fix bug in energy spectrum

3 files changed, 16 insertions, 21 deletions

diff --git a/submitter/mcmc_dag.py b/submitter/mcmc_dag.py
index 7a0cde9..e40c043 100644
--- a/submitter/mcmc_dag.py
+++ b/submitter/mcmc_dag.py
@@ -38,7 +38,7 @@ dimension         = [3]
 # dimension         = [4, 5, 7, 8]
 GLOBAL_PARAMS.update(dict(
     threads           = 1,
-    binning           = '6e4 1e7 5',
+    binning           = '6e4 1e7 20',
     no_bsm            = 'False',
     scale_region      = "1E10",
     energy_dependance = 'spectral',
@@ -57,7 +57,7 @@ GLOBAL_PARAMS.update(dict(
 # GolemFit
 GLOBAL_PARAMS.update(dict(
     ast  = 'p2_0',
-    data = 'real'
+    data = 'asimov'
 ))
 
 # Plot
@@ -82,6 +82,7 @@ with open(outfile, 'w') as f:
             outchains = outchain_head + '/fix_ifr/'
             if GLOBAL_PARAMS['likelihood'].lower() == 'gaussian':
                 outchains += '{0}/'.format(str(GLOBAL_PARAMS['sigma_ratio']).replace('.', '_'))
+            outchains += '{0}/'.format(GLOBAL_PARAMS['data'].lower())
             outchains += 'mcmc_chain'
             f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))
             f.write('VARS\tjob{0}\tdimension="{1}"\n'.format(job_number, dim))
diff --git a/submitter/mcmc_submit.sub b/submitter/mcmc_submit.sub
index 998932e..fa36250 100644
--- a/submitter/mcmc_submit.sub
+++ b/submitter/mcmc_submit.sub
@@ -32,9 +32,10 @@ Notification    = never
 
 # +TransferOutput=""
 
++NATIVE_OS = True
 # Requirements = IS_GLIDEIN && HAS_CVMFS_icecube_opensciencegrid_org && (OpSysAndVer =?= "CentOS6" || OpSysAndVer =?= "RedHat6" || OpSysAndVer =?= "SL6")
 # Requirements = IS_GLIDEIN
-Requirements = (OpSysMajorVer =?= 6)
+# Requirements = (OpSysMajorVer =?= 6)
 
 # GO! 
 queue
diff --git a/submitter/sens_dag.py b/submitter/sens_dag.py
index 666a0dd..5e00dfd 100644
--- a/submitter/sens_dag.py
+++ b/submitter/sens_dag.py
@@ -35,27 +35,25 @@ GLOBAL_PARAMS.update(dict(
 
 # MultiNest
 GLOBAL_PARAMS.update(dict(
-    mn_live_points = 300,
+    mn_live_points = 1000,
     mn_tolerance   = 0.1,
     mn_output      = './mnrun'
 ))
 
 # FR
-# dimension         = [3]
-dimension         = [3, 6]
-# dimension         = [4, 5, 7, 8]
-# dimension         = [3, 4, 5, 6, 7, 8]
+dimension         = [3]
+# dimension         = [3, 6]
 GLOBAL_PARAMS.update(dict(
     threads           = 1,
-    # binning           = '6e4 1e7 5',
-    binning           = '1e5 1e7 5',
+    binning           = '6e4 1e7 20',
+    # binning           = '1e5 1e7 5',
     no_bsm            = 'False',
     scale_region      = "1E10",
     energy_dependance = 'spectral',
     spectral_index    = -2,
     fix_mixing        = 'False',
     fix_mixing_almost = 'False',
-    fold_index        = 'False'
+    fold_index        = 'True'
 ))
 
 # Likelihood
@@ -67,7 +65,7 @@ GLOBAL_PARAMS.update(dict(
 # GolemFit
 GLOBAL_PARAMS.update(dict(
     ast  = 'p2_0',
-    data = 'real'
+    data = 'asimov'
 ))
 
 # Plot
@@ -75,8 +73,9 @@ GLOBAL_PARAMS.update(dict(
     plot_statistic = 'True'
 ))
 
-outfile = 'dagman_FR_SENS_{0}_{1}_{2}_data_100TeV.submit'.format(
-    GLOBAL_PARAMS['stat_method'], GLOBAL_PARAMS['run_method'], GLOBAL_PARAMS['likelihood']
+outfile = 'dagman_FR_SENS_{0}_{1}_{2}_{3}.submit'.format(
+    GLOBAL_PARAMS['stat_method'], GLOBAL_PARAMS['run_method'],
+    GLOBAL_PARAMS['likelihood'], GLOBAL_PARAMS['data']
 )
 golemfitsourcepath = os.environ['GOLEMSOURCEPATH'] + '/GolemFit'
 condor_script = golemfitsourcepath + '/scripts/flavour_ratio/submitter/sens_submit.sub'
@@ -97,14 +96,9 @@ with open(outfile, 'w') as f:
         )
         for frs in fix_sfr_mfr:
             print 'frs', frs
-            # output = outchain_head + '/fix_ifr/'
-            # output = outchain_head + '/fix_ifr/HESESim'
-            # output = outchain_head + '/fix_ifr/sim'
-            # output = outchain_head + '/fix_ifr/data'
-            output = outchain_head + '/fix_ifr/data/100TeV/'
+            output = outchain_head + '/fix_ifr/'
             if GLOBAL_PARAMS['likelihood'].lower() == 'gaussian':
                 output += '{0}/'.format(str(GLOBAL_PARAMS['sigma_ratio']).replace('.', '_'))
-            output += 'fr_stat'
             for r in xrange(sens_runs):
                 print 'run', r
                 f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))
@@ -130,7 +124,6 @@ with open(outfile, 'w') as f:
             output = outchain_head + '/full/'
             if GLOBAL_PARAMS['likelihood'].lower() == 'gaussian':
                 output += '{0}/'.format(str(GLOBAL_PARAMS['sigma_ratio']).replace('.', '_'))
-            output += 'fr_stat'
             for r in xrange(sens_runs):
                 print 'run', r
                 f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))