fit_logic_standalone.py 文件源码

def fit_data():
    data=np.loadtxt('data.dat')
    print(data)
    params = dict()
    params["c"] = {"min" : -np.inf,"max" : np.inf}
    result = qudi_fitting.make_lorentzian_fit(axis=data[:,0], data=data[:,3], add_parameters=params)
    print(result.fit_report())
    plt.plot(data[:,0],-data[:,3]+2,"b-o",label="data mean")
#    plt.plot(data[:,0],data[:,1],label="data")
#    plt.plot(data[:,0],data[:,2],label="data")
    plt.plot(data[:,0],-result.best_fit+2,"r-",linewidth=2.,label="fit")
#    plt.plot(data[:,0],result.init_fit,label="init")
    plt.xlabel("time (ns)")
    plt.ylabel("polarization transfer (arb. u.)")
    plt.legend(loc=1)
#    plt.savefig("pol20_24repetition_pol.pdf")
#    plt.savefig("pol20_24repetition_pol.png")
    plt.show()
    savedata=[[data[ii,0],-data[ii,3]+2,-result.best_fit[ii]+2] for ii in range(len(data[:,0]))]
    np.savetxt("pol_data_fit.csv",savedata)
#    print(result.params)

    print(result.params)