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TST replace assert_raises by pytest.raises in test_least_angle, test_omp, test_test_theil_sen #19406

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Merged
merged 9 commits into from
Apr 9, 2021
Merged

TST replace assert_raises by pytest.raises in test_least_angle, test_omp, test_test_theil_sen #19406

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e3a240f
fix test_least_angle, test_omp, test_test_theil_sen
abdulelahsm Feb 8, 2021
10eaca6
pytest import fixes
abdulelahsm Feb 9, 2021
b64bb2e
linting fixes
abdulelahsm Feb 9, 2021
68c9aa3
pytest raises changes
abdulelahsm Mar 13, 2021
b2a4ef6
resolving conflicts
abdulelahsm Mar 13, 2021
957ae4b
fix merge conflict
abdulelahsm Mar 13, 2021
7afbd1e
Merge branch 'main' into fix_assert_raises
ogrisel Mar 30, 2021
d903625
Update sklearn/linear_model/tests/test_omp.py
abdulelahsm Mar 31, 2021
08190c2
Update sklearn/linear_model/tests/test_least_angle.py
glemaitre Apr 9, 2021
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10 changes: 5 additions & 5 deletions 10 sklearn/linear_model/tests/test_least_angle.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,12 +3,10 @@
import numpy as np
import pytest
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from scipy import linalg

from sklearn.base import clone
from sklearn.model_selection import train_test_split
from sklearn.utils._testing import assert_allclose
from sklearn.utils._testing import assert_array_almost_equal
from sklearn.utils._testing import assert_raises
from sklearn.utils._testing import ignore_warnings
from sklearn.utils._testing import TempMemmap
from sklearn.utils.fixes import np_version, parse_version
Expand Down Expand Up @@ -96,8 +94,8 @@ def test_lars_path_gram_equivalent(method, return_path):
def test_x_none_gram_none_raises_value_error():
# Test that lars_path with no X and Gram raises exception
Xy = np.dot(X.T, y)
assert_raises(ValueError, linear_model.lars_path, None, y, Gram=None,
Xy=Xy)
with pytest.raises(ValueError):
linear_model.lars_path(None, y, Gram=None, Xy=Xy)


def test_all_precomputed():
Expand Down Expand Up @@ -489,7 +487,9 @@ def test_lasso_lars_ic():

# test error on unknown IC
lars_broken = linear_model.LassoLarsIC('<unknown>')
assert_raises(ValueError, lars_broken.fit, X, y)

with pytest.raises(ValueError):
lars_broken.fit(X, y)


def test_lars_path_readonly_data():
Expand Down
26 changes: 12 additions & 14 deletions 26 sklearn/linear_model/tests/test_omp.py
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Expand Up @@ -4,7 +4,6 @@
import numpy as np
import pytest

from sklearn.utils._testing import assert_raises
from sklearn.utils._testing import assert_array_equal
from sklearn.utils._testing import assert_array_almost_equal
from sklearn.utils._testing import ignore_warnings
Expand Down Expand Up @@ -33,16 +32,16 @@

def test_correct_shapes():
assert (orthogonal_mp(X, y[:, 0], n_nonzero_coefs=5).shape ==
(n_features,))
(n_features,))
assert (orthogonal_mp(X, y, n_nonzero_coefs=5).shape ==
(n_features, 3))
(n_features, 3))


def test_correct_shapes_gram():
assert (orthogonal_mp_gram(G, Xy[:, 0], n_nonzero_coefs=5).shape ==
(n_features,))
(n_features,))
assert (orthogonal_mp_gram(G, Xy, n_nonzero_coefs=5).shape ==
(n_features, 3))
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It's ok for this time, but next time please try to refrain to change the formatting of the lines that are fare away from the real changes of your PR to keep the review focused on the main topic (and keep the git history meaningful).

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I apologize, I have a lot to learn and I appreciate your time and effort. Thank you for the valuable feedback

(n_features, 3))


def test_n_nonzero_coefs():
Expand Down Expand Up @@ -88,15 +87,14 @@ def test_unreachable_accuracy():
n_nonzero_coefs=n_features))


def test_bad_input():
assert_raises(ValueError, orthogonal_mp, X, y, tol=-1)
assert_raises(ValueError, orthogonal_mp, X, y, n_nonzero_coefs=-1)
assert_raises(ValueError, orthogonal_mp, X, y,
n_nonzero_coefs=n_features + 1)
assert_raises(ValueError, orthogonal_mp_gram, G, Xy, tol=-1)
assert_raises(ValueError, orthogonal_mp_gram, G, Xy, n_nonzero_coefs=-1)
assert_raises(ValueError, orthogonal_mp_gram, G, Xy,
n_nonzero_coefs=n_features + 1)
@pytest.mark.parametrize("positional_params", [(X, y), (G, Xy)])
@pytest.mark.parametrize(
"keyword_params",
[{"tol": -1}, {"n_nonzero_coefs": -1}, {"n_nonzero_coefs": n_features + 1}]
)
def test_bad_input(positional_params, keyword_params):
with pytest.raises(ValueError):
orthogonal_mp(*positional_params, **keyword_params)


def test_perfect_signal_recovery():
Expand Down
15 changes: 10 additions & 5 deletions 15 sklearn/linear_model/tests/test_theil_sen.py
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Expand Up @@ -17,7 +17,7 @@
from sklearn.linear_model import LinearRegression, TheilSenRegressor
from sklearn.linear_model._theil_sen import _spatial_median, _breakdown_point
from sklearn.linear_model._theil_sen import _modified_weiszfeld_step
from sklearn.utils._testing import assert_almost_equal, assert_raises
from sklearn.utils._testing import assert_almost_equal


@contextmanager
Expand Down Expand Up @@ -209,19 +209,23 @@ def test_calc_breakdown_point():
def test_checksubparams_negative_subpopulation():
X, y, w, c = gen_toy_problem_1d()
theil_sen = TheilSenRegressor(max_subpopulation=-1, random_state=0)
assert_raises(ValueError, theil_sen.fit, X, y)

with pytest.raises(ValueError):
theil_sen.fit(X, y)


def test_checksubparams_too_few_subsamples():
X, y, w, c = gen_toy_problem_1d()
theil_sen = TheilSenRegressor(n_subsamples=1, random_state=0)
assert_raises(ValueError, theil_sen.fit, X, y)
with pytest.raises(ValueError):
theil_sen.fit(X, y)


def test_checksubparams_too_many_subsamples():
X, y, w, c = gen_toy_problem_1d()
theil_sen = TheilSenRegressor(n_subsamples=101, random_state=0)
assert_raises(ValueError, theil_sen.fit, X, y)
with pytest.raises(ValueError):
theil_sen.fit(X, y)


def test_checksubparams_n_subsamples_if_less_samples_than_features():
Expand All @@ -230,7 +234,8 @@ def test_checksubparams_n_subsamples_if_less_samples_than_features():
X = random_state.normal(size=(n_samples, n_features))
y = random_state.normal(size=n_samples)
theil_sen = TheilSenRegressor(n_subsamples=9, random_state=0)
assert_raises(ValueError, theil_sen.fit, X, y)
with pytest.raises(ValueError):
theil_sen.fit(X, y)


def test_subpopulation():
Expand Down
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