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# numpy.fft.rfft2

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

  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.

      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.

    axes sequence of ints, optional

      Axes over which to compute the FFT. Default: `(-2, -1)`.

      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.

    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`).

      New in version 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        ]])