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 events(args):
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
unique_evt_label = label
if _set and 'events' in _set:
unique_evt_label = _set.split('=')[1]
tab = DHadTable()
row = ['Mode']
row.extend(attr.datasets_281)
tab.row_append(row)
for mode in modes:
modename = mode.replace('Single_', '')
evtfile = get_unique_evtfile(datatype,
mode,
unique_evt_label,
debug=_debug)
f = EventsFile(evtfile)
row = map(str, f.datasets_sorted)
row.insert(0, modename)
tab.row_append(row)
tab.output(_tabname)
def events(args):
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label_A = parsed[3]
label_B = args[3]
datpath = attr.datpath
tab = DHadTable()
tab.row_append(['Mode', label_A, label_B, 'Common',
'Unique(%s)' %label_A, 'Unique(%s)' %label_B ])
tab.head = tab.data[0]
for mode in modes:
modename = mode.replace('Single_', '')
evtname = datatype + '_' + mode + '.evt'
evtpath_A = os.path.join(datpath, 'evt', label_A, 'events')
evtfile_A = os.path.join(evtpath_A, evtname)
f_A = UserFile(evtfile_A)
events_A = Set(f_A.data)
evtpath_B = os.path.join(datpath, 'evt', label_B, 'events')
evtfile_B = os.path.join(evtpath_B, evtname)
f_B = UserFile(evtfile_B)
events_B = Set(f_B.data)
events_inter = events_A & events_B
entries_A = len(events_A)
entries_B = len(events_B)
common = len(events_inter)
unique_A = len(events_A - events_inter)
unique_B = len(events_B - events_inter)
row = [modename, entries_A, entries_B, common, unique_A, unique_B]
tab.row_append(map(str, row))
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 ratios_signal(args):
if args[0] == '537ipb/281ipb' and args[1] == '537ipbv2/281ipb':
tabfilename1 = 'compare_yields_signal_divide_537ipb_9.03_regular12.txt'
title1 = args[0]
headname1 = title1
tabfilename2 = 'compare_yields_signal_divide_537ipbv2_9.03_regular12.txt'
title2 = args[1]
headname2 = title2
else:
raise NameError(args)
tabfile1 = os.path.join(attr.tabpath, tabfilename1)
tabfile2 = os.path.join(attr.tabpath, tabfilename2)
if opts.set and opts.set == 'info':
print 'here'
tab = DHadTable()
tab.column_append_from_tab_file('Mode', tabfile1, 'Mode')
tab.column_append_from_tab_file(title1, tabfile1, headname1)
tab.column_append_from_tab_file(title2, tabfile2, headname2)
tab.column_append_by_diff_sigma_pct('diff(%)', title2, title1)
tab.output(_tabname)
def para_md(args):
para = 'md'
namestyle = 'fname'
rnd = '0.0000001'
tag = 's'
tab_A = args[0]
tab_B = args[1]
latel_A = tab_A
latel_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_fit_files(label_A, tab_A, para, tag, rnd)
tab.column_append_from_fit_files(label_B, tab_B, para, tag, rnd)
tab.column_append_by_diff('diff[MeV]', label_B,label_A, rnd=rnd, factor=1000)
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 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 md(opts, tabname, args):
para = 'md'
namestyle = 'fname'
rnd = '0.0000001'
tag = 's'
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 == 'label':
label = value
if args[0] == '281ipb':
tab_A_name = args[1]
tab_B_name = args[2]
tab_C_name = args[3]
if label:
labels = label.split(',')
tab_A_name = labels[0]
tab_B_name = labels[1]
tab_C_name = labels[2]
tab = DHadTable()
tab.column_append_from_dict('Mode', namestyle)
tab.column_append_from_fit_files(tab_A_name, args[1], para, tag, rnd)
