Module « scipy.fft »

Fonction fft2 - module scipy.fft

Signature de la fonction fft2

def fft2(x, s=None, axes=(-2, -1), norm=None, overwrite_x=False, workers=None, *, plan=None) 

Description

fft2.__doc__

    Compute the 2-D discrete Fourier Transform

    This function computes the N-D discrete Fourier Transform
    over any axes in an M-D array by means of the
    Fast Fourier Transform (FFT). By default, the transform is computed over
    the last two axes of the input array, i.e., a 2-dimensional FFT.

    Parameters
    ----------
    x : array_like
        Input array, can be complex
    s : sequence of ints, optional
        Shape (length of each transformed axis) of the output
        (``s[0]`` refers to axis 0, ``s[1]`` to axis 1, etc.).
        This corresponds to ``n`` for ``fft(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.
    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
    --------
    ifft2 : The inverse 2-D FFT.
    fft : The 1-D FFT.
    fftn : The N-D FFT.
    fftshift : Shifts zero-frequency terms to the center of the array.
        For 2-D input, swaps first and third quadrants, and second
        and fourth quadrants.

    Notes
    -----
    `fft2` is just `fftn` with a different default for `axes`.

    The output, analogously to `fft`, contains the term for zero frequency in
    the low-order corner of the transformed 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
    the axes, in order of decreasingly negative frequency.

    See `fftn` for details and a plotting example, and `fft` for
    definitions and conventions used.


    Examples
    --------
    >>> import scipy.fft
    >>> x = np.mgrid[:5, :5][0]
    >>> scipy.fft.fft2(x)
    array([[ 50.  +0.j        ,   0.  +0.j        ,   0.  +0.j        , # may vary
              0.  +0.j        ,   0.  +0.j        ],
           [-12.5+17.20477401j,   0.  +0.j        ,   0.  +0.j        ,
              0.  +0.j        ,   0.  +0.j        ],
           [-12.5 +4.0614962j ,   0.  +0.j        ,   0.  +0.j        ,
              0.  +0.j        ,   0.  +0.j        ],
           [-12.5 -4.0614962j ,   0.  +0.j        ,   0.  +0.j        ,
              0.  +0.j        ,   0.  +0.j        ],
           [-12.5-17.20477401j,   0.  +0.j        ,   0.  +0.j        ,
              0.  +0.j        ,   0.  +0.j        ]])