def setUp(self):
"""Create dictionaries needed by combiners."""
dirname = os.path.dirname(__file__) + '/'
orfdata = TFile(os.path.abspath(dirname+'data/dqm_data.root'), 'read')
orfref = TFile(os.path.abspath(dirname+'data/dqm_ref.root'), 'read')
# valid ROOT files
assert(not orfdata.IsZombie())
assert(not orfref.IsZombie())
self.rfdata = TFile('/tmp/fdata.root', 'recreate')
self.rfref = TFile('/tmp/fref.root', 'recreate')
# histogram names: folder, old name, new name
hist_recipes = [
('Velo/VeloClusterMonitor', '# VELO clusters', 'velo_clusters'),
('Velo/VeloClusterMonitor', '# VELO clusters (zoom)', 'velo_clusters_zoom'),
('Velo/VeloClusterMonitor', 'Cluster size', 'cluster_size')
]
# comparison fns: fn, options, expected DQ status, histogram
# to compare
comp_fns = [
(KolmogorovSmirnovTest(), '', OK, 0), # Velo clusters
(KolmogorovSmirnovTest(), '', OK, 1),
# (KolmogorovSmirnovTest(), '', ERROR, 2), # cluster size
(Chi2Test(), '', OK, 0),
(Chi2Test(), '', OK, 1),
(Chi2Test(), 'chi2/ndf', OK, 0),
(Chi2Test(), 'chi2/ndf', OK, 1),
# (Chi2Test(), '', ERROR, 2),
# (Chi2Test(), 'chi2/ndf', ERROR, 2)
]
# FIXME: Does not work with cluster size because of really
# small errors; see commit message for detailed explanation.
comb_dict = {}
eval_dict = {}
self.results = []
for i in comp_fns:
# last element is histogram name index
hname = hist_recipes[i[-1]][-1]
# should be of the form: *Combiner
cname = '{}_{}_{}_Combiner'.format(hname, type(i[0]).__name__, i[1])
comb_dict[cname] = create_leaf_dict_with_path(hname)
eval_dict[cname] = {'Function': i[0], 'Argument': i[1]}
# expected result
self.results.append((cname, i[2]))
comb_dict = {
'MasterCombiner': merge_dicts(
{"weight": 1.0, "minWW": 10, "minWE": 25, "minEW": 1, "minEE": 2},
comb_dict)
}
self.results.append(('MasterCombiner', OK))
# histograms: make, save, and cleanup
for recipe in hist_recipes:
href = orfref.Get('/'.join(recipe[:-1]))
href.SetName(recipe[-1])
self.rfref.WriteTObject(href)
del href
hdata = orfdata.Get('/'.join(recipe[:-1]))
hdata.SetName(recipe[-1])
self.rfdata.WriteTObject(hdata)
del hdata
self.rfref.Close()
self.rfdata.Close()
self.mycombiner = Combiner(comb_dict, eval_dict,
self.rfdata.GetName(), self.rfref.GetName())
self.mycombiner.evaluate()
def setUp(self):
"""Create dictionaries needed by combiners."""
dirname = os.path.dirname(__file__) + '/'
orfdata = TFile(os.path.abspath(dirname+'data/dqm_data.root'), 'read')
orfref = TFile(os.path.abspath(dirname+'data/dqm_ref.root'), 'read')
# valid ROOT files
assert(not orfdata.IsZombie())
assert(not orfref.IsZombie())
self.rfdata = TFile('/tmp/fdata.root', 'recreate')
self.rfref = TFile('/tmp/fref.root', 'recreate')
# histogram recipes: function to call, dir in orig ROOT file,
# rest of the arguments for function (orig hist name, new hist
# name, other options, etc)
hist_recipes = [
(get_avg_trend, 'Vetra/NoiseMon/ADCCMSuppressed',
('RMSNoise_vs_ChipChannel', 'AvgRMSNoise_trend')),
(get_avg_hist, 'Vetra/NoiseMon/ADCCMSuppressed',
('RMSNoise_vs_ChipChannel', 'AvgRMSNoise_all')),
(get_avg_hist, 'Vetra/NoiseMon/ADCCMSuppressed',
('RMSNoise_vs_ChipChannel', 'AvgRMSNoise_R', 'r')),
(get_avg_hist, 'Vetra/NoiseMon/ADCCMSuppressed',
('RMSNoise_vs_ChipChannel', 'AvgRMSNoise_Phi', 'p')),
# (get_avg_hist, 'Vetra/VeloPedestalSubtractorMoni',
# ('Ped_Sub_ADCs_Profile', 'Ped_Sub_ADCs_all'))
]
# comparison fns: fn, argument, expected DQ status, histogram
# to compare
comp_fns = [
(FloorThreshold(), 1.5, OK, 0), # avg noise trend
(CeilingThreshold(), 2.5, OK, 0),
(MeanWidthDiffRef(), 0.1, OK, 1), # avg all TELL1 noise
