diff --git a/pkgs/development/python-modules/mlxtend/0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch b/pkgs/development/python-modules/mlxtend/0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch new file mode 100644 index 000000000000..2d807ef2c2e0 --- /dev/null +++ b/pkgs/development/python-modules/mlxtend/0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch @@ -0,0 +1,80 @@ +From 1fb59eb42f4bef229b953de313c7e78f0857ea42 Mon Sep 17 00:00:00 2001 +From: Philip Wilk +Date: Sun, 23 Mar 2025 16:14:51 +0000 +Subject: [PATCH] StackingCVClassifier/fit: ensure compatibility with + *scikit-learn* versions 1.4 and above by dynamically selecting between + `fit_params` and `params` + +--- + mlxtend/classifier/stacking_cv_classification.py | 5 ++++- + mlxtend/regressor/stacking_cv_regression.py | 6 +++++- + 2 files changed, 9 insertions(+), 2 deletions(-) + +diff --git a/mlxtend/classifier/stacking_cv_classification.py b/mlxtend/classifier/stacking_cv_classification.py +index 5bff6907..f4c45b8c 100644 +--- a/mlxtend/classifier/stacking_cv_classification.py ++++ b/mlxtend/classifier/stacking_cv_classification.py +@@ -15,6 +15,7 @@ from sklearn.base import TransformerMixin, clone + from sklearn.model_selection import cross_val_predict + from sklearn.model_selection._split import check_cv + from sklearn.preprocessing import LabelEncoder ++from sklearn import __version__ as sklearn_version + + from ..externals.estimator_checks import check_is_fitted + from ..externals.name_estimators import _name_estimators +@@ -266,6 +267,8 @@ class StackingCVClassifier( + if self.verbose > 1: + print(_name_estimators((model,))[0][1]) + ++ param_name = "fit_params" if sklearn_version < "1.4" else "params" ++ + prediction = cross_val_predict( + model, + X, +@@ -273,10 +276,10 @@ class StackingCVClassifier( + groups=groups, + cv=final_cv, + n_jobs=self.n_jobs, +- fit_params=fit_params, + verbose=self.verbose, + pre_dispatch=self.pre_dispatch, + method="predict_proba" if self.use_probas else "predict", ++ **{param_name: fit_params}, + ) + + if not self.use_probas: +diff --git a/mlxtend/regressor/stacking_cv_regression.py b/mlxtend/regressor/stacking_cv_regression.py +index a1faf2ff..d2fb1c49 100644 +--- a/mlxtend/regressor/stacking_cv_regression.py ++++ b/mlxtend/regressor/stacking_cv_regression.py +@@ -19,6 +19,7 @@ from sklearn.base import RegressorMixin, TransformerMixin, clone + from sklearn.model_selection import cross_val_predict + from sklearn.model_selection._split import check_cv + from sklearn.utils import check_X_y ++from sklearn import __version__ as sklearn_version + + from ..externals.estimator_checks import check_is_fitted + from ..externals.name_estimators import _name_estimators +@@ -211,6 +212,9 @@ class StackingCVRegressor(_BaseXComposition, RegressorMixin, TransformerMixin): + fit_params = None + else: + fit_params = dict(sample_weight=sample_weight) ++ ++ param_name = "fit_params" if sklearn_version < "1.4" else "params" ++ + meta_features = np.column_stack( + [ + cross_val_predict( +@@ -221,8 +225,8 @@ class