matplotlib.pyplot.gca()函数

Matplotlib是Python中的一个库，它是NumPy库的数值-数学扩展。Pyplot是一个基于状态的Matplotlib模块接口，该模块提供了一个类似matlab的接口。

matplotlib.pyplot.gca()函数

使用matplotlib库的pyplot模块中的gca()函数获取与给定关键字args匹配的当前图形上的当前axis实例，或创建一个。

语法:matplotlib.pyplot.gca(**kwargs)

参数:此方法不接受任何参数。

返回:此方法不返回任何值。

下面的例子演示了matplotlib.pyplot.gca()函数在matplotlib.pyplot中的作用:

示例1

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.gridspec as gridspec
from mpl_toolkits.axes_grid1 import make_axes_locatable
 
 
plt.close('all')
arr = np.arange(100).reshape((10, 10))
fig = plt.figure(figsize =(4, 4))
im = plt.imshow(arr,
                interpolation ="none",
                cmap ="plasma")
 
divider = make_axes_locatable(plt.gca())
cax = divider.append_axes("left",
                          "15 %",
                          pad ="30 %")
 
plt.colorbar(im, cax = cax)
 
fig.suptitle('matplotlib.pyplot.gca() function\
Example\n\n', fontweight ="bold")
plt.show()

输出:

示例2

# Implementation of matplotlib function
import matplotlib.pyplot as plt
from matplotlib.tri import Triangulation
from matplotlib.patches import Polygon
import numpy as np
  
 
def update_polygon(tri):
     
    if tri == -1:
        points = [0, 0, 0]
    else:
        points = triang.triangles[tri]
         
    xs = triang.x[points]
    ys = triang.y[points]
    polygon.set_xy(np.column_stack([xs, ys]))
  
  
def motion_notify(event):
     
    if event.inaxes is None:
        tri = -1
    else:
        tri = trifinder(event.xdata, event.ydata)
         
    update_polygon(tri)
    plt.title('matplotlib.pyplot.gca() function \
    Example\n\n Potion number : % i' % tri,
              fontweight ="bold")
     
    event.canvas.draw()
 
ang = 3
radi = 8
radii = np.linspace(0.25, 0.95, radi)
res = np.linspace(0, 4 * np.pi, ang)
res = np.repeat(res[..., np.newaxis], radi, axis = 1)
res[:, 1::2] += np.pi / ang
 
x = (radii * np.cos(2 * res)).flatten()
y = (radii * np.sin(2 * res)).flatten()
triang = Triangulation(x, y)
triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1),
                         y[triang.triangles].mean(axis = 1))
                < 0.25)
  
trifinder = triang.get_trifinder()
  
plt.subplot(111, aspect ='equal')
plt.triplot(triang, 'go-')
polygon = Polygon([[0, 0], [0, 0]],
                  facecolor ='r')
update_polygon(-1)
 
plt.gca().add_patch(polygon)
plt.gcf().canvas.mpl_connect('motion_notify_event',
                             motion_notify)
  
plt.show()

输出: