def brf_data_results(opts, tabname, args): ''' ----------------------------- Results of the Data Fit ----------------------------- ''' label_A = args[0] label_B = args[1] verbose = opts.verbose bffilename = 'bf_stat_sys' labels = [] labels.append(label_A) labels.append(label_B) tab = DHadTable() paras = False for label in labels: if '281ipb' in label: factor = 0.000001 elif '537ipb' in label: factor = 0.000001*281/537 elif '818ipb' in label or 'v13' in label: factor = 0.000001*281/818 else: raise NameError(label) if '818ipb' in label_A and '818ipb' in label_B: factor = 0.000001 if '818ipb' in label_A and 'v13' in label_B: factor = 0.000001 bffile = os.path.join(attr.brfpath, label, bffilename) if not paras: tab.column_append(tools.parse_result(bffile, 'paras'), 'Parameters') paras = True tab.column_append(tools.parse_result(bffile, 'value'), 'value', rnd='.00001' ) tab.column_append(tools.parse_result(bffile, 'stat'), 'stat') tab.column_append(tools.parse_result(bffile, 'syst'), 'syst') tab.columns_join3('Fitted Value', 'value', 'stat', 'syst') tab.column_trim('Fitted Value', row=['ND0D0Bar', 'ND+D-'], rnd='.0001', factor=factor, opt='(cell)x1E6') tab.column_trim('Fitted Value', rnd='.00001', except_row=['ND0D0Bar', 'ND+D-']) tab.column_append(tools.parse_result(bffile, 'err_frac'), 'Frac. Err', rnd='.1', opt='(cell%)') tab.columns_join(label, 'Fitted Value','Frac. Err', str=' ') tab.column_append_by_diff_sigma('Difference', label_B,label_A) tab.output(tabname, test=opts.test)
def fitResultsMC(opts, tabname, label): bffilename = 'bf_stat' bffile = tools.set_file(extbase=attr.brfpath, prefix='dir_' + label, comname=bffilename) if '281ipbv0' in label and '/generic' in label: generated = attr.Generic281v0_NBF power = '10E6' factor = 0.000001 elif '281ipbv12' in label and '/generic' in label: generated = attr.Generic281_NBF power = '10E7' factor = 0.0000001 elif '818ipbv12' in label and '/generic' in label: generated = attr.Generic818_NBF power = '10E7' factor = 0.0000001 else: raise NameError(label) tab = DHadTable() tab.column_append(parse_result(bffile, 'paras'), 'Parameters') tab.column_append(parse_result(bffile, 'value_err'), 'Fitted Value') tab.column_append(generated, 'Generated Value') tab.column_append_by_diff_sigma('Difference', 'Fitted Value', 'Generated Value') tab.column_trim('Fitted Value', row=['ND0D0Bar', 'ND+D-'], rnd='.001', factor=factor, opt='(cell)x%s' % power) tab.column_trim('Fitted Value', rnd='.00001', except_row=['ND0D0Bar', 'ND+D-']) tab.column_append(parse_result(bffile, 'err_frac'), 'Frac. Err', rnd='.1', opt='(cell%)') tab.columns_join('Fitted Value', 'Fitted Value', 'Frac. Err', str=' ') tab.column_trim('Generated Value', row=['ND0D0Bar', 'ND+D-'], rnd='.001', factor=factor, opt='cellx%s' % power) tab.output(tabname, label=label)
def pdg2009(args): ''' -------------------------------------------------------- Results of the Data Fit Compare with PDG 2009 -------------------------------------------------------- ''' label = args[0] verbose = opts.verbose bffilename = 'bf_stat_sys' bffile = os.path.join(attr.brfpath, label, bffilename) tab = DHadTable() tab.column_append(tools.parse_result(bffile, 'paras'), 'Parameters') tab.column_append(tools.parse_result(bffile, 'value'), 'value') tab.column_append(tools.parse_result(bffile, 'stat'), 'stat') tab.column_append(tools.parse_result(bffile, 'syst'), 'syst') tab.columns_join3('Fitted Value', 'value', 'stat', 'syst') tab.column_trim('Fitted Value', row = ['ND0D0Bar', 'ND+D-'], rnd = '.001', factor = 0.000001, opt = '(cell)x10E6') tab.column_trim('Fitted Value', rnd = '.0001', except_row = ['ND0D0Bar', 'ND+D-']) tab.column_append(tools.parse_result(bffile, 'err_frac'), 'Frac. Err', rnd = '.1', opt = '(cell%)') tab.columns_join('Fitted Value','Fitted Value','Frac. Err', str=' ') tab.column_append(attr.PDG2009_NBF, 'PDG 2009') tab.column_append_by_diff_sigma('Difference', 'Fitted Value', 'PDG 2009') tab.output(_tabname)