def testDraw():
""" ./check-files.py -t
Make sure we can actually do a Draw on the final product! """
from ROOT import TChain
# don't have this pkg in the shifter image
# import psutil
# process = psutil.Process(os.getpid())
# METHOD 1: load massive chainz dawg.
# this segfaults on Draw() if the chain's boot too big (not enough mem available)
# the default batch options can't handle this for most of the datasets. (login node can ...)
# ds = 1
# dsMap = bkg.dsMap()
# ch = TChain("skimTree")
# for sub in range(dsMap[ds]+1):
# latList = dsi.getSplitList("%s/latSkimDS%d_%d*" % (dsi.latDir, ds, sub), sub)
# tmpList = [f for idx, f in sorted(latList.items())]
# for f in tmpList: ch.Add(f)
# nEnt = ch.GetEntries()
# print("nEnt",nEnt)
# n = ch.Draw("trapENFCal:riseNoise:fitSlo","trapENFCal < 250","goff")
# t1, t2, t3 = ch.GetV1(), ch.GetV2(), ch.GetV3()
# t1 = np.asarray([t1[i] for i in range(n)])
# t2 = np.asarray([t2[i] for i in range(n)])
# print("nEnt %-8d nDraw %-8d mem: %d MB" % (nEnt, n, process.memory_info().rss/1e6))
# METHOD 2: file-by-file, to save memory
fileList = []
dsMap = bkg.dsMap()
# for ds in dsMap:
for ds in [1]:
for sub in range(dsMap[ds] + 1):
latList = dsi.getSplitList(
"%s/latSkimDS%d_%d*" % (dsi.latDir, ds, sub), sub)
tmpList = [f for idx, f in sorted(latList.items())]
fileList.extend(tmpList)
for f in fileList:
tf = TFile(f)
tt = tf.Get("skimTree")
nEnt = tt.GetEntries()
n = tt.Draw("trapENFCal:riseNoise:fitSlo", "trapENFCal < 250", "goff")
t1, t2, t3 = tt.GetV1(), tt.GetV2(), tt.GetV3()
t1 = np.asarray([t1[i] for i in range(n)])
t2 = np.asarray([t2[i] for i in range(n)])
# print("%s: nEnt %-8d nDraw %-8d mem: %d MB" % (f.split("/")[-1], nEnt, n, process.memory_info().rss/1e6))
print("%s: nEnt %-8d nDraw %-8d" % (f.split("/")[-1], nEnt, n))
tf.Close()
def makeJobList():
""" ./check-files.py -m """
# bkg
if not checkCal:
# open the job list to compare
with open("./jobs/bkgLAT.ls") as f:
latJobs = f.readlines()
latJobs = [j.rstrip() for j in latJobs]
# write failed jobs to a cleanup list
fOut = open("./jobs/bkgLAT_cleanup.ls", "w")
dsMap = bkg.dsMap()
for ds in dsMap:
for sub in range(dsMap[ds] + 1):
splList = dsi.getSplitList(
"%s/splitSkimDS%d_%d*" % (dsi.splitDir, ds, sub), sub)
latList = dsi.getSplitList(
"%s/latSkimDS%d_%d*" % (dsi.latDir, ds, sub), sub)
if len(splList) != len(latList):
print(
"Error: ds %d sub %d. Found %d split files but %d lat files."
