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fft.py
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fft.py
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import six
import numpy as np
import cupy
from cupy.cuda import cufft
def _convert_dtype(a, value_type):
if value_type != 'R2C':
if a.dtype in [np.float16, np.float32]:
return a.astype(np.complex64)
elif a.dtype not in [np.complex64, np.complex128]:
return a.astype(np.complex128)
else:
if a.dtype in [np.complex64, np.complex128]:
return a.real
elif a.dtype == np.float16:
return a.astype(np.float32)
elif a.dtype not in [np.float32, np.float64]:
return a.astype(np.float64)
return a
def _cook_shape(a, s, axes, value_type):
if s is None:
return a
if (value_type == 'C2R') and (s[-1] is not None):
s = list(s)
s[-1] = s[-1] // 2 + 1
for sz, axis in zip(s, axes):
if (sz is not None) and (sz != a.shape[axis]):
shape = list(a.shape)
if shape[axis] > sz:
index = [slice(None)] * a.ndim
index[axis] = slice(0, sz)
a = a[index]
else:
index = [slice(None)] * a.ndim
index[axis] = slice(0, shape[axis])
shape[axis] = sz
z = cupy.zeros(shape, a.dtype.char)
z[index] = a
a = z
return a
def _convert_fft_type(a, value_type):
if value_type == 'C2C' and a.dtype == np.complex64:
return cufft.CUFFT_C2C
elif value_type == 'R2C' and a.dtype == np.float32:
return cufft.CUFFT_R2C
elif value_type == 'C2R' and a.dtype == np.complex64:
return cufft.CUFFT_C2R
elif value_type == 'C2C' and a.dtype == np.complex128:
return cufft.CUFFT_Z2Z
elif value_type == 'R2C' and a.dtype == np.float64:
return cufft.CUFFT_D2Z
else:
return cufft.CUFFT_Z2D
def _exec_fft(a, direction, value_type, norm, axis, out_size=None):
fft_type = _convert_fft_type(a, value_type)
if axis % a.ndim != a.ndim - 1:
a = a.swapaxes(axis, -1)
if a.base is not None or not a.flags.c_contiguous:
a = a.copy()
plan = cufft.Plan1d(a.shape[-1] if out_size is None else out_size,
fft_type, a.size // a.shape[-1])
out = plan.get_output_array(a)
plan.fft(a, out, direction)
sz = out.shape[-1]
if fft_type == cufft.CUFFT_R2C or fft_type == cufft.CUFFT_D2Z:
sz = a.shape[-1]
if norm is None:
if direction == cufft.CUFFT_INVERSE:
out /= sz
else:
out /= cupy.sqrt(sz)
if axis % a.ndim != a.ndim - 1:
out = out.swapaxes(axis, -1)
return out
def _fft_c2c(a, direction, norm, axes):
for axis in axes:
a = _exec_fft(a, direction, 'C2C', norm, axis)
return a
def _fft(a, s, axes, norm, direction, value_type='C2C'):
if norm not in (None, 'ortho'):
raise ValueError('Invalid norm value %s, should be None or \"ortho\".'
% norm)
if s is not None:
for n in s:
if (n is not None) and (n < 1):
raise ValueError(
"Invalid number of FFT data points (%d) specified." % n)
if (s is not None) and (axes is not None) and len(s) != len(axes):
raise ValueError("Shape and axes have different lengths.")
a = _convert_dtype(a, value_type)
if axes is None:
if s is None:
dim = a.ndim
else:
dim = len(s)
axes = [i for i in six.moves.range(-dim, 0)]
a = _cook_shape(a, s, axes, value_type)
if value_type == 'C2C':
a = _fft_c2c(a, direction, norm, axes)
elif value_type == 'R2C':
a = _exec_fft(a, direction, value_type, norm, axes[-1])
a = _fft_c2c(a, direction, norm, axes[:-1])
else:
a = _fft_c2c(a, direction, norm, axes[:-1])
if (s is None) or (s[-1] is None):
out_size = a.shape[axes[-1]] * 2 - 2
else:
out_size = s[-1]
a = _exec_fft(a, direction, value_type, norm, axes[-1], out_size)
return a
def fft(a, n=None, axis=-1, norm=None):
"""Compute the one-dimensional FFT.
Args:
a (cupy.ndarray): Array to be transform.
n (None or int): Length of the transformed axis of the output. If ``n``
is not given, the length of the input along the axis specified by
``axis`` is used.
axis (int): Axis over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``n`` and type
will convert to complex if the input is other.
