Matplotlib.patches.PathPatch in Python
Last Updated :
27 Apr, 2020
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Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
Example 1:
Python3 1==
Output:
Example 2:
Python3 1==
Output:
matplotlib.patches.PathPatch
The matplotlib.patches.PathPatch
class used to draw general polycurve path patch.
Syntax: class matplotlib.patches.PathPatch(path, **kwargs) Parameter:The below tables gives the list of valid kwargs arguments:
- path: path is a
matplotlib.path.Path
object.
PROPERTY | DESCRIPTION |
---|---|
agg_filter | a filter function that takes a (m, n, 3) float array and a dpi value that returns a (m, n, 3) array |
alpha | float or None |
animated | bool |
antialiased or aa | unknown |
capstyle | {‘butt’, ’round’, ‘projecting’} |
clip_box | Bbox |
clip_on | bool |
clip_path | [(Path, Transform)|Patch|None] |
color | color or sequence of rgba tuples |
contains | callable |
edgecolor or ec or edgecolors | color or None or ‘auto’ |
facecolor or fc or facecolors | color or None |
figure | figure |
fill | bool |
gid | str |
hatch | {‘/’, ‘\’, ‘|’, ‘-‘, ‘+’, ‘x’, ‘o’, ‘O’, ‘.’, ‘*’} |
in_layout | bool |
joinstyle | {‘miter’, ’round’, ‘bevel’} |
linestyle or ls | {‘-‘, ‘–‘, ‘-.’, ‘:’, ”, (offset, on-off-seq), …} |
linewidth or linewidths or lw | float or None |
path_effects | AbstractPathEffect |
picker | None or bool or float or callable |
path_effects | AbstractPathEffect |
picker | float or callable[[Artist, Event], Tuple[bool, dict]] |
rasterized | bool or None |
sketch_params | (scale: float, length: float, randomness: float) |
snap | bool or None |
transform | matplotlib.transforms.Transform |
url | str |
visible | bool |
zorder | float |
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
from matplotlib.path import Path
from matplotlib.patches import PathPatch
delta = 0.025
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
Z = (Z1 - Z2) * 2
path = Path([[0, 1], [1, 0], [0, -1], [-1, 0], [0, 1]])
patch = PathPatch(path, facecolor ='none')
fig, ax = plt.subplots()
ax.add_patch(patch)
im = ax.imshow(Z, interpolation ='bilinear', cmap = cm.gray,
origin ='lower', extent =[-3, 3, -3, 3],
clip_path = patch, clip_on = True)
im.set_clip_path(patch)
plt.show()

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.path import Path
from matplotlib.patches import PathPatch
fig = plt.figure()
ax = fig.add_subplot(111, aspect ='equal')
path = Path([[0, 0], [0, 1], [1, 0], [0, 0]])
patch = PathPatch(path, facecolor ='none')
ax.add_patch(patch)
Z, Z2 = np.meshgrid(np.linspace(0, 1), np.linspace(0, 1))
im = plt.imshow(Z-Z2,
interpolation ='bilinear',
cmap = plt.cm.RdYlGn,
origin ='lower',
extent =[0, 1, 0, 1],
clip_path = patch,
clip_on = True)
im.set_clip_path(patch)
ax.set_xlim((0, 1))
ax.set_ylim((0, 1))
plt.show()