% (ds, sub, len(splList), len(latList)))
spl = unpackFileName(splList)
lat = unpackFileName(latList)
diffs = list(set(spl).symmetric_difference(set(lat)))
for diff in diffs:
fname = "latSkimDS%d_%d_%d.root" % (diff[0], diff[1],
diff[2])
job = [s for s in latJobs if fname in s][0]
fOut.write(job + "\n")
fOut.close()
# cal
else:
# open the job lists to compare
with open("./jobs/calLAT.ls") as f:
latJobs = f.readlines()
latJobs = [j.rstrip() for j in latJobs]
with open("./jobs/calLAT_ds5c.ls") as f:
latJobs2 = f.readlines()
latJobs.extend([j.rstrip() for j in latJobs2])
# write failed jobs to a cleanup list
fOut = open("./jobs/calLAT_cleanup.ls", "w")
dsMap = cal.GetKeys()
for key in dsMap:
ds = int(key[2])
if skipDS6Cal and ds == 6: continue
for sub in range(cal.GetIdxs(key)):
cRuns = cal.GetCalList(key, sub)
for run in cRuns:
splList = dsi.getSplitList(
"%s/splitSkimDS%d_run%d*" % (dsi.calSplitDir, ds, run),
run)
latList = dsi.getSplitList(
"%s/latSkimDS%d_run%d*" % (dsi.calLatDir, ds, run),
run)
if len(splList) != len(latList):
print(
"Error: ds %d run %d. Found %d split files but %d lat files."
% (ds, run, len(splList), len(latList)))
spl = unpackFileName(splList)
lat = unpackFileName(latList)
diffs = list(set(spl).symmetric_difference(set(lat)))
for diff in diffs:
fname = "latSkimDS%d_run%d_%d.root" % (
diff[0], diff[1], diff[2])
job = [s for s in latJobs if fname in s][0]
fOut.write(job + "\n")
fOut.close()
def checkLAT():
""" ./check-files.py [-c] -l """
# make sure nLat matches nSplit files
# repeat the checkWave checks
print("Checking lats. Cal?", checkCal)
fileList = []
# bkg
if not checkCal:
dsMap = bkg.dsMap()
for ds in dsMap:
for sub in range(dsMap[ds] + 1):
sList = dsi.getSplitList(
"%s/splitSkimDS%d_%d*" % (dsi.splitDir, ds, sub), sub)
latList = dsi.getSplitList(
"%s/latSkimDS%d_%d*" % (dsi.latDir, ds, sub), sub)
if len(sList) != len(latList):
print(
"Error: ds %d sub %d. Found %d split files but %d lat files."
% (ds, sub, len(sList), len(latList)))
tmpList = [f for idx, f in sorted(latList.items())]
fileList.extend(tmpList)
# cal
else:
dsMap = cal.GetKeys()
for key in dsMap:
ds = int(key[2])
if skipDS6Cal and ds == 6: continue
for sub in range(cal.GetIdxs(key)):
cRuns = cal.GetCalList(key, sub)
for run in cRuns:
sList = dsi.getSplitList(
"%s/splitSkimDS%d_run%d*" % (dsi.calSplitDir, ds, run),
run)
latList = dsi.getSplitList(
"%s/latSkimDS%d_run%d*" % (dsi.calLatDir, ds, run),
run)
if len(sList) != len(latList):
print(
"Error: ds %d sub %d run %d. Found %d split files but %d lat files."
% (ds, sub, run, len(sList), len(latList)))
tmpList = [f for idx, f in sorted(latList.items())]
fileList.extend(tmpList)
if testMode:
fileList = []
ds = 1
# dsMap = bkg.dsMap()
# for sub in range(dsMap[ds]+1):
# latList = dsi.getSplitList("%s/latSkimDS%d_%d*" % (dsi.latDir, ds, sub), sub)
# tmpList = [f for idx, f in sorted(latList.items())]
# fileList.extend(tmpList)
dsMap = cal.GetKeys()
key = dsMap[1]
for sub in range(cal.GetIdxs(key)):
cRuns = cal.GetCalList(key, sub)
for run in cRuns:
latList = dsi.getSplitList(
"%s/latSkimDS%d_run%d*" % (dsi.calLatDir, ds, run), run)
fileList.extend([f for idx, f in sorted(latList.items())])
# loop over files, repeating the same checks in checkWave
for idx, fname in enumerate(fileList[:fLimit]):
f = TFile(fname)
t = f.Get("skimTree")
