simulate.py 文件源码

def calibrateNoise(self):

        bg, bgstd, las, time, conc, ok = CalibrationDialog.setExt()

        _np.asarray(bg)
        _np.asarray(bgstd)
        _np.asarray(las)
        _np.asarray(time)
        _np.asarray(conc)

        x_3d = _np.array([conc, las, time])
        p0 = [1, 1]
        fitParamsBg, fitCovariances = curve_fit(fitFuncBg, x_3d, bg, p0)
        print(' fit coefficients :\n', fitParamsBg)

        # SET VALUES TO PARAMETER
        self.lasercEdit.setValue(fitParamsBg[0])
        self.imagercEdit.setValue(fitParamsBg[1])

        x_3dStd = _np.array([las, time, bg])
        p0S = [1, 1, 1]
        fitParamsStd, fitCovariances = curve_fit(fitFuncStd, x_3dStd, bgstd, p0S)

        print(' fit coefficients2:\n', fitParamsStd)

        self.EquationAEdit.setValue(fitParamsStd[0])
        self.EquationBEdit.setValue(fitParamsStd[1])
        self.EquationCEdit.setValue(fitParamsStd[2])

        # Noise model working point

        figure4 = plt.figure()

        # Background
        bgmodel = fitFuncBg(x_3d, fitParamsBg[0], fitParamsBg[1])
        ax1 = figure4.add_subplot(121)
        ax1.cla()
        ax1.plot(bg, bgmodel, 'o')
        x = _np.linspace(*ax1.get_xlim())
        ax1.plot(x, x)
        title = "Background Model:"
        ax1.set_title(title)

        # Std
        bgmodelstd = fitFuncStd(x_3dStd, fitParamsStd[0], fitParamsStd[1], fitParamsStd[2])
        ax2 = figure4.add_subplot(122)
        ax2.cla()
        ax2.plot(bgstd, bgmodelstd, 'o')
        x = _np.linspace(*ax2.get_xlim())
        ax2.plot(x, x)
        title = "Background Model Std:"
        ax2.set_title(title)

        figure4.show()