func(a, s=None, axes=None)
The axis along which the FFT is applied must have only one chunk. To change the array's chunking use dask.Array.rechunk.
The numpy.fft.rfftn docstring follows below:
Compute the N-dimensional discrete Fourier Transform for real input.
This function computes the N-dimensional discrete Fourier Transform over any number of axes in an M-dimensional real array by means of the Fast Fourier Transform (FFT). By default, all axes are transformed, with the real transform performed over the last axis, while the remaining transforms are complex.
The transform for real input is performed over the last transformation axis, as by :None:None:`rfft`, then the transform over the remaining axes is performed as by :None:None:`fftn`. The order of the output is as for :None:None:`rfft` for the final transformation axis, and as for :None:None:`fftn` for the remaining transformation axes.
See fft
for details, definitions and conventions used.
Input array, taken to be real.
Shape (length along each transformed axis) to use from the input. ( s[0]
refers to axis 0, s[1]
to axis 1, etc.). The final element of s corresponds to n for rfft(x, n)
, while for the remaining axes, it corresponds to n for fft(x, n)
. Along any axis, if the given shape is smaller than that of the input, the input is cropped. If it is larger, the input is padded with zeros. if s is not given, the shape of the input along the axes specified by :None:None:`axes` is used.
Axes over which to compute the FFT. If not given, the last len(s)
axes are used, or all axes if s is also not specified.
Normalization mode (see numpy.fft
). Default is "backward". Indicates which direction of the forward/backward pair of transforms is scaled and with what normalization factor.
The "backward", "forward" values were added.
If s and :None:None:`axes` have different length.
If an element of :None:None:`axes` is larger than than the number of axes of a.
The truncated or zero-padded input, transformed along the axes indicated by :None:None:`axes`, or by a combination of s and a, as explained in the parameters section above. The length of the last axis transformed will be s[-1]//2+1
, while the remaining transformed axes will have lengths according to s, or unchanged from the input.
Wrapping of numpy.fft.rfftn
fft
The one-dimensional FFT, with definitions and conventions used.
fftn
The n-dimensional FFT.
irfftn
The inverse of :None:None:`rfftn`, i.e. the inverse of the n-dimensional FFT of real input.
rfft
The one-dimensional FFT of real input.
rfft2
The two-dimensional FFT of real input.
>>> a = np.ones((2, 2, 2)) # doctest: +SKIPThis example is valid syntax, but we were not able to check execution
... np.fft.rfftn(a) # doctest: +SKIP array([[[8.+0.j, 0.+0.j], # may vary [0.+0.j, 0.+0.j]], [[0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j]]])
>>> np.fft.rfftn(a, axes=(2, 0)) # doctest: +SKIP array([[[4.+0.j, 0.+0.j], # may vary [4.+0.j, 0.+0.j]], [[0.+0.j, 0.+0.j], [0.+0.j, 0.+0.j]]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
dask.array.ufunc.frompyfunc
dask.array.gufunc.apply_gufunc
dask.array.core._pass_extra_kwargs
dask.array.routines.apply_over_axes
dask.utils.Dispatch.register
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