOC update comment in metrics/tests/test_classification.py (scikit-learn#26150) * CI small cleanup of Cirrus CI test script (scikit-learn#26168) * MAINT remove deprecated is_categorical_dtype (scikit-learn#26156) * DOC Add skforecast to related projects page (scikit-learn#26133) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * FIX Keeps namedtuple's class when transform returns a tuple (scikit-learn#26121) * DOC corrected letter case for better readability in sklearn/metrics/_classification.py / (scikit-learn#26169) * MAINT Parameters validation for sklearn.preprocessing.power_transform (scikit-learn#26142) * FIX `roc_auc_score` now uses `y_prob` instead of `y_pred` (scikit-learn#26155) * MAINT Parameters validation for sklearn.datasets.load_iris (scikit-learn#26177) * MAINT Parameters validation for sklearn.datasets.load_diabetes (scikit-learn#26166) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.datasets.load_breast_cancer (scikit-learn#26165) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.metrics.cluster.entropy (scikit-learn#26162) * MAINT Parameters validation for sklearn.datasets.fetch_species_distributions (scikit-learn#26161) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * ASV Fix tol in SGDRegressorBenchmark (scikit-learn#26146) Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr> * MNT use api.openml.org URLs for fetch_openml (scikit-learn#26171) * MAINT Parameters validation for sklearn.utils.resample (scikit-learn#26139) * MAINT make it explicit that additive_chi2_kernel does not accept sparse matrix (scikit-learn#26178) * MNT fix circleci link in README.rst (scikit-learn#26183) * CI Fix circleci artifact redirector action (scikit-learn#26181) * GOV introduce rights for groups as discussed in SLEP019 (scikit-learn#25753) Co-authored-by: Julien <git@jjerphan.xyz> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * MAINT Parameters validation for sklearn.neighbors.sort_graph_by_row_values (scikit-learn#26173) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * FIX improve convergence criterion for LogisticRegression(penalty="l1", solver='liblinear') (scikit-learn#25214) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * MAINT Fix several typos in src and doc files (scikit-learn#26187) * PERF fix overhead of _rescale_data in LinearRegression (scikit-learn#26207) * ENH add Huber loss (scikit-learn#25966) * MAINT Refactor GraphicalLasso and graphical_lasso (scikit-learn#26033) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Cython linting (scikit-learn#25861) * DOC Add JupyterLite button in example gallery (scikit-learn#25887) * MAINT Parameters validation for sklearn.covariance.ledoit_wolf_shrinkage (scikit-learn#26200) * MAINT Parameters validation for sklearn.datasets.load_linnerud (scikit-learn#26199) * MAINT Parameters validation for sklearn.datasets.load_wine (scikit-learn#26196) * DOC Added redirect to Provost paper + minor refactor (scikit-learn#26223) * MAINT Parameter Validation for `covariance.graphical_lasso` (scikit-learn#25053) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.datasets.load_digits (scikit-learn#26195) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.preprocessing.quantile_transform (scikit-learn#26144) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.model_selection.cross_validate (scikit-learn#26129) Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr> * DOC Adds TargetEncoder example explaining the internal CV (scikit-learn#26185) Co-authored-by: Tim Head <betatim@gmail.com> * spelling mistake corrected in documentation for script `plot_document_clustering.py` (scikit-learn#26228) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * FIX possible UnboundLocalError in fetch_openml (scikit-learn#26236) * ENH Adds PyTorch support to LinearDiscriminantAnalysis (scikit-learn#25956) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Tim Head <betatim@gmail.com> * MNT Use fixed version of Pyodide (scikit-learn#26247) * MNT Reset transform_output default in example to fix doc build build (scikit-learn#26269) * DOC Update example plot_nearest_centroid.py (scikit-learn#26263) * MNT reduce JupyterLite build size (scikit-learn#26246) * DOC term -> meth in GradientBoosting (scikit-learn#26225) * MNT speed-up html-noplot build (scikit-learn#26245) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * MNT Use copy=False when creating DataFrames (scikit-learn#26272) * MAINT Parameters validation for sklearn.model_selection.permutation_test_score (scikit-learn#26230) * MAINT Parameters validation for