def histogram_deltas(raw1, raw2, book):
fed1 = filter(lambda x: x is not None, sorted(raw1.keys()))[0]
d1 = raw1[fed1]
for fed2, d2 in raw2.iteritems():
if fed2 is None:
continue
utca1 = d1["header"]["utca"]
utca2 = d2["header"]["utca"]
bcnDelta = matching.bcnDelta(utca1) - matching.bcnDelta(utca2)
for x in ["BcN", "OrN", "EvN"]:
title = ";".join([x+("%d" % bcnDelta if (x == "BcN" and bcnDelta) else ""),
"FED %s - FED %s" % (fed1, fed2),
"Events / bin",
])
delta = d1["header"][x] - d2["header"][x]
book.fill(delta, "delta%s_%s_%s" % (x, fed1, fed2), 11, -5.5, 5.5, title=title)
def histogram_deltas(raw1, raw2, book, okFeds):
fed1 = filter(lambda x: x is not None, sorted(raw1.keys()))[0]
d1 = raw1[fed1]
for fed2, d2 in raw2.iteritems():
if fed2 is None:
continue
utca1 = d1["header"]["utca"]
utca2 = d2["header"]["utca"]
bcnDelta = matching.bcnDelta(utca1) - matching.bcnDelta(utca2)
if (fed1 in okFeds) and (fed2 in okFeds):
for x in ["BcN", "OrN", "EvN"]:
title = ";".join([x+("%d" % bcnDelta if (x == "BcN" and bcnDelta) else ""),
"FED %s - FED %s" % (fed1, fed2),
"Events / bin",
])
delta = d1["header"][x] - d2["header"][x]
book.fill(delta, "delta%s_%s_%s" % (x, fed1, fed2), 11, -5.5, 5.5, title=title)
def ornBcn(ornIn, bcnIn, utca):
bcnDelta = matching.bcnDelta(utca)
if not bcnDelta:
return ornIn, bcnIn
orn = ornIn
bcn = bcnIn + bcnDelta
if bcn < 0:
bcn += hw.nBx
orn -= 1
if hw.nBx - 1 < bcn:
bcn -= hw.nBx
orn += 1
return orn, bcn
def ornBcn(ornIn, bcnIn, utca):
bcnDelta = matching.bcnDelta(utca)
if not bcnDelta:
return ornIn, bcnIn
orn = ornIn
bcn = bcnIn + bcnDelta
if bcn < 0:
bcn += hw.nBx
orn -= 1
if hw.nBx - 1 < bcn:
bcn -= hw.nBx
orn += 1
return orn, bcn
def compare(raw1={},
raw2={},
book=None,
anyEmap=False,
printEmap=False,
printMismatches=False,
warnQuality=True,
fewerHistos=False):
doDump = (1 <= raw1[None]["dump"]) or raw1[None]["patterns"]
if raw2 and anyEmap:
mapF1, mapB1, _ = dataMap(raw1, book)
mapF2, mapB2, _ = dataMap(raw2, book)
matched12, nonMatched12 = matchStatsAnyMap(mapF1, mapB2, iStart=4)
matched21, nonMatched21 = matchStatsAnyMap(mapF2, mapB1, iStart=4)
tMatched12 = tMisMatched12 = misMatched12 = [] # dummy
tMatched21 = tMisMatched21 = misMatched21 = [] # dummy
if printEmap:
reportMatched(matched12)
reportFailed(nonMatched12)
histogram_nMatched(book,
matched=matched12.keys(),
nonMatched=nonMatched12)
elif raw2:
mapF1, _, _ = dataMap(raw1, book)
mapF2, _, _ = dataMap(raw2, book)
titlePrefix = "ErrF == %s;ADC;ADC" % ",".join(
["%d" % x for x in matching.okErrF()])
matched12, misMatched12 = adc_vs_adc(mapF1,
mapF2,
book=book,
titlePrefix=titlePrefix,
printMismatches=printMismatches,
iEntry=raw1[None]["iEntry"])
if doDump:
matched21, misMatched21 = adc_vs_adc(mapF2,
mapF1,
book=None,
titlePrefix=titlePrefix)
tF1 = tpMap(raw1, warnQuality, book)[0]
tF2 = tpMap(raw2, warnQuality, book)[0]
tMatched12, tMisMatched12 = adc_vs_adc(tF1,
tF2,
book=book,
name="tp_vs_tp",
transf=hw.transformed_tp,
xMin=-20.5,
xMax=275.5,
printMismatches=printMismatches,
iEntry=raw1[None]["iEntry"])
tMatched21 = tMisMatched21 = [] # tp_vs_tp(tF2, tF1, book) # FIXME
histogram_nMatched(book,
matched=matched12,
misMatched=misMatched12,
tMatched=tMatched12,
tMisMatched=tMisMatched12)
else:
# dummy
matched12 = misMatched12 = {}
matched21 = misMatched21 = {}
tMatched12 = tMisMatched12 = []
tMatched21 = tMisMatched21 = []
if doDump:
slim1 = (raw1[None]["dump"] == 1) and (len(raw1) == 2) and not raw2
printRaw.oneEvent(raw1,
nonMatchedQie=misMatched12,
nonMatchedTp=tMisMatched12,
slim1=slim1)
