move golemfit test to another repo and slightly reluctantly use american style flavor spelling consistently

1 files changed, 0 insertions, 106 deletions

diff --git a/test/test_NSI.py b/test/test_NSI.py
deleted file mode 100644
index d144420..0000000
--- a/test/test_NSI.py
+++ /dev/null
@@ -1,106 +0,0 @@
-#!/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()
-npp = gf.NewPhysicsParams()
-
-steer.quiet = False
-steer.fastmode = True
-
-golem = gf.GolemFit(dp, steer, npp)
-
-fit_params = gf.FitParameters(gf.sampleTag.HESE)
-golem.SetupAsimov(fit_params)
-
-fig = plt.figure(figsize=[6, 5])
-ax = fig.add_subplot(111)
-ax.set_xscale('log')
-ax.set_yscale('log')
-
-binning = golem.GetEnergyBinsMC()
-ax.set_xlim(binning[0], binning[-1])
-# ax.set_ylim(binning[0], binning[-1])
-
-print 'NULL min_llh', golem.MinLLH().likelihood
-
-# 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 expectation', exp
-print
-
-npp.type = gf.NewPhysicsType.NonStandardInteraction
-npp.epsilon_mutau = 0.1
-golem.SetNewPhysicsParams(npp)
-
-print '0.1 mutau min_llh', golem.MinLLH().likelihood
-
-# 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 expectation', exp
-print
-
-np.epsilon_mutau = 0.2
-golem.SetNewPhysicsParams(npp)
-
-print '0.2 mutau min_llh', golem.MinLLH().likelihood
-
-# 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='0.2 mutau', linestyle='--')
-
-# print '0.2 mutau expectation', exp
-print
-
-np.epsilon_mutau = 0.3
-golem.SetNewPhysicsParams(npp)
-
-print '0.3 mutau min_llh', golem.MinLLH().likelihood
-
-# 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='0.3 mutau', linestyle='--')
-
-# print '0.3 mutau expectation', exp
-print
-
-np.epsilon_mutau = 0.4
-golem.SetNewPhysicsParams(npp)
-
-print '0.4 mutau min_llh', golem.MinLLH().likelihood
-
-# 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='0.4 mutau', linestyle='--')
-
-# print '0.4 mutau expectation', exp
-print
-
-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)
-