tab.column_append_from_fit_files(tab_B_name, args[2], para, tag, rnd)
tab.column_append_from_fit_files(tab_C_name, args[3], para, tag, rnd)
tab.output(_tabname)
else:
raise ValueError(args)
def events(args):
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
unique_evt_label = label
if _set and 'events' in _set:
unique_evt_label = _set.split('=')[1]
tab = DHadTable()
row = ['Mode']
row.extend(attr.datasets_281)
tab.row_append(row)
for mode in modes:
modename = mode.replace('Single_', '')
evtfile = get_unique_evtfile(
datatype, mode, unique_evt_label, debug=_debug)
f = EventsFile(evtfile)
row = map(str, f.datasets_sorted)
row.insert(0, modename)
tab.row_append(row)
tab.output(_tabname)
def entries(args):
dt_type = args[0]
tag = args[1]
label_A = args[2]
label_B = args[3]
evtpath = attr.evtpath
rnd='.01'
err_type=None
label = None
diff = 'pct'
tab = DHadTable()
tab.row_append(['Mode', label_A, label_B])
tab.head = tab.data[0]
for mode in attr.modes:
for sign in [1, -1]:
evtfile_A = tools.set_file('evt', dt_type, mode, tag, sign=sign,
prefix='dir_'+label_A, extbase=evtpath)
evtfile_B = tools.set_file('evt', dt_type, mode, tag, sign=sign,
prefix='dir_'+label_B, extbase=evtpath)
entries_A = tools.count_lines(evtfile_A)
entries_B = tools.count_lines(evtfile_B)
if sign == 1:
modename = attr.modes[mode]['fname']
else:
modename = attr.modes[mode]['fnamebar']
row = [modename, entries_A, entries_B]
tab.row_append(map(str, row))
tab.column_append_by_diff_pct('diff(%)', label_B,label_A, rnd=rnd, err_type=err_type)
tab.output(_tabname)
def diff(args):
label= None
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 == 'label':
label = value
if label:
labels = label.split(',')
label_A = labels[0]
label_B = labels[1]
tab_A = 'compare_%s.txt' % args[0]
tab_B = 'compare_%s.txt' % args[1]
tabfile_A = os.path.join(attr.tabpath, tab_A)
tabfile_B = os.path.join(attr.tabpath, tab_B)
tab = DHadTable()
tab.column_append_from_tab_file('Mode', tabfile_A, 'Mode')
tab.column_append_from_tab_file(label_A, tabfile_A, 'diff(%)')
tab.column_append_from_tab_file(label_B, tabfile_B, 'diff(%)')
tab.column_append_by_diff('diff', label_B,label_A)
tab.output(_tabname)
def make_overview_table(tabname, datatype, modes, label, test=False):
tab = DHadTable()
tab.row_append(['Mode', 'Backgrounds'])
for mode in modes:
modename = mode.replace('Single_', '')
bkgtable = get_bkg_tab_link(datatype, mode, label)
line = [modename, bkgtable]
tab.row_append(line)
tab.output(tabname, test=test)
def bkg_generic_cont(tabname, datatype, tag, modes, label, test, debug):
tab = DHadTable()
row = ['Mode', 'Continuum Backgrounds']
tab.row_append(row)
for mode in modes:
new_row = bkg_cont_single_mode(datatype, mode, label, debug)
tab.row_append(new_row)
tab.output(tabname, test=test)
def make_overview_table(tabname, datatype, modes, label, test=False):
tab = DHadTable()
tab.row_append(['Mode', 'Backgrounds'])
for mode in modes:
modename = mode.replace('Single_', '')
bkgtable = get_bkg_tab_link(datatype, mode, label)
line = [modename, bkgtable]
tab.row_append(line)
tab.output(tabname, test=test)
def evt(opts, args):
tabname = 'entries_evt_' + '_'.join(args).replace('/', '_')
if args[0] == 'log':
return evt_log(args[1:])
if args[0] not in ['data']:
raise NameError(args)
dt_type = args[0]
tag = args[1]
label = args[2]
evtpath = attr.evtpath()
if '/' in label:
