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# Copyright 2017 Knowledge Economy Developments Ltd
#
# Henry Gomersall
# heng@kedevelopments.co.uk
# Frederik Beaujean
# Frederik.Beaujean@lmu.de
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# * Neither the name of the copyright holder nor the names of its contributors
# may be used to endorse or promote products derived from this software without
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
from pyfftw import (
FFTW, empty_aligned,
interfaces,
_all_types_np, _all_types_human_readable, _supported_types
)
from pyfftw.builders._utils import _rc_dtype_pairs
import numpy as np
import unittest
import warnings
@unittest.skipIf(len(_all_types_human_readable) == len(_supported_types), "All data types available")
class FFTWPartialTest(unittest.TestCase):
def __init__(self, *args, **kwargs):
super(FFTWPartialTest, self).__init__(*args, **kwargs)
if not hasattr(self, 'assertRaisesRegex'):
self.assertRaisesRegex = self.assertRaisesRegexp
def test_failure(self):
for dtype, npdtype in zip(['32', '64', 'ld'], [np.complex64, np.complex128, np.clongdouble]):
if dtype == 'ld' and np.dtype(np.clongdouble) == np.dtype(np.complex128):
# skip this test on systems where clongdouble is complex128
continue
if dtype not in _supported_types:
a = empty_aligned((1,1024), npdtype, n=16)
b = empty_aligned(a.shape, dtype=a.dtype, n=16)
msg = "Rebuild pyFFTW with support for %s precision!" % _all_types_human_readable[dtype]
with self.assertRaisesRegex(NotImplementedError, msg):
FFTW(a,b)
def conversion(self, missing, alt1, alt2):
'''If the ``missing`` precision is not available, the builder should convert to
``alt1`` precision. If that isn't available either, it should fall back to
``alt2``. If input precision is lost, a warning should be emitted.
'''
missing, alt1, alt2 = [np.dtype(x) for x in (missing, alt1, alt2)]
if _all_types_np[missing] in _supported_types:
return
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
itemsize = alt1.itemsize
a = empty_aligned((1, 512), dtype=missing)
b = interfaces.numpy_fft.fft(a)
res = _rc_dtype_pairs.get(alt1.char, None)
if res is not None:
self.assertEqual(b.dtype, res)
else:
itemsize = alt2.itemsize
self.assertEqual(b.dtype, _rc_dtype_pairs[alt2.char])
if itemsize < missing.itemsize:
print(itemsize, missing.itemsize)
assert len(w) == 1
assert "Narrowing conversion" in str(w[-1].message)
print("Found narrowing conversion from %d to %d bytes" % (missing.itemsize, itemsize))
else:
assert len(w) == 0
def test_conversion(self):
self.conversion('float32', 'float64', 'longdouble')
self.conversion('float64', 'longdouble', 'single')
self.conversion('longdouble', 'float64', 'float32')
test_cases = (
FFTWPartialTest,)
test_set = None
if __name__ == '__main__':
run_test_suites(test_cases, test_set)
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