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-rw-r--r--submitter/make_dag.py121
1 files changed, 85 insertions, 36 deletions
diff --git a/submitter/make_dag.py b/submitter/make_dag.py
index 849020e..ccd1fee 100644
--- a/submitter/make_dag.py
+++ b/submitter/make_dag.py
@@ -29,15 +29,40 @@ fix_sfr_mfr = [
# (1, 2, 0, 1, 2, 0)
]
-sigmas = ['0.01']
-dimensions = [3]
-energy = [1e6]
-flat = False
-burnin = 20
+# MCMC
+run_mcmc = 'True'
+burnin = 20
+nsteps = 100
nwalkers = 200
-nsteps = 100
-scales = "1E-20 1E-30"
-no_bsm = False
+seed = 24
+threads = 1
+
+# FR
+dimension = [3]
+energy = [1e6]
+likelihood = 'gaussian'
+no_bsm = 'False'
+sigma_ratio = ['0.01']
+scale = "1E-20 1E-30"
+scale_region = "1E10"
+
+# Nuisance
+astroDeltaGamma = 2.
+astroNorm = 1.
+convNorm = 1.
+muonNorm = 1.
+promptNorm = 0.
+
+# GolemFit
+aft = 'hesespl'
+ast = 'baseline'
+axs = 'nom'
+data = 'real'
+priors = 'uniform'
+
+# Plot
+plot_angles = 'True'
+plot_elements = 'False'
outfile = 'dagman_FR.submit'
golemfitsourcepath = os.environ['GOLEMSOURCEPATH'] + '/GolemFit'
@@ -45,14 +70,14 @@ condor_script = golemfitsourcepath + '/scripts/flavour_ratio/submitter/submit.su
with open(outfile, 'w') as f:
job_number = 1
- for dim in dimensions:
+ for dim in dimension:
print 'dimension', dim
for en in energy:
print 'energy {0:.0E}'.format(en)
outchain_head = '/data/user/smandalia/flavour_ratio/data/DIM{0}/{1:.0E}'.format(dim, en)
- for sig in sigmas:
+ for sig in sigma_ratio:
print 'sigma', sig
for frs in fix_sfr_mfr:
print frs
@@ -61,45 +86,69 @@ with open(outfile, 'w') as f:
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}\tsigma="{1}"\n'.format(job_number, sig))
+ f.write('VARS\tjob{0}\tsigma_ratio="{1}"\n'.format(job_number, sig))
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]))
f.write('VARS\tjob{0}\tfix_scale="{1}"\n'.format(job_number, 'False'))
f.write('VARS\tjob{0}\tscale="{1}"\n'.format(job_number, 0))
+ f.write('VARS\tjob{0}\tscale_region="{1}"\n'.format(job_number, scale_region))
f.write('VARS\tjob{0}\tdimension="{1}"\n'.format(job_number, dim))
f.write('VARS\tjob{0}\tenergy="{1}"\n'.format(job_number, en))
- f.write('VARS\tjob{0}\tflat_llh="{1}"\n'.format(job_number, flat))
+ f.write('VARS\tjob{0}\tlikelihood="{1}"\n'.format(job_number, likelihood))
f.write('VARS\tjob{0}\tburnin="{1}"\n'.format(job_number, burnin))
f.write('VARS\tjob{0}\tnwalkers="{1}"\n'.format(job_number, nwalkers))
f.write('VARS\tjob{0}\tnsteps="{1}"\n'.format(job_number, nsteps))
f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outchains))
f.write('VARS\tjob{0}\tfix_mixing="{1}"\n'.format(job_number, 'False'))
f.write('VARS\tjob{0}\tno_bsm="{1}"\n'.format(job_number, no_bsm))
+ f.write('VARS\tjob{0}\trun_mcmc="{1}"\n'.format(job_number, run_mcmc))
+ f.write('VARS\tjob{0}\tastroDeltaGamma="{1}"\n'.format(job_number, astroDeltaGamma))
+ f.write('VARS\tjob{0}\tastroNorm="{1}"\n'.format(job_number, astroNorm))
+ f.write('VARS\tjob{0}\tconvNorm="{1}"\n'.format(job_number, convNorm))
+ f.write('VARS\tjob{0}\tmuonNorm="{1}"\n'.format(job_number, muonNorm))
+ f.write('VARS\tjob{0}\tpromptNorm="{1}"\n'.format(job_number, promptNorm))
+ f.write('VARS\tjob{0}\taft="{1}"\n'.format(job_number, aft))
+ f.write('VARS\tjob{0}\tast="{1}"\n'.format(job_number, ast))
+ f.write('VARS\tjob{0}\taxs="{1}"\n'.format(job_number, axs))
+ f.write('VARS\tjob{0}\tplot_angles="{1}"\n'.format(job_number, plot_angles))
