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Module « numpy.fft »

Fonction rfft2 - module numpy.fft

Signature de la fonction rfft2

def rfft2(a, s=None, axes=(-2, -1), norm=None, out=None) 

Description

help(numpy.fft.rfft2)

Compute the 2-dimensional FFT of a real array.

Parameters
----------
a : array
    Input array, taken to be real.
s : sequence of ints, optional
    Shape of the 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
    Axes over which to compute the FFT. Default: ``(-2, -1)``.

    .. 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 : complex ndarray, optional
    If provided, the result will be placed in this array. It should be
    of the appropriate shape and dtype for the last inverse transform.
    incompatible with passing in all but the trivial ``s``).

    .. versionadded:: 2.0.0

Returns
-------
out : ndarray
    The result of the real 2-D FFT.

See Also
--------
rfftn : Compute the N-dimensional discrete Fourier Transform for real
        input.

Notes
-----
This is really just `rfftn` with different default behavior.
For more details see `rfftn`.

Examples
--------
>>> import numpy as np
>>> a = np.mgrid[:5, :5][0]
>>> np.fft.rfft2(a)
array([[ 50.  +0.j        ,   0.  +0.j        ,   0.  +0.j        ],
       [-12.5+17.20477401j,   0.  +0.j        ,   0.  +0.j        ],
       [-12.5 +4.0614962j ,   0.  +0.j        ,   0.  +0.j        ],
       [-12.5 -4.0614962j ,   0.  +0.j        ,   0.  +0.j        ],
       [-12.5-17.20477401j,   0.  +0.j        ,   0.  +0.j        ]])

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