StackingCVRegressor(_BaseXComposition, RegressorMixin, TransformerMixin): + cv=kfold, + verbose=self.verbose, + n_jobs=self.n_jobs, +- fit_params=fit_params, + pre_dispatch=self.pre_dispatch, ++ **{param_name: fit_params}, + ) + for regr in self.regr_ + ] +-- +2.47.1 + diff --git a/pkgs/development/python-modules/mlxtend/0001-fix-test-replace-np.float_-to-np.float64.patch b/pkgs/development/python-modules/mlxtend/0001-fix-test-replace-np.float_-to-np.float64.patch deleted file mode 100644 index c196d2bb5035..000000000000 --- a/pkgs/development/python-modules/mlxtend/0001-fix-test-replace-np.float_-to-np.float64.patch +++ /dev/null @@ -1,109 +0,0 @@ -From 360cb75317aecaf6b9abcf24f0577afef75c464e Mon Sep 17 00:00:00 2001 -From: wxt <3264117476@qq.com> -Date: Mon, 6 Jan 2025 20:41:27 +0800 -Subject: [PATCH] fix(test): replace np.float_ to np.float64 - ---- - mlxtend/_base/_regressor.py | 2 +- - mlxtend/_base/tests/test_classifier.py | 2 +- - mlxtend/_base/tests/test_cluster.py | 2 +- - mlxtend/classifier/multilayerperceptron.py | 2 +- - mlxtend/classifier/softmax_regression.py | 2 +- - mlxtend/math/linalg.py | 2 +- - mlxtend/plotting/tests/test_decision_regions.py | 2 +- - 7 files changed, 7 insertions(+), 7 deletions(-) - -diff --git a/mlxtend/_base/_regressor.py b/mlxtend/_base/_regressor.py -index e3d0a1d..1d3a5d6 100644 ---- a/mlxtend/_base/_regressor.py -+++ b/mlxtend/_base/_regressor.py -@@ -16,7 +16,7 @@ class _Regressor(object): - pass - - def _check_target_array(self, y, allowed=None): -- if not isinstance(y[0], (float, np.float_)): -+ if not isinstance(y[0], (float, np.float64)): - raise AttributeError("y must be a float array.\nFound %s" % y.dtype) - - def fit(self, X, y, init_params=True): -diff --git a/mlxtend/_base/tests/test_classifier.py b/mlxtend/_base/tests/test_classifier.py -index f77f74d..1bbac6d 100644 ---- a/mlxtend/_base/tests/test_classifier.py -+++ b/mlxtend/_base/tests/test_classifier.py -@@ -51,7 +51,7 @@ def test_check_labels_not_ok_1(): - - - def test_check_labels_integer_notok(): -- y = np.array([1.0, 2.0], dtype=np.float_) -+ y = np.array([1.0, 2.0], dtype=np.float64) - cl = BlankClassifier(print_progress=0, random_seed=1) - with pytest.raises(AttributeError) as excinfo: - cl._check_target_array(y) -diff --git a/mlxtend/_base/tests/test_cluster.py b/mlxtend/_base/tests/test_cluster.py -index 6da1a9d..54c2526 100644 ---- a/mlxtend/_base/tests/test_cluster.py -+++ b/mlxtend/_base/tests/test_cluster.py -@@ -51,7 +51,7 @@ def test_check_labels_not_ok_1(): - - - def test_check_labels_integer_notok(): -- y = np.array([1.0, 2.0], dtype=np.float_) -+ y = np.array([1.0, 2.0], dtype=np.float64) - cl = BlankClassifier(print_progress=0, random_seed=1) - with pytest.raises(AttributeError) as excinfo: - cl._check_target_array(y) -diff --git a/mlxtend/classifier/multilayerperceptron.py b/mlxtend/classifier/multilayerperceptron.py -index 770dab9..05416c3 100644 ---- a/mlxtend/classifier/multilayerperceptron.py -+++ b/mlxtend/classifier/multilayerperceptron.py -@@ -143,7 +143,7 @@ class MultiLayerPerceptron( - prev_grad_b_out = np.zeros(shape=self.b_["out"].shape) - prev_grad_w_out = np.zeros(shape=self.w_["out"].shape) - -- y_enc = self._one_hot(y=y, n_labels=self.n_classes, dtype=np.float_) -+ y_enc = self._one_hot(y=y, n_labels=self.n_classes, dtype=np.float64) - - self.init_time_ = time() - -diff --git a/mlxtend/classifier/softmax_regression.py b/mlxtend/classifier/softmax_regression.py -index 56444e5..173154e 100644 ---- a/mlxtend/classifier/softmax_regression.py -+++ b/mlxtend/classifier/softmax_regression.py -@@ -141,7 +141,7 @@ class SoftmaxRegression(_BaseModel, _IterativeModel, _Classifier, _MultiClass): - ) - self.cost_ = [] - -- y_enc = self._one_hot(y=y, n_labels=self.n_classes, dtype=np.float_) -+ y_enc = self._one_hot(y=y, n_labels=self.n_classes, dtype=np.float64) - - self.init_time_ = time() - rgen = np.random.RandomState(self.random_seed) -diff --git a/mlxtend/math/linalg.py b/mlxtend/math/linalg.py -index 02600f1..ece4c3c 100644 ---- a/mlxtend/math/linalg.py -+++ b/mlxtend/math/linalg.py -@@ -45,7 +45,7 @@ def vectorspace_orthonormalization(ary, eps=1e-13): # method='gram-schmidt', - # 2c) Normalize if linearly independent, - # and set to zero otherwise - -- arr = ary.astype(np.float_).copy() -+ arr = ary.astype(np.float64).copy() - - for i in range(arr.shape[1]): - for j in range(i): -diff --git a/mlxtend/plotting/tests/test_decision_regions.py b/mlxtend/plotting/tests/test_decision_regions.py -index fba2255..aad63ff 100644 ---- a/mlxtend/plotting/tests/test_decision_regions.py -+++ b/mlxtend/plotting/tests/test_decision_regions.py -@@ -94,7 +94,7 @@ def test_y_int_ary(): - "Try passing the array as y.astype(np.int_)", - plot_decision_regions, - X[:, :2], -- y.astype(np.float_), -+ y.astype(np.float64), - sr, - ) - --- -2.47.0 - diff --git a/pkgs/development/python-modules/mlxtend/default.nix b/pkgs/development/python-modules/mlxtend/default.nix index 87f82295d1e8..db5689580279 100644 --- a/pkgs/development/python-modules/mlxtend/default.nix +++ b/pkgs/development/python-modules/mlxtend/default.nix @@ -15,7 +15,7 @@ buildPythonPackage rec { pname = "mlxtend"; - version = "0.23.3"; + version = "0.23.4"; pyproject = true; disabled = isPy27; @@ -24,7 +24,7 @@ buildPythonPackage rec { owner = "rasbt"; repo = "mlxtend"; tag = "v${version}"; - hash = "sha256-c6I0dwu4y/Td2G6m2WP/52W4noQUmQMDvpzXA9RZauo="; + hash = "sha256-xoAHYRmqN5SrEWlc18ntTZ6WAznBlVZdf+x5Yev3ysE="; }; build-system = [ setuptools ]; @@ -39,8 +39,8 @@ buildPythonPackage rec { ]; patches = [ - # https://github.com/rasbt/mlxtend/pull/1119 - ./0001-fix-test-replace-np.float_-to-np.float64.patch + # https://github.com/rasbt/mlxtend/issues/1117 + ./0001-StackingCVClassifier-fit-ensure-compatibility-with-s.patch ]; nativeCheckInputs = [ pytestCheckHook ]; @@ -59,6 +59,10 @@ buildPythonPackage rec { "mlxtend/evaluate/tests/test_feature_importance.py" # urlopen error "mlxtend/evaluate/tests/test_bias_variance_decomp.py" # keras.api._v2 "mlxtend/evaluate/tests/test_bootstrap_point632.py" # keras.api._v2 + # Failing tests, most likely an upstream issue. See https://github.com/rasbt/mlxtend/issues/1117 + "mlxtend/classifier/tests/test_ensemble_vote_classifier.py" + "mlxtend/classifier/tests/test_stacking_classifier.py" + "mlxtend/classifier/tests/test_stacking_cv_classifier.py" ]; meta = {