post_BAOlensingPantheon = [[BAO, lensing, Pantheon], [BAOdata, 'lensing.ini', 'Pantheon.ini'], importanceFilterNotOmegak()] post_Pantheon = [[Pantheon], ['Pantheon.ini'], importanceFilterNotOmegak()] post_CookeBBN = ['Cooke17'] post_Aver15 = [['Aver15'], ['Aver15BBN.ini'], importanceFilterNnu()] post_BBN = [['Cooke17', 'Aver15'], ['Aver15BBN.ini', 'Cooke17BBN.ini'], importanceFilterNnu()] # set up groups of parameters and data sets groups = [] g = batchjob.jobGroup('main') g.datasets = copy.deepcopy(planck_highL_sets) for d in g.datasets: d.add(lowl) d.add(lowE, lowEdata) g.params = [[], ['omegak'], ['mnu'], ['r'], ['nrun', 'r'], ['nnu'], ['nrun'], ['Alens'], ['yhe'], ['w'], ['alpha1']] g.importanceRuns = [ post_BAO, post_lensing, post_lensingBAO, post_HST, post_BBN ] groups.append(g) gpol = batchjob.jobGroup('mainpol') gpol.datasets = copy.deepcopy(planck_pol_sets) for d in gpol.datasets:
# Directory to find .ini files ini_dir = 'batch2/' # directory to look for existing covariance matrices cov_dir = 'planck_covmats/' # ini files you want to base each set of runs on defaults = ['common.ini'] importanceDefaults = ['importance_sampling.ini'] # set up list of groups of parameters and data sets groups = [] # make first group of runs (all parameter variations with all data combinations) g = batchjob.jobGroup('main') g.params = [[], ['mnu'], ['nnu']] g.datasets = [] # lists of dataset names to combine, with corresponding sets of inis to include g.datasets.append(batchjob.dataSet(['plikHM', 'TT', 'lowTEB'], ['plik_dx11dr2_HM_v18_TT.ini', 'lowTEB.ini'])) g.datasets.append(batchjob.dataSet(['plikHM', 'TT', 'lowTEB', 'lensing'], ['plik_dx11dr2_HM_v18_TT.ini', 'lowTEB.ini', 'lensing.ini'])) # add importance name tags, and list of specific .ini files to include (in batch1/) g.importanceRuns = [] g.importanceRuns.append([['BAO'], ['BAO.ini']])
post_all = [[lensing, BAO, HST, JLA], [lensing, BAOdata, HSTdata, 'JLA_marge.ini'], importanceFilterNotOmegak()] post_allnonBAO = [[lensing, HST, JLA], [lensing, HSTdata, 'JLA_marge.ini'], importanceFilterBAO()] post_WP = [['WMAPtau'], [WMAPtau]] post_zre = zre_importance(['zre6p5'], ['zre_prior.ini'], dist_settings={'limits[zrei]': '6.5 N'}, minimize=False) post_BAOzre = zre_importance([BAO, 'zre6p5'], [BAOdata, 'zre_prior.ini'], dist_settings={'limits[zrei]': '6.5 N'}, minimize=False) post_reion = zre_importance(['reion'], ['reion_tau.ini'], dist_settings={'limits[zrei]': '6.5 N'}, minimize=False) # post_fix = [[ 'fix'], ['postfix.ini']] # set up groups of parameters and data sets groups = [] g = batchjob.jobGroup('main') # Main group with just tau prior g.datasets = copy.deepcopy(planck_highL_sets) for d in g.datasets: d.add(lowTEB) g.params = [[], ['omegak'], ['mnu'], ['r'], ['nrun', 'r'], ['nnu'], ['nrun'], ['Alens'], ['yhe'], ['w'], ['alpha1']] g.importanceRuns = [post_BAO, post_JLA, post_lensing, post_HST, post_all, post_zre] groups.append(g) gpol = batchjob.jobGroup('mainpol') gpol.datasets = copy.deepcopy(planck_pol_sets) for d in gpol.datasets: d.add(lowTEB) for d in copy.deepcopy(planck_pol_sets):
dist_settings={'limits[zrei]': '6.5 N'}, minimize=False) post_BAOzre = zre_importance([BAO, 'zre6p5'], [BAOdata, 'zre_prior.ini'], dist_settings={'limits[zrei]': '6.5 N'}, minimize=False) post_reion = zre_importance(['reion'], ['reion_tau.ini'], dist_settings={'limits[zrei]': '6.5 N'}, minimize=False) # post_fix = [[ 'fix'], ['postfix.ini']] # set up groups of parameters and data sets groups = [] g = batchjob.jobGroup('main') # Main group with just tau prior g.datasets = copy.deepcopy(planck_highL_sets) for d in g.datasets: d.add(lowTEB) g.params = [[], ['omegak'], ['mnu'], ['r'], ['nrun', 'r'], ['nnu'], ['nrun'], ['Alens'], ['yhe'], ['w'], ['alpha1']] g.importanceRuns = [ post_BAO, post_JLA, post_lensing, post_HST, post_all, post_zre ] groups.append(g) gpol = batchjob.jobGroup('mainpol') gpol.datasets = copy.deepcopy(planck_pol_sets)
post_BAOHSTJLA = [[BAO, JLA, HST], [BAOdata, 'JLA_marge.ini', HSTdata], importanceFilterNotOmegak()] post_BAOHSTPantheon = [[BAO, Pantheon, HST], [BAOdata, 'Pantheon.ini', HSTdata], importanceFilterNotOmegak()] post_BAOlensingPantheon = [[BAO, lensing, Pantheon], [BAOdata, 'lensing.ini', 'Pantheon.ini'], importanceFilterNotOmegak()] post_Pantheon = [[Pantheon], ['Pantheon.ini'], importanceFilterNotOmegak()] post_CookeBBN = ['Cooke17'] post_Aver15 = [['Aver15'], ['Aver15BBN.ini'], importanceFilterNnu()] post_BBN = [['Cooke17', 'Aver15'], ['Aver15BBN.ini', 'Cooke17BBN.ini'], importanceFilterNnu()] # set up groups of parameters and data sets groups = [] g = batchjob.jobGroup('main') g.datasets = copy.deepcopy(planck_highL_sets) for d in g.datasets: d.add(lowl) d.add(lowE, lowEdata) g.params = [[], ['omegak'], ['mnu'], ['r'], ['nrun', 'r'], ['nnu'], ['nrun'], ['Alens'], ['yhe'], ['w'], ['alpha1']] g.importanceRuns = [post_BAO, post_lensing, post_lensingBAO, post_HST, post_BBN] groups.append(g) gpol = batchjob.jobGroup('mainpol') gpol.datasets = copy.deepcopy(planck_pol_sets) for d in gpol.datasets: d.add(lowE, lowEdata) gpol.params = [[], ['mnu'], ['nnu'], ['nrun'], ['Alens'], ['yhe'], ['r']] gpol.importanceRuns = [post_BAO]