ver = label.split('/')[0]
label = label.split('/')[1]
evtpath = attr.evtpath(ver)
prefix = 'dir_' + label
tab = DHadTable()
tab.row_append(['Mode', 'fname', 'fnamebar', 'combined', 'sum(theory)'])
for mode in attr.modes:
evtfile1 = tools.set_file('evt',
dt_type,
mode,
tag,
sign=-1,
prefix=prefix,
extbase=evtpath)
evtfile2 = tools.set_file('evt',
dt_type,
mode,
tag,
sign=1,
prefix=prefix,
extbase=evtpath)
evtfile_combined = tools.set_file('evt',
dt_type,
mode,
tag,
prefix=prefix,
extbase=evtpath)
entries1 = tools.count_lines(evtfile1)
entries2 = tools.count_lines(evtfile2)
sumup = entries1 + entries2
entries_combined = tools.count_lines(evtfile_combined)
row = [mode, entries1, entries2, entries_combined, sumup]
tab.row_append(map(str, row))
tab.output(tabname)
def bkg_generic_cont(tabname, datatype, tag, modes,
label, test, debug):
tab = DHadTable()
row = ['Mode', 'Continuum Backgrounds']
tab.row_append(row)
for mode in modes:
new_row = bkg_cont_single_mode(datatype, mode, label, debug)
tab.row_append(new_row)
tab.output(tabname, test=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 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 bkg_generic_ddbar(tabname, datatype, tag, modes, label, test, debug):
ranges = ['>0', '>50', '>100', '>200', '>500', '>1000', '>2000', '>3000']
tab = DHadTable()
row = ['Mode', 'Backgrounds']
row.extend(ranges)
tab.row_append(row)
for mode in modes:
new_row = bkg_ddbar_single_mode(datatype, mode, label, ranges, debug)
tab.row_append(new_row)
tab.output(tabname, test=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 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 bkg_names(opts, args):
debug_ = opts.debug
test_ = opts.test
set_ = opts.set
prefix = None
if args[0] == 'peak':
prefix = 'peak'
args = args[1:]
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
limit = None
if set_ != None and 'min' in set_:
min_ = set_.split('=')[1]
limit = '>%s' %min_
bkgmodes = 20
if set_ != None and 'bkgmodes' in set_:
bkgmodes = int(set_.split('=')[1])
for mode in modes:
tabname = 'bkg_names_%s_%s_%s' %(
datatype, mode, label)
if prefix != None:
tabname = 'bkg_names_%s_%s_%s_%s' %(
prefix, datatype, mode, label)
tabname = tabname.replace('/', '_')
tab = DHadTable()
modename = get_orgname_from_fname(mode)
bkg_names, bkg_numbers = bkg_names_single_mode(
datatype, mode, label, limit, bkgmodes, debug_, prefix)
tab.column_append(bkg_names, title='Backgrounds for %s' %modename)
tab.column_append(bkg_numbers, title='Number of Events')
tab.sort_by_column('Number of Events', reverse=True)
orgfooter = ': '+sys.argv[0].split('/')[-1]+\
' tab backgrounds names %s %s %s ' %(
datatype, mode, label)
if prefix != None:
orgfooter = ': '+sys.argv[0].split('/')[-1]+\
' tab backgrounds names %s %s %s %s ' %(
prefix, datatype, mode, label)
tab.output(tabname, orgfooter=orgfooter, test=test_)
def bkg_generic_ddbar(tabname, datatype, tag, modes, label, test, debug):
ranges = ['>0', '>50', '>100', '>200', '>500',
'>1000', '>2000', '>3000']
tab = DHadTable()
row = ['Mode', 'Backgrounds']
row.extend(ranges)
tab.row_append(row)
for mode in modes:
new_row = bkg_ddbar_single_mode(datatype, mode, label, ranges, debug)
tab.row_append(new_row)
tab.output(tabname, test=test)
def mctruth_names(opts, args):
debug_ = opts.debug
test_ = opts.test
set_ = opts.set
prefix = None
if args[0] == 'peak':
