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from __future__ import print_function
from time import time
import importlib
import functools
import numpy as np
from mpi4py_fft import fftw
from mpi4py_fft.libfft import FFT
has_backend = {'fftw': True}
for backend in ('pyfftw', 'mkl_fft', 'scipy', 'numpy'):
has_backend[backend] = True
try:
importlib.import_module(backend)
except ImportError:
has_backend[backend] = False
abstol = dict(f=5e-5, d=1e-14, g=1e-14)
def allclose(a, b):
atol = abstol[a.dtype.char.lower()]
return np.allclose(a, b, rtol=0, atol=atol)
def test_libfft():
from itertools import product
dims = (1, 2, 3)
sizes = (7, 8, 9)
types = ''
for t in 'fd':
if fftw.get_fftw_lib(t):
types += t+t.upper()
for backend in ('pyfftw', 'mkl_fft', 'scipy', 'numpy', 'fftw'):
if has_backend[backend] is False:
continue
t0 = 0
for typecode in types:
for dim in dims:
for shape in product(*([sizes]*dim)):
allaxes = tuple(reversed(range(dim)))
for i in range(dim):
for j in range(i+1, dim):
for axes in (None, allaxes[i:j]):
#print(shape, axes, typecode)
fft = FFT(shape, axes, dtype=typecode, backend=backend,
planner_effort='FFTW_ESTIMATE')
A = fft.forward.input_array
B = fft.forward.output_array
A[...] = np.random.random(A.shape).astype(typecode)
X = A.copy()
B.fill(0)
t0 -= time()
B = fft.forward(A, B)
t0 += time()
A.fill(0)
t0 -= time()
A = fft.backward(B, A)
t0 += time()
assert allclose(A, X)
print('backend: ', backend, t0)
# Padding is different because the physical space is padded and as such
# difficult to initialize. We solve this problem by making one extra
# transform
for backend in ('pyfftw', 'mkl_fft', 'scipy', 'numpy', 'fftw'):
if has_backend[backend] is False:
continue
for padding in (1.5, 2.0):
for typecode in types:
for dim in dims:
for shape in product(*([sizes]*dim)):
allaxes = tuple(reversed(range(dim)))
for i in range(dim):
axis = allaxes[i]
axis -= len(shape)
shape = list(shape)
shape[axis] = int(shape[axis]*padding)
#print(shape, axis, typecode, backend)
fft = FFT(shape, axis, dtype=typecode, backend=backend,
padding=padding, planner_effort='FFTW_ESTIMATE')
A = fft.forward.input_array
B = fft.forward.output_array
A[...] = np.random.random(A.shape).astype(typecode)
B.fill(0)
B = fft.forward(A, B)
X = B.copy()
A.fill(0)
A = fft.backward(B, A)
B.fill(0)
B = fft.forward(A, B)
assert allclose(B, X), np.linalg.norm(B-X)
for backend in ('pyfftw', 'mkl_fft', 'scipy', 'numpy', 'fftw'):
if has_backend[backend] is False:
continue
if backend == 'fftw':
dctn = functools.partial(fftw.dctn, type=3)
idctn = functools.partial(fftw.idctn, type=3)
transforms = {(1,): (dctn, idctn),
(0, 1): (dctn, idctn)}
elif backend == 'pyfftw':
import pyfftw
transforms = {(1,): (pyfftw.builders.rfftn, pyfftw.builders.irfftn),
(0, 1): (pyfftw.builders.rfftn, pyfftw.builders.irfftn)}
elif backend == 'numpy':
transforms = {(1,): (np.fft.rfftn, np.fft.irfftn),
(0, 1): (np.fft.rfftn, np.fft.irfftn)}
elif backend == 'mkl_fft':
import mkl_fft
transforms = {(1,): (mkl_fft._numpy_fft.rfftn, mkl_fft._numpy_fft.irfftn),
(0, 1): (mkl_fft._numpy_fft.rfftn, mkl_fft._numpy_fft.irfftn)}
elif backend == 'scipy':
from scipy.fftpack import fftn, ifftn
transforms = {(1,): (fftn, ifftn),
(0, 1): (fftn, ifftn)}
for axis in ((1,), (0, 1)):
fft = FFT(shape, axis, backend=backend, transforms=transforms)
A = fft.forward.input_array
B = fft.forward.output_array
A[...] = np.random.random(A.shape)
X = A.copy()
B.fill(0)
B = fft.forward(A, B)
A.fill(0)
A = fft.backward(B, A)
assert allclose(A, X)
if __name__ == '__main__':
test_libfft()
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