n = t.GetEntries()
if n == 0:
print("No entries in file", fname)
continue
brSingle, brVector = [], []
for br in t.GetListOfBranches():
if "vector" in br.GetClassName():
brVector.append(br.GetName())
else:
brSingle.append(br.GetName())
if n < 20:
eList = np.arange(0, n, 1)
else:
eList = np.arange(0, 20, 1)
eList = np.append(eList, np.arange(n - 20, n, 1))
for i in eList:
t.GetEntry(i)
# make sure individual entries are accessible (no segfaults)
for br in brSingle:
val = getattr(t, br)
# print(val)
for br in brVector:
try:
nCh = getattr(t, br).size()
except AttributeError:
print("Error:", br)
for j in range(nCh):
val = getattr(t, br)[j]
# print(br,nCh,val)
# make sure we can process waveforms
for j in range(nCh):
wf = t.MGTWaveforms.at(j)
ch = t.channel.at(j)
# be absolutely sure you're matching the right waveform to this hit
if wf.GetID() != ch:
print(
"ERROR -- Vector matching failed. entry %d, file: %s" %
(i, fname))
# run the LAT routine to convert into numpy arrays
truncLo, truncHi = 0, 2
if ds == 6 or ds == 2: truncLo = 4
signal = wl.processWaveform(wf, truncLo, truncHi)
if verbose:
print("%d/%d %s nEnt %d" % (idx, len(
fileList[:fLimit]), fname.split("/")[-1], t.GetEntries()))
f.Close()
def checkSplit():
""" ./check-files.py [-c] -p """
# make sure every file has a TCut
# do a sum file size check - make sure sum(size(splits)) = size(waves)
print("Checking splits. Cal?", checkCal)
# bkg
if not checkCal:
dsMap = bkg.dsMap()
for ds in dsMap:
for sub in range(dsMap[ds] + 1)[:fLimit]:
# dict: {'DSX_X_X':filePath} to list[file paths]
tmpList = dsi.getSplitList(
"%s/splitSkimDS%d_%d*" % (dsi.splitDir, ds, sub), sub)
sList = [f for idx, f in sorted(tmpList.items())]
# check file existence
wFile = "%s/waveSkimDS%d_%d.root" % (dsi.waveDir, ds, sub)
if len(sList) == 0 or not os.path.isfile(wFile):
print(
"Files not found! len(split): %d, wave file:" %
len(sList), wFile)
continue
# check file sizes - result: wave files are slightly larger. weird.
# I guess ROOT has some kinda overhead for larger files?
wSize = os.stat(wFile).st_size / 1e6
sSize = sum([os.stat(f).st_size for f in sList]) / 1e6
# critical check - number of entries match, and TCut is the same
f1 = TFile(wFile)
t1 = f1.Get("skimTree")
wCut = f1.Get("theCut").GetTitle()
nEnt = t1.GetEntries()
f1.Close()
nEntS = 0
for f in sList:
f2 = TFile(f)
t2 = f2.Get("skimTree")
sCut = f2.Get("theCut").GetTitle()
nEntS += t2.GetEntries()
f2.Close()
if nEnt != nEntS:
print(
"Error: nEntries don't match! ds %d sub %d size(wave) %.2f size(split) %.2f nEnt(wave) %d nEnt(split) %d"
% (ds, sub, wSize, sSize, nEnt, nEntS))
if wCut != sCut:
print(
"Error: TCut doesn't match!\nwaveFile:%s\nsplitFile:%s"
% (wCut, sCut))
if verbose:
print("%d/%d DS-%d-%d nEnt %d" %
(sub, dsMap[ds] + 1, ds, sub, nEnt))
# cal
else:
dsMap = cal.GetKeys()
for key in dsMap:
ds = int(key[2])
if skipDS6Cal and ds == 6: continue
for sub in range(cal.GetIdxs(key))[:fLimit]:
cRuns = cal.GetCalList(key, sub)
for run in cRuns:
tmpList = dsi.getSplitList(
"%s/splitSkimDS%d_run%d*" % (dsi.calSplitDir, ds, run),
run)
sList = [f for idx, f in sorted(tmpList.items())]
# check file existence
wFile = "%s/waveSkimDS%d_run%d.root" % (dsi.calWaveDir, ds,
run)
if len(sList) == 0 or not os.path.isfile(wFile):
print(
"Files not found! len(split): %d, wave file:" %
len(sList), wFile)
