Python DHadTable.column_append_from_dict方法代码示例

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)

# 需要导入模块: from tools import DHadTable [as 别名]
# 或者: from tools.DHadTable import column_append_from_dict [as 别名]
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)