Module « scipy.fft »

Fonction ifft2 - module scipy.fft

Signature de la fonction ifft2

def ifft2(x, s=None, axes=(-2, -1), norm=None, overwrite_x=False, workers=None, *, plan=None) 

Description

ifft2.__doc__

    Compute the 2-D inverse discrete Fourier Transform.

    This function computes the inverse of the 2-D discrete Fourier
    Transform over any number of axes in an M-D array by means of
    the Fast Fourier Transform (FFT). In other words, ``ifft2(fft2(x)) == x``
    to within numerical accuracy. By default, the inverse transform is
    computed over the last two axes of the input array.

    The input, analogously to `ifft`, should be ordered in the same way as is
    returned by `fft2`, i.e., it should have the term for zero frequency
    in the low-order corner of the two axes, the positive frequency terms in
    the first half of these axes, the term for the Nyquist frequency in the
    middle of the axes and the negative frequency terms in the second half of
    both axes, in order of decreasingly negative frequency.

    Parameters
    ----------
    x : array_like
        Input array, can be complex.
    s : sequence of ints, optional
        Shape (length of each axis) of the output (``s[0]`` refers to axis 0,
        ``s[1]`` to axis 1, etc.). This corresponds to `n` for ``ifft(x, n)``.
        Along each 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 `axes` is used.  See notes for issue on `ifft` zero padding.
    axes : sequence of ints, optional
        Axes over which to compute the FFT. If not given, the last two
        axes are used.
    norm : {"backward", "ortho", "forward"}, optional
        Normalization mode (see `fft`). Default is "backward".
    overwrite_x : bool, optional
        If True, the contents of `x` can be destroyed; the default is False.
        See :func:`fft` for more details.
    workers : int, optional
        Maximum number of workers to use for parallel computation. If negative,
        the value wraps around from ``os.cpu_count()``.
        See :func:`~scipy.fft.fft` for more details.
    plan : object, optional
        This argument is reserved for passing in a precomputed plan provided
        by downstream FFT vendors. It is currently not used in SciPy.

        .. versionadded:: 1.5.0

    Returns
    -------
    out : complex ndarray
        The truncated or zero-padded input, transformed along the axes
        indicated by `axes`, or the last two axes if `axes` is not given.

    Raises
    ------
    ValueError
        If `s` and `axes` have different length, or `axes` not given and
        ``len(s) != 2``.
    IndexError
        If an element of `axes` is larger than than the number of axes of `x`.

    See Also
    --------
    fft2 : The forward 2-D FFT, of which `ifft2` is the inverse.
    ifftn : The inverse of the N-D FFT.
    fft : The 1-D FFT.
    ifft : The 1-D inverse FFT.

    Notes
    -----
    `ifft2` is just `ifftn` with a different default for `axes`.

    See `ifftn` for details and a plotting example, and `fft` for
    definition and conventions used.

    Zero-padding, analogously with `ifft`, is performed by appending zeros to
    the input along the specified dimension. Although this is the common
    approach, it might lead to surprising results. If another form of zero
    padding is desired, it must be performed before `ifft2` is called.

    Examples
    --------
    >>> import scipy.fft
    >>> x = 4 * np.eye(4)
    >>> scipy.fft.ifft2(x)
    array([[1.+0.j,  0.+0.j,  0.+0.j,  0.+0.j], # may vary
           [0.+0.j,  0.+0.j,  0.+0.j,  1.+0.j],
           [0.+0.j,  0.+0.j,  1.+0.j,  0.+0.j],
           [0.+0.j,  1.+0.j,  0.+0.j,  0.+0.j]])