class_docstr: A mixin class to map scalar data to RGBA.
  
  The ScalarMappable applies data normalization before returning RGBA colors
  from the given colormap.
docstr: Set the norm limits for image scaling.
  
  Parameters
  ----------
  vmin, vmax : float
       The limits.
  
       The limits may also be passed as a tuple (*vmin*, *vmax*) as a
       single positional argument.
  
       .. ACCEPTS: (vmin: float, vmax: float)
docstr_tok: ["Set","the","norm","limits","for","image","scaling",".","Parameters","--","--","--","--","--","vmin",",","vmax",":","float","The","limits",".","The","limits","may","also","be","passed","as","a","tuple","(","*","vmin","*",",","*","vmax","*",")","as","a","single","positional","argument",".","..","ACCEPTS",":","(","vmin",":","float",",","vmax",":","float",")"]
code: def set_clim(self, vmin=None, vmax=None):
      """
      Set the norm limits for image scaling.
  
      Parameters
      ----------
      vmin, vmax : float
           The limits.
  
           The limits may also be passed as a tuple (*vmin*, *vmax*) as a
           single positional argument.
  
           .. ACCEPTS: (vmin: float, vmax: float)
      """
      # If the norm's limits are updated self.changed() will be called
      # through the callbacks attached to the norm
      if vmax is None:
          try:
              vmin, vmax = vmin
          except (TypeError, ValueError):
              pass
      if vmin is not None:
          self.norm.vmin = colors._sanitize_extrema(vmin)
      if vmax is not None:
          self.norm.vmax = colors._sanitize_extrema(vmax)
  
imports: from collections.abc import Mapping
  import functools
  import numpy
  from numpy import ma
  import matplotlib
  from matplotlib import _api, colors, cbook, scale
  from matplotlib._cm import datad
  from matplotlib._cm_listed import cmaps
label_desc: Use image node_id 8 for calling the ScalarMappable obj's underlying member method code with example usage: obj.set_clim(vmin, vmax) without return types