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#!/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.
#
# ###########################################################################*/
from .fftw import FFTW
from .clfft import CLFFT
from .npfft import NPFFT
from .cufft import CUFFT
def FFT(
shape=None,
dtype=None,
template=None,
shape_out=None,
axes=None,
normalize="rescale",
backend="numpy",
**kwargs
):
"""
Initialize a FFT plan.
:param List[int] shape:
Shape of the input data.
:param numpy.dtype dtype:
Data type of the input data.
:param numpy.ndarray template:
Optional data, replacement for "shape" and "dtype".
If provided, the arguments "shape" and "dtype" are ignored,
and are instead inferred from it.
:param List[int] shape_out:
Optional shape of output data.
By default, the data has the same shape as the input
data (in case of C2C transform), or a shape with the last dimension halved
(in case of R2C transform). If shape_out is provided, it must be greater
or equal than the shape of input data. In this case, FFT is performed
with zero-padding.
:param List[int] axes:
Axes along which FFT is computed.
* For 2D transform: axes=(1,0)
* For batched 1D transform of 2D image: axes=(0,)
:param str normalize:
Whether to normalize FFT and IFFT. Possible values are:
* "rescale": in this case, Fourier data is divided by "N"
before IFFT, so that (FFT(data)) = data
* "ortho": in this case, FFT and IFFT are adjoint of eachother,
the transform is unitary. Both FFT and IFFT are scaled with 1/sqrt(N).
* "none": no normalizatio is done : IFFT(FFT(data)) = data*N
:param str backend:
FFT Backend to use. Value can be "numpy", "fftw", "opencl", "cuda".
"""
backends = {
"numpy": NPFFT,
"np": NPFFT,
"fftw": FFTW,
"opencl": CLFFT,
"clfft": CLFFT,
"cuda": CUFFT,
"cufft": CUFFT,
}
backend = backend.lower()
if backend not in backends:
raise ValueError("Unknown backend %s, available are %s" % (backend, backends))
F = backends[backend](
shape=shape,
dtype=dtype,
template=template,
shape_out=shape_out,
axes=axes,
normalize=normalize,
**kwargs
)
return F
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