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| author | shivesh <s.p.mandalia@qmul.ac.uk> | 2018-04-06 17:21:57 -0500 |
|---|---|---|
| committer | shivesh <s.p.mandalia@qmul.ac.uk> | 2018-04-06 17:21:57 -0500 |
| commit | ccffb521195eb5f41471e166e1ba8f695740bcb3 (patch) | |
| tree | 28734a167b71a1d3f2a438fb09835de11aa730df /test/test_NSI.py | |
| parent | 30fddc32cfd5af1fc1f49de2e91b39c81cdf10e2 (diff) | |
| download | GolemFlavor-ccffb521195eb5f41471e166e1ba8f695740bcb3.tar.gz GolemFlavor-ccffb521195eb5f41471e166e1ba8f695740bcb3.zip | |
add test scripts for Golem LV and NSI
Diffstat (limited to 'test/test_NSI.py')
| -rw-r--r-- | test/test_NSI.py | 89 |
1 files changed, 89 insertions, 0 deletions
diff --git a/test/test_NSI.py b/test/test_NSI.py new file mode 100644 index 0000000..617c353 --- /dev/null +++ b/test/test_NSI.py @@ -0,0 +1,89 @@ +#!/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) |
