diff options
| -rwxr-xr-x | fr.py | 5 | ||||
| -rw-r--r-- | submitter/make_dag.py | 121 | ||||
| -rw-r--r-- | submitter/submit.sub | 2 | ||||
| -rw-r--r-- | utils/misc.py | 14 |
4 files changed, 102 insertions, 40 deletions
@@ -109,7 +109,10 @@ def process_args(args): def parse_args(): """Parse command line arguments""" - parser = argparse.ArgumentParser(description="BSM flavour ratio analysis") + parser = argparse.ArgumentParser( + description="BSM flavour ratio analysis", + formatter_class=misc_utils.SortingHelpFormatter, + ) parser.add_argument( '--measured-ratio', type=int, nargs=3, default=[1, 1, 1], help='Set the central value for the measured flavour ratio at IceCube' 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 diff --git a/submitter/submit.sub b/submitter/submit.sub index 45c8a58..07c0a85 100644 --- a/submitter/submit.sub +++ b/submitter/submit.sub @@ -1,5 +1,5 @@ Executable = /home/smandalia/Documents/flavour_ratio/mcmc_scan.py -Arguments = --measured-ratio $(mr0) $(mr1) $(mr2) --sigma-ratio $(sigma) --fix-source-ratio $(fix_source_ratio) --source-ratio $(sr0) $(sr1) $(sr2) --fix-scale $(fix_scale) --scale $(scale) --dimension $(dimension) --energy $(energy) --flat-llh $(flat_llh) --burnin $(burnin) --nwalkers $(nwalkers) --nsteps $(nsteps) --seed 24 --outfile $(outfile) --fix-mixing $(fix_mixing) --no-bsm $(no_bsm) +Arguments = "--aft $(aft) --ast $(ast) --astroDeltaGamma $(astroDeltaGamma) --astroNorm $(astroNorm) --axs $(axs) --burnin $(burnin) --convNorm $(convNorm) --data $(data) --dimension $(dimension) --energy $(energy) --fix-mixing $(fix_mixing) --fix-scale $(fix_scale) --fix-source-ratio $(fix_source_ratio) --likelihood $(likelihood) --measured-ratio $(mr0) $(mr1) $(mr2) --muonNorm $(muonNorm) --no-bsm $(no_bsm) --nsteps $(nsteps) --nwalkers $(nwalkers) --outfile $(outfile) --plot-angles $(plot_angles) --plot-elements $(plot_elements) --priors $(priors) --promptNorm $(promptNorm) --run-mcmc $(run_mcmc) --scale $(scale) --scale-region $(scale_region) --seed $(seed) --sigma-ratio $(sigma_ratio) --source-ratio $(sr0) $(sr1) $(sr2) --threads $(threads)" # All logs will go to a single file log = /home/smandalia/Documents/flavour_ratio/submitter/logs/job_$(Cluster).log diff --git a/utils/misc.py b/utils/misc.py index c54d25c..2ff0664 100644 --- a/utils/misc.py +++ b/utils/misc.py @@ -11,9 +11,12 @@ from __future__ import absolute_import, division import os import errno -from collections import Sequence import multiprocessing +import argparse +from collections import Sequence +from operator import attrgetter + import numpy as np from utils.enums import Likelihood, ParamTag @@ -152,6 +155,13 @@ class ParamSet(Sequence): if obj.tag is tag]) +class SortingHelpFormatter(argparse.HelpFormatter): + """Sort argparse help options alphabetically.""" + def add_arguments(self, actions): + actions = sorted(actions, key=attrgetter('option_strings')) + super(SortingHelpFormatter, self).add_arguments(actions) + + def gen_outfile_name(args): """Generate a name for the output file based on the input args. @@ -238,7 +248,7 @@ def print_args(args): """ arg_vars = vars(args) - for key in arg_vars.iterkeys(): + for key in sorted(arg_vars): print '== {0:<25} = {1}'.format(key, arg_vars[key]) |