- 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
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.