sklearn.datasets.clear_data_home (scikit-learn#26259) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.datasets.load_files (scikit-learn#26203) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.datasets.get_data_home (scikit-learn#26260) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * DOC Fix y-axis plot labels in permutation test score example (scikit-learn#26240) * MAINT cython-lint ignores asv_benchmarks (scikit-learn#26282) * MAINT Parameter validation for metrics.cluster._supervised (scikit-learn#26258) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * DOC Improve docstring for tol in SequentialFeatureSelector (scikit-learn#26271) * MAINT Parameters validation for sklearn.datasets.load_sample_image (scikit-learn#26226) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * DOC Consistent param type for pos_label (scikit-learn#26237) * DOC Minor grammar fix to imputation docs (scikit-learn#26283) * MAINT Parameters validation for sklearn.calibration.calibration_curve (scikit-learn#26198) Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr> * MAINT Parameters validation for sklearn.inspection.partial_dependence (scikit-learn#26209) Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr> * MAINT Parameters validation for sklearn.model_selection.validation_curve (scikit-learn#26229) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MAINT Parameters validation for sklearn.model_selection.learning_curve (scikit-learn#26227) Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr> * MNT Remove deprecated pandas.api.types.is_sparse (scikit-learn#26287) * CI Use Trusted Publishers for uploading wheels to PyPI (scikit-learn#26249) * MAINT Parameters validation for sklearn.metrics.pairwise.manhattan_distances (scikit-learn#26122) * PERF revert openmp use in csr_row_norms (scikit-learn#26275) * MAINT Parameters validation for metrics.check_scoring (scikit-learn#26041) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> * MNT Improve error message when checking classification target is of a non-regression type (scikit-learn#26281) Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * DOC fix link to User Guide encoder_infrequent_categories (scikit-learn#26309) * MNT remove unused args in _predict_regression_tree_inplace_fast_dense (scikit-learn#26314) * ENH Adds missing value support for trees (scikit-learn#23595) Co-authored-by: Tim Head <betatim@gmail.com> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> * CLN Clean up logic in validate_data and cast_to_ndarray (scikit-learn#26300) * MAINT refactor scorer using _get_response_values (scikit-learn#26037) Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com> * DOC Add HGBDT to "see also" section of random forests (scikit-learn#26319) Co-authored-by: ArturoAmorQ <arturo.amor-quiroz@polytechnique.edu> Co-authored-by: Tim Head <betatim@gmail.com> * MNT Bump Github Action labeler version to use newer Node (scikit-learn#26302) * FIX thresholds should not exceed 1.0 with probabilities in `roc_curve` (scikit-learn#26194) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * ENH Allow for appropriate dtype us in `preprocessing.PolynomialFeatures` for sparse matrices (scikit-learn#23731) Co-authored-by: Aleksandr Kokhaniukov <alexander.kohanyukov@gmail.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> * DOC Fix minor typo (scikit-learn#26327) * MAINT bump minimum version for pytest (scikit-learn#26184) Co-authored-by: Loïc Estève <loic.esteve@ymail.com> Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> * DOC fix return type in isotonic_regression (scikit-learn#26332) * FIX fix available_if for MultiOutputRegressor.partial_fit (scikit-learn#26333) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> * FIX make pipeline pass check_estimator (scikit-learn#26325) * FEA Add multiclass support to `average_precision_score` (scikit-learn#24769) Co-authored-by: Geoffrey <geoffrey.bolmier@gmail.com> Co-authored-by: gbolmier <geoffrey.bolmier@volvocars.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> --------- Signed-off-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Meekail Zain <34613774+Micky774@users.noreply.github.com> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: zeeshan lone <56621467+still-learning-ev@users.noreply.github.com> Co-authored-by: jeremiedbb <jeremiedbb@yahoo.fr> Co-authored-by: Adrin Jalali <adrin.jalali@gmail.com> Co-authored-by: Shiva chauhan <103742975+Shivachauhan17@users.noreply.github.com> Co-authored-by: AymericBasset <45051041+AymericBasset@users.noreply.github.com> Co-authored-by: Maren Westermann <maren.westermann@gmail.com> Co-authored-by: Nishu Choudhary <51842539+choudharynishu@users.noreply.github.