import numpy as np
import matplotlib.pyplot as plt
path='H:'#圖片輸出路徑
fig=plt.figure()#創(chuàng)建畫板
ax=fig.add_subplot()
x1 = np.linspace(0, 10, 50)
y1 =(x1*x1)
ax.plot(x1,y1,label='y=x$^2$')
ax.legend()#添加圖例
fig.savefig(path+'輸出圖片.svg',format='svg',dpi=150)#輸出

import numpy as np
import matplotlib.pyplot as plt
import cv2
fig, ax = plt.subplots()
plt.figure(1)
image=cv2.imread("2.jpg")
# you can specify the marker size two ways directly:
# 這樣一個一個像素太慢了故而要將同樣顏色的坐標進行分類處理
color_class=[]
x_y=dict()
for x,w in enumerate(image):
    for y,colors in enumerate(w):
        if colors.tolist() not in color_class:
            s=image[:, :, :1] == colors[0]
            s1=image[:, :, 1:2] == colors[1]
            s2=image[:, :, 2:3] == colors[2]
            ss=s*s1*s2
            color_class.append(colors.tolist())
            x_y[len(color_class)]=np.where(ss.reshape((ss.shape[0],ss.shape[1])))
        print(x,y)
for i ,colors in enumerate(color_class):
    a, b = x_y[i + 1]
    plt.plot(a,b, ".",color=[colors[2]/255,colors[1]/255,colors[0]/255], markersize=1, label='a')  # blue circle with size 20
fig.savefig('scatter.svg', dpi=200, format='svg')
if __name__ == '__main__':
    pass