matplotlib.pyplot.close()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。Pyplot中可以使用的绘图有直线图、轮廓图、直方图、散点图、三维图等。

matplotlib.pyplot.close()函数

使用matplotlib库的pyplot模块中的close()函数关闭图形窗口。

语法:matplotlib.pyplot.close(图=没有)

参数:该方法只接受一个参数。

这个参数接受以下值:

None:该值将关闭当前图形

图:该值将关闭给定的图实例

int:该值将关闭一个数字

这个值将关闭一个图形名

‘ all ‘:该值将关闭所有数字

返回:此方法不返回任何值。

下面的例子演示了matplotlib.pyplot.close()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
from matplotlib.colors import LogNorm
  
  
dx, dy = 0.015, 0.05
x = np.arange(-4.0, 4.0, dx)
y = np.arange(-4.0, 4.0, dy)
X, Y = np.meshgrid(x, y)
   
extent = np.min(x), np.max(x), np.min(y), np.max(y)
   
Z1 = np.add.outer(range(8), range(8)) % 2
plt.imshow(Z1, cmap ="binary_r", 
           interpolation ='nearest',
           extent = extent, 
           alpha = 1)
   
def geeks(x, y):
    return (1 - x / 2 + x**5 + y**6) * np.exp(-(x**2 + y**2))
   
Z2 = geeks(X, Y)
   
x = plt.imshow(Z2, cmap ="Greens", 
               alpha = 0.7, 
               interpolation ='bilinear',
               extent = extent)
plt.close()
plt.title('matplotlib.pyplot.close Example')
plt.show()

输出:

matplotlib.pyplot.close()函数

示例2

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LogNorm
import matplotlib.tri as tri
      
dx, dy = 0.015, 0.05
x = np.arange(-4.0, 4.0, dx)
y = np.arange(-4.0, 4.0, dy)
X, Y = np.meshgrid(x, y)
   
extent = np.min(x), np.max(x), np.min(y), np.max(y)
   
Z1 = np.add.outer(range(8), range(8)) % 2
plt.imshow(Z1, cmap ="binary_r", 
           interpolation ='nearest',
           extent = extent,
           alpha = 1)
   
def geeks(x, y):
    return (1 - x / 2 + x**5 + y**6) * np.exp(-(x**2 + y**2))
   
Z2 = geeks(X, Y)
   
x = plt.imshow(Z2, cmap ="Greens",
               alpha = 0.7, 
               interpolation ='bilinear',
               extent = extent)
plt.close(1)
ang = 40
rad = 10
radm = 0.35
radii = np.linspace(radm, 0.95, rad)
     
angles = np.linspace(0, 0.5 * np.pi, ang)
angles = np.repeat(angles[...,
                          np.newaxis], 
                   rad, axis = 1)
  
angles[:, 1::2] += np.pi / ang
     
x = (radii * np.cos(angles)).flatten()
y = (radii * np.sin(angles)).flatten()
z = (np.sin(4 * radii) * np.cos(4 * angles)).flatten()
     
triang = tri.Triangulation(x, y)
triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1),
                         y[triang.triangles].mean(axis = 1))
                < radm)
     
tpc = plt.tripcolor(triang, z,
                    shading ='flat')
  
plt.colorbar(tpc)
plt.plasma()
  
plt.title('matplotlib.pyplot.close() Example')
plt.show()