commit: 716a22e8cfcc8db49e96b764405648a6be1cc3a6 Author: Andrew Ammerlaan <andrewammerlaan <AT> gentoo <DOT> org> AuthorDate: Thu Apr 11 14:36:00 2024 +0000 Commit: Andrew Ammerlaan <andrewammerlaan <AT> gentoo <DOT> org> CommitDate: Thu Apr 11 14:36:00 2024 +0000 URL: https://gitweb.gentoo.org/repo/gentoo.git/commit/?id=716a22e8
sci-libs/scikit-optimize: treeclean Closes: https://bugs.gentoo.org/920439 Closes: https://bugs.gentoo.org/906565 Signed-off-by: Andrew Ammerlaan <andrewammerlaan <AT> gentoo.org> profiles/package.mask | 6 -- sci-libs/scikit-optimize/Manifest | 1 - .../files/scikit-optimize-0.9.0-numpy-1.24.patch | 22 ----- .../scikit-optimize-0.9.0-scikit-learn-1.2.0.patch | 104 --------------------- sci-libs/scikit-optimize/metadata.xml | 12 --- .../scikit-optimize-0.9.0-r1.ebuild | 39 -------- .../scikit-optimize/scikit-optimize-0.9.0.ebuild | 31 ------ 7 files changed, 215 deletions(-) diff --git a/profiles/package.mask b/profiles/package.mask index e5309eeeb5b9..bef723653deb 100644 --- a/profiles/package.mask +++ b/profiles/package.mask @@ -328,12 +328,6 @@ games-engines/renpy net-misc/econnman sci-chemistry/mdtraj -# Andrew Ammerlaan <andrewammerl...@gentoo.org> (2024-03-10) -# Archived upstream, latest release is 3 years old. One test -# failure with python 3.11, more with python 3.12. -# Removal on: 2024-04-10. Bug #920439 -sci-libs/scikit-optimize - # Eray Aslan <e...@gentoo.org> (2024-03-10) # Mask experimental software =mail-mta/postfix-3.10* diff --git a/sci-libs/scikit-optimize/Manifest b/sci-libs/scikit-optimize/Manifest deleted file mode 100644 index 460f16a85cb6..000000000000 --- a/sci-libs/scikit-optimize/Manifest +++ /dev/null @@ -1 +0,0 @@ -DIST scikit-optimize-0.9.0.tar.gz 275570 BLAKE2B ab481bf1cfc2b8c7cff213ae0ce2fa937de8f6269b491cf63ae115eea5c936c8a5c26b7fb339fa6cd2927c5105068635c008d6dc8b3f99b4b5d3abfed1a1c5a2 SHA512 a4c1bd589686dbbabcc5de38a4eb581c040cc2c3f83bc250ddcbe66314f03fc68b7b12d7679049da34c42445b446e1af3873f7ce90bec2a5361f0077ff3e9b74 diff --git a/sci-libs/scikit-optimize/files/scikit-optimize-0.9.0-numpy-1.24.patch b/sci-libs/scikit-optimize/files/scikit-optimize-0.9.0-numpy-1.24.patch deleted file mode 100644 index 65fc26f3eed1..000000000000 --- a/sci-libs/scikit-optimize/files/scikit-optimize-0.9.0-numpy-1.24.patch +++ /dev/null @@ -1,22 +0,0 @@ -diff --git a/skopt/space/transformers.py b/skopt/space/transformers.py -index 68892952..87cc3b68 100644 ---- a/skopt/space/transformers.py -+++ b/skopt/space/transformers.py -@@ -259,7 +259,7 @@ def transform(self, X): - if (self.high - self.low) == 0.: - return X * 0. - if self.is_int: -- return (np.round(X).astype(np.int) - self.low) /\ -+ return (np.round(X).astype(np.int64) - self.low) /\ - (self.high - self.low) - else: - return (X - self.low) / (self.high - self.low) -@@ -272,7 +272,7 @@ def inverse_transform(self, X): - raise ValueError("All values should be greater than 0.0") - X_orig = X * (self.high - self.low) + self.low - if self.is_int: -- return np.round(X_orig).astype(np.int) -+ return np.round(X_orig).astype(np.int64) - return X_orig - - diff --git a/sci-libs/scikit-optimize/files/scikit-optimize-0.9.0-scikit-learn-1.2.0.patch b/sci-libs/scikit-optimize/files/scikit-optimize-0.9.0-scikit-learn-1.2.0.patch deleted file mode 100644 index 8cf8cff9479f..000000000000 --- a/sci-libs/scikit-optimize/files/scikit-optimize-0.9.0-scikit-learn-1.2.0.patch +++ /dev/null @@ -1,104 +0,0 @@ -diff --git a/skopt/learning/forest.py b/skopt/learning/forest.py -index 096770c1d..ebde568f5 100644 ---- a/skopt/learning/forest.py -+++ b/skopt/learning/forest.py -@@ -27,7 +27,7 @@ def _return_std(X, trees, predictions, min_variance): - ------- - std : array-like, shape=(n_samples,) - Standard deviation of `y` at `X`. If criterion -- is set to "mse", then `std[i] ~= std(y | X[i])`. -+ is set to "squared_error", then `std[i] ~= std(y | X[i])`. - - """ - # This derives std(y | x) as described in 4.3.2 of arXiv:1211.0906 -@@ -61,9 +61,9 @@ class RandomForestRegressor(_sk_RandomForestRegressor): - n_estimators : integer, optional (default=10) - The number of trees in the forest. - -- criterion : string, optional (default="mse") -+ criterion : string, optional (default="squared_error") - The function to measure the quality of a split. Supported criteria -- are "mse" for the mean squared error, which is equal to variance -+ are "squared_error" for the mean squared error, which is equal to variance - reduction as feature selection criterion, and "mae" for the mean - absolute error. - -@@ -194,7 +194,7 @@ class RandomForestRegressor(_sk_RandomForestRegressor): - .. [1] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32, 2001. - - """ -- def __init__(self, n_estimators=10, criterion='mse', max_depth=None, -+ def __init__(self, n_estimators=10, criterion='squared_error', max_depth=None, - min_samples_split=2, min_samples_leaf=1, - min_weight_fraction_leaf=0.0, max_features='auto', - max_leaf_nodes=None, min_impurity_decrease=0., -@@ -228,20 +228,20 @@ def predict(self, X, return_std=False): - Returns - ------- - predictions : array-like of shape = (n_samples,) -- Predicted values for X. If criterion is set to "mse", -+ Predicted values for X. If criterion is set to "squared_error", - then `predictions[i] ~= mean(y | X[i])`. - - std : array-like of shape=(n_samples,) - Standard deviation of `y` at `X`. If criterion -- is set to "mse", then `std[i] ~= std(y | X[i])`. -+ is set to "squared_error", then `std[i] ~= std(y | X[i])`. - - """ - mean = super(RandomForestRegressor, self).predict(X) - - if return_std: -- if self.criterion != "mse": -+ if self.criterion != "squared_error": - raise ValueError( -- "Expected impurity to be 'mse', got %s instead" -+ "Expected impurity to be 'squared_error', got %s instead" - % self.criterion) - std = _return_std(X, self.estimators_, mean, self.min_variance) - return mean, std -@@ -257,9 +257,9 @@ class ExtraTreesRegressor(_sk_ExtraTreesRegressor): - n_estimators : integer, optional (default=10) - The number of trees in the forest. - -- criterion : string, optional (default="mse") -+ criterion : string, optional (default="squared_error") - The function to measure the quality of a split. Supported criteria -- are "mse" for the mean squared error, which is equal to variance -+ are "squared_error" for the mean squared error, which is equal to variance - reduction as feature selection criterion, and "mae" for the mean - absolute error. - -@@ -390,7 +390,7 @@ class ExtraTreesRegressor(_sk_ExtraTreesRegressor): - .. [1] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32, 2001. - - """ -- def __init__(self, n_estimators=10, criterion='mse', max_depth=None, -+ def __init__(self, n_estimators=10, criterion='squared_error', max_depth=None, - min_samples_split=2, min_samples_leaf=1, - min_weight_fraction_leaf=0.0, max_features='auto', - max_leaf_nodes=None, min_impurity_decrease=0., -@@ -425,19 +425,19 @@ def predict(self, X, return_std=False): - Returns - ------- - predictions : array-like of shape=(n_samples,) -- Predicted values for X. If criterion is set to "mse", -+ Predicted values for X. If criterion is set to "squared_error", - then `predictions[i] ~= mean(y | X[i])`. - - std : array-like of shape=(n_samples,) - Standard deviation of `y` at `X`. If criterion -- is set to "mse", then `std[i] ~= std(y | X[i])`. -+ is set to "squared_error", then `std[i] ~= std(y | X[i])`. - """ - mean = super(ExtraTreesRegressor, self).predict(X) - - if return_std: -- if self.criterion != "mse": -+ if self.criterion != "squared_error": - raise ValueError( -- "Expected impurity to be 'mse', got %s instead" -+ "Expected impurity to be 'squared_error', got %s instead" - % self.criterion) - std = _return_std(X, self.estimators_, mean, self.min_variance) - return mean, std diff --git a/sci-libs/scikit-optimize/metadata.xml b/sci-libs/scikit-optimize/metadata.xml deleted file mode 100644 index d554e7c990fa..000000000000 --- a/sci-libs/scikit-optimize/metadata.xml +++ /dev/null @@ -1,12 +0,0 @@ -<?xml version="1.0" encoding="UTF-8"?> -<!DOCTYPE pkgmetadata SYSTEM "https://www.gentoo.org/dtd/metadata.dtd";> -<pkgmetadata> - <maintainer type="project"> - <email>s...@gentoo.org</email> - <name>Gentoo Science Project</name> - </maintainer> - <upstream> - <remote-id type="pypi">scikit-optimize</remote-id> - <remote-id type="github">scikit-optimize/scikit-optimize</remote-id> - </upstream> -</pkgmetadata> diff --git a/sci-libs/scikit-optimize/scikit-optimize-0.9.0-r1.ebuild b/sci-libs/scikit-optimize/scikit-optimize-0.9.0-r1.ebuild deleted file mode 100644 index e908335940a8..000000000000 --- a/sci-libs/scikit-optimize/scikit-optimize-0.9.0-r1.ebuild +++ /dev/null @@ -1,39 +0,0 @@ -# Copyright 2020-2024 Gentoo Authors -# Distributed under the terms of the GNU General Public License v2 - -EAPI=8 - -DISTUTILS_USE_PEP517=setuptools -PYPI_NO_NORMALIZE=1 -PYTHON_COMPAT=( python3_{10..11} ) -inherit distutils-r1 pypi - -DESCRIPTION="Sequential model-based optimization library" -HOMEPAGE="https://scikit-optimize.github.io/"; - -LICENSE="BSD" -SLOT="0" -KEYWORDS="~amd64" - -RDEPEND=" - >=dev-python/joblib-0.11[${PYTHON_USEDEP}] - dev-python/pyyaml[${PYTHON_USEDEP}] - >=dev-python/matplotlib-2.0.0[${PYTHON_USEDEP}] - >=dev-python/numpy-1.13.3[${PYTHON_USEDEP}] - >=dev-python/scikit-learn-0.20.0[${PYTHON_USEDEP}] - >=dev-python/scipy-0.19.1[${PYTHON_USEDEP}] -" - -PATCHES=( - # https://github.com/scikit-optimize/scikit-optimize/pull/1187 - "${FILESDIR}/${P}-numpy-1.24.patch" - # https://github.com/scikit-optimize/scikit-optimize/pull/1184/files - "${FILESDIR}/${P}-scikit-learn-1.2.0.patch" -) - -distutils_enable_tests pytest -# No such file or directory: image/logo.png -#distutils_enable_sphinx doc \ -# dev-python/numpydoc \ -# dev-python/sphinx-issues \ -# dev-python/sphinx-gallery diff --git a/sci-libs/scikit-optimize/scikit-optimize-0.9.0.ebuild b/sci-libs/scikit-optimize/scikit-optimize-0.9.0.ebuild deleted file mode 100644 index b712b3f5252d..000000000000 --- a/sci-libs/scikit-optimize/scikit-optimize-0.9.0.ebuild +++ /dev/null @@ -1,31 +0,0 @@ -# Copyright 2020-2024 Gentoo Authors -# Distributed under the terms of the GNU General Public License v2 - -EAPI=8 - -PYPI_NO_NORMALIZE=1 -PYTHON_COMPAT=( python3_{10..11} ) -inherit distutils-r1 pypi - -DESCRIPTION="Sequential model-based optimization library" -HOMEPAGE="https://scikit-optimize.github.io/"; - -LICENSE="BSD" -SLOT="0" -KEYWORDS="~amd64" - -RDEPEND=" - >=dev-python/joblib-0.11[${PYTHON_USEDEP}] - dev-python/pyyaml[${PYTHON_USEDEP}] - >=dev-python/matplotlib-2.0.0[${PYTHON_USEDEP}] - >=dev-python/numpy-1.13.3[${PYTHON_USEDEP}] - >=dev-python/scikit-learn-0.20.0[${PYTHON_USEDEP}] - >=dev-python/scipy-0.19.1[${PYTHON_USEDEP}] -" - -distutils_enable_tests pytest -# No such file or directory: image/logo.png -#distutils_enable_sphinx doc \ -# dev-python/numpydoc \ -# dev-python/sphinx-issues \ -# dev-python/sphinx-gallery
