numpy.fft.irfft2#

fft.irfft2(a, s=None, axes=(-2, -1), norm=None, out=None)[source]#

Computes the inverse of rfft2.

Parameters:

aarray_like: The input array
ssequence of ints, optional: Shape of the real output to the inverse FFT.

Changed in version 2.0: If it is -1, the whole input is used (no padding/trimming).

Deprecated since version 2.0: If s is not None, axes must not be None either.

Deprecated since version 2.0: s must contain only int s, not None values. None values currently mean that the default value for n is used in the corresponding 1-D transform, but this behaviour is deprecated.
axessequence of ints, optional: The axes over which to compute the inverse fft. Default: (-2, -1), the last two axes.

Deprecated since version 2.0: If s is specified, the corresponding axes to be transformed must not be None.
norm{backward, ortho, forward}, optional: 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.

New in version 1.20.0: The backward, forward values were added.
outndarray, optional: If provided, the result will be placed in this array. It should be of the appropriate shape and dtype for the last transformation.

New in version 2.0.0.

Returns:

outndarray: The result of the inverse real 2-D FFT.

See also

rfft2: The forward two-dimensional FFT of real input, of which irfft2 is the inverse.
rfft: The one-dimensional FFT for real input.
irfft: The inverse of the one-dimensional FFT of real input.
irfftn: Compute the inverse of the N-dimensional FFT of real input.

Notes

This is really irfftn with different defaults. For more details see irfftn.

Examples

Try it in your browser!

>>> import numpy as np
>>> a = np.mgrid[:5, :5][0]
>>> A = np.fft.rfft2(a)
>>> np.fft.irfft2(A, s=a.shape)
array([[0., 0., 0., 0., 0.],
       [1., 1., 1., 1., 1.],
       [2., 2., 2., 2., 2.],
       [3., 3., 3., 3., 3.],
       [4., 4., 4., 4., 4.]])

numpy.fft.rfft2

numpy.fft.rfftn