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scipy.signal.ShortTimeFFT.

# nearest_k_p

ShortTimeFFT.nearest_k_p(k, left=True)

  Return nearest sample index k_p for which `t[k_p] == t[p]` holds.

  The nearest next smaller time sample p (where `t[p]` is the center position of the window of the p-th slice) is `p_k = k // hop`. If `hop` is a divisor of k then k is returned. If left is set then `p_k * hop` is returned else `(p_k+1) * hop`.

  This method can be used to slice an input signal into chunks for calculating the STFT and iSTFT incrementally.

  Parameters:
    k int

      Sample index for which the nearest slice center index is sought.

    left bool, optional

      If `True` then the nearest smaller index is returned, else the nearest larger index is returned. Defaults to `True`.

  Returns:
    int

      Nearest sample index k_p for which `t[k_p] == t[p]` holds.

  See also

  `delta_t`

    Time increment of STFT (`hop*T`)

  `hop`

    Time increment in signal samples for sliding window.

  `T`

    Sampling interval of input signal and of the window (`1/fs`).

  `fs`

    Sampling frequency (being `1/T`)

  `t`

    Times of STFT for an input signal with n samples.

  `ShortTimeFFT`

    Class this method belongs to.