fit_static

fit static: fitting static spectrum with theoretically calculated line spectrum broadened by spectral line shape v: voigt profile, g: gaussian, l: lorenzian, It uses lmfit python package to fit experimental spectrum and estimates the error bound of broadening and peak parameter

Note

  1. Currently it uses linear line to correct baseline of experimental spectrum.

  2. The unit between calculated line shape spectrum and experimental spectrum should be same.

  • usage: fit_static.py [-h] [-ls {v,g,l}] [–fwhm_G FWHM_G] [–fwhm_L FWHM_L] [–no_base] [–scale_energy] [-o OUT] [–fix_fwhm_G] [–fix_fwhm_L] prefix num_scan peak_file peak_factor

  • positional arguments:

    • prefix prefix for experimental spectrum files It will read prefix_i.txt files

    • num_scan the number of static peak scan files

    • peak_file filename for theoretical line shape spectrum

    • peak_factor parameter to match descrepency between thoretical spectrum and experimental spectrum

  • optional arguments:

    • -h, –help show this help message and exit

    • -ls {v,g,l}, –line_shape {v,g,l} line shape of spectrum

      1. v: voigt profile

      2. g: gaussian shape

      3. l: lorenzian shape

    • –fwhm_G FWHM_G full width at half maximum for gaussian shape It would be not used when you set lorenzian line shape

    • –fwhm_L FWHM_L full width at half maximum for lorenzian shape It would be not used when you use gaussian line shape

    • –no_base Do not include linear base line during fitting process

    • –scale_energy Scaling the energy of peak instead of shifting peak position to match experimental spectrum

    • -o OUT, –out OUT prefix for output files

    • –fix_fwhm_G fix gaussian fwhm value

    • –fix_fwhm_L fix lorenzian fwhm value

    • –slow use slower but robust global optimization algorithm