code: from . import axes_size as Size
  from .axes_divider import Divider, SubplotDivider, LocatableAxes, \
       make_axes_locatable
  from .axes_grid import Grid, ImageGrid, AxesGrid
  #from axes_divider import make_axes_locatable
  from matplotlib.cbook import warn_deprecated
  warn_deprecated(since='2.1',
                  name='mpl_toolkits.axes_grid',
                  alternative='mpl_toolkits.axes_grid1 and'
                              ' mpl_toolkits.axisartist, which provide'
                              ' the same functionality',
                  obj_type='module')
   import numpy as np
  
  from matplotlib.collections import PolyCollection, TriMesh
  from matplotlib.colors import Normalize
  from matplotlib.tri.triangulation import Triangulation
  
  
  def tripcolor(ax, *args, alpha=1.0, norm=None, cmap=None, vmin=None,
                vmax=None, shading='flat', facecolors=None, **kwargs):
      """
      Create a pseudocolor plot of an unstructured triangular grid.
  
      The triangulation can be specified in one of two ways; either::
  
        tripcolor(triangulation, ...)
  
      where triangulation is a :class:`matplotlib.tri.Triangulation`
      object, or
  
      ::
  
        tripcolor(x, y, ...)
        tripcolor(x, y, triangles, ...)
        tripcolor(x, y, triangles=triangles, ...)
        tripcolor(x, y, mask=mask, ...)
        tripcolor(x, y, triangles, mask=mask, ...)
  
      in which case a Triangulation object will be created.  See
      :class:`~matplotlib.tri.Triangulation` for a explanation of these
      possibilities.
  
      The next argument must be *C*, the array of color values, either
      one per point in the triangulation if color values are defined at
      points, or one per triangle in the triangulation if color values
      are defined at triangles. If there are the same number of points
      and triangles in the triangulation it is assumed that color
      values are defined at points; to force the use of color values at
      triangles use the kwarg ``facecolors=C`` instead of just ``C``.
  
      *shading* may be 'flat' (the default) or 'gouraud'. If *shading*
      is 'flat' and C values are defined at points, the color values
      used for each triangle are from the mean C of the triangle's
      three points. If *shading* is 'gouraud' then color values must be
      defined at points.
  
      The remaining kwargs are the same as for
      :meth:`~matplotlib.axes.Axes.pcolor`.
      """
      if shading not in ['flat', 'gouraud']:
          raise ValueError("shading must be one of ['flat', 'gouraud'] "
                           "not {0}".format(shading))
  
      tri, args, kwargs = Triangulation.get_from_args_and_kwargs(*args, **kwargs)
  
      # C is the colors array defined at either points or faces (i.e. triangles).
      # If facecolors is None, C are defined at points.
      # If facecolors is not None, C are defined at faces.
      if facecolors is not None:
          C = facecolors
      else:
          C = np.asarray(args[0])
  
      # If there are a different number of points and triangles in the
      # triangulation, can omit facecolors kwarg as it is obvious from
      # length of C whether it refers to points or faces.
      # Do not do this for gouraud shading.
      if (facecolors is None and len(C) == len(tri.triangles) and
              len(C) != len(tri.x) and shading != 'gouraud'):
          facecolors = C
  
      # Check length of C is OK.
      if ((facecolors is None and len(C) != len(tri.x)) or
              (facecolors is not None and len(C) != len(tri.triangles))):
          raise ValueError('Length of color values array must be the same '
                           'as either the number of triangulation points '
                           'or triangles')
  
      # Handling of linewidths, shading, edgecolors and antialiased as
      # in Axes.pcolor
      linewidths = (0.25,)
      if 'linewidth' in kwargs:
          kwargs['linewidths'] = kwargs.pop('linewidth')
      kwargs.setdefault('linewidths', linewidths)
  
      edgecolors = 'none'
      if 'edgecolor' in kwargs:
          kwargs['edgecolors'] = kwargs.pop('edgecolor')
      ec = kwargs.setdefault('edgecolors', edgecolors)
  
      if 'antialiased' in kwargs:
          kwargs['antialiaseds'] = kwargs.pop('antialiased')
      if 'antialiaseds' not in kwargs and ec.lower() == "none":
          kwargs['antialiaseds'] = False
  
      if shading == 'gouraud':
          if facecolors is not None:
              raise ValueError('Gouraud shading does not support the use '
                               'of facecolors kwarg')
          if len(C) != len(tri.x):
              raise ValueError('For gouraud shading, the length of color '
                               'values array must be the same as the '
                               'number of triangulation points')
          collection = TriMesh(tri, **kwargs)
      else:
          # Vertices of triangles.
          maskedTris = tri.get_masked_triangles()
          verts = np.stack((tri.x[maskedTris], tri.y[maskedTris]), axis=-1)
  
          # Color values.
          if facecolors is None:
              # One color per triangle, the mean of the 3 vertex color values.
              C = C[maskedTris].mean(axis=1)
          elif tri.mask is not None:
              # Remove color values of masked triangles.
              C = C.compress(1-tri.mask)
  
          collection = PolyCollection(verts, **kwargs)
  
      collection.set_alpha(alpha)
      collection.set_array(C)
      if norm is not None and not isinstance(norm, Normalize):
          raise ValueError("'norm' must be an instance of 'Normalize'")
      collection.set_cmap(cmap)
      collection.set_norm(norm)
      if vmin is not None or vmax is not None:
          collection.set_clim(vmin, vmax)
      else:
          collection.autoscale_None()
      ax.grid(False)
  
      minx = tri.x.min()
      maxx = tri.x.max()
      miny = tri.y.min()
      maxy = tri.y.max()
      corners = (minx, miny), (maxx, maxy)
      ax.update_datalim(corners)
      ax.autoscale_view()
      ax.add_collection(collection)
      return collection
  
apis: matplotlib.cbook.warn_deprecated
apis: matplotlib.collections.TriMesh matplotlib.tri.triangulation.Triangulation.get_from_args_and_kwargs matplotlib.collections.PolyCollection numpy.asarray numpy.stack