1 files changed, 116 insertions, 0 deletions
diff --git a/submitter/mcmc_dag.py b/submitter/mcmc_dag.py
new file mode 100644
index 0000000..79f9b6d
--- /dev/null
+++ b/submitter/mcmc_dag.py
@@ -0,0 +1,116 @@
+#! /usr/bin/env python
+
+import os
+import numpy as np
+
+full_scan_mfr = [
+    # (1, 1, 1), (1, 0, 0)
+]
+
+fix_sfr_mfr = [
+    (1, 1, 1, 1, 2, 0),
+    (1, 1, 1, 1, 0, 0),
+    (1, 1, 1, 0, 1, 0),
+    (1, 1, 1, 0, 0, 1),
+    # (1, 1, 0, 1, 2, 0),
+    # (1, 1, 0, 1, 0, 0),
+    # (1, 1, 0, 0, 1, 0),
+    # (1, 0, 0, 1, 0, 0),
+    # (0, 1, 0, 0, 1, 0),
+    # (1, 2, 0, 1, 2, 0),
+    # (1, 2, 0, 0, 1, 0),
+]
+
+GLOBAL_PARAMS = {}
+
+# MCMC
+GLOBAL_PARAMS.update(dict(
+    run_mcmc = 'True',
+    burnin   = 2500,
+    nsteps   = 10000,
+    nwalkers = 60,
+    seed     = 'None',
+    mcmc_seed_type = 'uniform'
+))
+
+# FR
+dimension         = [3, 6]
+GLOBAL_PARAMS.update(dict(
+    threads           = 1,
+    binning           = '1e4 1e7 5',
+    no_bsm            = 'False',
+    scale_region      = "1E10",
+    energy_dependance = 'spectral',
+    spectral_index    = -2,
+    fix_mixing        = 'False',
+    fix_mixing_almost = 'False'
+))
+
+# Likelihood
+GLOBAL_PARAMS.update(dict(
+    likelihood  = 'gaussian',
+    sigma_ratio = '0.01'
+))
+
+# GolemFit
+GLOBAL_PARAMS.update(dict(
+    ast  = 'p2_0',
+    data = 'real'
+))
+
+# Plot
+GLOBAL_PARAMS.update(dict(
+    plot_angles       = 'True',
+    plot_elements     = 'False',
+))
+
+outfile = 'dagman_FR_MCMC.submit'
+golemfitsourcepath = os.environ['GOLEMSOURCEPATH'] + '/GolemFit'
+condor_script = golemfitsourcepath + '/scripts/flavour_ratio/submitter/mcmc_submit.sub'
+
+with open(outfile, 'w') as f:
+    job_number = 1
+    for dim in dimension:
+        print 'dimension', dim
+        outchain_head = '/data/user/smandalia/flavour_ratio/data/{0}/DIM{1}/SI_{2}'.format(
+            GLOBAL_PARAMS['likelihood'], dim, GLOBAL_PARAMS['spectral_index']
+        )
+        for frs in fix_sfr_mfr:
+            print 'frs', frs
+            outchains = outchain_head + '/fix_ifr/'
+            if GLOBAL_PARAMS['likelihood'].lower() == 'gaussian':
+                outchains += '{0}/'.format(str(GLOBAL_PARAMS['sigma_ratio']).replace('.', '_'))
+            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))
+            f.write('VARS\tjob{0}\tmr0="{1}"\n'.format(job_number, frs[0]))
+            f.write('VARS\tjob{0}\tmr1="{1}"\n'.format(job_number, frs[1]))
+            f.write('VARS\tjob{0}\tmr2="{1}"\n'.format(job_number, frs[2]))
+            f.write('VARS\tjob{0}\tfix_source_ratio="{1}"\n'.format(job_number, True))
+            f.write('VARS\tjob{0}\tsr0="{1}"\n'.format(job_number, frs[3]))
+            f.write('VARS\tjob{0}\tsr1="{1}"\n'.format(job_number, frs[4]))
+            f.write('VARS\tjob{0}\tsr2="{1}"\n'.format(job_number, frs[5]))
+            for key in GLOBAL_PARAMS.keys():
+                f.write('VARS\tjob{0}\tmr0="{1}"\n'.format(job_number, GLOBAL_PARAMS[key]))
+            f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outfile))
+            job_number += 1
+
+        for frs in full_scan_mfr:
+            print 'frs', frs
+            outchains = outchain_head + '/full/'
+            if GLOBAL_PARAMS['likelihood'].lower() == 'gaussian':
+                outchains += '{0}/'.format(str(GLOBAL_PARAMS['sigma_ratio']).replace('.', '_'))
+            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))
+            f.write('VARS\tjob{0}\tmr0="{1}"\n'.format(job_number, frs[0]))
+            f.write('VARS\tjob{0}\tmr1="{1}"\n'.format(job_number, frs[1]))
+            f.write('VARS\tjob{0}\tmr2="{1}"\n'.format(job_number, frs[2]))
+            f.write('VARS\tjob{0}\tfix_source_ratio="{1}"\n'.format(job_number, False))
+            f.write('VARS\tjob{0}\tsr0="{1}"\n'.format(job_number, 0))
+            f.write('VARS\tjob{0}\tsr1="{1}"\n'.format(job_number, 0))
+            f.write('VARS\tjob{0}\tsr2="{1}"\n'.format(job_number, 0))
+            for key in GLOBAL_PARAMS.keys():
+                f.write('VARS\tjob{0}\tmr0="{1}"\n'.format(job_number, GLOBAL_PARAMS[key]))
+            f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outfile))
+            job_number += 1