forked from 170010011/fr
106 lines
3.9 KiB
Python
106 lines
3.9 KiB
Python
"""
|
|
Tests used to verify running PyWavelets transforms in parallel via
|
|
concurrent.futures.ThreadPoolExecutor does not raise errors.
|
|
"""
|
|
|
|
from __future__ import division, print_function, absolute_import
|
|
|
|
import warnings
|
|
import numpy as np
|
|
from functools import partial
|
|
from numpy.testing import assert_array_equal, assert_allclose
|
|
from pywt._pytest import uses_futures, futures, max_workers
|
|
|
|
import pywt
|
|
|
|
|
|
def _assert_all_coeffs_equal(coefs1, coefs2):
|
|
# return True only if all coefficients of SWT or DWT match over all levels
|
|
if len(coefs1) != len(coefs2):
|
|
return False
|
|
for (c1, c2) in zip(coefs1, coefs2):
|
|
if isinstance(c1, tuple):
|
|
# for swt, swt2, dwt, dwt2, wavedec, wavedec2
|
|
for a1, a2 in zip(c1, c2):
|
|
assert_array_equal(a1, a2)
|
|
elif isinstance(c1, dict):
|
|
# for swtn, dwtn, wavedecn
|
|
for k, v in c1.items():
|
|
assert_array_equal(v, c2[k])
|
|
else:
|
|
return False
|
|
return True
|
|
|
|
|
|
@uses_futures
|
|
def test_concurrent_swt():
|
|
# tests error-free concurrent operation (see gh-288)
|
|
# swt on 1D data calls the Cython swt
|
|
# other cases call swt_axes
|
|
with warnings.catch_warnings():
|
|
# can remove catch_warnings once the swt2 FutureWarning is removed
|
|
warnings.simplefilter('ignore', FutureWarning)
|
|
for swt_func, x in zip([pywt.swt, pywt.swt2, pywt.swtn],
|
|
[np.ones(8), np.eye(16), np.eye(16)]):
|
|
transform = partial(swt_func, wavelet='haar', level=3)
|
|
for _ in range(10):
|
|
arrs = [x.copy() for _ in range(100)]
|
|
with futures.ThreadPoolExecutor(max_workers=max_workers) as ex:
|
|
results = list(ex.map(transform, arrs))
|
|
|
|
# validate result from one of the concurrent runs
|
|
expected_result = transform(x)
|
|
_assert_all_coeffs_equal(expected_result, results[-1])
|
|
|
|
|
|
@uses_futures
|
|
def test_concurrent_wavedec():
|
|
# wavedec on 1D data calls the Cython dwt_single
|
|
# other cases call dwt_axis
|
|
for wavedec_func, x in zip([pywt.wavedec, pywt.wavedec2, pywt.wavedecn],
|
|
[np.ones(8), np.eye(16), np.eye(16)]):
|
|
transform = partial(wavedec_func, wavelet='haar', level=1)
|
|
for _ in range(10):
|
|
arrs = [x.copy() for _ in range(100)]
|
|
with futures.ThreadPoolExecutor(max_workers=max_workers) as ex:
|
|
results = list(ex.map(transform, arrs))
|
|
|
|
# validate result from one of the concurrent runs
|
|
expected_result = transform(x)
|
|
_assert_all_coeffs_equal(expected_result, results[-1])
|
|
|
|
|
|
@uses_futures
|
|
def test_concurrent_dwt():
|
|
# dwt on 1D data calls the Cython dwt_single
|
|
# other cases call dwt_axis
|
|
for dwt_func, x in zip([pywt.dwt, pywt.dwt2, pywt.dwtn],
|
|
[np.ones(8), np.eye(16), np.eye(16)]):
|
|
transform = partial(dwt_func, wavelet='haar')
|
|
for _ in range(10):
|
|
arrs = [x.copy() for _ in range(100)]
|
|
with futures.ThreadPoolExecutor(max_workers=max_workers) as ex:
|
|
results = list(ex.map(transform, arrs))
|
|
|
|
# validate result from one of the concurrent runs
|
|
expected_result = transform(x)
|
|
_assert_all_coeffs_equal([expected_result, ], [results[-1], ])
|
|
|
|
|
|
@uses_futures
|
|
def test_concurrent_cwt():
|
|
atol = rtol = 1e-14
|
|
time, sst = pywt.data.nino()
|
|
dt = time[1]-time[0]
|
|
transform = partial(pywt.cwt, scales=np.arange(1, 4), wavelet='cmor1.5-1',
|
|
sampling_period=dt)
|
|
for _ in range(10):
|
|
arrs = [sst.copy() for _ in range(50)]
|
|
with futures.ThreadPoolExecutor(max_workers=max_workers) as ex:
|
|
results = list(ex.map(transform, arrs))
|
|
|
|
# validate result from one of the concurrent runs
|
|
expected_result = transform(sst)
|
|
for a1, a2 in zip(expected_result, results[-1]):
|
|
assert_allclose(a1, a2, atol=atol, rtol=rtol)
|