def mult(runs,mergedfilename,Qbins,FeedbackTransducer, lightBins, binsname, LED_INDUCED_DEAD_TIME_FRACTION):
if FeedbackTransducer == "PT4":
pt = 3
elif FeedbackTransducer == "PT6":
pt = 5
spectrumFile = open('/nashome/b/bressler/sbcoutput/'+mergedfilename+"%s_coincident_spectrum.txt"%binsname,'w')
separator = '\t'
spectrumFile.write("lightBin\t"+separator.join(["Q=%.1f-%.1fkeV"%(Qbins[i],
Qbins[i+1]) for i in range(len(Qbins)-1)])+"\n")
spectrumFile_multiples = open('/nashome/b/bressler/sbcoutput/'+mergedfilename+"%s_coincident_spectrum_multibub.txt"%binsname,'w')
spectrumFile_multiples.write("lightBin\t"+separator.join(["Q=%.1f-%.1fkeV"%(Qbins[i],
Qbins[i+1]) for i in range(len(Qbins)-1)])+"\n")
fractionFile = open('/nashome/b/bressler/sbcoutput/'+mergedfilename+"%s_coincident_spectrum_fraction.txt"%binsname,'w')
fractionFile.write("lightBin\t"+separator.join(["Q=%.1f-%.1fkeV"%(Qbins[i],
Qbins[i+1]) for i in range(len(Qbins)-1)])+"\n")
#with open("/nashome/b/bressler/sbcoutput/%s_merged_oldPMT.txt"%mergedfilename,"r") as fin:
with open("/nashome/b/bressler/sbcoutput/%s_merged.txt"%mergedfilename,"r") as fin:
data = fin.readlines()
headers = data[0].split()
runind = headers.index("run")
eventind = headers.index("event")
xind = headers.index("x")
yind = headers.index("y")
zind = headers.index("z")
lagind = headers.index("lag")
spectind = headers.index("PMTphe")
blockedind = headers.index('isBlocked')
nbubind = headers.index('nbub')
x=[]
y=[]
z=[]
evid = []
lag = []
spect = []
isblocked = []
nbub = []
i=0
for line in data:
if i>0:
split_line = line.split()
evid.append(split_line[runind]+"-"+split_line[eventind])
isblocked.append(float(split_line[blockedind]))
x.append(float(split_line[xind]))
y.append(float(split_line[yind]))
z.append(float(split_line[zind]))
lag.append(float(split_line[lagind]))
spect.append(float(split_line[spectind]))
nbub.append(float(split_line[nbubind]))
i+=1
counts = []
nbubs = []
didntpass = 0
bubInfo = []
eventcount = np.zeros(87)
spectra = [[] for i in range(87)]
twobub_spectra = [[] for i in range(87)]
threebub_spectra = [[] for i in range(87)]
LT = np.zeros(87)
LT_by_Q = np.zeros(len(Qbins)-1)
expand_times = [[] for i in range(87)]
totbub = 0
onebubcount = np.zeros(87)
twobubcount = np.zeros(87)
threebubcount = np.zeros(87)
setpoints = []
elt = 0
temps = []
for run in runs:
print(run)
z_low = -4
z_high = 0
preq = 1
runrawpath = '/bluearc/storage/SBC-17-data/'+run
events = [evnt for evnt in listdir(runrawpath) if not isfile(join(runrawpath,evnt))]
Nevents = len(events)
runreconpath = "/pnfs/coupp/persistent/grid_output/SBC-17/output/%s/"%run
historyfilename = runreconpath+"HistoryAnalysis_%s.bin"%run
history = sbc.DataHandling.ReadBinary.ReadBlock(historyfilename)
getbubfile = "/coupp/data/home/coupp/HumanGetBub_output_SBC-17/HumanGetBub_%s.bin"%run
c = sbc.DataHandling.ReadBinary.ReadBlock(getbubfile)
eventn = c["ev"]
count = Counter(eventn)
edges = history["PressureEdge"][pt]
centersp = [(edges[i]+edges[i+1])/2 for i in range(len(edges)-1)]
#centers = Qvals
e0 = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath,0,"slowDAQ")
T=np.mean(e0["slowDAQ"]["T1"])
temps.append(T)
sm = SeitzModel(list(edges),T,'xenon')
edges_by_Q = sm.Q
centers = [(edges_by_Q[i] + edges_by_Q[i+1])/2 for i in range(len(edges_by_Q)-1)]
print("T=%f C"%T)
for c in count:
N = count[c]
counts.append(N)
"""
if N%2 != 0 and N != 1:
print("lines isn't even")
print(c)
print(N)
elif N%2 == 0:
n = N/2
nbubs.append(n)
"""
for eventn in range(Nevents):
try:
indices_back = 30
event_ID = run+"-"+str(eventn)
mergedind = evid.index(event_ID)
bl = isblocked[mergedind]
light = spect[mergedind]
ev_z = z[mergedind]
if np.isnan(light):
light = 0
ev_z = z[mergedind]
#onebub = not np.isnan(runposreco["z"][0][int(eventn)])
