docs: def plot_connectivity_significance(s, fs=2, freq_range=(-np.inf, np.inf), diagonal=0, border=False, fig=None):
      """Plot significance.
  
      Significance is drawn as a background image where dark vertical stripes indicate freuquencies where a evaluates to
      True.
  
      Parameters
      ----------
      a : array, shape (n_channels, n_channels, n_fft), dtype bool
          Significance
      fs : float
          Sampling frequency
      freq_range : (float, float)
          Frequency range to plot
      diagonal : {-1, 0, 1}
          If diagonal == -1 nothing is plotted on the diagonal (a[i,i,:] are not plotted),
          if diagonal == 0, a is plotted on the diagonal too (all a[i,i,:] are plotted),
          if diagonal == 1, a is plotted on the diagonal only (only a[i,i,:] are plotted)
      border : bool
          If border == true the leftmost column and the topmost row are left blank
      fig : Figure object, optional
          Figure to plot into. If set to `None`, a new figure is created.
  
      Returns
      -------
      fig : Figure object
          The figure into which was plotted.
      """
  
      a = np.atleast_3d(s)
      [_, m, f] = a.shape
      freq = np.linspace(0, fs / 2, f)
  
      left = max(freq_range[0], freq[0])
      right = min(freq_range[1], freq[-1])
  
      imext = (freq[0], freq[-1], -1e25, 1e25)
  
      if fig is None:
          fig = new_figure()
  
      axes = []
      for i in range(m):
          if diagonal == 1:
              jrange = [i]
          elif diagonal == 0:
              jrange = range(m)
          else:
              jrange = [j for j in range(m) if j != i]
          for j in jrange:
              if border:
                  ax = fig.add_subplot(m+1, m+1, j + (i+1) * (m+1) + 2)
              else:
                  ax = fig.add_subplot(m, m, j + i * m + 1)
              axes.append((i, j, ax))
              ax.imshow(s[i, j, np.newaxis], vmin=0, vmax=2, cmap='binary', aspect='auto', extent=imext, zorder=-999)
  
              ax.xaxis.set_major_locator(MaxNLocator(max(1, 7 - m)))
              ax.yaxis.set_major_locator(MaxNLocator(max(1, 7 - m)))
              ax.set_xlim(left, right)
  
              if 0 < i < m - 1:
                  ax.set_xticks([])
              if 0 < j < m - 1:
                  ax.set_yticks([])
  
              if j == 0:
                  ax.yaxis.tick_left()
              if j == m-1:
                  ax.yaxis.tick_right()
  
      _plot_labels(fig,
                   {'x': 0.5, 'y': 0.025, 's': 'frequency (Hz)', 'horizontalalignment': 'center'},
                   {'x': 0.05, 'y': 0.5, 's': 'magnitude', 'horizontalalignment': 'center', 'rotation': 'vertical'})
  
      return fig