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Add code for 1D detector #69

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usov_i merged 118 commits from det1d into master 2020-10-22 12:07:50 +02:00
Conversation 22 Commits 118 Files Changed 15 +171 -817
8 changed files with 171 additions and 817 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)