Closed
Description
Bug summary
The Path objects produced by tricontourf to draw its contours lead to spurious polygons when running the respective to_polygons method.
Code for reproduction
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.tri
# Example for TriContour based from:
# https://matplotlib.org/2.0.2/examples/pylab_examples/tricontour_smooth_delaunay.html
def experiment_res(x, y):
""" An analytic function representing experiment results """
x = 2.*x
r1 = np.sqrt((0.5 - x)**2 + (0.5 - y)**2)
theta1 = np.arctan2(0.5 - x, 0.5 - y)
r2 = np.sqrt((-x - 0.2)**2 + (-y - 0.2)**2)
theta2 = np.arctan2(-x - 0.2, -y - 0.2)
z = (4*(np.exp((r1/10)**2) - 1)*30. * np.cos(3*theta1) +
(np.exp((r2/10)**2) - 1)*30. * np.cos(5*theta2) +
2*(x**2 + y**2))
return (np.max(z) - z)/(np.max(z) - np.min(z))
n = 200
random_gen = np.random.mtrand.RandomState(seed=127260)
x = random_gen.uniform(-1., 1., size=n)
y = random_gen.uniform(-1., 1., size=n)
v = experiment_res(x, y)
## triangulate
tri = mpl.tri.Triangulation(x, y)
mask = mpl.tri.TriAnalyzer(tri).get_flat_tri_mask(min_circle_ratio=.01)
tri.set_mask(mask)
## refine triangular mesh
refiner = mpl.tri.UniformTriRefiner(tri)
triFiner, vFiner = refiner.refine_field(v, subdiv=2) # uses CubicTriInterpolator
## plot the mesh
plt.close('all')
plt.triplot(tri, color='k', lw=.8)
plt.triplot(triFiner, color='k', alpha=.3, lw=.5)
plt.show()
## plot and create TriCounterSet object
levels = [.7, .9, 1]
cmap = mpl.cm.plasma
plt.close('all')
cl = plt.tricontour(triFiner, vFiner, levels=levels, colors='k', linewidths=2, linestyles='--')
cf = plt.tricontourf(triFiner, vFiner, levels=levels, cmap=cmap, extend='both', alpha=.8)
_ = [collection.set_edgecolor("face") for collection in cf.collections] # https://stackoverflow.com/a/73805556/921580
plt.triplot(tri, color='k', lw=1.5, alpha=.1) # refined mesh
plt.triplot(triFiner, color='k', lw=.5, alpha=.1) # original mesh
cb = plt.colorbar(cf)
plt.show()
## retrieve contours from TriContourSet (paths) and convert to polygons
for i in range(len(cf.collections)):
plt.gca().set_xlim(-1.1, 1.1)
plt.gca().set_ylim(-1.1, 1.1)
[plt.gca().add_patch(
mpl.patches.PathPatch(
cf.collections[i].get_paths()[j],
facecolor=cf.collections[i].get_facecolor()
)
) for j in range(len(cf.collections[i].get_paths()))]
[plt.plot(*list(zip(*p)), c='red', ls='--')
for path in cf.collections[i].get_paths()
for p in path.to_polygons()
]
if i == (len(cf.collections) - 2):
plt.savefig('bug_actual_outcome.png')
plt.show()
## compare path vertices with output from to_polygons method
path = cf.collections[-2].get_paths()[0]
print("\npath vertices and codes:\n", path)
print("\npath.to_polygons() = \n", path.to_polygons())Actual outcome
Expected outcome
Additional information
The issue seems to be related to the Path object and its to_polygons method. More specifically the problem may happen when a Path contains multiple polylines but is defined without the CLOSEPOLY codes ending each polyline. When producing contour plots the code can cope with this data without problems, but the to_polygons method cannot.
I have tested in both 3.4.1 and 3.0.2 versions and both have the same problem.
I have a fix where I defined a function path2polygons:
def path2polygons(path):
assert isinstance(path, mpl.path.Path), f"Type of input is {type(path)} instead of Path."
codesOld = path.codes[path.codes != mpl.path.Path.CLOSEPOLY]
vertsOld = path.vertices[path.codes != mpl.path.Path.CLOSEPOLY]
jj = np.append(np.flatnonzero(codesOld == path.MOVETO), [len(codesOld)])
verts, codes = [], []
for ji, je in zip(jj[:-1], jj[1:]):
codes.extend( [mpl.path.Path.MOVETO]
+ [mpl.path.Path.LINETO]*(je - ji - 1)
+ [mpl.path.Path.CLOSEPOLY]
)
verts.extend( list(vertsOld[ji:je]) + [vertsOld[ji]] )
return mpl.path.Path(verts, codes).to_polygons()but is not tested with other Path codes such as CURVE3 and CURVE4.
Operating system
Debian 10
Matplotlib Version
3.4.1
Matplotlib Backend
TkAgg
Python version
3.7.3
Jupyter version
No response
Installation
pip
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