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com> Co-authored-by: Loïc Estève <loic.esteve@ymail.com> Co-authored-by: Benedek Harsanyi <80836204+hbenedek@users.noreply.github.com> Co-authored-by: Pooja Subramaniam <poojas2086@gmail.com> Co-authored-by: Rushil Desai <rushildesai01@gmail.com> Co-authored-by: Xiao Yuan <yuanx749@gmail.com> Co-authored-by: Omar Salman <omar.salman@arbisoft.com> Co-authored-by: 2357juan <29247195+2357juan@users.noreply.github.com> Co-authored-by: Théophile Baranger <39696928+tbaranger@users.noreply.github.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> Co-authored-by: Andreas Mueller <t3kcit@gmail.com> Co-authored-by: Jovan Stojanovic <62058944+jovan-stojanovic@users.noreply.github.com> Co-authored-by: Rahil Parikh <75483881+rprkh@users.noreply.github.com> Co-authored-by: Bharat Raghunathan <bharatraghunthan9767@gmail.com> Co-authored-by: Sortofamudkip <wishyutp0328@gmail.com> Co-authored-by: Gleb Levitski <36483986+glevv@users.noreply.github.com> Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com> Co-authored-by: Ashwin Mathur <97467100+awinml@users.noreply.github.com> Co-authored-by: Sahil Gupta <sahil@Sahils-MBP.lan> Co-authored-by: Veghit <itay.vegh@gmail.com> Co-authored-by: Itay <itayvegh@gmail.com> Co-authored-by: precondition <57645186+precondition@users.noreply.github.com> Co-authored-by: Marc Torrellas Socastro <marc.torsoc@gmail.com> Co-authored-by: Dominic Fox <dominicjfox2@gmail.com> Co-authored-by: futurewarning <36329275+futurewarning@users.noreply.github.com> Co-authored-by: Yao Xiao <108576690+Charlie-XIAO@users.noreply.github.com> Co-authored-by: Joey Ortiz <orangesherbet0@gmail.com> Co-authored-by: Tim Head <betatim@gmail.com> Co-authored-by: Christian Veenhuis <veenhuis@gmail.com> Co-authored-by: adienes <51664769+adienes@users.noreply.github.com> Co-authored-by: Dave Berenbaum <dave.berenbaum@gmail.com> Co-authored-by: Lene Preuss <lene.preuss@gmail.com> Co-authored-by: A.H.Mansouri <83764851+A-H-Mansoury@users.noreply.github.com> Co-authored-by: Boris Feld <lothiraldan@gmail.com> Co-authored-by: Carla J <ca.jancik@gmail.com> Co-authored-by: windiana42 <61181806+windiana42@users.noreply.github.com> Co-authored-by: mdarii <dariimaxim@gmail.com> Co-authored-by: murezzda <47388020+murezzda@users.noreply.github.com> Co-authored-by: Peter Piontek <piontek0@gmail.com> Co-authored-by: John Pangas <swiftyxswaggy@outlook.com> Co-authored-by: Dmitry Nesterov <76070534+dmitrylala@users.noreply.github.com> Co-authored-by: Yuchen Zhou <72342196+ROMEEZHOU@users.noreply.github.com> Co-authored-by: Ekaterina Butyugina <102963496+ekaterinabutyugina@users.noreply.github.com> Co-authored-by: Jiawei Zhang <jiawei.zhang@nyu.edu> Co-authored-by: Ansam Zedan <86729068+ansamz@users.noreply.github.com> Co-authored-by: genvalen <genvalen@protonmail.com> Co-authored-by: farhan khan <86480450+BabaYaga1221@users.noreply.github.com> Co-authored-by: Arturo Amor <86408019+ArturoAmorQ@users.noreply.github.com> Co-authored-by: Jiawei Zhang <jz4721@nyu.edu> Co-authored-by: Ralf Gommers <ralf.gommers@gmail.com> Co-authored-by: Jessicakk0711 <106110789+Jessicakk0711@users.noreply.github.com> Co-authored-by: Ankur Singh <singankur28@gmail.com> Co-authored-by: Seoeun(Sun☀️) Hong <75988952+seoeunHong@users.noreply.github.com> Co-authored-by: Nightwalkx <74856680+xi-jiajun@users.noreply.github.com> Co-authored-by: VIGNESH D <35656793+dvignesh1995@users.noreply.github.com> Co-authored-by: Vincent-violet <130581473+Vincent-violet@users.noreply.github.com> Co-authored-by: Elabonga Atuo <elabongaatuo@gmail.com> Co-authored-by: Tom Dupré la Tour <tom.dupre-la-tour@m4x.org> Co-authored-by: André Pedersen <andrped94@gmail.com> Co-authored-by: Ashish Dutt <ashish.dutt8@gmail.com> Co-authored-by: Phil <philsupertramp@users.noreply.github.com> Co-authored-by: Stanislav (Stanley) Modrak <44023416+smith558@users.noreply.github.com> Co-authored-by: hujiahong726 <52920842+hujiahong726@users.noreply.github.com> Co-authored-by: James Dean <24254612+AcylSilane@users.noreply.github.com> Co-authored-by: ArturoAmorQ <arturo.amor-quiroz@polytechnique.edu> Co-authored-by: Aleksandr Kokhaniukov <alexander.kohanyukov@gmail.com> Co-authored-by: c-git <43485962+c-git@users.noreply.github.com> Co-authored-by: annegnx <64203599+annegnx@users.noreply.github.com> Co-authored-by: Geoffrey <geoffrey.bolmier@gmail.com> Co-authored-by: gbolmier <geoffrey.bolmier@volvocars.com>