printRaw.oneEvent(raw2,
nonMatchedQie=misMatched21,
nonMatchedTp=tMisMatched21)
okFeds = loop_over_feds(
raw1,
book,
adcTag="feds1",
warn=warnQuality,
fewerHistos=fewerHistos,
adcMatches=matched12,
adcMismatches=misMatched12,
tpMatches=tMatched12,
tpMismatches=tMisMatched12,
)
noGood = [[], [None]]
if raw1.keys() in noGood or raw2.keys() in noGood:
return
okFeds = okFeds.union(
loop_over_feds(raw2, book, adcTag="feds2", warn=warnQuality))
# histogram some deltas
fed1 = filter(lambda x: x is not None, sorted(raw1.keys()))[0]
d1 = raw1[fed1]
for fed2, d2 in raw2.iteritems():
if fed2 is None:
continue
utca1 = d1["header"]["utca"]
utca2 = d2["header"]["utca"]
bcnDelta = matching.bcnDelta(utca1) - matching.bcnDelta(utca2)
if (fed1 in okFeds) and (fed2 in okFeds):
for x in ["BcN", "OrN", "EvN"]:
title = ";".join([
x + ("%d" % bcnDelta if (x == "BcN" and bcnDelta) else ""),
"FED %s - FED %s" % (fed1, fed2),
"Events / bin",
])
delta = d1["header"][x] - d2["header"][x]
book.fill(delta,
"delta%s_%s_%s" % (x, fed1, fed2),
11,
-5.5,
5.5,
title=title)
def compare(raw1={}, raw2={}, book={}, anyEmap=False, printEmap=False, warnQuality=True):
doDump = (1 <= raw1[None]["dump"]) or raw1[None]["patterns"]
if anyEmap:
mapF1, mapB1, _ = dataMap(raw1, book)
mapF2, mapB2, _ = dataMap(raw2, book)
matched12, nonMatched12 = matchStats(mapF1, mapB2)
matched21, nonMatched21 = matchStats(mapF2, mapB1)
tMatched12 = tMisMatched12 = misMatched12 = [] # passed to loop_over_feds
if printEmap:
reportMatched(matched12)
reportFailed(nonMatched12)
histogram_nMatched(book, matched=matched12.keys(), nonMatched=nonMatched12)
else:
mapF1, _, _ = dataMap(raw1, book)
mapF2, _, _ = dataMap(raw2, book)
titlePrefix = "ErrF == %s;ADC;ADC" % ",".join(["%d" % x for x in matching.okErrF()])
matched12, misMatched12 = adc_vs_adc(mapF1, mapF2, book=book, titlePrefix=titlePrefix)
if doDump:
matched21, misMatched21 = adc_vs_adc(mapF2, mapF1, titlePrefix=titlePrefix)
tF1 = tpMap(raw1, warnQuality, book)[0]
tF2 = tpMap(raw2, warnQuality, book)[0]
tMatched12, tMisMatched12 = adc_vs_adc(tF1, tF2, book=book,
name="tp_vs_tp",
transf=hw.transformed_tp,
xMin=-20.5, xMax=255.5)
tMatched21 = tMisMatched21 = [] # tp_vs_tp(tF2, tF1, book) # FIXME
histogram_nMatched(book,
matched=matched12, misMatched=misMatched12,
tMatched=tMatched12,
tMisMatched=tMisMatched12)
if doDump:
slim1 = (raw1[None]["dump"] == 1) and (len(raw1) == 2) and not raw2
printRaw.oneEvent(raw1, nonMatchedQie=misMatched12, nonMatchedTp=tMisMatched12, slim1=slim1)
printRaw.oneEvent(raw2, nonMatchedQie=misMatched21, nonMatchedTp=tMisMatched21)
okFeds = loop_over_feds(raw1, book, adcTag="feds1", warn=warnQuality,
adcMatches=matched12, adcMismatches=misMatched12,
tpMatches=tMatched12, tpMismatches=tMisMatched12,
)
noGood = [[], [None]]
if raw1.keys() in noGood or raw2.keys() in noGood:
return
okFeds = okFeds.union(loop_over_feds(raw2, book, adcTag="feds2", warn=warnQuality))
# histogram some deltas
fed1 = filter(lambda x: x is not None, sorted(raw1.keys()))[0]
d1 = raw1[fed1]
for fed2, d2 in raw2.iteritems():
if fed2 is None:
continue
utca1 = d1["header"]["utca"]
utca2 = d2["header"]["utca"]
bcnDelta = matching.bcnDelta(utca1) - matching.bcnDelta(utca2)
if (fed1 in okFeds) and (fed2 in okFeds):
for x in ["BcN", "OrN", "EvN"]:
title = ";".join([x+("%d" % bcnDelta if (x == "BcN" and bcnDelta) else ""),
"FED %s - FED %s" % (fed1, fed2),
"Events / bin",
])
delta = d1["header"][x] - d2["header"][x]
book.fill(delta, "delta%s_%s_%s" % (x, fed1, fed2), 11, -5.5, 5.5, title=title)
