diff options
Diffstat (limited to 'silx/math/fft/test/test_fft.py')
| -rw-r--r-- | silx/math/fft/test/test_fft.py | 270 |
1 files changed, 0 insertions, 270 deletions
diff --git a/silx/math/fft/test/test_fft.py b/silx/math/fft/test/test_fft.py deleted file mode 100644 index 9ef2fd2..0000000 --- a/silx/math/fft/test/test_fft.py +++ /dev/null @@ -1,270 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 -# /*########################################################################## -# -# Copyright (c) 2018-2019 European Synchrotron Radiation Facility -# -# Permission is hereby granted, free of charge, to any person obtaining a copy -# of this software and associated documentation files (the "Software"), to deal -# in the Software without restriction, including without limitation the rights -# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -# copies of the Software, and to permit persons to whom the Software is -# furnished to do so, subject to the following conditions: -# -# The above copyright notice and this permission notice shall be included in -# all copies or substantial portions of the Software. -# -# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN -# THE SOFTWARE. -# -# ###########################################################################*/ -"""Test of the FFT module""" - -import numpy as np -import unittest -import logging -try: - from scipy.misc import ascent - __have_scipy = True -except ImportError: - __have_scipy = False -from silx.utils.testutils import ParametricTestCase -from silx.math.fft.fft import FFT -from silx.math.fft.clfft import __have_clfft__ -from silx.math.fft.cufft import __have_cufft__ -from silx.math.fft.fftw import __have_fftw__ - -from silx.test.utils import test_options - -logger = logging.getLogger(__name__) - - -class TransformInfos(object): - def __init__(self): - self.dimensions = [ - "1D", - "batched_1D", - "2D", - "batched_2D", - "3D", - ] - self.modes = { - "R2C": np.float32, - "R2C_double": np.float64, - "C2C": np.complex64, - "C2C_double": np.complex128, - } - self.sizes = { - "1D": [(128,), (127,)], - "2D": [(128, 128), (128, 127), (127, 128), (127, 127)], - "3D": [(64, 64, 64), (64, 64, 63), (64, 63, 64), (63, 64, 64), - (64, 63, 63), (63, 64, 63), (63, 63, 64), (63, 63, 63)] - } - self.axes = { - "1D": None, - "batched_1D": (-1,), - "2D": None, - "batched_2D": (-2, -1), - "3D": None, - } - self.sizes["batched_1D"] = self.sizes["2D"] - self.sizes["batched_2D"] = self.sizes["3D"] - - -class TestData(object): - def __init__(self): - self.data = ascent().astype("float32") - self.data1d = self.data[:, 0] # non-contiguous data - self.data3d = np.tile(self.data[:64, :64], (64, 1, 1)) - self.data_refs = { - 1: self.data1d, - 2: self.data, - 3: self.data3d, - } - - -@unittest.skipUnless(__have_scipy, "scipy is missing") -class TestFFT(ParametricTestCase): - """Test cuda/opencl/fftw backends of FFT""" - - def setUp(self): - self.tol = { - np.dtype("float32"): 1e-3, - np.dtype("float64"): 1e-9, - np.dtype("complex64"): 1e-3, - np.dtype("complex128"): 1e-9, - } - self.transform_infos = TransformInfos() - self.test_data = TestData() - - @staticmethod - def calc_mae(arr1, arr2): - """ - Compute the Max Absolute Error between two arrays - """ - return np.max(np.abs(arr1 - arr2)) - - @unittest.skipIf(not __have_cufft__, - "cuda back-end requires pycuda and scikit-cuda") - def test_cuda(self): - import pycuda.autoinit - - # Error is higher when using cuda. fast_math mode ? - self.tol[np.dtype("float32")] *= 2 - - self.__run_tests(backend="cuda") - - @unittest.skipIf(not __have_clfft__, - "opencl back-end requires pyopencl and gpyfft") - def test_opencl(self): - from silx.opencl.common import ocl - if ocl is not None: - self.__run_tests(backend="opencl", ctx=ocl.create_context()) - - @unittest.skipIf(not __have_fftw__, - "fftw back-end requires pyfftw") - def test_fftw(self): - self.