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.
matplotlib.patches.PathPatch
The matplotlib.patches.PathPatch
class used to draw general polycurve path patch.
Syntax: class matplotlib.patches.PathPatch(path, **kwargs)
Parameter:
- path: path is a
matplotlib.path.Path
object.
The below tables gives the list of valid kwargs arguments:
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 |
Example 1:
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() |
Output:
Example 2:
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() |
Output: