How to access the information after the fitting?

[nicocopez]

This might rather be a question about coding in python than ramanchada2. But, how can I access the information after I do
fitres = spe.fit_peak_multimodel(profile='Gaussian', candidates=peak_candidates, no_fit=False) ?

I see I can get a summary of the parameters if I do: fitres.to_dataframe_peaks()

I can get fit statistics and variables for every peak if I do fitres[i], where i would be the peak 0, 1, 2,...

I get plots of the peak, fitting and residual if I do fitres[i].plot()

and I can get the values of the best fit and residuals if I do fitres[0].best_fit and fitres[0].residual

But how do I get the x axis for these fitres[0].best_fit and fitres[0].residual?

what other operations can I do over fitres to get what information? Where could I see this?

Thank you!

[georgievgeorgi]

fitres[i] is of type lmfit.model.ModelResult. Documentation for lmfit library is available here.

I didn't know to to access the x-values (those provided during fit) so i found out that it is available in dictionary of user-provided keywords.
You can reproduce the plot by:

ax = spe.plot()
ax.plot(fitres[1].userkws['x'], fitres[1].best_fit)

Anyway, usually one needs to compare the result with a known y-values at fixed x-position or x-positions may be manually generated.

fitres[1].eval(x=np.arange(100, 1000))

I always generated new x-values based on the FWHM / STDEV of leftmost and rightmost peaks of the group.