import numpy as np
import matplotlib.pyplot as plt
def f_1(x, A, B):
return Ax + B
def plot_test():
plt.figure()
x=[2.4,1.5,2.4,1.8,1.8,2.9,1.2,3,1.2]
y=[2.9,2.1,2.3,2.1,1.8,2.7,1.5,2.9,1.5]
plt.scatter(x0[:], y0[:], 25, "red")
A1, B1 = optimize.curve_fit(f_1, x0, y0)[0]
x1 = np.arange(0, 6, 0.01)
y1 = A1x1 + B1
plt.plot(x1, y1, "blue")
plt.title("test")
plt.xlabel('x')
plt.ylabel('y')
plt.show()
对不起,我不会,求上面解答
变量使用前一定要确认是否定义
import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
def f_1(x, A, B):
return A*x + B #公式需要修正
def plot_test():
plt.figure()
x0=[2.4,1.5,2.4,1.8,1.8,2.9,1.2,3,1.2] #x0没有定义,或则将x变为x0
y0=[2.9,2.1,2.3,2.1,1.8,2.7,1.5,2.9,1.5]#同上
plt.scatter(x0[:], y0[:], 25, "red")
A1, B1 = optimize.curve_fit(f_1, x0, y0)[0]
x1 = np.arange(0, 6, 0.01)
y1 = A1*x1 + B1#公式需要修正
plt.plot(x1, y1, "blue")
plt.title("test")
plt.xlabel('x')
plt.ylabel('y')
plt.show()
plot_test()