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Update fit2.py

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JakHolzer 2020-09-11 15:02:34 +02:00 committed by Ivan Usov
parent 087fe0fe2f
commit fe5ed4b987
1 changed files with 0 additions and 23 deletions
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pyzebra/fit2.py
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@ -1,12 +1,9 @@
from lmfit import minimize, Parameters, Model
from lmfit.models import LinearModel, LorentzianModel, GaussianModel
import matplotlib.pyplot as plt
from scipy.integrate import simps
import scipy as sc
from scipy import integrate
import numpy as np
from time import sleep
def fitccl(data, keys, guess, vary, constraints_min, constraints_max, numfit_min=None, numfit_max=None):
"""Made for fitting of ccl date where 1 peak is expected. Allows for combination of gaussian, lorentzian and linear model combination
@ -113,26 +110,6 @@ def fitccl(data, keys, guess, vary, constraints_min, constraints_max, numfit_min
print(result.params['g_cen'].value)
num_int_area = simps(y[numfit_min:numfit_max], x[numfit_min:numfit_max])
num_int_bacground = integrate.quad(background, numfit_min, numfit_max, args=(result.params['slope'].value,result.params['intercept'].value))
plt.plot(x, y, 'b', label='Original data')
plt.plot(x, comps['gaussian'], 'r--', label='Gaussian component')
plt.fill_between(x, comps['gaussian'], facecolor="red", alpha=0.4)
plt.plot(x, comps['lorentzian'], 'b--', label='Lorentzian component')
plt.fill_between(x, comps['lorentzian'], facecolor="blue", alpha=0.4)
plt.plot(x, comps['background'], 'g--', label='Line component')
plt.fill_between(x, comps['background'], facecolor="green", alpha=0.4)
#plt.plot(x[numfit_min:numfit_max],y[numfit_min:numfit_max], 'vy', markersize=7)
plt.fill_between(x[numfit_min:numfit_max], y[numfit_min:numfit_max], facecolor="yellow", alpha=0.4, label='Integrated area')
#plt.plot(x, result.init_fit, 'k--', label='initial fit')
plt.plot(x, result.best_fit, 'k-', label='Best fit')
plt.title('%s \n Gaussian: centre = %9.4f, width = %9.4f, amp = %9.4f \n'
'Lorentzian: centre, %9.4f, width = %9.4f, amp = %9.4f \n'
'background: slope = %9.4f, intercept = %9.4f, int_area %9.4f' % (keys, result.params['g_cen'].value, result.params['g_width'].value,
result.params['g_amp'].value, result.params['l_cen'].value, result.params['l_width'].value,
result.params['l_amp'].value, result.params['slope'].value, result.params['intercept'].value, num_int_area))
plt.legend(loc='best')
plt.show()
d = {}
for pars in result.params:
d[str(pars)] = (result.params[str(pars)].value, result.params[str(pars)].vary)