diff options
Diffstat (limited to 'submitter/make_dag.py')
| -rw-r--r-- | submitter/make_dag.py | 49 |
1 files changed, 24 insertions, 25 deletions
diff --git a/submitter/make_dag.py b/submitter/make_dag.py index c6e7400..0e41c9a 100644 --- a/submitter/make_dag.py +++ b/submitter/make_dag.py @@ -17,29 +17,29 @@ full_scan_mfr = [ 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, 2, 0, 1, 2, 0), - # (1, 1, 1, 1, 0, 0), # (1, 1, 0, 1, 0, 0), - # (1, 0, 0, 1, 0, 0), - (1, 1, 1, 0, 1, 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), - # (1, 1, 1, 0, 0, 1), ] # MCMC -run_mcmc = 'False' +run_mcmc = 'True' burnin = 2500 nsteps = 10000 nwalkers = 60 seed = 'None' -threads = 4 +threads = 1 mcmc_seed_type = 'uniform' # FR -dimension = [4, 5, 7, 8] +dimension = [3, 6] energy = [1e6] no_bsm = 'False' sigma_ratio = ['0.01'] @@ -52,7 +52,7 @@ fix_mixing = 'False' fix_mixing_almost = 'False' # Likelihood -likelihood = 'golemfit' +likelihood = 'gaussian' # Nuisance convNorm = 1. @@ -66,7 +66,7 @@ ast = 'p2_0' data = 'real' # Bayes Factor -run_bayes_factor = 'True' +run_bayes_factor = 'False' run_angles_limit = 'False' run_angles_correlation = 'False' bayes_bins = 100 @@ -75,13 +75,12 @@ bayes_tolerance = 0.01 bayes_eval_bin = 'all' # set to 'all' to run normally # Plot -plot_angles = 'False' +plot_angles = 'True' plot_elements = 'False' plot_bayes = 'False' plot_angles_limit = 'False' -outfile = 'dagman_FR_freq_fullscan_otherdims.submit' -# outfile = 'dagman_FR_bayes_freq.submit' +outfile = 'dagman_FR.submit' golemfitsourcepath = os.environ['GOLEMSOURCEPATH'] + '/GolemFit' condor_script = golemfitsourcepath + '/scripts/flavour_ratio/submitter/submit.sub' @@ -161,18 +160,18 @@ with open(outfile, 'w') as f: f.write('VARS\tjob{0}\tbinning_1="{1}"\n'.format(job_number, binning[1])) f.write('VARS\tjob{0}\tbinning_2="{1}"\n'.format(job_number, binning[2])) f.write('VARS\tjob{0}\tfix_mixing_almost="{1}"\n'.format(job_number, fix_mixing_almost)) - f.write('VARS\tjob{0}\trun_bayes_factor="{1}"\n'.format(job_number, run_bayes_factor)) - f.write('VARS\tjob{0}\tbayes_bins="{1}"\n'.format(job_number, bayes_bins)) - f.write('VARS\tjob{0}\tbayes_output="{1}"\n'.format(job_number, bayes_output)) - f.write('VARS\tjob{0}\tbayes_live_points="{1}"\n'.format(job_number, bayes_live_points)) - f.write('VARS\tjob{0}\tbayes_tolerance="{1}"\n'.format(job_number, bayes_tolerance)) - f.write('VARS\tjob{0}\tplot_bayes="{1}"\n'.format(job_number, plot_bayes)) - f.write('VARS\tjob{0}\tbayes_eval_bin="{1}"\n'.format(job_number, r)) - f.write('VARS\tjob{0}\trun_angles_limit="{1}"\n'.format(job_number, run_angles_limit)) - f.write('VARS\tjob{0}\tangles_lim_output="{1}"\n'.format(job_number, angles_lim_output)) - f.write('VARS\tjob{0}\tplot_angles_limit="{1}"\n'.format(job_number, plot_angles_limit)) - f.write('VARS\tjob{0}\trun_angles_correlation="{1}"\n'.format(job_number, run_angles_correlation)) - f.write('VARS\tjob{0}\tangles_corr_output="{1}"\n'.format(job_number, angles_corr_output)) + # f.write('VARS\tjob{0}\trun_bayes_factor="{1}"\n'.format(job_number, run_bayes_factor)) + # f.write('VARS\tjob{0}\tbayes_bins="{1}"\n'.format(job_number, bayes_bins)) + # f.write('VARS\tjob{0}\tbayes_output="{1}"\n'.format(job_number, bayes_output)) + # f.write('VARS\tjob{0}\tbayes_live_points="{1}"\n'.format(job_number, bayes_live_points)) + # f.write('VARS\tjob{0}\tbayes_tolerance="{1}"\n'.format(job_number, bayes_tolerance)) + # f.write('VARS\tjob{0}\tplot_bayes="{1}"\n'.format(job_number, plot_bayes)) + # f.write('VARS\tjob{0}\tbayes_eval_bin="{1}"\n'.format(job_number, r)) + # f.write('VARS\tjob{0}\trun_angles_limit="{1}"\n'.format(job_number, run_angles_limit)) + # f.write('VARS\tjob{0}\tangles_lim_output="{1}"\n'.format(job_number, angles_lim_output)) + # f.write('VARS\tjob{0}\tplot_angles_limit="{1}"\n'.format(job_number, plot_angles_limit)) + # f.write('VARS\tjob{0}\trun_angles_correlation="{1}"\n'.format(job_number, run_angles_correlation)) + # f.write('VARS\tjob{0}\tangles_corr_output="{1}"\n'.format(job_number, angles_corr_output)) job_number += 1 for frs in full_scan_mfr: |