continue
# check file sizes - result: wave files are slightly larger. weird.
# i guess ROOT has some kinda overhead for larger files?
wSize = os.stat(wFile).st_size / 1e6
sSize = sum([os.stat(f).st_size for f in sList]) / 1e6
# critical check - number of entries match, and TCut is the same
f1 = TFile(wFile)
t1 = f1.Get("skimTree")
wCut = f1.Get("theCut").GetTitle()
nEnt = t1.GetEntries()
f1.Close()
nEntS = 0
for f in sList:
f2 = TFile(f)
t2 = f2.Get("skimTree")
sCut = f2.Get("theCut").GetTitle()
nEntS += t2.GetEntries()
f2.Close()
if nEnt != nEntS:
print(
"Error: nEntries don't match! ds %d sub %d size(wave) %.2f size(split) %.2f nEnt(wave) %d nEnt(split) %d"
% (ds, sub, wSize, sSize, nEnt, nEntS))
if wCut != sCut:
print(
"Error: TCut doesn't match!\nwaveFile:%s\nsplitFile:%s"
% (wCut, sCut))
if verbose:
print("%d/%d DS-%d-c%d run %d nEnt %d" %
(sub, cal.GetIdxs(key), ds, sub, run, nEnt))
def scanRunsRise(ds, key, mod, cIdx):
from ROOT import TFile, TTree
rLim, eLim = 4, 250
print("Limiting to", rLim, "runs and a", eLim, "keV hit upper limit.")
# load file and channel list
fileList = []
calRuns = cal.GetCalList(
key, cIdx, runLimit=rLim) # should not need much for riseNoise
for run in calRuns:
latList = dsi.getSplitList(
"%s/latSkimDS%d_run%d*" % (dsi.calLatDir, ds, run), run)
tmpList = [f for idx, f in sorted(latList.items())]
fileList.extend(tmpList)
chList = det.getGoodChanList(ds)
print(
"Scanning DS:%d calIdx %d mod %d key %s nFiles:%d" %
(ds, cIdx, mod, key, len(fileList)), time.strftime('%X %x %Z'))
outFile = "%s/rise_%s_c%d.npz" % (dsi.effDir, key, cIdx)
print("Saving output in:", outFile)
# this is what we'll output for every calIdx
hitE, chan, rise = [], [], []
# loop over LAT cal files
scanStart = time.time()
prevRun = 0
evtCtr, totCtr, totRunTime = 0, 0, 0
for iF, f in enumerate(fileList):
print("%d/%d %s" % (iF, len(fileList), f))
tf = TFile(f)
tt = tf.Get("skimTree")
tt.GetEntry(0)
run = tt.run
if run != prevRun:
calIdx = cal.GetCalIdx(key, run)
start = tt.startTime_s
stop = tt.stopTime_s
runTime = stop - start
if runTime < 0 or runTime > 9999:
print("run time error, run", run, "start", start, "stop")
else:
totRunTime += runTime
# find thresholds for this run,
# to calculate sumET and mHT in the loop.
n = tt.Draw("channel:threshKeV:threshSigma", "", "goff")
thrC, thrM, thrS = tt.GetV1(), tt.GetV2(), tt.GetV3()
tmpThresh = {}
for i in range(n):
if thrC[i] not in chList:
continue
if thrC[i] in tmpThresh.keys():
continue
if thrM[i] < 9999:
thrK = thrM[i] + 3 * thrS[i]
tmpThresh[thrC[i]] = [run, thrM[i], thrS[i], thrK]
for ch in chList:
if ch not in tmpThresh.keys():
tmpThresh[ch] = [-1, -1, -1, -1]
prevRun = run
# continue
# loop over tree
for iE in range(tt.GetEntries()):
tt.GetEntry(iE)
if tt.EventDC1Bits != 0: continue
# totCtr += 1
n = tt.channel.size()
chTmp = np.asarray([tt.channel.at(i) for i in range(n)])
idxRaw = [
i for i in range(tt.channel.size())
if tt.channel.at(i) in chList
]
hitERaw = np.asarray([tt.trapENFCal.at(i) for i in idxRaw])
# get indexes of hits above threshold (use thresholds from THIS CAL RUN)
idxList = [
i for i in range(tt.channel.size())
if tt.channel.at(i) in chList
and tt.trapENFCal.at(i) > tmpThresh[tt.channel.at(i)][3]
and 0.7 < tt.trapENFCal.at(i) < eLim
]
# save riseNoise data
for i in idxList:
hitE.append(tt.trapENFCal.at(i))
chan.append(tt.channel.at(i))
rise.append(tt.riseNoise.at(i))
print("done.")