__run_tests(backend="fftw") - - def __run_tests(self, backend, **extra_args): - """Run all tests with the given backend - - :param str backend: - :param dict extra_args: Additional arguments to provide to FFT - """ - for trdim in self.transform_infos.dimensions: - for mode in self.transform_infos.modes: - for size in self.transform_infos.sizes[trdim]: - with self.subTest(trdim=trdim, mode=mode, size=size): - self.__test(backend, trdim, mode, size, **extra_args) - - def __test(self, backend, trdim, mode, size, **extra_args): - """Compare given backend with numpy for given conditions""" - logger.debug("backend: %s, trdim: %s, mode: %s, size: %s", - backend, trdim, mode, str(size)) - if size == "3D" and test_options.TEST_LOW_MEM: - self.skipTest("low mem") - - ndim = len(size) - input_data = self.test_data.data_refs[ndim].astype( - self.transform_infos.modes[mode]) - tol = self.tol[np.dtype(input_data.dtype)] - if trdim == "3D": - tol *= 10 # Error is relatively high in high dimensions - # It seems that cuda has problems with C2D batched 1D - if trdim == "batched_1D" and backend == "cuda" and mode == "C2C": - tol *= 10 - - # Python < 3.5 does not want to mix **extra_args with existing kwargs - fft_args = { - "template": input_data, - "axes": self.transform_infos.axes[trdim], - "backend": backend, - } - fft_args.update(extra_args) - F = FFT( - **fft_args - ) - F_np = FFT( - template=input_data, - axes=self.transform_infos.axes[trdim], - backend="numpy" - ) - - # Forward FFT - res = F.fft(input_data) - res_np = F_np.fft(input_data) - mae = self.calc_mae(res, res_np) - all_close = np.allclose(res, res_np, atol=tol, rtol=tol), - self.assertTrue( - all_close, - "FFT %s:%s, MAE(%s, numpy) = %f (tol = %.2e)" % (mode, trdim, backend, mae, tol) - ) - - # Inverse FFT - res2 = F.ifft(res) - mae = self.calc_mae(res2, input_data) - self.assertTrue( - mae < tol, - "IFFT %s:%s, MAE(%s, numpy) = %f" % (mode, trdim, backend, mae) - ) - - -@unittest.skipUnless(__have_scipy, "scipy is missing") -class TestNumpyFFT(ParametricTestCase): - """ - Test the Numpy backend individually. - """ - - def setUp(self): - transforms = { - "1D": { - True: (np.fft.rfft, np.fft.irfft), - False: (np.fft.fft, np.fft.ifft), - }, - "2D": { - True: (np.fft.rfft2, np.fft.irfft2), - False: (np.fft.fft2, np.fft.ifft2), - }, - "3D": { - True: (np.fft.rfftn, np.fft.irfftn), - False: (np.fft.fftn, np.fft.ifftn), - }, - } - transforms["batched_1D"] = transforms["1D"] - transforms["batched_2D"] = transforms["2D"] - self.transforms = transforms - self.transform_infos = TransformInfos() - self.test_data = TestData() - - def test(self): - """Test the numpy backend against native fft. - - Results should be exactly the same. - """ - for trdim in self.transform_infos.dimensions: - for mode in self.transform_infos.modes: - for size in self.transform_infos.sizes[trdim]: - with self.subTest(trdim=trdim, mode=mode, size=size): - self.__test(trdim, mode, size) - - def __test(self, trdim, mode, size): - logger.debug("trdim: %s, mode: %s, size: %s", trdim, mode, str(size)) - ndim = len(size) - input_data = self.test_data.data_refs[ndim].astype( - self.transform_infos.modes[mode]) - np_fft, np_ifft = self.transforms[trdim][np.isrealobj(input_data)] - - F = FFT( - template=input_data, - axes=self.transform_infos.axes[trdim], - backend="numpy" - ) - # Test FFT - res = F.fft(input_data) - ref = np_fft(input_data) - self.assertTrue(np.allclose(res, ref)) - - # Test IFFT - res2 = F.ifft(res) - ref2 = np_ifft(ref) - self.assertTrue(np.allclose(res2, ref2)) - - -def suite(): - suite = unittest.TestSuite() - for cls in (TestNumpyFFT, TestFFT): - suite.addTest( - unittest.defaultTestLoader.loadTestsFromTestCase(cls)) - return suite - - -if __name__ == '__main__': - unittest.main(defaultTest="suite") - - |