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 para_argus(para, args):
namestyle = 'fname'
rnd = '0.01'
tag = 's'
rowName = para
extbase = attr.fitbase
ext = 'txt'
dt_type = args[0]
tab_A = args[1]
tab_B = args[2]
label_A = tab_A
label_B = tab_B
label = tools.parseopts_set(opts.set, 'label')
if label:
labels = label.split(',')
label_A = labels[0]
label_B = labels[1]
tab = DHadTable()
tab.column_append_from_dict('Mode', namestyle)
tab.column_append_from_files(label_A, rowName, extbase, 'dir_'+tab_A,
dt_type, tag, ext, rnd=rnd)
tab.column_append_from_files(label_B, rowName, extbase, 'dir_'+tab_B,
dt_type, tag, ext, rnd=rnd)
tab.column_append_by_diff_pct('diff(%)', label_B, label_A, rnd=rnd)
tab.output(_tabname)
def momentum(opts, tabname, args):
if args[0] != 'resolution':
raise NameError(args)
label = args[1]
dt_type = 'signal'
tag = 'double'
#ver = opts.analysis
fitbase = attr.fitpath
prefix = 'dir_%s/resolution' % label
# Mode | sigma(MeV) | fa | fb | sa | sb | [sigmaE (MeV)]
tab = DHadTable()
tab.column_append_from_dict('Mode', 'fname')
tab.column_append_from_files(
'sigma (MeV)', 'sigmacommon1', fitbase, prefix,
dt_type, tag, 'txt', rnd='.01', factor=1000)
tab.column_append_from_files('fa', 'f1a', fitbase, prefix,
dt_type, tag, 'txt', rnd='.001')
tab.column_append_from_files('fb', 'f1b', fitbase, prefix,
dt_type, tag, 'txt', rnd='.0001')
tab.column_append_from_files('sa', 's1a', fitbase, prefix,
dt_type, tag, 'txt', rnd='.01')
tab.column_append_from_files('sb', 's1b', fitbase, prefix,
dt_type, tag, 'txt', rnd='.01')
tab.output(tabname, test=opts.test)
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 vary_argus_single(opts, tabname, label):
tab = DHadTable()
print tabname
tabprefix0 = 'dir_818ipbv7/argus_low/fix_n1n2'
tabprefix1 = 'dir_818ipbv7'
tabprefix2 = 'dir_818ipbv7/argus_high/fix_n1n2'
tab.column_append_from_dict('Mode', 'fname,fnamebar')
titles = ['argus_low', 'std', 'argus_high']
tab.column_append_from_files(titles[0], 'N1,N2', fitbase, tabprefix0, 'd',
's', 'txt')
tab.column_append_from_files(titles[1], 'N1,N2', fitbase, tabprefix1, 'd',
's', 'txt')
tab.column_append_from_files(titles[2], 'N1,N2', fitbase, tabprefix2, 'd',
's', 'txt')
std = titles[1]
colA = titles[0]
colB = titles[2]
headA = 'diff(%s)' % colA
headB = 'diff(%s)' % colB
headC = 'max-diff(%)'
tab.column_append_by_diff_pct(headA, colA, std)
tab.column_append_by_diff_pct(headB, colB, std)
tab.column_append_by_max(headC, headA, headB)
#tab.columns_delete([headA, headB])
tab.columns_trim(titles, rnd='1.')
tab.output() #tabname, texhead, outputtxt=True)
def evtfile(args):
if args[0] not in ['signal', 'data'] :
raise NameError(args)
variable = 'yields'
dt_type = args[0]
tag = args[1]
evt_A = args[2]
evt_B = args[3]
label_A, evtbase_A, prefix_A = tools.parse_evtname(opts, evt_A)
label_B, evtbase_B, prefix_B = tools.parse_evtname(opts, evt_B)
filelist_A = tools.set_file_list(evtbase_A, prefix_A, dt_type, tag, 'evt')
filelist_B = tools.set_file_list(evtbase_B, prefix_B, dt_type, tag, 'evt')
zipped = zip(filelist_A, filelist_B)
for f in zipped:
fa = f[0]
fb = f[1]
diff = tools.diff(fa, fb)
print diff
sys.exit()
sys.stdout.write('dhad.tab : Compare %s between %s and %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_diff_sigma_pct('diff(%)', label_B,label_A, rnd=rnd)
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)
def argus(opts, tabname, args):
if args[0] == 'slope':
rowname_A = 'xi'
rowname_B = 'xi'
rowname_C = 'xi'
if args[0] == 'power':
rowname_A = 'p'
rowname_B = 'p'
rowname_C = 'p'
label = args[1]
if args[2] != 'desidebands':
raise NameError(args)
namestyle = 'fname'
rnd = '0.01'
tag = 's'
extbase = attr.fitbase
ext = 'txt'
dt_type = 'data'
label_A = label
prefix_A = 'dir_%s' % label_A
label_B = 'desideband_low'
prefix_B = 'dir_%s/%s' % (label, label_B)
label_C = 'desideband_high'
prefix_C = 'dir_%s/%s' % (label, label_C)
tab = DHadTable()
tab.column_append_from_dict('Mode', namestyle)
tab.column_append_from_files(label_A, rowname_A, extbase, prefix_A,
dt_type, tag, ext, rnd=rnd)
tab.column_append_from_files(label_B, rowname_B, extbase, prefix_B,
dt_type, tag, ext, rnd=rnd)
tab.column_append_from_files(label_C, rowname_C, extbase, prefix_C,
dt_type, tag, ext, rnd=rnd)
tab.output(tabname)