hitE, chan, rise = np.asarray(hitE), np.asarray(chan), np.asarray(rise)
print(len(hitE), 'total entries')
for ch in chList:
idx = np.where(chan == ch)
idx2 = np.where(hitE[idx] < 10)
print(ch, "nTot", len(hitE[idx]), "nCts under 10 keV:",
len(hitE[idx2]), "nCts<10/0.5 keV: ",
len(hitE[idx2]) / 20)
np.savez(outFile, hitE, chan, rise)
print("Done:", time.strftime('%X %x %Z'),
", %.2f sec/file." % ((time.time() - scanStart) / len(fileList)))
def runLAT(dsNum, subNum=None, runNum=None, calList=[]):
""" ./job-panda.py [-q] -lat (-ds dsNum) (-sub dsNum subNum) (-run dsNum subNum) [-cal]
Runs LAT on splitSkim output. Does not combine output files back together.
"""
bkg = dsi.BkgInfo()
# bg
if not calList:
dsMap = bkg.dsMap()
# -ds
if subNum == None and runNum == None:
for subNum in range(dsMap[dsNum] + 1):
files = dsi.getSplitList(
"%s/splitSkimDS%d_%d*" % (dsi.splitDir, dsNum, subNum),
subNum)
for idx, inFile in sorted(files.items()):
outFile = "%s/latSkimDS%d_%d_%d.root" % (dsi.latDir, dsNum,
subNum, idx)
job = "./lat.py -b -r %d %d -p %s %s" % (dsNum, subNum,
inFile, outFile)
# jspl = job.split() # make SUPER sure stuff is matched
# print(jspl[3],jspl[4],jspl[6].split("/")[-1],jspl[7].split("/")[-1])
if useJobQueue:
sh("%s >& ./logs/lat-ds%d-%d-%d.txt" %
(job, dsNum, subNum, idx))
else:
sh("""%s '%s'""" % (jobStr, job))
# -sub
elif runNum == None:
files = dsi.getSplitList(
"%s/splitSkimDS%d_%d*" % (dsi.splitDir, dsNum, subNum), subNum)
for idx, inFile in sorted(files.items()):
outFile = "%s/latSkimDS%d_%d_%d.root" % (dsi.latDir, dsNum,
subNum, idx)
job = "./lat.py -b -r %d %d -p %s %s" % (dsNum, subNum, inFile,
outFile)
if useJobQueue:
sh("%s >& ./logs/lat-ds%d-run%d-%d.txt" %
(job, dsNum, subNum, idx))
else:
sh("""%s '%s'""" % (jobStr, job))
# -run
elif subNum == None:
files = dsi.getSplitList(
"%s/splitSkimDS%d_run%d*" % (dsi.splitDir, dsNum, runNum),
runNum)
for idx, inFile in sorted(files.items()):
outFile = "%s/latSkimDS%d_run%d_%d.root" % (dsi.latDir, dsNum,
runNum, idx)
job = "./lat.py -b -r %d %d -p %s %s" % (dsNum, runNum, inFile,
outFile)
if useJobQueue:
sh("%s >& ./logs/lat-ds%d-run%d-%d.txt" %
(job, dsNum, runNum, idx))
else:
sh("""%s '%s'""" % (jobStr, job))
# cal
else:
dsRanges = bkg.dsRanges()
for run in calList:
for key in dsRanges:
if dsRanges[key][0] <= run <= dsRanges[key][1]:
dsNum = key
files = dsi.getSplitList(
"%s/splitSkimDS%d_run%d*" % (dsi.calSplitDir, dsNum, run), run)
for idx, inFile in sorted(files.items()):
outFile = "%s/latSkimDS%d_run%d_%d.root" % (dsi.calLatDir,
dsNum, run, idx)
job = "./lat.py -b -f %d %d -p %s %s" % (dsNum, run, inFile,
outFile)
if useJobQueue:
sh("%s >& ./logs/lat-ds%d-run%d-%d.txt" %
(job, dsNum, run, idx))
else:
sh("""%s '%s'""" % (jobStr, job))
def scanRuns(ds, key, mod, cIdx):
from ROOT import TFile, TTree
# load file and channel list
fileList = []
calRuns = cal.GetCalList(key,cIdx)
for run in calRuns:
latList = dsi.getSplitList("%s/latSkimDS%d_run%d*" % (dsi.calLatDir, ds, run), run)
tmpList = [f for idx, f in sorted(latList.items())]
fileList.extend(tmpList)
chList = det.getGoodChanList(ds)
print("Scanning DS:%d calIdx %d mod %d key %s nFiles:%d" % (ds, cIdx, mod, key, len(fileList)), time.strftime('%X %x %Z'))
outFile = "%s/eff_%s_c%d.npz" % (dsi.effDir, key, cIdx)
print("Saving output in:",outFile)
# declare the output stuff
evtIdx, evtSumET, evtHitE, evtChans, evtSlo, evtRise = [], [], [], [], [], []
thrCal = {ch:[] for ch in chList}
fLo, fHi, fpb = -200, 400, 1
nbf = int((fHi-fLo)/fpb)+1
fSloSpec = {ch:[np.zeros(nbf) for i in range(3)] for ch in chList} # 0-10, 10-200, 236-240
# loop over LAT cal files
scanStart = time.time()
prevRun = 0
evtCtr, totCtr, totRunTime = 0, 0, 0
for iF, f in enumerate(fileList):
print("%d/%d %s" % (iF, len(fileList), f))
tf = TFile(f)
tt = tf.Get("skimTree")
# histogram these for each file (and then add to total)
fs10 = {ch:[] for ch in chList}
fs200 = {ch:[] for ch in chList}
fs238 = {ch:[] for ch in chList}
# increment the run time and fill the output dict of thresholds
tt.GetEntry(0)
run = tt.run
if run!=prevRun:
start = tt.startTime_s
stop = tt.stopTime_s
runTime = stop-start
if runTime < 0 or runTime > 9999:
print("run time error, run",run,"start",start,"stop")
else:
