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#!/usr/bin/env python
from __future__ import absolute_import, division
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import rc
import GolemFitPy as gf
rc('text', usetex=True)
rc('font', **{'family':'serif', 'serif':['Computer Modern'], 'size':18})
dp = gf.DataPaths()
steer = gf.SteeringParams()
fig = plt.figure(figsize=[12, 8])
ax = fig.add_subplot(111)
ax.set_xscale('log')
ax.set_yscale('log')
npp = gf.NewPhysicsParams()
npp.type = gf.NewPhysicsType.None
# npp.epsilon_mutau = 0
# npp.epsilon_prime = 0
golem = gf.GolemFit(dp, steer, npp)
binning = golem.GetEnergyBinsMC()
ax.set_xlim(binning[0], binning[-1])
# ax.set_ylim(binning[0], binning[-1])
fit_params = gf.FitParameters(gf.sampleTag.HESE)
golem.SetupAsimov(fit_params)
exp = np.sum(golem.GetExpectation(fit_params), axis=(0, 1, 2, 3))
ax.step(binning, np.concatenate([[exp[0]], exp]), alpha=1,
drawstyle='steps-pre', label='NULL', linestyle='--')
print 'NULL min_llh', golem.MinLLH().likelihood
print 'NULL expectation', exp
print
npp = gf.NewPhysicsParams()
npp.type = gf.NewPhysicsType.NonStandardInteraction
npp.epsilon_mutau = 0.1
# npp.epsilon_prime = 0
golem.SetNewPhysicsParams(npp)
exp = np.sum(golem.GetExpectation(fit_params), axis=(0, 1, 2, 3))
ax.step(binning, np.concatenate([[exp[0]], exp]), alpha=1,
drawstyle='steps-pre', label='0.1 mutau', linestyle='--')
print '0.1 mutau min_llh', golem.MinLLH().likelihood
print '0.1 mutau expectation', exp
# npp = gf.NewPhysicsParams()
# npp.epsilon_mutau = 0
# # npp.epsilon_prime = 0
# golem.SetNewPhysicsParams(npp)
# exp = np.sum(golem.GetExpectation(fit_params), axis=(0, 1, 2, 3))
# ax.step(binning, np.concatenate([[exp[0]], exp]), alpha=1,
# drawstyle='steps-pre', label='1e-10 LV', linestyle='--')
# print '1e10 LV min_llh', golem.MinLLH().likelihood
# print '1e10 LV expectation', exp
# npp = gf.NewPhysicsParams()
# npp.epsilon_mutau = 0
# # npp.epsilon_prime = 0
# golem.SetNewPhysicsParams(npp)
ax.tick_params(axis='x', labelsize=12)
ax.tick_params(axis='y', labelsize=12)
ax.set_xlabel(r'Deposited energy / GeV')
ax.set_ylabel(r'Events')
for xmaj in ax.xaxis.get_majorticklocs():
ax.axvline(x=xmaj, ls=':', color='gray', alpha=0.7, linewidth=1)
for ymaj in ax.yaxis.get_majorticklocs():
ax.axhline(y=ymaj, ls=':', color='gray', alpha=0.7, linewidth=1)
legend = ax.legend(prop=dict(size=12))
fig.savefig('test_NSI.png', bbox_inches='tight', dpi=250)
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