Peak fitting
Rampy does not offer a dedicated function for peak fitting. Instead, we invite users to use lmfit or scipy.optimize to perform peak fitting, which is basically the action to fit a model (sum of peaks) to your data.
Rampy offers functions for various peak shapes, including:
gaussian peaks >
rampy.gaussianlorentzian peaks >
rampy.lorentzianpseudo-voigt peaks >
rampy.pseudovoigtpearson7 peaks >
rampy.pearson7
See the help for each function on this website. Those can be used to easily create a model that will be fitted to your spectrum.
We will upload soon an example of Bayesian peak fitting with a function integrated to rampy.
lmfit
We provide an example of peak-fitting with the lmfit for instance. See this notebook for an example of use.
Calculate peak areas
Peak area can be calculated using the rampy.peakarea function. For instance, for a Gaussian peak at 1100 cm-1 with an amplitude of 1.0 and a half-width at half maximum of 25.0, we can do:
position = 1100.
amplitude = 1.0
hwhm = 25.0
area = rp.peakarea("gaussian", amp=amplitude, HWHM=hwhm)
Propagate uncertainties
The best way to propagate the uncertainties of your model is to directly use the uncertainties package, see the docs here.