fit_logic_standalone.py 文件源码

def gaussianlinearoffset_testing_data():

    x = np.linspace(0, 5, 30)
    x_nice=np.linspace(0, 5, 101)

    mod_final,params = qudi_fitting.make_gaussianwithslope_model()

    data=np.loadtxt("./../1D_shllow.csv")
    data_noisy=data[:,1]
    data_fit=data[:,3]
    x=data[:,2]


    update=dict()
    update["slope"]={"min":-np.inf,"max":np.inf}
    update["offset"]={"min":-np.inf,"max":np.inf}
    update["sigma"]={"min":-np.inf,"max":np.inf}
    update["center"]={"min":-np.inf,"max":np.inf}
    update["amplitude"]={"min":-np.inf,"max":np.inf}
    result=qudi_fitting.make_gaussianwithslope_fit(x_axis=x, data=data_noisy, add_params=update)
#
##
#    gaus=gaussian(3,5)
#    qudi_fitting.data_smooth = filters.convolve1d(qudi_fitting.data_noisy, gaus/gaus.sum(),mode='mirror')

    plt.plot(x,data_noisy,label="data")
    plt.plot(x,data_fit,"k",label="old fit")
    plt.plot(x,result.init_fit,'-g',label='init')
    plt.plot(x,result.best_fit,'-r',label='fit')
    plt.legend()
    plt.show()
    print(result.fit_report())