class_docstr: Calculate and show a spectrogram
  
  Parameters
  ----------
  x : array-like
      1D signal to operate on. ``If len(x) < n_fft``, x will be
      zero-padded to length ``n_fft``.
  n_fft : int
      Number of FFT points. Much faster for powers of two.
  step : int | None
      Step size between calculations. If None, ``n_fft // 2``
      will be used.
  fs : float
      The sample rate of the data.
  window : str | None
      Window function to use. Can be ``'hann'`` for Hann window, or None
      for no windowing.
  normalize : bool
      Normalization of spectrogram values across frequencies.
  color_scale : {'linear', 'log'}
      Scale to apply to the result of the STFT.
      ``'log'`` will use ``10 * log10(power)``.
  cmap : str
      Colormap name.
  clim : str | tuple
      Colormap limits. Should be ``'auto'`` or a two-element tuple of
      min and max values.
docstr: The step of fft window
docstr_tok: ["The","step","of","fft","window"]
code: def step(self):
      """The step of fft window"""
      if self._step is None:
          return self._n_fft // 2
      else:
          return self._step
  
imports: import numpy
  from .image import ImageVisual
  from ..util.fourier import stft, fft_freqs
label_desc: Use image node_id 7 for calling the SpectrogramVisual obj's underlying member method code with example usage: obj.step() and returns: unknown, self