python双曲线拟合
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待拟合函数 y = alpha * pow(x, beta)
输入: x数组,y数组
输出: alpha,beta,相关系数R2
from scipy.optimize import leastsq from pylab import * import numpy as np xdata = np.array([4.79616, 11.63, 37.5534, 105.414]) ydata = np.array([1.33921, 0.755319, 0.34085, 0.0554339]) # Define function for calculating a power law powerlaw = lambda x, alpha, beta: alpha * (x ** beta) logx = log10(xdata) logy = log10(ydata) # define our (line) fitting function fitfunc = lambda p, x: p[0] + p[1] * x errfunc = lambda p, x, y: (y - fitfunc(p, x)) pinit = [1.0, -1.0] out, cov, infodict, mesg, ier = leastsq(errfunc, pinit, args = (logx, logy), full_output=1) beta = out[1] alpha = 10.0 ** out[0] ss_err = (infodict[‘fvec‘] ** 2).sum() ss_tot = ((ydata - ydata.mean()) ** 2).sum() r2 = 1 - (ss_err / ss_tot) print(‘Alpha: %f, Beta: %f‘ % (alpha, beta)) print (‘R2: %f‘ % r2)
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