+ f.write('VARS\tjob{0}\tplot_elements="{1}"\n'.format(job_number, plot_elements))
job_number += 1
- # for frs in full_scan_mfr:
- # print frs
- # outchains = outchain_head + '/full_scan/{0}/mcmc_chain'.format(str(sig).replace('.', '_'))
- # f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))
- # 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}\tsigma="{1}"\n'.format(job_number, sig))
- # 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))
- # f.write('VARS\tjob{0}\tfix_scale="{1}"\n'.format(job_number, 'False'))
- # f.write('VARS\tjob{0}\tscale="{1}"\n'.format(job_number, 0))
- # f.write('VARS\tjob{0}\tdimension="{1}"\n'.format(job_number, dim))
- # f.write('VARS\tjob{0}\tenergy="{1}"\n'.format(job_number, en))
- # f.write('VARS\tjob{0}\tflat_llh="{1}"\n'.format(job_number, flat))
- # f.write('VARS\tjob{0}\tburnin="{1}"\n'.format(job_number, burnin))
- # f.write('VARS\tjob{0}\tnwalkers="{1}"\n'.format(job_number, nwalkers))
- # f.write('VARS\tjob{0}\tnsteps="{1}"\n'.format(job_number, nsteps))
- # f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outchains))
- # f.write('VARS\tjob{0}\tfix_mixing="{1}"\n'.format(job_number, 'False'))
- # f.write('VARS\tjob{0}\tno_bsm="{1}"\n'.format(job_number, no_bsm))
- # job_number += 1
+ for frs in full_scan_mfr:
+ print frs
+ outchains = outchain_head + '/full_scan/{0}/mcmc_chain'.format(str(sig).replace('.', '_'))
+ f.write('JOB\tjob{0}\t{1}\n'.format(job_number, condor_script))
+ 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}\tsigma_ratio="{1}"\n'.format(job_number, sig))
+ 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))
+ f.write('VARS\tjob{0}\tfix_scale="{1}"\n'.format(job_number, 'False'))
+ f.write('VARS\tjob{0}\tscale="{1}"\n'.format(job_number, 0))
+ f.write('VARS\tjob{0}\tscale_region="{1}"\n'.format(job_number, scale_region))
+ f.write('VARS\tjob{0}\tdimension="{1}"\n'.format(job_number, dim))
+ f.write('VARS\tjob{0}\tenergy="{1}"\n'.format(job_number, en))
+ f.write('VARS\tjob{0}\tlikelihood="{1}"\n'.format(job_number, likelihood))
+ f.write('VARS\tjob{0}\tburnin="{1}"\n'.format(job_number, burnin))
+ f.write('VARS\tjob{0}\tnwalkers="{1}"\n'.format(job_number, nwalkers))
+ f.write('VARS\tjob{0}\tnsteps="{1}"\n'.format(job_number, nsteps))
+ f.write('VARS\tjob{0}\toutfile="{1}"\n'.format(job_number, outchains))
+ f.write('VARS\tjob{0}\tfix_mixing="{1}"\n'.format(job_number, 'False'))
+ f.write('VARS\tjob{0}\tno_bsm="{1}"\n'.format(job_number, no_bsm))
+ f.write('VARS\tjob{0}\trun_mcmc="{1}"\n'.format(job_number, run_mcmc))
+ f.write('VARS\tjob{0}\tastroDeltaGamma="{1}"\n'.format(job_number, astroDeltaGamma))
+ f.write('VARS\tjob{0}\tastroNorm="{1}"\n'.format(job_number, astroNorm))
+ f.write('VARS\tjob{0}\tconvNorm="{1}"\n'.format(job_number, convNorm))
+ f.write('VARS\tjob{0}\tmuonNorm="{1}"\n'.format(job_number, muonNorm))
+ f.write('VARS\tjob{0}\tpromptNorm="{1}"\n'.format(job_number, promptNorm))
+ f.write('VARS\tjob{0}\taft="{1}"\n'.format(job_number, aft))
+ f.write('VARS\tjob{0}\tast="{1}"\n'.format(job_number, ast))
+ f.write('VARS\tjob{0}\taxs="{1}"\n'.format(job_number, axs))
+ f.write('VARS\tjob{0}\tplot_angles="{1}"\n'.format(job_number, plot_angles))
+ f.write('VARS\tjob{0}\tplot_elements="{1}"\n'.format(job_number, plot_elements))
+ job_number += 1
generated by cgit v1.2.3 (git 2.25.1) at 2025-12-17 17:35:20 +0000