DReconvolutionModel.py

#*************************************************************************************************
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#** DLTReconvolution v1.3 (06.12.2019)
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import numpy as np
from scipy.special import beta
from enum import Enum

#list of available models:
class ReconvolutionModel(Enum):
     Gaussian       = 1
     Lorentz_Cauchy = 2
     Pseudovoigt1   = 3
     Pearson7       = 4

#definition of available models:
def Gaussian(x, ampl, sigma, y0, x0, args=()):
    h=np.zeros(x.size)
    N=np.zeros(x.size)
    N=1.0/(sigma*np.sqrt(2*np.pi))
    h=N*np.exp(-0.5*((x-x0)/sigma)**2);
    return ampl*h+y0

def Lorentz_Cauchy(x, ampl, s, y0, x0, args=()):
    h=np.zeros(x.size)
    h=s/(np.pi*((x-x0)*(x-x0) + s*s))
    return ampl*h+y0

def Pseudovoigt1(x, ampl, a, sigma, s, y0, x0, args=()):
    G=np.zeros(x.size)
    L=np.zeros(x.size)

    G=(1.0/(sigma*np.sqrt(2*np.pi)))*np.exp(-0.5*((x-x0)/sigma)**2)
    L=s/(np.pi*((x-x0)**2 + s*s))
    return ampl*(a*G+(1-a)*L)+y0

def Pearson7(x, ampl, alpha, m, y0, x0, args=()):
    h=np.zeros(x.size)
    h=(1/(alpha*beta(m-0.5,0.5)))*(1+((x-x0)/alpha)**2)**(-m)
    return ampl*h+y0