diff options
Diffstat (limited to 'submitter/make_dag.py')
| -rw-r--r-- | submitter/make_dag.py | 53 |
1 files changed, 34 insertions, 19 deletions
diff --git a/submitter/make_dag.py b/submitter/make_dag.py index 53878a2..78b7bff 100644 --- a/submitter/make_dag.py +++ b/submitter/make_dag.py @@ -19,10 +19,10 @@ fix_sfr_mfr = [ (1, 1, 1, 1, 2, 0), # (1, 1, 0, 1, 2, 0), # (1, 2, 0, 1, 2, 0), - # (1, 1, 1, 1, 0, 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, 1, 0, 1, 0), # (1, 1, 0, 0, 1, 0), # (0, 1, 0, 0, 1, 0), # (1, 2, 0, 0, 1, 0), @@ -31,17 +31,16 @@ fix_sfr_mfr = [ # MCMC run_mcmc = 'False' -burnin = 500 -nsteps = 2000 +burnin = 2500 +nsteps = 10000 nwalkers = 60 seed = 24 -threads = 1 +threads = 4 mcmc_seed_type = 'uniform' # FR dimension = [6] energy = [1e6] -likelihood = 'golemfit' no_bsm = 'False' sigma_ratio = ['0.01'] scale = "1E-20 1E-30" @@ -67,23 +66,30 @@ ast = 'p2_0' data = 'real' # Bayes Factor -run_bayes_factor = 'False' -run_angles_limit = 'True' -bayes_bins = 10 -bayes_live_points = 200 -bayes_tolerance = 0.01 -bayes_eval_bin = True # set to 'all' to run normally +run_bayes_factor = 'False' +run_angles_limit = 'False' +run_angles_correlation = 'True' +bayes_bins = 20 +bayes_live_points = 1000 +bayes_tolerance = 0.01 +bayes_eval_bin = 'None' # set to 'all' to run normally # Plot -plot_angles = 'False' -plot_elements = 'False' -plot_bayes = 'False' +plot_angles = 'False' +plot_elements = 'False' +plot_bayes = 'False' +plot_angles_limit = 'False' -outfile = 'dagman_FR_angles_limit.submit' +# outfile = 'dagman_FR.submit'.format(dimension[0]) +outfile = 'dagman_FR_angles_correlation_DIM{0}.submit'.format(dimension[0]) golemfitsourcepath = os.environ['GOLEMSOURCEPATH'] + '/GolemFit' condor_script = golemfitsourcepath + '/scripts/flavour_ratio/submitter/submit.sub' -if bayes_eval_bin != 'all': b_runs = bayes_bins +if bayes_eval_bin != 'all': + if run_angles_correlation == 'True': + b_runs = bayes_bins**2 + else: + b_runs = bayes_bins else: b_runs = 1 with open(outfile, 'w') as f: @@ -99,6 +105,7 @@ with open(outfile, 'w') as f: outchain_head = '/data/user/smandalia/flavour_ratio/data/{0}/DIM{1}/SI_{2}'.format(likelihood, dim, spectral_index) bayes_output = 'None' + angles_lim_output = 'None' for sig in sigma_ratio: print 'sigma', sig for frs in fix_sfr_mfr: @@ -108,6 +115,8 @@ with open(outfile, 'w') as f: bayes_output = outchains + '/bayes_factor/' if run_angles_limit == 'True': angles_lim_output = outchains + '/angles_limit/' + if run_angles_correlation == 'True': + angles_corr_output = outchains + '/angles_corr/' outchains += 'mcmc_chain' for r in range(b_runs): print 'run', r @@ -144,7 +153,6 @@ with open(outfile, 'w') as f: f.write('VARS\tjob{0}\tplot_elements="{1}"\n'.format(job_number, plot_elements)) f.write('VARS\tjob{0}\tseed="{1}"\n'.format(job_number, seed)) f.write('VARS\tjob{0}\tthreads="{1}"\n'.format(job_number, threads)) - f.write('VARS\tjob{0}\tlikelihood="{1}"\n'.format(job_number, likelihood)) f.write('VARS\tjob{0}\tmcmc_seed_type="{1}"\n'.format(job_number, mcmc_seed_type)) f.write('VARS\tjob{0}\tenergy_dependance="{1}"\n'.format(job_number, energy_dependance)) f.write('VARS\tjob{0}\tspectral_index="{1}"\n'.format(job_number, spectral_index)) @@ -161,6 +169,9 @@ with open(outfile, 'w') as f: 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: @@ -170,6 +181,8 @@ with open(outfile, 'w') as f: bayes_output = outchains + '/bayes_factor/' if run_angles_limit == 'True': angles_lim_output = outchains + '/angles_limit/' + if run_angles_correlation == 'True': + angles_corr_output = outchains + '/angles_corr/' outchains += 'mcmc_chain' for r in range(b_runs): print 'run', r @@ -206,7 +219,6 @@ with open(outfile, 'w') as f: f.write('VARS\tjob{0}\tplot_elements="{1}"\n'.format(job_number, plot_elements)) f.write('VARS\tjob{0}\tseed="{1}"\n'.format(job_number, seed)) f.write('VARS\tjob{0}\tthreads="{1}"\n'.format(job_number, threads)) - f.write('VARS\tjob{0}\tlikelihood="{1}"\n'.format(job_number, likelihood)) f.write('VARS\tjob{0}\tmcmc_seed_type="{1}"\n'.format(job_number, mcmc_seed_type)) f.write('VARS\tjob{0}\tenergy_dependance="{1}"\n'.format(job_number, energy_dependance)) f.write('VARS\tjob{0}\tspectral_index="{1}"\n'.format(job_number, spectral_index)) @@ -223,4 +235,7 @@ with open(outfile, 'w') as f: 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 |