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[WIP] TST use global_random_seed in sklearn/linear_model/tests/test_base.py #23464

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[WIP] TST use global_random_seed in sklearn/linear_model/tests/test_base.py #23464

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8f94fee
change ensemble/plot_adaboost_regression to notebook-style
svenstehle May 2, 2022
f036618
change wordings to gerund
svenstehle May 2, 2022
2d049a0
improve wording in paragraphs and headings
svenstehle May 2, 2022
0f0e75f
fix matplotlib colors with keyword argument
svenstehle May 5, 2022
3808d81
add doi
glemaitre May 13, 2022
015615f
Merge branch 'main' into doc_ensemble_plot_adaboost_regression
glemaitre May 13, 2022
9ee3794
Merge branch 'main' of https://github.com/scikit-learn/scikit-learn i…
svenstehle May 13, 2022
f4898c4
add period back to H, since it does render correctly with the doi wra…
svenstehle May 13, 2022
0c56044
change linking from incompatible doi to html
svenstehle May 13, 2022
48fc357
update link to lead to summary landing page where pdf (among other th…
svenstehle May 13, 2022
0d61503
Merge branch 'main' of https://github.com/scikit-learn/scikit-learn i…
svenstehle May 25, 2022
6a6ac94
add global_random_seed fixture to test_linear_regression_sample_weigh…
svenstehle May 25, 2022
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14 changes: 14 additions & 0 deletions .env
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Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
###
# settings for OpenMP install
# ----------------------------
# export CC=/usr/bin/clang
# export CXX=/usr/bin/clang++
# export CPPFLAGS="$CPPFLAGS -Xpreprocessor -fopenmp"
# export CFLAGS="$CFLAGS -I/usr/local/opt/libomp/include"
# export CXXFLAGS="$CXXFLAGS -I/usr/local/opt/libomp/include"
# export LDFLAGS="$LDFLAGS -Wl,-rpath,/usr/local/opt/libomp/lib -L/usr/local/opt/libomp/lib -lomp"
# ----------------------------
# export SKLEARN_SKIP_OPENMP_TEST=True # only set if we cannot install OpenMP
export EXAMPLES_PATTERN=plot_adaboost_regression

# SKLEARN_TESTS_GLOBAL_RANDOM_SEED="all" pytest sklearn/linear_model/tests/test_base.py -k test_linear_regression
40 changes: 20 additions & 20 deletions sklearn/linear_model/tests/test_base.py
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Expand Up @@ -4,28 +4,26 @@
#
# License: BSD 3 clause

import pytest
import warnings

import numpy as np
from scipy import sparse
from scipy import linalg

from sklearn.utils._testing import assert_array_almost_equal
from sklearn.utils._testing import assert_array_equal
from sklearn.utils._testing import assert_allclose
from sklearn.utils import check_random_state

import pytest
from scipy import linalg, sparse
from sklearn.datasets import load_iris, make_regression, make_sparse_uncorrelated
from sklearn.linear_model import LinearRegression
from sklearn.linear_model._base import _deprecate_normalize
from sklearn.linear_model._base import _preprocess_data
from sklearn.linear_model._base import _rescale_data
from sklearn.linear_model._base import make_dataset
from sklearn.datasets import make_sparse_uncorrelated
from sklearn.datasets import make_regression
from sklearn.datasets import load_iris
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import add_dummy_feature
from sklearn.linear_model._base import (
_deprecate_normalize,
_preprocess_data,
_rescale_data,
make_dataset,
)
from sklearn.preprocessing import StandardScaler, add_dummy_feature
from sklearn.utils import check_random_state
from sklearn.utils._testing import (
assert_allclose,
assert_array_almost_equal,
assert_array_equal,
)

rng = np.random.RandomState(0)
rtol = 1e-6
Expand Down Expand Up @@ -57,8 +55,10 @@ def test_linear_regression():

@pytest.mark.parametrize("array_constr", [np.array, sparse.csr_matrix])
@pytest.mark.parametrize("fit_intercept", [True, False])
def test_linear_regression_sample_weights(array_constr, fit_intercept):
rng = np.random.RandomState(0)
def test_linear_regression_sample_weights(
array_constr, fit_intercept, global_random_seed
):
rng = np.random.RandomState(global_random_seed)

# It would not work with under-determined systems
n_samples, n_features = 6, 5
Expand Down