直接导入matplotlib库。
import matplotlib.pyplot as plt
用list分别准备横坐标和纵坐标的数据。
X1 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y1 = [971,1344,1953,3064,4766,15522,4389,2615,1696,1210,798]
X2 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y2 = [554,861,1238,1979,3206,10663,2916,1639,1047,704,489]
X3 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y3 = [363,547,801,1254,2205,7535,1984,1115,677,464,340]
X4 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y4 = [293,478,681,1070,1819,6563,1750,953,583,410,287]
直接绘制折线图。
plt.figure()
# X1的分布
plt.plot(X1, Y1, label="X1", color="#FF3B1D", marker='*', linestyle="-")
# X2的分布
plt.plot(X2, Y2,label="X2", color="#3399FF", marker='o', linestyle="-")
# X3的分布
plt.plot(X3, Y3, label="X3", color="#F9A602", marker='s', linestyle="-")
# X4的分布
plt.plot(X4, Y4, label="X4", color="#13C4A3", marker='d', linestyle="-")
# plt.gca().xaxis.set_major_locator(ticker.MultipleLocator(1)) # 将横坐标的值全部显示出来
X_labels = ['-5','-4','-3','-2','-1','0','1','2','3','4','5']
plt.xticks(X1,X_labels,rotation=0)
plt.legend()
plt.title("Lake.bmp")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
上述结果亲测有效。
import matplotlib.pyplot as plt
X1 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y1 = [971,1344,1953,3064,4766,15522,4389,2615,1696,1210,798]
X2 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y2 = [554,861,1238,1979,3206,10663,2916,1639,1047,704,489]
X3 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y3 = [363,547,801,1254,2205,7535,1984,1115,677,464,340]
X4 = [-5,-4,-3,-2,-1,0,1,2,3,4,5]
Y4 = [293,478,681,1070,1819,6563,1750,953,583,410,287]
plt.figure()
# X1的分布
plt.plot(X1, Y1, label="X1", color="#FF3B1D", marker='*', linestyle="-")
# X2的分布
plt.plot(X2, Y2,label="X2", color="#3399FF", marker='o', linestyle="-")
# X3的分布
plt.plot(X3, Y3, label="X3", color="#F9A602", marker='s', linestyle="-")
# X4的分布
plt.plot(X4, Y4, label="X4", color="#13C4A3", marker='d', linestyle="-")
# plt.gca().xaxis.set_major_locator(ticker.MultipleLocator(1)) # 将横坐标的值全部显示出来
X_labels = ['-5','-4','-3','-2','-1','0','1','2','3','4','5']
plt.xticks(X1,X_labels,rotation=0)
plt.legend()
plt.title("Lake.bmp")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()