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import os
import subprocess
import tempfile
import pytest
import numpy as np
from packaging.version import Version
NUMPY_LT_2_0 = Version(np.__version__) < Version("2.0.dev")
reference_dir = 'baseline'
@pytest.mark.array_compare(reference_dir=reference_dir)
def test_succeeds_func_default():
return np.arange(3 * 5).reshape((3, 5))
@pytest.mark.array_compare(file_format='text', reference_dir=reference_dir)
def test_succeeds_func_text():
return np.arange(3 * 5).reshape((3, 5))
@pytest.mark.skipif(not NUMPY_LT_2_0, reason="AttributeError: `np.unicode_` was removed in the NumPy 2.0 release. Use `np.str_` instead.")
@pytest.mark.array_compare(file_format='pd_hdf', reference_dir=reference_dir)
def test_succeeds_func_pdhdf():
pd = pytest.importorskip('pandas')
return pd.DataFrame(data=np.arange(20, dtype='int64'),
columns=['test_data'])
@pytest.mark.array_compare(file_format='fits', reference_dir=reference_dir)
def test_succeeds_func_fits():
return np.arange(3 * 5).reshape((3, 5)).astype(np.int64)
@pytest.mark.array_compare(file_format='fits', reference_dir=reference_dir)
def test_succeeds_func_fits_hdu():
from astropy.io import fits
return fits.PrimaryHDU(np.arange(3 * 5).reshape((3, 5)).astype(np.int64))
class TestClass(object):
@pytest.mark.array_compare(file_format='fits', reference_dir=reference_dir)
def test_succeeds_class(self):
return np.arange(2 * 4 * 3).reshape((2, 4, 3)).astype(np.int64)
TEST_FAILING = """
import pytest
import numpy as np
from astropy.io import fits
@pytest.mark.array_compare
def test_fail():
return np.ones((3, 4))
"""
def test_fails():
tmpdir = tempfile.mkdtemp()
test_file = os.path.join(tmpdir, 'test.py')
with open(test_file, 'w') as f:
f.write(TEST_FAILING)
# If we use --arraydiff, it should detect that the file is missing
code = subprocess.call('pytest --arraydiff {0}'.format(test_file), shell=True)
assert code != 0
# If we don't use --arraydiff option, the test should succeed
code = subprocess.call('pytest {0}'.format(test_file), shell=True)
assert code == 0
TEST_GENERATE = """
import pytest
import numpy as np
from astropy.io import fits
@pytest.mark.array_compare(file_format='{file_format}')
def test_gen():
return np.arange(6 * 5).reshape((6, 5))
"""
@pytest.mark.parametrize('file_format', ('fits', 'text'))
def test_generate(file_format):
tmpdir = tempfile.mkdtemp()
test_file = os.path.join(tmpdir, 'test.py')
with open(test_file, 'w') as f:
f.write(TEST_GENERATE.format(file_format=file_format))
gen_dir = os.path.join(tmpdir, 'spam', 'egg')
# If we don't generate, the test will fail
try:
subprocess.check_output(['pytest', '--arraydiff', test_file], timeout=10)
except subprocess.CalledProcessError as grepexc:
assert b'File not found for comparison test' in grepexc.output
# If we do generate, the test should succeed and a new file will appear
code = subprocess.call(['pytest', '--arraydiff-generate-path={0}'.format(gen_dir), test_file],
timeout=10)
assert code == 0
assert os.path.exists(os.path.join(gen_dir, 'test_gen.' + ('fits' if file_format == 'fits' else 'txt')))
TEST_DEFAULT = """
import pytest
import numpy as np
from astropy.io import fits
@pytest.mark.array_compare
def test_default():
return np.arange(6 * 5).reshape((6, 5))
"""
@pytest.mark.parametrize('file_format', ('fits', 'text'))
def test_default_format(file_format):
tmpdir = tempfile.mkdtemp()
test_file = os.path.join(tmpdir, 'test.py')
with open(test_file, 'w') as f:
f.write(TEST_DEFAULT)
gen_dir = os.path.join(tmpdir, 'spam', 'egg')
# If we do generate, the test should succeed and a new file will appear
code = subprocess.call('pytest -s --arraydiff-default-format={0}'
' --arraydiff-generate-path={1} {2}'.format(file_format, gen_dir, test_file), shell=True)
assert code == 0
assert os.path.exists(os.path.join(gen_dir, 'test_default.' + ('fits' if file_format == 'fits' else 'txt')))
@pytest.mark.array_compare(reference_dir=reference_dir, rtol=0.5,
file_format='fits')
def test_relative_tolerance():
# Scale up the output values by 1.5 to ensure the large `rtol` value is
# needed. (The comparison file contains all 1.6.)
return np.ones((3, 4)) * 1.6 * 1.5
@pytest.mark.array_compare(reference_dir=reference_dir, atol=1.5,
file_format='fits')
def test_absolute_tolerance():
# Increase the output values by 1.4 to ensure the large `atol` value is
# needed. (The comparison file contains all 1.6.)
return np.ones((3, 4)) * 1.6 + 1.4
@pytest.mark.array_compare(
reference_dir=reference_dir,
atol=1.5,
file_format='fits',
single_reference=True)
@pytest.mark.parametrize('spam', ('egg', 'bacon'))
def test_single_reference(spam):
return np.ones((3, 4)) * 1.6 + 1.4
class TestSingleReferenceClass:
@pytest.mark.array_compare(
reference_dir=reference_dir,
atol=1.5,
file_format='fits',
single_reference=True)
@pytest.mark.parametrize('spam', ('egg', 'bacon'))
def test_single_reference(self, spam):
return np.ones((3, 4)) * 1.6 + 1.4
def test_nofile():
pass
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