【绘图】【python】曲线的拟合，函数的拟合

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import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
 
#直线方程函数
def f_1(x, A, B):
    return A*x + B
 
#二次曲线方程
def f_2(x, A, B, C):
    return A*x*x + B*x + C
 
#三次曲线方程
def f_3(x, A, B, C, D):
    return A*x*x*x + B*x*x + C*x + D
 
def plot_test():
 
    plt.figure()
 
    #拟合点
    x0 = [1, 2, 3, 4, 5]
    y0 = [1, 3, 8, 18, 36]
 
    #绘制散点
    plt.scatter(x0[:], y0[:], 25, "red")
 
    #直线拟合与绘制
    A1, B1 = optimize.curve_fit(f_1, x0, y0)[0]
    x1 = np.arange(0, 6, 0.01)
    y1 = A1*x1 + B1
    plt.plot(x1, y1, "blue")
 
    #二次曲线拟合与绘制
    A2, B2, C2 = optimize.curve_fit(f_2, x0, y0)[0]
    x2 = np.arange(0, 6, 0.01)
    y2 = A2*x2*x2 + B2*x2 + C2 
    plt.plot(x2, y2, "green")
 
    #三次曲线拟合与绘制
    A3, B3, C3, D3= optimize.curve_fit(f_3, x0, y0)[0]
    x3 = np.arange(0, 6, 0.01)
    y3 = A3*x3*x3*x3 + B3*x3*x3 + C3*x3 + D3 
    plt.plot(x3, y3, "purple")
 
    plt.title("test")
    plt.xlabel('x')
    plt.ylabel('y')
 
    plt.show()
 
plot_test()