Python Matplotlib.pyplot.gcf()用法及代碼示例

import numpy as np 
from matplotlib.backends.backend_agg import FigureCanvasAgg 
import matplotlib.pyplot as plot 
  
plot.plot([2, 3, 4]) 
  
# implementation of the  
# matplotlib.pyplot.gcf() 
# function 
figure = plot.gcf().canvas 
  
ag = figure.switch_backends(FigureCanvasAgg) 
ag.draw() 
A = np.asarray(ag.buffer_rgba()) 
  
# Pass off to PIL. 
from PIL import Image 
img = Image.fromarray(A) 
  
# show image 
img.show()

import matplotlib.pyplot as plt 
from matplotlib.tri import Triangulation 
from matplotlib.patches import Polygon 
import numpy as np 
  
# helper function to update  
# the polygon 
def polygon_updater(tr):
    if tr == -1:
        points = [0, 0, 0] 
    else:
        points = tri.triangles[tr] 
    x_axis = tri.x[points] 
    y_axis = tri.y[points] 
    polygon.set_xy(np.column_stack([x_axis, y_axis])) 
  
# helper function to set the motion  
# of polygon 
def motion_handler(e):
    if e.inaxes is None:
        tr = -1
    else:
        tr = trifinder(e.xdata, e.ydata) 
    polygon_updater(tr) 
    e.canvas.draw() 
  
  
# Making the  Triangulation. 
all_angles = 16
all_radii = 5
minimum_radii = 0.25
radii = np.linspace(minimum_radii, 0.95, all_radii) 
triangulation_angles = np.linspace(0, 2 * np.pi, 
                                   all_angles, 
                                   endpoint = False) 
  
triangulation_angles = np.repeat(triangulation_angles[..., 
                                                      np.newaxis], 
                                 all_radii, axis = 1) 
  
triangulation_angles[:, 1::2] += np.pi / all_angles 
a = (radii * np.cos(triangulation_angles)).flatten() 
b = (radii * np.sin(triangulation_angles)).flatten() 
tri = Triangulation(a, b) 
tri.set_mask(np.hypot(a[tri.triangles].mean(axis = 1), 
                         b[tri.triangles].mean(axis = 1)) 
                < minimum_radii) 
  
# Useing TriFinder object from  
# Triangulation 
trifinder = tri.get_trifinder() 
  
# Setting up the plot and the callbacks. 
plt.subplot(111, aspect ='equal') 
plt.triplot(tri, 'g-') 
  
 # dummy data for (x-axis, y-axis) 
polygon = Polygon([[0, 0], [0, 0]],  
                  facecolor ='b')  
polygon_updater(-1) 
plt.gca().add_patch(polygon) 
  
# implementation of the matplotlib.pyplot.gcf() function 
plt.gcf().canvas.mpl_connect('motion_notification', 
                             motion_handler) 
plt.show()