def divide_yields(args):
if args[0] not in ['signal', 'data'] :
raise NameError(args)
variable = 'yields'
rnd='.01'
dt_type = args[0]
tag = args[1]
tab_A = args[2]
tab_B = args[3]
label_A, fitbase_A, prefix_A = tools.parse_tabname(_opts, tab_A)
label_B, fitbase_B, prefix_B = tools.parse_tabname(_opts, tab_B)
sys.stdout.write('dhad.tab : Divide %s of %s by %s:' %(
variable, tab_A, tab_B))
tab = DHadTable()
namestyle = 'fname,fnamebar'
tab.column_append_from_dict('Mode', namestyle)
tab.column_append_from_files(label_A, 'N1,N2', fitbase_A, prefix_A,
dt_type, tag ,'txt', rnd='1.')
tab.column_append_from_files(label_B, 'N1,N2', fitbase_B, prefix_B,
dt_type, tag ,'txt', rnd='1.')
tab.column_append_by_divide('%s/%s' %(label_A, label_B), label_A,
label_B, rnd=rnd, err_type='Indp')
tab.output(_tabname)
def yields(opts, tabname, args):
if args[0] not in ['signal', 'data'] :
raise NameError(args)
rnd='.01'
err_type=None
diff = 'pct'
sign = 1
if opts.set:
for li in opts.set.split(':'):
name = li.split('=')[0]
value = li.split('=')[1]
sys.stdout.write('Set %s = %s \n' % (name, value))
if name == 'diff':
diff = value
if name == 'err_type':
err_type = value
if name == 'sign':
sign = value
variable = 'yields'
dt_type = args[0]
tag = args[1]
label_A = args[2]
label_B = args[3]
fitbase = attr.fitbase
sys.stdout.write('dhad.tab : Compare %s between %s and %s:\n' %(
variable, label_A, label_B ))
tab = DHadTable()
namestyle = 'fname,fnamebar'
tab.column_append_from_dict('Mode', namestyle)
tab.column_append_from_files(label_A, 'N1,N2', fitbase, 'dir_%s' %label_A,
dt_type, tag ,'txt', rnd='1.')
tab.column_append_from_files(label_B, 'N1,N2', fitbase, 'dir_%s' %label_B,
dt_type, tag ,'txt', rnd='1.')
if sign == '0':
tab.rows_join_by_average(rnd='1.')
if diff == 'pct':
tab.column_append_by_diff_pct(
'diff(%)', label_B,label_A, rnd=rnd, err_type=err_type)
elif diff == 'sigma_pct':
tab.column_append_by_diff_sigma_pct('diff(%)', label_B,label_A, rnd=rnd)
elif diff == 'sigma2_pct':
tab.column_append_by_diff_sigma2_pct('diff(%)', label_B,label_A, rnd=rnd)
elif diff == 'ratio':
tab.column_append_by_divide(
'ratio', label_B,label_A, rnd=rnd, err_type='Indp')
else:
raise NameError(diff)
tab.output(tabname, test=opts.test)
def eff_kkpi_comp(opts, tabname, label):
tab = DHadTable()
tabprefix = 'dir_' + label
mode = 205
tab.column_append_from_dict('Mode', 'fname,fnamebar', mode=mode)
tab.column_append([20000, 20000], 'Generated')
tab.column_append_from_files('Yield',
'N1,N2',
fitbase,
tabprefix,
's',
's',
'txt',
rnd='1.',
mode=mode)
tab.column_append_by_divide('Eff(%)', 'Yield', 'Generated', 'Efcy', '.01',
100)
tab.columns_delete(['Generated', 'Yield'])
def get_eff(subdir):
logname = 'signal_Single_%s.txt' % modes[mode]['fname']
logpath = os.path.join(attr.logpath, label, subdir, 'yld')
logfile = tools.set_file(extbase=logpath, comname=logname)
for line in file(logfile):
if 'selected' in line:
total = int(line.split()[-1].replace('.', ''))
break
t = DHadTable()
t.column_append([total, total], 'Generated')
t.column_append_from_files('Yield',
'N1,N2',
fitbase,
'%s/%s' % (tabprefix, subdir),
's',
's',
'txt',
rnd='1.',
mode=mode)
t.column_append_by_divide('%s(%%)' % subdir, 'Yield', 'Generated',
'Efcy', '.01', 100)
return t.column_get('%s(%%)' % subdir)
for subdir in ['phipi', 'k0star', 'phsp']:
tab.column_append(get_eff(subdir))
#head_diff = subdir
#col = '%s(%%)' % subdir
#std = 'Eff(%)'
#tab.column_append_by_diff_pct(head_diff, col, std)
tab.output(tabname, label=label)
def divide_yields(args):
if args[0] not in ['signal', 'data']:
raise NameError(args)
variable = 'yields'
rnd = '.01'
dt_type = args[0]
tag = args[1]
tab_A = args[2]
tab_B = args[3]
label_A, fitbase_A, prefix_A = tools.parse_tabname(_opts, tab_A)
label_B, fitbase_B, prefix_B = tools.parse_tabname(_opts, tab_B)
sys.stdout.write('dhad.tab : Divide %s of %s by %s:' %
(variable, tab_A, tab_B))
tab = DHadTable()
namestyle = 'fname,fnamebar'
tab.column_append_from_dict('Mode', namestyle)
tab.column_append_from_files(label_A,
'N1,N2',
fitbase_A,
prefix_A,
dt_type,
tag,
'txt',
rnd='1.')
tab.column_append_from_files(label_B,
'N1,N2',
fitbase_B,
prefix_B,
dt_type,
tag,
'txt',
rnd='1.')
tab.column_append_by_divide('%s/%s' % (label_A, label_B),
label_A,
label_B,
rnd=rnd,
err_type='Indp')
tab.output(_tabname)
def get_eff(subdir):
logname = 'signal_Single_%s.txt' % modes[mode]['fname']
logpath = os.path.join(attr.logpath, label, subdir, 'yld')
logfile = tools.set_file(extbase=logpath, comname=logname)
for line in file(logfile):
if 'selected' in line:
total = int(line.split()[-1].replace('.', ''))
break
t = DHadTable()
t.column_append([total, total], 'Generated')
t.column_append_from_files('Yield',
'N1,N2',
fitbase,
'%s/%s' % (tabprefix, subdir),
's',
's',
'txt',
rnd='1.',
mode=mode)
t.column_append_by_divide('%s(%%)' % subdir, 'Yield', 'Generated',
'Efcy', '.01', 100)
return t.column_get('%s(%%)' % subdir)
