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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

help(scipy.fft.fft2)

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 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
>>> import numpy as np
>>> 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        ]])

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