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