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Classe « ShortTimeFFT »

Méthode scipy.signal.ShortTimeFFT.istft

Signature de la méthode istft

def istft(self, S: numpy.ndarray, k0: int = 0, k1: int | None = None, *, f_axis: int = -2, t_axis: int = -1) -> numpy.ndarray 

Description

help(ShortTimeFFT.istft)

Inverse short-time Fourier transform.

It returns an array of dimension ``S.ndim - 1``  which is real
if `onesided_fft` is set, else complex. If the STFT is not
`invertible`, or the parameters are out of bounds  a ``ValueError`` is
raised.

Parameters
----------
S
    A complex valued array where `f_axis` denotes the frequency
    values and the `t-axis` dimension the temporal values of the
    STFT values.
k0, k1
    The start and the end index of the reconstructed signal. The
    default (``k0 = 0``, ``k1 = None``) assumes that the maximum length
    signal should be reconstructed.
f_axis, t_axis
    The axes in `S` denoting the frequency and the time dimension.

Notes
-----
It is required that `S` has `f_pts` entries along the `f_axis`. For
the `t_axis` it is assumed that the first entry corresponds to
`p_min` * `delta_t` (being <= 0). The length of `t_axis` needs to be
compatible with `k1`. I.e., ``S.shape[t_axis] >= self.p_max(k1)`` must
hold, if `k1` is not ``None``. Else `k1` is set to `k_max` with::

    q_max = S.shape[t_range] + self.p_min
    k_max = (q_max - 1) * self.hop + self.m_num - self.m_num_mid

The :ref:`tutorial_stft` section of the :ref:`user_guide` discussed the
slicing behavior by means of an example.

See Also
--------
invertible: Check if STFT is invertible.
:meth:`~ShortTimeFFT.stft`: Perform Short-time Fourier transform.
:class:`scipy.signal.ShortTimeFFT`: Class this method belongs to.

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