.. seealso:: :func:`numpy.fft.fft`
"""
return _fft(a, (n,), (axis,), norm, cupy.cuda.cufft.CUFFT_FORWARD)
def ifft(a, n=None, axis=-1, norm=None):
"""Compute the one-dimensional inverse FFT.
Args:
a (cupy.ndarray): Array to be transform.
n (None or int): Length of the transformed axis of the output. If ``n``
is not given, the length of the input along the axis specified by
``axis`` is used.
axis (int): Axis over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``n`` and type
will convert to complex if the input is other.
.. seealso:: :func:`numpy.fft.ifft`
"""
return _fft(a, (n,), (axis,), norm, cufft.CUFFT_INVERSE)
def fft2(a, s=None, axes=(-2, -1), norm=None):
"""Compute the two-dimensional FFT.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape of the transformed axes of the
output. If ``s`` is not given, the lengths of the input along the
axes specified by ``axes`` are used.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other.
.. seealso:: :func:`numpy.fft.fft2`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_FORWARD)
def ifft2(a, s=None, axes=(-2, -1), norm=None):
"""Compute the two-dimensional inverse FFT.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape of the transformed axes of the
output. If ``s`` is not given, the lengths of the input along the
axes specified by ``axes`` are used.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other.
.. seealso:: :func:`numpy.fft.ifft2`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_INVERSE)
def fftn(a, s=None, axes=None, norm=None):
"""Compute the N-dimensional FFT.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape of the transformed axes of the
output. If ``s`` is not given, the lengths of the input along the
axes specified by ``axes`` are used.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other.
.. seealso:: :func:`numpy.fft.fftn`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_FORWARD)
def ifftn(a, s=None, axes=None, norm=None):
"""Compute the N-dimensional inverse FFT.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape of the transformed axes of the
output. If ``s`` is not given, the lengths of the input along the
axes specified by ``axes`` are used.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other.
.. seealso:: :func:`numpy.fft.ifftn`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_INVERSE)
def rfft(a, n=None, axis=-1, norm=None):
"""Compute the one-dimensional FFT for real input.
Args:
a (cupy.ndarray): Array to be transform.
n (None or int): Number of points along transformation axis in the
input to use. If ``n`` is not given, the length of the input along
the axis specified by ``axis`` is used.
axis (int): Axis over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``n`` and type
will convert to complex if the input is other. The length of the
transformed axis is ``n//2+1``.
.. seealso:: :func:`numpy.fft.rfft`
"""
return _fft(a, (n,), (axis,), norm, cufft.CUFFT_FORWARD, 'R2C')
def irfft(a, n=None, axis=-1, norm=None):
"""Compute the one-dimensional inverse FFT for real input.
Args:
a (cupy.ndarray): Array to be transform.
n (None or int): Length of the transformed axis of the output. For
``n`` output points, ``n//2+1`` input points are necessary. If
``n`` is not given, it is determined from the length of the input
along the axis specified by ``axis``.
axis (int): Axis over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``n`` and type
will convert to complex if the input is other. If ``n`` is not
given, the length of the transformed axis is`2*(m-1)` where `m`
is the length of the transformed axis of the input.
.. seealso:: :func:`numpy.fft.irfft`
"""
return _fft(a, (n,), (axis,), norm, cufft.CUFFT_INVERSE, 'C2R')
def rfft2(a, s=None, axes=(-2, -1), norm=None):
"""Compute the two-dimensional FFT for real input.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape to use from the input. If ``s`` is not
given, the lengths of the input along the axes specified by
``axes`` are used.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other. The length of the
last axis transformed will be ``s[-1]//2+1``.
.. seealso:: :func:`numpy.fft.rfft2`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_FORWARD, 'R2C')
def irfft2(a, s=None, axes=(-2, -1), norm=None):
"""Compute the two-dimensional inverse FFT for real input.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape of the output. If ``s`` is not given,
they are determined from the lengths of the input along the axes
specified by ``axes``.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other. If ``s`` is not
given, the length of final transformed axis of output will be
`2*(m-1)` where `m` is the length of the final transformed axis of
the input.
.. seealso:: :func:`numpy.fft.irfft2`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_INVERSE, 'C2R')
def rfftn(a, s=None, axes=None, norm=None):
"""Compute the N-dimensional FFT for real input.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape to use from the input. If ``s`` is not
given, the lengths of the input along the axes specified by
``axes`` are used.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other. The length of the
last axis transformed will be ``s[-1]//2+1``.
.. seealso:: :func:`numpy.fft.rfftn`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_FORWARD, 'R2C')
def irfftn(a, s=None, axes=None, norm=None):
"""Compute the N-dimensional inverse FFT for real input.
Args:
a (cupy.ndarray): Array to be transform.
s (None or tuple of ints): Shape of the output. If ``s`` is not given,
they are determined from the lengths of the input along the axes
specified by ``axes``.
axes (tuple of ints): Axes over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``s`` and type
will convert to complex if the input is other. If ``s`` is not
given, the length of final transformed axis of output will be
``2*(m-1)`` where `m` is the length of the final transformed axis
of the input.
.. seealso:: :func:`numpy.fft.irfftn`
"""
return _fft(a, s, axes, norm, cufft.CUFFT_INVERSE, 'C2R')
def hfft(a, n=None, axis=-1, norm=None):
"""Compute the FFT of a signal that has Hermitian symmetry.
Args:
a (cupy.ndarray): Array to be transform.
n (None or int): Length of the transformed axis of the output. For
``n`` output points, ``n//2+1`` input points are necessary. If
``n`` is not given, it is determined from the length of the input
along the axis specified by ``axis``.
axis (int): Axis over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``n`` and type
will convert to complex if the input is other. If ``n`` is not
given, the length of the transformed axis is ``2*(m-1)`` where `m`
is the length of the transformed axis of the input.
.. seealso:: :func:`numpy.fft.hfft`
"""
a = irfft(a.conj(), n, axis)
return a * (a.shape[axis] if norm is None else
cupy.sqrt(a.shape[axis], dtype=a.dtype))
def ihfft(a, n=None, axis=-1, norm=None):
"""Compute the FFT of a signal that has Hermitian symmetry.
Args:
a (cupy.ndarray): Array to be transform.
n (None or int): Number of points along transformation axis in the
input to use. If ``n`` is not given, the length of the input along
the axis specified by ``axis`` is used.
axis (int): Axis over which to compute the FFT.
norm (None or ``"ortho"``): Keyword to specify the normalization mode.
Returns:
cupy.ndarray:
The transformed array which shape is specified by ``n`` and type
will convert to complex if the input is other. The length of the
transformed axis is ``n//2+1``.
.. seealso:: :func:`numpy.fft.ihfft`
"""
if n is None:
n = a.shape[axis]
return rfft(a, n, axis, norm).conj() / (n if norm is None else 1)
def fftfreq(n, d=1.0):
"""Return the FFT sample frequencies.
Args:
n (int): Window length.
d (scalar): Sample spacing.
Returns:
cupy.ndarray: Array of length ``n`` containing the sample frequencies.
.. seealso:: :func:`numpy.fft.fftfreq`
"""
return cupy.hstack((cupy.arange(0, (n - 1) // 2 + 1, dtype=np.float64),
cupy.arange(-(n // 2), 0, dtype=np.float64))) / n / d
def rfftfreq(n, d=1.0):
"""Return the FFT sample frequencies for real input.
Args:
n (int): Window length.
d (scalar): Sample spacing.
Returns:
cupy.ndarray:
Array of length ``n//2+1`` containing the sample frequencies.
.. seealso:: :func:`numpy.fft.rfftfreq`
"""
return cupy.arange(0, n // 2 + 1, dtype=np.float64) / n / d
def fftshift(x, axes=None):
"""Shift the zero-frequency component to the center of the spectrum.
Args:
x (cupy.ndarray): Input array.
axes (int or tuple of ints): Axes over which to shift. Default is
``None``, which shifts all axes.
Returns:
cupy.ndarray: The shifted array.
.. seealso:: :func:`numpy.fft.fftshift`
"""
x = cupy.asarray(x)
if axes is None:
axes = list(six.moves.range(x.ndim))
elif isinstance(axes, np.compat.integer_types):
axes = (axes,)
for axis in axes:
x = cupy.roll(x, x.shape[axis] // 2, axis)
return x
def ifftshift(x, axes=None):
"""The inverse of :meth:`fftshift`.
Args:
x (cupy.ndarray): Input array.
axes (int or tuple of ints): Axes over which to shift. Default is
``None``, which shifts all axes.
Returns:
cupy.ndarray: The shifted array.
.. seealso:: :func:`numpy.fft.ifftshift`
"""
x = cupy.asarray(x)
if axes is None:
axes = list(six.moves.range(x.ndim))
elif isinstance(axes, np.compat.integer_types):
axes = (axes,)
for axis in axes:
x = cupy.roll(x, -(x.shape[axis] // 2), axis)
return x