# -*- coding: utf-8 -*-

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import leastsq
%pylab inline
plt.rcParams['font.sans-serif']=['simhei']
plt.rcParams['axes.unicode_minus']=Falsedr = np.array([22,28,33,39,44,50,55,61,66,72,77,83,88])
v = np.array([20., 25., 30., 35., 40., 45., 50., 55., 60., 65., 70., 75., 80.])
db = np.array([20,28,40.5,52.5,72,92.5,118,148.5,182,220.5,266,318,376])
d = np.array([42,56,73.5,91.5,116,142.5,173,209.5,248,292.5,343,401,464])x = v
y = drdef func(p):k = preturn y - k*xr = leastsq(func,[np.sum(dr)/np.sum(v)])
k = r[0]
print('k=',k)plt.scatter(x,k*x,label = '拟合解')
plt.plot(x,k*x)
plt.scatter(x,y,label='观测解')
plt.plot(x,y)
plt.xlabel('dr')
plt.ylabel('v')
plt.title('最小二乘法则应用')
plt.legend()
plt.show()

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.optimize import leastsq
%pylab inline
plt.rcParams['font.sans-serif']=['simhei']
plt.rcParams['axes.unicode_minus']=Falsedr = np.array([22,28,33,39,44,50,55,61,66,72,77,83,88])
v = np.array([20., 25., 30., 35., 40., 45., 50., 55., 60., 65., 70., 75., 80.])
db = np.array([20,28,40.5,52.5,72,92.5,118,148.5,182,220.5,266,318,376])
d = np.array([42,56,73.5,91.5,116,142.5,173,209.5,248,292.5,343,401,464])x = v**2
y = dbdef func(p):k = preturn y - k*xr = leastsq(func,[np.sum(db)/np.sum(v**2)])
k = r[0]
print('k=',k)plt.scatter(x,k*x,label = '拟合解')
plt.plot(x,k*x)
plt.scatter(x,y,label='观测解')
plt.plot(x,y)
plt.xlabel('dr')
plt.ylabel('v')
plt.title('最小二乘法则应用')
plt.legend()
plt.show()