prefix = 'peak'
args = args[1:]
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
limit = None
if set_ != None and 'min' in set_:
min_ = set_.split('=')[1]
limit = '>%s' % min_
mctruthmodes = 50
if set_ != None and 'mctruthmodes' in set_:
mctruthmodes = int(set_.split('=')[1])
for mode in modes:
tabname = 'mctruth_names_%s_%s_%s' % (datatype, mode, label)
if prefix != None:
tabname = 'mctruth_names_%s_%s_%s_%s' % (prefix, datatype, mode,
label)
tabname = tabname.replace('/', '_')
tab = DHadTable()
modename = get_orgname_from_fname(mode)
mctruth_names, mctruth_numbers = mctruth_names_single_mode(
datatype, mode, label, limit, mctruthmodes, debug_, prefix)
tab.column_append(mctruth_names, title='MC Truth for %s' % modename)
tab.column_append(mctruth_numbers, title='Number of Events')
tab.sort_by_column('Number of Events', reverse=True)
orgfooter = ': '+sys.argv[0].split('/')[-1]+\
' tab mctruth names %s %s %s ' %(
datatype, mode, label)
if prefix != None:
orgfooter = ': '+sys.argv[0].split('/')[-1]+\
' tab mctruth names %s %s %s %s ' %(
prefix, datatype, mode, label)
tab.output(tabname, orgfooter=orgfooter, test=test_)
def compare_yields_data_signal_divide_537ipb(args):
sys.stdout.write('dhad.table: Creating %s ...\n' % _tabname)
tabpath1 = os.path.join(
attr.base, '7.06', 'tab')
tabfile1 = os.path.join(
tabpath1, 'compare_yields_data_divide_281ipb_537ipb.txt')
tabfile2 = os.path.join(
attr.tabpath, 'compare_yields_signal_divide_537ipb_9.03_regular12.txt')
tab = DHadTable()
tab.column_append_from_tab_file('Mode', tabfile1, 'Mode')
tab.column_append_from_tab_file('Data', tabfile1, '537ipb/281ipb')
tab.column_append_from_tab_file('Signal', tabfile2, '537ipb/281ipb')
tab.column_append_by_diff_sigma_pct('diff(%)', 'Signal', 'Data')
tab.output(_tabname)
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 evt(opts, args):
tabname = 'entries_evt_' + '_'.join(args).replace('/', '_')
if args[0] == 'log':
return evt_log(args[1:])
if args[0] not in ['data'] :
raise NameError(args)
dt_type = args[0]
tag = args[1]
label = args[2]
evtpath = attr.evtpath()
if '/' in label:
ver = label.split('/')[0]
label = label.split('/')[1]
evtpath = attr.evtpath(ver)
prefix = 'dir_' + label
tab = DHadTable()
tab.row_append(['Mode', 'fname', 'fnamebar', 'combined', 'sum(theory)'])
for mode in attr.modes:
evtfile1 = tools.set_file('evt', dt_type, mode, tag, sign=-1,
prefix=prefix, extbase=evtpath)
evtfile2 = tools.set_file('evt', dt_type, mode, tag, sign=1,
prefix=prefix, extbase=evtpath)
evtfile_combined = tools.set_file('evt', dt_type, mode, tag,
prefix=prefix, extbase=evtpath)
entries1 = tools.count_lines(evtfile1)
entries2 = tools.count_lines(evtfile2)
sumup = entries1 + entries2
entries_combined = tools.count_lines(evtfile_combined)
row = [mode, entries1, entries2, entries_combined, sumup]
tab.row_append(map(str, row))
tab.output(tabname)
def main(opts, args):
if args[0] == 'names':
return bkg_names(opts, args[1:])
tabname = 'bkg_' + '_'.join(args).replace('/', '_')
debug = opts.debug
test = opts.test
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
if args[0] == 'generic':
return bkg_generic_ddbar(tabname, datatype, tag, modes, label, test,
debug)
elif args[0] == 'generic/cont':
return bkg_generic_cont(tabname, datatype, tag, modes, label, test,
debug)
elif args[0] == 'generic/ddbar':
return bkg_generic_ddbar(tabname, datatype, tag, modes, label, test,
debug)
tab = DHadTable()
row = [
'Mode', 'Number of DDbar Backgrounds',
'Number of Continuum Backgrounds'
]
tab.row_append(row)
for mode in modes:
modename = mode.replace('Single_', '')
ddbarnum = get_bkg_total('generic/ddbar', mode, label, debug)
contnum = get_bkg_total('generic/cont', mode, label, debug)
row = [modename, ddbarnum, contnum]
tab.row_append(row)
tab.column_trim('Number of DDbar Backgrounds', rnd='1')
tab.column_trim('Number of Continuum Backgrounds', rnd='1')
tab.output(tabname, test=test)
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)
def brf_data_syst(args):
print args
label_A = args[0]
label_B = args[1]
bffilename = 'bf_stat_sys'
tab = DHadTable()
bffileA = os.path.join(attr.brfpath, label_A, bffilename)
tab.column_append(tools.parse_result(bffileA, 'paras'), 'Parameters')
tab.column_append(tools.parse_result(bffileA, 'value'), 'value_A')
tab.column_append(tools.parse_result(bffileA, 'syst'), label_A)
bffileB = os.path.join(attr.brfpath, label_B, bffilename)
tab.column_append(tools.parse_result(bffileB, 'value'), 'value_B')
tab.column_append(tools.parse_result(bffileB, 'syst'), label_B)
#tab.column_append_by_diff_sigma_pct('diff(%)', label_B,label_A, rnd=rnd)
tab.output()
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 main(opts, args):
if args[0] == 'names':
return bkg_names(opts, args[1:])
tabname = 'bkg_' + '_'.join(args).replace('/', '_')
debug = opts.debug
test = opts.test
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
if args[0] == 'generic':
return bkg_generic_ddbar(tabname, datatype,
tag, modes, label, test, debug)
elif args[0] == 'generic/cont':
return bkg_generic_cont(tabname, datatype,
tag, modes, label, test, debug)
elif args[0] == 'generic/ddbar':
return bkg_generic_ddbar(tabname, datatype,
tag, modes, label, test, debug)
tab = DHadTable()
row = ['Mode', 'Number of DDbar Backgrounds',
'Number of Continuum Backgrounds']
tab.row_append(row)
for mode in modes:
modename = mode.replace('Single_', '')
ddbarnum = get_bkg_total('generic/ddbar', mode, label, debug)
contnum = get_bkg_total('generic/cont', mode, label, debug)
row = [modename, ddbarnum, contnum]
tab.row_append(row)
tab.column_trim('Number of DDbar Backgrounds', rnd='1')
tab.column_trim('Number of Continuum Backgrounds', rnd='1')
tab.output(tabname, test=test)
def brf_data_syst(args):
print args
label_A = args[0]
label_B = args[1]
bffilename = 'bf_stat_sys'
tab = DHadTable()
bffileA = os.path.join(attr.brfpath, label_A, bffilename)
tab.column_append(tools.parse_result(bffileA, 'paras'), 'Parameters')
tab.column_append(tools.parse_result(bffileA, 'value'), 'value_A')
tab.column_append(tools.parse_result(bffileA, 'syst'), label_A)
bffileB = os.path.join(attr.brfpath, label_B, bffilename)
tab.column_append(tools.parse_result(bffileB, 'value'), 'value_B')
tab.column_append(tools.parse_result(bffileB, 'syst'), label_B)
#tab.column_append_by_diff_sigma_pct('diff(%)', label_B,label_A, rnd=rnd)
tab.output()
def evt_log(args):
print args
if args[0] not in ['data'] :
raise NameError(args)
dt_type = args[0]
tag = args[1]
label = args[2]
evtpath = attr.evtpath()
if '/' in label:
ver = label.split('/')[0]
label = label.split('/')[1]
evtpath = attr.evtpath(ver)
prefix = 'dir_' + label
evttab = 'entries_evt' + '_'.join(args).replace('/', '_') + '.tab'
tab = DHadTable()
tab.column_append_from_tab_file('Mode', evttab)
tab.output()
sys.exit()
def evt_log(args):
print args
if args[0] not in ['data']:
raise NameError(args)
dt_type = args[0]
tag = args[1]
label = args[2]
evtpath = attr.evtpath()
if '/' in label:
ver = label.split('/')[0]
label = label.split('/')[1]
evtpath = attr.evtpath(ver)
prefix = 'dir_' + label
evttab = 'entries_evt' + '_'.join(args).replace('/', '_') + '.tab'
tab = DHadTable()
tab.column_append_from_tab_file('Mode', evttab)
tab.output()
sys.exit()
def fsr_syst(args):
'''
--------------------
FSR systematics
--------------------
'''
tab_name = 'FSR_syst'
tabbase = os.path.join(attr.base, '7.06', 'tab')
tab = DHadTable()
tab.column_append_from_dict('Mode', 'fname,fnamebar')
tab_file = os.path.join(tabbase, 'noFSR_single_signal_eff.txt')
columnA = 'Efficiency without FSR(%)'
tab.column_append_from_tab_file(columnA, tab_file)
columnB = 'Efficiency with FSR(%)'
tab.column_append_from_tab_file(columnB, tab_file)
tab.column_append_by_diff('diff(%)', columnA, columnB, factor=100)
tab.column_append_by_times_number('diff X 30%', 'diff(%)', '0.3',
rnd='.01')
tab.rows_join_by_max('diff X 30%')
tab.output(tab_name)
def runs(args):
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
unique_evt_label = label
datatype = 'data'
run_event_set = Set([])
for mode in attr.single_mode_list:
evtname = '%s_%s_unqiue_%s.evt' %(datatype, mode, label)
evtpath = os.path.join(attr.datpath, 'evt', label, 'events')
unique_file = os.path.join(evtpath, evtname)
f = UserFile(unique_file)
events = Set(f.data)
run_event_set.update(events)
fe = EventsFile()
fe.data = list(run_event_set)
fe.parse()
tab = DHadTable()
row = ['Dataset', 'Run', 'Number of Events']
tab.row_append(row)
for run, num in sorted(fe.runs.iteritems()):
dataset = get_dataset_by_run(run)
row = [dataset, run, num]
tab.row_append(map(str, row))
if _test:
tab.output()
sys.stdout.write('\ntest: Will write to %s\n' %_tabname)
else:
tab.output(_tabname)
def signal_line_shape_syst(args):
'''
--------------------------------------------------
Signal line shape systematics
--------------------------------------------------
'''
tab_name = 'signal_line_shape_syst'
tabbase = os.path.join(attr.base, '7.06', 'tab')
tab = DHadTable()
tab.column_append_from_dict('Mode', 'fname,fnamebar')
tab_file_A = os.path.join(
tabbase, 'yields_M_3.7713_regular_M_3.7723_data_Single.txt')
name_A = 'Mass(+/-0.5 MeV)%'
column = 'max-diff(%)'
tab.column_append_from_tab_file(name_A, tab_file_A, column)
tab_file_B = os.path.join(
tabbase, 'yields_Gamma_0.0261_regular_Gamma_0.0311_data_Single.txt')
name_B = 'Gamma(+/-2.5 MeV)%'
tab.column_append_from_tab_file(name_B, tab_file_B, column)
tab_file_C = os.path.join(
tabbase, 'yields_R_8.3_regular_R_16.3_data_Single.txt')
name_C = 'R(+/- 4)%'
tab.column_append_from_tab_file(name_C, tab_file_C, column)
name_D = 'Total(%)'
tab.column_append_by_add_quadrature3(name_D, name_A,
name_B, name_C, rnd='.01')
tab.rows_join_by_max(name_D)
tab.output(tab_name)
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)
def runs(args):
parsed = yld.parse_args(args)
datatype = parsed[0]
tag = parsed[1]
modes = parsed[2]
label = parsed[3]
unique_evt_label = label
datatype = 'data'
run_event_set = Set([])
for mode in attr.single_mode_list:
evtname = '%s_%s_unqiue_%s.evt' % (datatype, mode, label)
