Module « scipy.fft »

Fonction idstn - module scipy.fft

Signature de la fonction idstn

def idstn(x, type=2, s=None, axes=None, norm=None, overwrite_x=False, workers=None) 

Description

idstn.__doc__

    Return multidimensional Discrete Sine Transform along the specified axes.

    Parameters
    ----------
    x : array_like
        The input array.
    type : {1, 2, 3, 4}, optional
        Type of the DST (see Notes). Default type is 2.
    s : int or array_like of ints or None, optional
        The shape of the result.  If both `s` and `axes` (see below) are None,
        `s` is ``x.shape``; if `s` is None but `axes` is not None, then `s` is
        ``numpy.take(x.shape, axes, axis=0)``.
        If ``s[i] > x.shape[i]``, the ith dimension is padded with zeros.
        If ``s[i] < x.shape[i]``, the ith dimension is truncated to length
        ``s[i]``.
        If any element of `s` is -1, the size of the corresponding dimension of
        `x` is used.
    axes : int or array_like of ints or None, optional
        Axes over which the IDST is computed. If not given, the last ``len(s)``
        axes are used, or all axes if `s` is also not specified.
    norm : {"backward", "ortho", "forward"}, optional
        Normalization mode (see Notes). Default is "backward".
    overwrite_x : bool, optional
        If True, the contents of `x` can be destroyed; the default is False.
    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.

    Returns
    -------
    y : ndarray of real
        The transformed input array.

    See Also
    --------
    dstn : multidimensional DST

    Notes
    -----
    For full details of the IDST types and normalization modes, as well as
    references, see `idst`.

    Examples
    --------
    >>> from scipy.fft import dstn, idstn
    >>> rng = np.random.default_rng()
    >>> y = rng.standard_normal((16, 16))
    >>> np.allclose(y, idstn(dstn(y)))
    True