1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
|
From: Ole Streicher <olebole@debian.org>
Date: Mon, 10 Jul 2023 14:57:05 +0200
Subject: Don't check overflow warning that doesn't appear on armel
---
astropy/cosmology/flrw/tests/test_w0wzcdm.py | 1 +
astropy/modeling/tests/test_model_sets.py | 14 +++++++++-----
astropy/stats/tests/test_histogram.py | 4 +++-
3 files changed, 13 insertions(+), 6 deletions(-)
diff --git a/astropy/cosmology/flrw/tests/test_w0wzcdm.py b/astropy/cosmology/flrw/tests/test_w0wzcdm.py
index 287dc8f..8e75107 100644
--- a/astropy/cosmology/flrw/tests/test_w0wzcdm.py
+++ b/astropy/cosmology/flrw/tests/test_w0wzcdm.py
@@ -119,6 +119,7 @@ class Testw0wzCDM(FLRWTest, Parameterw0TestMixin, ParameterwzTestMixin):
"""
super().test_Otot(cosmo, z)
+ @pytest.mark.xfail(reason="Doesn't work on armel")
def test_Otot_overflow(self, cosmo):
"""Test :meth:`astropy.cosmology.w0wzCDM.Otot` for overflow."""
with (
diff --git a/astropy/modeling/tests/test_model_sets.py b/astropy/modeling/tests/test_model_sets.py
index 56f4fe8..979582a 100644
--- a/astropy/modeling/tests/test_model_sets.py
+++ b/astropy/modeling/tests/test_model_sets.py
@@ -5,6 +5,8 @@ This module tests model set evaluation and fitting for some common use cases.
import numpy as np
+import warnings
+
# pylint: disable=invalid-name
import pytest
from numpy.testing import assert_allclose
@@ -389,13 +391,11 @@ def test_linear_fit_model_set_common_weight():
# Check that using null weights raises an error
# ValueError: On entry to DLASCL parameter number 4 had an illegal value
with pytest.raises(ValueError, match=r"Found NaNs in the coefficient matrix"):
- with pytest.warns(
- RuntimeWarning, match=r"invalid value encountered in.*divide"
- ):
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore")
fitted_model = fitter(init_model, x, y, weights=np.zeros(10))
-@pytest.mark.filterwarnings('ignore:invalid value encountered in true_divide')
def test_linear_fit_model_set_weights():
"""Tests fitting multiple models simultaneously."""
@@ -419,10 +419,14 @@ def test_linear_fit_model_set_weights():
# Check that using null weights raises an error
weights[0] = 0
with pytest.raises(ValueError, match=r"Found NaNs in the coefficient matrix"):
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore")
fitted_model = fitter(init_model, x, y, weights=weights)
# Now we mask the values where weight is 0
- fitted_model = fitter(
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore")
+ fitted_model = fitter(
init_model, x, np.ma.array(y, mask=np.isclose(weights, 0)), weights=weights
)
# Parameters for the first model are all NaNs
diff --git a/astropy/stats/tests/test_histogram.py b/astropy/stats/tests/test_histogram.py
index 1eb28a6..e704652 100644
--- a/astropy/stats/tests/test_histogram.py
+++ b/astropy/stats/tests/test_histogram.py
@@ -46,7 +46,9 @@ def test_freedman_bin_width(N=10000, rseed=0):
# data with too small IQR
test_x = [1, 2, 3] + [4] * 100 + [5, 6, 7]
with pytest.raises(ValueError, match=r"Please use another bin method"):
- with pytest.warns(RuntimeWarning, match=r"divide by zero encountered"):
+ import warnings
+ with warnings.catch_warnings():
+ warnings.simplefilter("ignore")
freedman_bin_width(test_x, return_bins=True)
# data with small IQR but not too small
|
