#Fityk shirley background free#

Average the values forВ a few points (1-5)В at the lowestВ BE. I worked around that by using negative numbers but it's not pretty and slowed the fitting considerably. However, I tried to yield the inverted integration by use of the Reverse function but the integration seems to go after the x values. I replaced it with the integration and the scaling problem seems solved. I suppose the main problem was a wave-scaling caused normalisation issue in the summation. The above does not seem to have a major effect but I might oversee something here. Thus I was hoping a flexible fitting that was not attached to the x axis extreme points would allow for a more correct determination of the asymmetry. *** I have some spectra with strongly asymmetric peaks leading to an overlap of the tails and background at the high BE end of the spectra. This goes hand in hand with the answer to question three: Plus, I hoped it would implicitly be taken care of in the subsequent iteration steps. * I did not consider subracting a baseline early on because with the noise I did not see a proper way to determine it. Setscale / P x xminM, xdeltaNew, '', shirley_bgДЇor ( j=nbxValM- 2 j >- 1 j-= 1 ) // -2 accounting for start at 0 and avoid max due to j+1 Model += LorentzForDS ( x, 0, pw, pw, pw ) // x, offset, amp, pos, fwhm Model = LorentzForDS ( x, 0, pw, pw, pw ) Setscale / P x xminM, xdeltaNew, '', model Variable nbxValM = floor ( abs (xmaxM-xminM ) / xdeltaNew ) + 1 Variable xmaxM = DimOffset (yw, 0 ) + DimDelta (yw, 0 ) * DimSize (yw, 0 ) + xhalfB Variable xminM = DimOffset (yw, 0 ) - xhalfB Extend the model area by half a Gaussian to avoid deconvolution effects Variable sumB = sum (broadening, - inf, inf ) SetScale / P x -xhalfB, xdeltaNew, '', broadeningД«roadening = Gauss ( x, 0, 1, 0, fwhmB ) // Gauss of amplitude 1 NbxValB = min (nbxValB, 2 *nbxValRef ) // limit the resolution of broadening Variable nbxValRef = DimSize (yw, 0 ) *oversampling // 'regular' size of the model without broadening addition

Variable nbxValB = 2 * floor (xhalfB / xdeltaNew ) + 1 Variable xhalfB = ( 1 / 2 ) * fwhmB * RangeIncreaseFactor // half energy range of wave Variable xdeltaNew = DimDelta (yw, 0 ) / oversampling // xw resolution of the fit wave Variable RangeIncreaseFactor = 5 // if G_FWHM=0.1eV, output wave spans RIF*0.1eV CurveFitDialog/ pw = Gaussian_broadening_FWHM_eV_instrumental) CurveFitDialog/ pw = Scaling_Factor_Shirley CurveFitDialog/ pw = Constant_background

CurveFitDialog/ Independent Variables 1 CurveFitDialog/ f(x) = L1+L2+shirley+offset

Return offset + amplitude * exp (- (x_val-peakpos )^ 2 / ( 2 *sigma^ 2 ) )ДЇunction Voigt2S_fit (pw, yw, xw ) : FitFunc Variable sigma = fwhm / ( 2 * sqrt ( 2 * ln ( 2 ) ) ) Variable x_val, offset, amplitude, peakpos, fwhm -ДЇunction Gauss (x_val, offset, amplitude, peakpos, fwhm )

#Fityk shirley background free#

Feel free to give advice for improvement independent of solving the problem. The fit function I use is based on others I found and adapted. All other parameters seem to still converge somewhat reasonably though in the second case the amplitudes were comparably well fitted but the numbers unexpectedly changed. In the shown case the scaling is about a factor of two too big, in a different case (fit withВ Doniach-Sunjic lineshapes) it was about 2.5 times too small. I attached an image showing the original converged fit, the converged fit with a Shirley background and a fit with identical fit parameters but adapted scaling factor. I used a scaling factor to resize the background, which turns out to be way off. I am trying to fit XPS data with a custom all-at-once fit function and while the basic fit generally seems to converge to the extend the model allows, adding a Shirley background (based on the model wave) shows unexpected behaviour. Wide-Angle Neutron Spin Echo Spectroscopy.