code: def variance(self, bins=None, low=None, high=None, nbins=500,
                   log=False, norm=False, density=False):
          
          from ..frequencyseries import SpectralVariance
          return SpectralVariance.from_spectrogram(
              self, bins=bins, low=low, high=high, nbins=nbins, log=log,
              norm=norm, density=density)
docs: Calculate the `SpectralVariance` of this `Spectrogram`.
  
          Parameters
          ----------
          bins : `~numpy.ndarray`, optional, default `None`
              array of histogram bin edges, including the rightmost edge
          low : `float`, optional, default: `None`
              left edge of lowest amplitude bin, only read
              if ``bins`` is not given
          high : `float`, optional, default: `None`
              right edge of highest amplitude bin, only read
              if ``bins`` is not given
          nbins : `int`, optional, default: `500`
              number of bins to generate, only read if ``bins`` is not
              given
          log : `bool`, optional, default: `False`
              calculate amplitude bins over a logarithmic scale, only
              read if ``bins`` is not given
          norm : `bool`, optional, default: `False`
              normalise bin counts to a unit sum
          density : `bool`, optional, default: `False`
              normalise bin counts to a unit integral
  
          Returns
          -------
          specvar : `SpectralVariance`
              2D-array of spectral frequency-amplitude counts
  
          See Also
          --------
          :func:`numpy.histogram`
              for details on specifying bins and weights