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Module « numpy.fft »

Fonction irfft2 - module numpy.fft

Signature de la fonction irfft2

def irfft2(a, s=None, axes=(-2, -1), norm=None, out=None) 

Description

help(numpy.fft.irfft2)

Computes the inverse of `rfft2`.

Parameters
----------
a : array_like
    The input array
s : sequence of ints, optional
    Shape of the real output to the inverse FFT.

    .. versionchanged:: 2.0

        If it is ``-1``, the whole input is used (no padding/trimming).

    .. deprecated:: 2.0

        If `s` is not ``None``, `axes` must not be ``None`` either.

    .. deprecated:: 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.

axes : sequence of ints, optional
    The axes over which to compute the inverse fft.
    Default: ``(-2, -1)``, the last two axes.

    .. deprecated:: 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.

    .. versionadded:: 1.20.0

        The "backward", "forward" values were added.

out : ndarray, optional
    If provided, the result will be placed in this array. It should be
    of the appropriate shape and dtype for the last transformation.

    .. versionadded:: 2.0.0

Returns
-------
out : ndarray
    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
--------
>>> 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.]])

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