import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from __future__ import division
from scipy.optimize import least_squares
import scipy.odr as odr
import matplotlib.pyplot as plt

nPoints = 4

AlphaArr = np.zeros(4)
PubArr = np.zeros(4)
AlphaErr = np.zeros(4)
PubErr = np.zeros(4)

AlphaArr = [popt1[1], popt2[1], popt3[1], popt4[1]]
PubArr = [8.04, 8.63, 7.47, 6.40]
AlphaErr = [FWHM1_1,FWHM1_2,FWHM1_3,FWHM1_4]
PubErr = [0.1,0.1,0.1,0.1]

xData = AlphaArr
yData = PubArr
xError = AlphaErr
yError = PubErr

def fitFunc(p, x):
    '''
    Fit function
    '''
    f = p[0] + p[1]*x
    return f

def fitFuncDiff(p, x):
    '''
    Differential of fit function
    '''
    df = p[1]
    return df

def calcChiSq(p, x, y, xerr, yerr):
    '''
    Error function for fit
    '''
    e = (y - fitFunc(p, x))/(np.sqrt(yerr**2 + fitFuncDiff(p, x)**2*xerr**2))
    return e
fig = plt.figure(figsize = (8, 6))
plt.errorbar(xdata, ydata, yerror, xerror, marker=".", linestyle = '')
plt.show
linearModel_1 = odr.Model(fitFunc)
fitData_1 = odr.Data(xdata, ydata, xdata, ydata)
odrObject_1 = odr.ODR(fitData_1, linearModel_1, beta0=[1.,1.])
odrFit_1 = odrObject_1.run()
odrFit_1.pprint()
plt.plot(xdata, fitFunc(odrFit_1.beta, xdata))
chi_array = calcChiSq(odrFit_1.beta, xdata, ydata, xerror, yerror)**2
chisqndf = np.sum(chi_array)/np.sqrt(len(xdata)-2)
print("ChiSq/NDF: {0:.3f}".format(chisqndf))
#
#
#
nPoints = 4

BetaArr = np.zeros(4)
PubArr = np.zeros(4)
BetaErr = np.zeros(4)
PubErr = np.zeros(4)

BetaArr = [popt1[1], popt2[1], popt3[1], popt4[1]]
PubArr = [8.04, 8.63, 7.47, 6.40]
BetaErr = [FWHM1_1,FWHM1_2,FWHM1_3,FWHM1_4]
PubErr = [0.1,0.1,0.1,0.1]

xData = AlphaArr
yData = PubArr
xError = AlphaErr
yError = PubErr

def fitFunc(p, x):
    '''
    Fit function
    '''
    f = p[0] + p[1]*x
    return f

def fitFuncDiff(p, x):
    '''
    Differential of fit function
    '''
    df = p[1]
    return df

def calcChiSq(p, x, y, xerr, yerr):
    '''
    Error function for fit
    '''
    e = (y - fitFunc(p, x))/(np.sqrt(yerr**2 + fitFuncDiff(p, x)**2*xerr**2))
    return e
fig = plt.figure(figsize = (8, 6))
plt.errorbar(xdata, ydata, yerror, xerror, marker=".", linestyle = '')
plt.show
linearModel_1 = odr.Model(fitFunc)
fitData_1 = odr.Data(xdata, ydata, xdata, ydata)
odrObject_1 = odr.ODR(fitData_1, linearModel_1, beta0=[1.,1.])
odrFit_1 = odrObject_1.run()
odrFit_1.pprint()
plt.plot(xdata, fitFunc(odrFit_1.beta, xdata))
chi_array = calcChiSq(odrFit_1.beta, xdata, ydata, xerror, yerror)**2
chisqndf = np.sum(chi_array)/np.sqrt(len(xdata)-2)
print("ChiSq/NDF: {0:.3f}".format(chisqndf))