code: def _get_cmap_data(data, kwargs) -> Tuple[colors.Normalize, np.ndarray]:
      
      norm = kwargs.pop("cmap_normalize", None)
      if norm == "log":
          cmap_max = kwargs.pop("cmap_max", data.max())
          cmap_min = kwargs.pop("cmap_min", data[data > 0].min())
          norm = colors.LogNorm(cmap_min, cmap_max)
      elif not norm:
          cmap_max = kwargs.pop("cmap_max", data.max())
          cmap_min = kwargs.pop("cmap_min", 0)
          if cmap_min == "min":
              cmap_min = data.min()
          norm = colors.Normalize(cmap_min, cmap_max, clip=True)
      return norm, norm(data)
docs: Get normalized values to be used with a colormap.
  
      Parameters
      ----------
      data : array_like
      cmap_min : Optional[float] or "min"
          By default 0. If "min", minimum value of the data.
      cmap_max : Optional[float]
          By default, maximum value of the data
      cmap_normalize : str or colors.Normalize
  
      Returns
      -------
      normalizer : colors.Normalize
      normalized_data : array_like