(MeanWidthDiffRef(), 0.1, OK, 2), # avg R TELL1 noise
(MeanWidthDiffRef(), 0.1, OK, 3), # avg Phi TELL1 noise
# (ZeroCentredBandRef(), 5, OK, 4), # pedestal subtracted ADC
]
# FIXME: add uniformity tests, maybe in different test file
comb_dict = {}
eval_dict = {}
self.results = []
for i in comp_fns:
# i[] - recipe #, last element in recipe, 2nd argument
hname = hist_recipes[i[-1]][-1][1]
# should be of the form: *Combiner
cname = '{}_{}_Combiner'.format(hname, type(i[0]).__name__)
comb_dict[cname] = create_leaf_dict_with_path(hname)
eval_dict[cname] = {'Function': i[0], 'Argument': i[1]}
# expected result
self.results.append((cname, i[2]))
comb_dict = {
'MasterCombiner': merge_dicts(
{"weight": 1.0, "minWW": 10, "minWE": 25, "minEW": 1, "minEE": 2},
comb_dict)
}
self.results.append(('MasterCombiner', OK))
# histograms: make, save, and cleanup
for recipe in hist_recipes:
href = recipe[0](orfref.GetDirectory(recipe[1]), *recipe[2])
self.rfref.WriteTObject(href)
del href
hdata = recipe[0](orfdata.GetDirectory(recipe[1]), *recipe[2])
self.rfdata.WriteTObject(hdata)
del hdata
self.rfref.Close()
self.rfdata.Close()
self.mycombiner = Combiner(comb_dict, eval_dict,
self.rfdata.GetName(), self.rfref.GetName())
self.mycombiner.evaluate()
def setUp(self):
"""Create dictionaries and ROOT files needed for testing."""
self.rfdata = TFile('/tmp/fdata.root', 'recreate')
self.rfref = TFile('/tmp/fref.root', 'recreate')
fns = {}
fns['pol0'] = get_simple_fns('5', (-10, 10))
fns['gauss01'] = get_fns('TMath::Gaus', (0, 1), (-10, 10))
fns['gauss02'] = get_fns('TMath::Gaus', (0, 2), (-10, 10))
fns['gauss03'] = get_fns('TMath::Gaus', (0, 3), (-10, 10))
fns['gauss12'] = get_fns('TMath::Gaus', (1, 2), (-10, 10))
fns['landau03'] = get_fns('TMath::Landau', (0, 3), (-10, 10))
N = 10000
rho = N/100.0
comp_fns = []
comp_fns.append((FloorThreshold(), rho - 5*sqrt(rho), 'pol0', 'pol0', OK, 'FT1')) # 5 sigma
comp_fns.append((FloorThreshold(), rho - sqrt(rho), 'pol0', 'pol0', ERROR, 'FT2')) # 1 sigma
comp_fns.append((CeilingThreshold(), rho + 5*sqrt(rho), 'pol0', 'pol0', OK, 'CT1')) # 5 sigma
comp_fns.append((CeilingThreshold(), rho + sqrt(rho), 'pol0', 'pol0', ERROR, 'CT2')) # 1 sigma
comp_fns.append((MeanWidthDiffRef(), 0.1, 'gauss03', 'gauss03', OK, 'MWDR1'))
comp_fns.append((MeanWidthDiffRef(), 0.1, 'gauss03', 'gauss12', ERROR, 'MWDR2'))
comp_fns.append((ZeroCentredBandRef(), 5, 'gauss01', 'gauss01', OK, 'ZCBR1')) # 5 sigma
comp_fns.append((ZeroCentredBandRef(), 3, 'gauss01', 'gauss02', ERROR, 'ZCBR2')) # 3 sigma
# comp_fns.append( , , 'landau03', 'landau03', )
comb_dict = {}
eval_dict = {}
self.results = []
for i in comp_fns:
name = '{}_{}_{}'.format(i[5], i[2], id(i)) # unique form: <name>_<fn>_<id>
hname = 'hist_' + name
cname = name + '_Combiner' # should be of the form: *Combiner
comb_dict[cname] = create_leaf_dict_with_path(hname)
eval_dict[cname] = {'Function': i[0], 'Argument': i[1]}
href = TH1D(hname, '', 100, -10 ,10)
href.FillRandom(fns[i[2]][0], N)
self.rfref.WriteTObject(href)
del href
hdata = TH1D(hname, '', 100, -10 ,10)
hdata.FillRandom(fns[i[3]][0], N)
self.rfdata.WriteTObject(hdata)
del hdata
self.results.append((cname, i[4]))
comb_dict = {
'MasterCombiner': merge_dicts(
{"weight": 1.0, "minWW": 10, "minWE": 25, "minEW": 1, "minEE": 2},
comb_dict)
}
self.results.append(('MasterCombiner', ERROR))
# close files cleanly
self.rfdata.Close()
self.rfref.Close()
self.mycombiner = Combiner(comb_dict, eval_dict,
self.rfdata.GetName(), self.rfref.GetName())
self.mycombiner.evaluate()