replacing cnp.ndarrays with memoryviews

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github-actions bot added the cython label Apr 3, 2023

BabaYaga1221 changed the title ~~Update scikit learn~~ Implements memoryviews instead of cnp.ndarray (as intended in #25484) Apr 3, 2023

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MAINT Improve scikit-learn reliability by replacing cnp.ndarrays with typed memoryviews #25484

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Changing np.float64 to np.uint8 in file sklearn\preprocessing\_encode…

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Use np.uint8 as default dtype for OneHotEncoder instead of np.float64 #26063

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thomasjpfan changed the title ~~Implements memoryviews instead of cnp.ndarray (as intended in #25484)~~ MNT Updates _isotonic.pyx to use memoryviews instead of cnp.ndarray Apr 4, 2023

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replaced cnp.ndarrays with typed memory views #26087

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changes as per suggested

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reverting changes for _endcoder.py file

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changing the code as per suggestion

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changing the code as per suggestion

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remove line 82

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Merge https://github.com/scikit-learn/scikit-learn into update-scikit…

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revert the changes in _isotonic.pyx as per suggestion

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Merge branch 'main' into update-scikit-learn

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jjerphan merged commit 10eaa52 into scikit-learn:main Apr 6, 2023

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MNT Updates _isotonic.pyx to use memoryviews instead of cnp.ndarray (…

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…scikit-learn#26068)

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MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` #26068

MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` #26068

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	cimport numpy as cnp
	from cython cimport floating

	cnp.import_array()

	def _make_unique(const floating[:, ::1] X,
	def _make_unique(const floating[:] X,

	def _build_y(self, X, y, sample_weight, trim_duplicates=True):
	"""Build the y_ IsotonicRegression."""
	self._check_input_data_shape(X)
	X = X.reshape(-1) # use 1d view

		dtype = np.float64

		cdef floating[::1] y_out = np.empty(unique_values, dtype=dtype)

	def _make_unique(const floating[:] X,
	def _make_unique(const floating[::1] X,

	order = np.lexsort((y, X))
	X, y, sample_weight = [array[order] for array in [X, y, sample_weight]]
	unique_X, unique_y, unique_sample_weight = _make_unique(X, y, sample_weight)

MNT Updates _isotonic.pyx to use memoryviews instead of cnp.ndarray #26068

MNT Updates _isotonic.pyx to use memoryviews instead of cnp.ndarray #26068

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BabaYaga1221 commented Apr 3, 2023

What does this implement/fix? Explain your changes.

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BabaYaga1221 Apr 4, 2023 • edited Loading

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BabaYaga1221 commented Apr 4, 2023

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BabaYaga1221 commented Apr 4, 2023

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BabaYaga1221 commented Apr 5, 2023

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BabaYaga1221 commented Apr 5, 2023 • edited Loading

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BabaYaga1221 commented Apr 6, 2023

MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` #26068

MNT Updates _isotonic.pyx to use memoryviews instead of `cnp.ndarray` #26068

BabaYaga1221 Apr 4, 2023 •

edited

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BabaYaga1221 commented Apr 5, 2023 •

edited

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