import numpy as np
from matplotlib import cbook
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 `.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 `.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 `~.Axes.pcolor`.
"""
cbook._check_in_list(['flat', 'gouraud'], shading=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[~tri.mask]
collection = PolyCollection(verts, **kwargs)
collection.set_alpha(alpha)
collection.set_array(C)
cbook._check_isinstance((Normalize, None), norm=norm)
collection.set_cmap(cmap)
collection.set_norm(norm)
collection._scale_norm(norm, vmin, vmax)
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
