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#!/usr/bin/env python
#<examples/doc_peakmodels.py>
from numpy import loadtxt
from lmfit.models import LorentzianModel, GaussianModel, VoigtModel
import matplotlib.pyplot as plt
data = loadtxt('test_peak.dat')
x = data[:, 0]
y = data[:, 1]
MODEL = 'gauss'
MODEL = 'loren'
MODEL = 'voigt'
# gamma_free = False
gamma_free = True
if MODEL.lower().startswith('g'):
mod = GaussianModel()
elif MODEL.lower().startswith('l'):
mod = LorentzianModel()
elif MODEL.lower().startswith('v'):
mod = VoigtModel()
pars = mod.guess(y, x=x)
if gamma_free:
pars['gamma'].set(value=0.7, vary=True, expr='')
out = mod.fit(y, pars, x=x)
print(out.fit_report(min_correl=0.25))
plt.plot(x, y, 'b-')
plt.plot(x, out.best_fit, 'r-')
plt.show()
#<end examples/doc_peakmodels.py>
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