import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
def f_1(x, A, B):
return A * x + B
plt.figure()
拟合点
x0 = [75, 70, 65, 60, 55,50,45,40,35,30]
y0 = [22.44, 22.17, 21.74, 21.37, 20.92,20.67,20.32,20.05,19.84,19.59]
绘制散点
plt.scatter(x0[:], y0[:], 3, "red")
直线拟合与绘制
A1, B1 = optimize.curve_fit(f_1, x0, y0)[0]
x1 = np.arange(30, 75, 0.01)#30和75要对应x0的两个端点，0.01为步长
y1 = A1 * x1 + B1
plt.plot(x1, y1, "blue")
print(A1)
print(B1)
plt.title(" ")
plt.xlabel('t')
plt.ylabel('Mt/g')
plt.show()
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