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#import numpy as np from scipy.optimize import curve_fit import pandas as pd import io import matplotlib.pyplot as plt txt = io.StringIO(""" nth retention 1 100 2 50 3 45 4 40 5 38 6 35 7 33 14 25 30 20 60 15 90 14 120 13 180 13 360 10 """) df = pd.read_csv(txt, sep="\t") df x = np.array(df.nth) y = np.array(df.retention) def func(x, p1, p2, p3, p4, p5, p6): return p1*np.exp(p2*x) + p3*np.exp(p4*x) + p5*np.exp(p6*x) popt, pcov = curve_fit(func, x, y, p0=(0.0, 0.0, 0.0, 0.0, 0.0, 0.0)) plt.plot(x, y, 'b-', label='data') plt.plot(x, func(x, *popt), 'r-', label='fit: p1=%5.3f, p2=%5.3f, p3=%5.3f, p4=%5.3f, p5=%5.3f, p6=%5.3f' % tuple(popt)) plt.xlabel('x') plt.ylabel('y') plt.legend() plt.show() 蟆郁骸
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