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)