Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.
Matplotlib.axis.Axis.get_clip_box() Function
The Axis.get_clip_box() function in axis module of matplotlib library is used to get the clipbox..
Syntax: Axis.get_clip_box(self)
Parameters: This method does not accepts any parameter.
Return value: This method return the clipbox.
Below examples illustrate the matplotlib.axis.Axis.get_clip_box() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import numpy as np from matplotlib.patches import Ellipse delta = 45.0 angles = np.arange(0, 360 + delta, delta) ells = [Ellipse((2, 2), 5, 2, a) for a in angles] fig, ax = plt.subplots() print("Value Return by get_clip_box()") for e in ells: e.set_clip_box(ax.bbox) print(Axis.get_clip_box(e)) e.set_alpha(0.1) ax.add_artist(e) plt.xlim(-1, 5) plt.ylim(-1, 5) fig.suptitle("""matplotlib.axis.Axis.get_clip_box() function Example\n""", fontweight ="bold") plt.show() |
Output:
Value Return by get_clip_box()
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import numpy as np from matplotlib.patches import Ellipse NUM = 200 ells = [Ellipse(xy = np.random.rand(2) * 10, width = np.random.rand(), height = np.random.rand(), angle = np.random.rand() * 360) for i in range(NUM)] fig, ax = plt.subplots(subplot_kw ={'aspect': 'equal'}) print("Value Return by get_clip_box()") x = 0 for e in ells: ax.add_artist(e) e.set_clip_box(ax.bbox) e.set_alpha(np.random.rand()) e.set_facecolor(np.random.rand(4)) if x<2: print(Axis.get_clip_box(e)) x+= 1 ax.set_xlim(3, 7) ax.set_ylim(3, 7) fig.suptitle("""matplotlib.axis.Axis.get_clip_box() function Example\n""", fontweight ="bold") plt.show() |
Output:
Value Return by get_clip_box()
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
TransformedBbox(
Bbox(x0=0.125, y0=0.10999999999999999, x1=0.9, y1=0.88),
BboxTransformTo(
TransformedBbox(
Bbox(x0=0.0, y0=0.0, x1=6.4, y1=4.8),
Affine2D(
[[100. 0. 0.]
[ 0. 100. 0.]
[ 0. 0. 1.]]))))
