def irfftn(x, s=None, axes=None, norm=None, overwrite_x=False, *, plan=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.
overwrite_x (bool): If True, the contents of ``x`` can be destroyed.
plan (:class:`cupy.cuda.cufft.PlanNd` or ``None``): a cuFFT plan for
transforming ``x`` over ``axes``, which can be obtained using::
plan = cupyx.scipy.fftpack.get_fft_plan(x, s, axes,
value_type='C2R')
Note that ``plan`` is defaulted to ``None``, meaning CuPy will use
an auto-generated plan behind the scene.
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.
.. warning:: The input array may be modified in CUDA 10.1 and above, even
when `overwrite_x is False`.
.. seealso:: :func:`scipy.fft.irfftn`
"""
s = _assequence(s)
axes = _assequence(axes)
if (10020 >= cupy.cuda.runtime.runtimeGetVersion() >= 10010
and int(cupy.cuda.device.get_compute_capability()) < 70
and _size_last_transform_axis(x.shape, s, axes) == 2):
warnings.warn('Output of irfftn might not be correct due to issue '
'of cuFFT in CUDA 10.1/10.2 on Pascal or older GPUs.')
func = _default_fft_func(x, s, axes, value_type='C2R')
return func(x,
s,
axes,
norm,
cufft.CUFFT_INVERSE,
'C2R',
overwrite_x=overwrite_x,
plan=plan)
def test_irfft2(self, xp, dtype, order, enable_nd):
assert config.enable_nd_planning == enable_nd
if (10020 >= cupy.cuda.runtime.runtimeGetVersion() >= 10010
and int(cupy.cuda.device.get_compute_capability()) < 70 and
_size_last_transform_axis(self.shape, self.s, self.axes) == 2):
raise unittest.SkipTest('work-around for cuFFT issue')
a = testing.shaped_random(self.shape, xp, dtype)
if order == 'F':
a = xp.asfortranarray(a)
out = xp.fft.irfft2(a, s=self.s, axes=self.axes, norm=self.norm)
if xp is np and dtype in [np.float16, np.float32, np.complex64]:
out = out.astype(np.float32)
return out
def irfftn(x, s=None, axes=None, norm=None, overwrite_x=False, *, plan=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.
overwrite_x (bool): If True, the contents of ``x`` can be destroyed.
plan (None): This argument is currently not supported.
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:`scipy.fft.irfftn`
"""
# TODO(leofang): support R2C & C2R plans
if plan is not None:
raise NotImplementedError('irfftn plan is currently not yet supported')
s = _assequence(s)
axes = _assequence(axes)
if (10020 >= cupy.cuda.runtime.runtimeGetVersion() >= 10010
and int(cupy.cuda.device.get_compute_capability()) < 70
and _size_last_transform_axis(x.shape, s, axes) == 2):
warnings.warn('Output of irfftn might not be correct due to issue '
'of cuFFT in CUDA 10.1/10.2 on Pascal or older GPUs.')
func = _default_fft_func(x, s, axes, value_type='C2R')
return func(x, s, axes, norm, cufft.CUFFT_INVERSE, 'C2R',
overwrite_x=overwrite_x)