evtpath = os.path.join(attr.datpath, 'evt', label, 'events')
unique_file = os.path.join(evtpath, evtname)
f = UserFile(unique_file)
events = Set(f.data)
run_event_set.update(events)
fe = EventsFile()
fe.data = list(run_event_set)
fe.parse()
tab = DHadTable()
row = ['Dataset', 'Run', 'Number of Events']
tab.row_append(row)
for run, num in sorted(fe.runs.iteritems()):
dataset = get_dataset_by_run(run)
row = [dataset, run, num]
tab.row_append(map(str, row))
if _test:
tab.output()
sys.stdout.write('\ntest: Will write to %s\n' % _tabname)
else:
tab.output(_tabname)
def draw_momenta_ks3pi(datatype, mode, label, test):
modekey = tools.get_modekey(mode)
sname = attr.modes[modekey]['sname'].lower()
figname = '%s_momenta' % sname
figpath = os.path.join(attr.figpath, label, 'trkmtm')
epsfile = set_file(extbase=figpath, comname=figname, ext='eps')
tab = DHadTable()
tab.row_append(['Name', 'Data/MC'])
# --------------------------------------------------
h_pks = {}; h_ppi1 = {}; h_ppi2 = {}; h_ppim = {}
h_pks_c = {}; h_ppi1_c = {}; h_ppi2_c = {}; h_ppim_c = {}
for datatype in datatype.split('/'):
selfile = get_selfile(datatype, mode, label, test=test)
selfile = selfile.replace('/trkmtm/', '/trkmtm2/')
f = TFile(selfile)
if datatype == 'signal' or datatype == 'generic':
tp = 'mc'
if datatype == 'data':
tp = 'data'
h_pks[tp]= f.Get('h_pks'+tp)
h_ppi1[tp]= f.Get('h_ppi1'+tp)
h_ppi2[tp]= f.Get('h_ppi2'+tp)
h_ppim[tp]= f.Get('h_ppim'+tp)
h_pks_c[tp]= f.Get('h_pk_c'+tp)
h_ppi1_c[tp]= f.Get('h_ppi1_c'+tp)
h_ppi2_c[tp]= f.Get('h_ppi2_c'+tp)
h_ppim_c[tp]= f.Get('h_ppim_c'+tp)
f.Clear()
ratio = h_pks['data'].Integral()/h_pks['mc'].Integral()
c1 = TCanvas('c1', 'canvas', 900, 900)
c1.Divide(2,2)
c1.cd(1)
h_pks['data'].Draw('PE')
h_pks['mc'].Scale(ratio)
h_pks['mc'].Draw('SAME')
c1.cd(2)
h_ppi1['data'].Draw('PE')
h_ppi1['mc'].Scale(ratio)
h_ppi1['mc'].Draw('SAME')
c1.cd(3)
h_ppi2['data'].Draw('PE')
h_ppi2['mc'].Scale(ratio)
h_ppi2['mc'].Draw('SAME')
c1.cd(4)
h_ppim['data'].Draw('PE')
h_ppim['mc'].Scale(ratio)
h_ppim['mc'].Draw('SAME')
c1.Print(epsfile)
tools.eps2pdf(epsfile)
# --------------------------------------------------
c1.Clear()
c1.Divide(2,2)
c1.cd(1)
h_pks_c['data'].Draw('PE')
lratio = h_pks_c['data'].Integral()/h_pks_c['mc'].Integral()
#print 'k:', lratio/ratio
tab.row_append(['K', lratio/ratio])
h_pks_c['mc'].Scale(lratio)
h_pks_c['mc'].Draw('SAME,HIST')
c1.cd(2)
h_ppi1_c['data'].Draw('PE')
lratio = h_ppi1_c['data'].Integral()/h_ppi1_c['mc'].Integral()
#print 'pi1:', lratio/ratio
tab.row_append(['pi1', lratio/ratio])
h_ppi1_c['mc'].Scale(lratio)
h_ppi1_c['mc'].Draw('SAME,HIST')
c1.cd(3)
h_ppi2_c['data'].Draw('PE')
lratio = h_ppi2_c['data'].Integral()/h_ppi2_c['mc'].Integral()
#print 'pi2:', lratio/ratio
tab.row_append(['pi2', lratio/ratio])
h_ppi2_c['mc'].Scale(lratio)
h_ppi2_c['mc'].Draw('SAME,HIST')
c1.cd(4)
h_ppim_c['data'].Draw('PE')
lratio = h_ppim_c['data'].Integral()/h_ppim_c['mc'].Integral()
#print 'pim:', lratio/ratio
tab.row_append(['pim', lratio/ratio])
h_ppim_c['mc'].Scale(lratio)
h_ppim_c['mc'].Draw('SAME,HIST')
tab.column_trim('Data/MC', rnd='.0001')
figname = '%s_momentacor' % sname
epsfile = set_file(extbase=figpath, comname=figname, ext='eps')
c1.Print(epsfile)
tools.eps2pdf(epsfile)
tabname = '%s_syst' % sname
tab.output(tabname, label=label, export_html=False)