totRunTime += runTime
# find thresholds for this run,
# to calculate sumET and mHT in the loop.
# save them into the output dict (so we can compare w/ DB later).
n = tt.Draw("channel:threshKeV:threshSigma","","goff")
chan, thrM, thrS = tt.GetV1(), tt.GetV2(), tt.GetV3()
tmpThresh = {}
for i in range(n):
if chan[i] not in chList:
continue
if chan[i] in tmpThresh.keys():
continue
if thrM[i] < 9999:
thrK = thrM[i] + 3*thrS[i]
tmpThresh[chan[i]] = [run,thrM[i],thrS[i],thrK]
for ch in chList:
if ch not in tmpThresh.keys():
tmpThresh[ch] = [-1,-1,-1,-1]
# fill the output dict
for ch in tmpThresh:
thrCal[ch].append(tmpThresh[ch]) # [run, thrM, thrS, thrK]
prevRun = run
# continue
# loop over tree
for iE in range(tt.GetEntries()):
tt.GetEntry(iE)
if tt.EventDC1Bits != 0: continue
totCtr += 1
n = tt.channel.size()
chTmp = np.asarray([tt.channel.at(i) for i in range(n)])
idxRaw = [i for i in range(tt.channel.size()) if tt.channel.at(i) in chList]
hitERaw = np.asarray([tt.trapENFCal.at(i) for i in idxRaw])
# get indexes of hits above threshold (use thresholds from THIS CAL RUN)
idxList = [i for i in range(tt.channel.size())
if tt.channel.at(i) in chList
and tt.trapENFCal.at(i) > tmpThresh[tt.channel.at(i)][3]
and 0.7 < tt.trapENFCal.at(i) < 9999
]
hitE = np.asarray([tt.trapENFCal.at(i) for i in idxList])
# calculate mHT and sumET
mHT, sumET = len(hitE), sum(hitE)
# save fitSlo data for 0-10 and 10-200 kev ranges for each channel
for i in idxList:
en = tt.trapENFCal.at(i)
ch = tt.channel.at(i)
fs = tt.fitSlo.at(i)
if fLo < fs < fHi:
if 0 < en < 10:
fs10[ch].append(fs)
if 10 < en < 200:
fs200[ch].append(fs)
if 236 < en < 240:
fs238[ch].append(fs)
# Save m2s238 events to output, skip everything else
if mHT!=2: continue
if not 237.28 < sumET < 239.46: continue
hitChans = np.asarray([tt.channel.at(i) for i in idxList])
hitSlo = np.asarray([tt.fitSlo.at(i) for i in idxList])
hitRise = np.asarray([tt.riseNoise.at(i) for i in idxList])
evtIdx.append([run,iE])
evtSumET.append(sumET)
evtHitE.append(hitE)
evtChans.append(hitChans)
evtSlo.append(hitSlo)
evtRise.append(hitRise)
evtCtr += 1
# fill the fitSlo histograms w/ the events from this file
for ch in chList:
x, h1 = wl.GetHisto(fs10[ch],fLo,fHi,fpb)
x, h2 = wl.GetHisto(fs200[ch],fLo,fHi,fpb)
x, h3 = wl.GetHisto(fs238[ch],fLo,fHi,fpb)
fSloSpec[ch][0] = np.sum([fSloSpec[ch][0], h1], axis=0)
fSloSpec[ch][1] = np.sum([fSloSpec[ch][1], h2], axis=0)
fSloSpec[ch][2] = np.sum([fSloSpec[ch][2], h3], axis=0)
# n1 = np.sum(fSloSpec[ch][0])
# n2 = np.sum(fSloSpec[ch][1])
# n3 = np.sum(fSloSpec[ch][2])
# print("ch:%d n10 %d n200 %d n238 %d" % (ch, n1, n2, n3))
# get average threshold for each channel in this file list
thrFinal = {chan:[] for chan in thrCal}
for chan in thrCal:
thrVals = []
for iT in range(len(thrCal[chan])):
run, thrM, thrS, thrK = thrCal[chan][iT]
# print("%d %d %.3f %.3f %.3f" % (chan,run,thrM,thrS,thrK))
if thrK > -1:
thrVals.append(thrK)
thrVals = np.asarray(thrVals)
thrAvg = np.mean(thrVals)
thrDev = np.std(thrVals)
# print("%d %.3f %.3f" % (chan, thrAvg, thrDev))
thrFinal[chan] = [thrAvg,thrDev]
# print to screen the final thresholds, stdev, and an error message if necessary
print("Detector Thresholds:")
for chan in sorted(thrFinal):
thKeV = thrFinal[chan][0]
thE = thrFinal[chan][1]
errString = ""
if thE/thKeV > 0.5:
errString = ">50pct error: thE/thKeV=%.2f" % (thE/thKeV)
if thKeV > 2:
errString = ">2kev"
print("%d %.3f %.3f %s" % (chan,thKeV,thE,errString))
# save output
np.savez(outFile, evtIdx, evtSumET, evtHitE, evtChans, thrCal, thrFinal, evtCtr, totCtr, totRunTime, fSloSpec, x, evtSlo, evtRise)
# output stats
print("Done:",time.strftime('%X %x %Z'),", %.2f sec/file." % ((time.time()-scanStart)/len(fileList)))
print(" m2s238 evts:",evtCtr, "total evts:",totCtr, "runTime:",totRunTime)