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.Rectangle
The matplotlib.patches.Rectangle class is used to rectangle patch to a plot with lower left at xy = (x, y) with specified width, height and rotation angle.
Syntax: class matplotlib.patches.Rectangle(xy, width, height, angle=0.0, **kwargs)
Parameters:
- xy: Lower left point to start the rectangle plotting
- width : width of the rectangle
- height: Height of the rectangle.
- angle: Angle of rotation of the rectangle.
The below table has a list of valid kwargs;
| 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 npimport matplotlib.pyplot as pltfrom matplotlib.patches import Rectangle # The imageX = np.arange(16).reshape(4, 4) # highlight some feature in the# middle boxes.fig = plt.figure() ax = fig.add_subplot(111)ax.imshow(X, cmap = plt.cm.gray, interpolation ='nearest')ax.add_patch( Rectangle((0.5, 0.5), 2, 2, fc ='none', ec ='g', lw = 10) ) plt.show() |
Output:
Example 2:
import matplotlibimport matplotlib.pyplot as plt fig = plt.figure()ax = fig.add_subplot(111) rect1 = matplotlib.patches.Rectangle((-200, -100), 400, 200, color ='green') rect2 = matplotlib.patches.Rectangle((0, 150), 300, 20, color ='pink') rect3 = matplotlib.patches.Rectangle((-300, -50), 40, 200, color ='yellow') ax.add_patch(rect1)ax.add_patch(rect2)ax.add_patch(rect3) plt.xlim([-400, 400])plt.ylim([-400, 400]) plt.show() |
Output:
