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Commit 071ddc7

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avigupta2612avigupta2612
authored
Removed assert_warns_message from gaussian_process/tests (#19697)
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‎sklearn/gaussian_process/tests/test_gpc.py

Copy file name to clipboardExpand all lines: sklearn/gaussian_process/tests/test_gpc.py
+9-9Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -17,7 +17,7 @@
1717
from sklearn.exceptions import ConvergenceWarning
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1919
from sklearn.utils._testing \
20-
import assert_almost_equal, assert_array_equal, assert_warns_message
20+
import assert_almost_equal, assert_array_equal
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2323
def f(x):
@@ -189,14 +189,14 @@ def test_multi_class_n_jobs(kernel):
189189
def test_warning_bounds():
190190
kernel = RBF(length_scale_bounds=[1e-5, 1e-3])
191191
gpc = GaussianProcessClassifier(kernel=kernel)
192-
assert_warns_message(ConvergenceWarning, "The optimal value found for "
193-
"dimension 0 of parameter "
194-
"length_scale is close to "
195-
"the specified upper bound "
196-
"0.001. Increasing the bound "
197-
"and calling fit again may "
198-
"find a better value.",
199-
gpc.fit, X, y)
192+
warning_message = (
193+
"The optimal value found for dimension 0 of parameter "
194+
"length_scale is close to the specified upper bound "
195+
"0.001. Increasing the bound and calling fit again may "
196+
"find a better value."
197+
)
198+
with pytest.warns(ConvergenceWarning, match=warning_message):
199+
gpc.fit(X, y)
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201201
kernel_sum = (WhiteKernel(noise_level_bounds=[1e-5, 1e-3]) +
202202
RBF(length_scale_bounds=[1e3, 1e5]))

‎sklearn/gaussian_process/tests/test_gpr.py

Copy file name to clipboardExpand all lines: sklearn/gaussian_process/tests/test_gpr.py
+20-17Lines changed: 20 additions & 17 deletions
Original file line numberDiff line numberDiff line change
@@ -5,6 +5,7 @@
55
# License: BSD 3 clause
66

77
import sys
8+
import re
89
import numpy as np
910
import warnings
1011

@@ -21,9 +22,8 @@
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2223
from sklearn.utils._testing \
2324
import (assert_array_less,
24-
assert_almost_equal, assert_raise_message,
25-
assert_array_almost_equal, assert_array_equal,
26-
assert_allclose, assert_warns_message)
25+
assert_almost_equal, assert_array_almost_equal,
26+
assert_array_equal, assert_allclose)
2727

2828

2929
def f(x):
@@ -404,12 +404,15 @@ def test_gpr_correct_error_message():
404404
y = np.ones(6)
405405
kernel = DotProduct()
406406
gpr = GaussianProcessRegressor(kernel=kernel, alpha=0.0)
407-
assert_raise_message(np.linalg.LinAlgError,
408-
"The kernel, %s, is not returning a "
409-
"positive definite matrix. Try gradually increasing "
410-
"the 'alpha' parameter of your "
411-
"GaussianProcessRegressor estimator."
412-
% kernel, gpr.fit, X, y)
407+
message = (
408+
"The kernel, %s, is not returning a "
409+
"positive definite matrix. Try gradually increasing "
410+
"the 'alpha' parameter of your "
411+
"GaussianProcessRegressor estimator."
412+
% kernel
413+
)
414+
with pytest.raises(np.linalg.LinAlgError, match=re.escape(message)):
415+
gpr.fit(X, y)
413416

414417

415418
@pytest.mark.parametrize('kernel', kernels)
@@ -474,14 +477,14 @@ def test_K_inv_reset(kernel):
474477
def test_warning_bounds():
475478
kernel = RBF(length_scale_bounds=[1e-5, 1e-3])
476479
gpr = GaussianProcessRegressor(kernel=kernel)
477-
assert_warns_message(ConvergenceWarning, "The optimal value found for "
478-
"dimension 0 of parameter "
479-
"length_scale is close to "
480-
"the specified upper bound "
481-
"0.001. Increasing the bound "
482-
"and calling fit again may "
483-
"find a better value.",
484-
gpr.fit, X, y)
480+
warning_message = (
481+
"The optimal value found for dimension 0 of parameter "
482+
"length_scale is close to the specified upper bound "
483+
"0.001. Increasing the bound and calling fit again may "
484+
"find a better value."
485+
)
486+
with pytest.warns(ConvergenceWarning, match=warning_message):
487+
gpr.fit(X, y)
485488

486489
kernel_sum = (WhiteKernel(noise_level_bounds=[1e-5, 1e-3]) +
487490
RBF(length_scale_bounds=[1e3, 1e5]))

‎sklearn/gaussian_process/tests/test_kernels.py

Copy file name to clipboardExpand all lines: sklearn/gaussian_process/tests/test_kernels.py
+7-5Lines changed: 7 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -20,7 +20,6 @@
2020
from sklearn.utils._testing import (assert_almost_equal, assert_array_equal,
2121
assert_array_almost_equal,
2222
assert_allclose,
23-
assert_raise_message,
2423
fails_if_pypy)
2524

2625

@@ -361,7 +360,10 @@ def test_repr_kernels(kernel):
361360

362361
def test_rational_quadratic_kernel():
363362
kernel = RationalQuadratic(length_scale=[1., 1.])
364-
assert_raise_message(AttributeError,
365-
"RationalQuadratic kernel only supports isotropic "
366-
"version, please use a single "
367-
"scalar for length_scale", kernel, X)
363+
message = (
364+
"RationalQuadratic kernel only supports isotropic "
365+
"version, please use a single "
366+
"scalar for length_scale"
367+
)
368+
with pytest.raises(AttributeError, match=message):
369+
kernel(X)

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