- cupyx.scipy.fftpack.get_fft_plan(a, shape=None, axes=None, value_type='C2C')#
Generate a CUDA FFT plan for transforming up to three axes.
a (cupy.ndarray) – Array to be transform, assumed to be either C- or F- contiguous.
shape (None or tuple of ints) – Shape of the transformed axes of the output. If
shapeis not given, the lengths of the input along the axes specified by
axes (None or int or tuple of int) –
The axes of the array to transform. If None, it is assumed that all axes are transformed.
Currently, for performing N-D transform these must be a set of up to three adjacent axes, and must include either the first or the last axis of the array.
value_type (str) –
The FFT type to perform. Acceptable values are:
’C2C’: complex-to-complex transform (default)
’R2C’: real-to-complex transform
’C2R’: complex-to-real transform
a cuFFT plan for either 1D transform (
cupy.cuda.cufft.Plan1d) or N-D transform (
The returned plan can not only be passed as one of the arguments of the functions in
cupyx.scipy.fftpack, but also be used as a context manager for both
x = cupy.random.random(16).reshape(4, 4).astype(complex) plan = cupyx.scipy.fftpack.get_fft_plan(x) with plan: y = cupy.fft.fftn(x) # alternatively: y = cupyx.scipy.fftpack.fftn(x) # no explicit plan is given! # alternatively: y = cupyx.scipy.fftpack.fftn(x, plan=plan) # pass plan explicitly
In the first case, no cuFFT plan will be generated automatically, even if
cupy.fft.config.enable_nd_planning = Trueis set.
If this function is called under the context of
set_cufft_callbacks(), the generated plan will have callbacks enabled.
This API is a deviation from SciPy’s, is currently experimental, and may be changed in the future version.