n_from_merged = nbub[mergedind]
n = 0
N = count[eventn]
if N%2 == 0:
n = N/2
nbubs.append(n)
if n_from_merged != n:
print('n and merged n dont match')
print("n here: %d"%n)
print("n from merged: %d"%n_from_merged)
e = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath,eventn,"slowDAQ","event")
t = e["slowDAQ"]["elapsed_time"]
tcenters = [(t[i+1] + t[i])/2 for i in range(len(t)-1)]
trig_time = t[list(e["slowDAQ"]["TriggerOut"]).index(1.0)-indices_back]
pslope = np.diff(e["slowDAQ"][FeedbackTransducer])
expstartind = list(pslope).index(min(list(pslope)))
exp_start = tcenters[expstartind]
trig_pressure = e["slowDAQ"][FeedbackTransducer][list(e["slowDAQ"]["TriggerOut"]).index(1.0)-indices_back]
T = np.mean(e["slowDAQ"]["T1"])
SM = SeitzModel(trig_pressure,T,'xenon')
Q = (SM.Q)
#print(Q[0])
pset = e["event"]["Pset"]
ev_lt = e["event"]['livetime']
elt += ev_lt
if pset not in setpoints:
setpoints.append(pset)
#print(pset)
#print(len(history["PressureBins"][eventn]))
times = history["PressureBins"][eventn][pt][:]
"""
plt.figure()
plt.plot([trig_time,trig_time],[0,200],label="Bubble time")
plt.plot([exp_start,exp_start],[0,200],label="Expansion start")
plt.plot([0,max(t)],[trig_pressure,trig_pressure],label="Bubble pressure")
plt.plot(t,e["slowDAQ"]["PT6"],label="PT6")
plt.plot(tcenters,pslope,label="Pressure slope")
plt.xlabel("time",fontsize=18)
plt.ylabel("signal",fontsize=18)
plt.legend(fontsize=18)
plt.show
"""
if n == 1 and ev_lt > 20:
totbub += 1
for i in range(len(centers)):
if trig_time > exp_start:
#print(trig_pressure)
#print(pset)
if (trig_pressure >= edges[i]
and trig_pressure <= edges[i+1]) and abs(trig_pressure-pset)<preq/2:
onebubcount[i] += 1
eventcount[i] += 1
if not bl:
spectra[i].append(light)
#if light < 1:
#print("%s-%d is passing single not blocked and light < 1"%(run, eventn))
bubInfo.append([n,Q,bl,light,ev_z])
#print("added %s-%d to bubInfo"%(run,eventn))
expand_times[i].append(ev_lt)
if abs(centersp[i]-pset)<preq/2:
LT[i] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
for j in range(len(Qbins)-1):
if Q >= Qbins[j] and Q <= Qbins[j+1]:
LT_by_Q[j] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
if Q>1.5 and Q<2 and abs(trig_pressure-pset)<preq/2 and trig_time > exp_start:
print(event_ID)
print(Q)
elif n == 2 and ev_lt > 20:
totbub += 1
for i in range(len(centers)):
if trig_time > exp_start:
if (trig_pressure >= edges[i]
and trig_pressure <= edges[i+1]) and abs(trig_pressure-pset)<preq/2:
eventcount[i] += 1
twobubcount[i] += 1
expand_times[i].append(ev_lt)
bubInfo.append([n,Q,bl,light,ev_z])
if not bl:
twobub_spectra[i].append(light)
print("%s-%d multibubble event: %d bubbles, %.2f phe"%(run, eventn, n, light))
if abs(centersp[i]-pset)<preq/2:
LT[i] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
for j in range(len(Qbins)-1):
if Q >= Qbins[j] and Q <= Qbins[j+1]:
LT_by_Q[j] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
elif n >= 3 and ev_lt > 20:
for i in range(len(centers)):
if trig_time > exp_start:
if (trig_pressure >= edges[i]
and trig_pressure <= edges[i+1]) and abs(trig_pressure-pset)<preq/2:
eventcount[i] += 1
threebubcount[i] += 1
expand_times[i].append(ev_lt)
bubInfo.append([n,Q,bl,light,ev_z])
if not bl:
threebub_spectra[i].append(light)
print("%s-%d multibubble event: %d bubbles, %.2f phe"%(run, eventn, n, light))
if abs(centersp[i]-pset)<preq/2:
LT[i] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
for j in range(len(Qbins)-1):
if Q >= Qbins[j] and Q <= Qbins[j+1]:
LT_by_Q[j] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
else:
if n>0:
didntpass += 1
for i in range(len(centers)):
if trig_time > exp_start and ev_lt > 20:
if (trig_pressure >= edges[i]
and trig_pressure <= edges[i+1]) and abs(trig_pressure-pset)<preq/2:
eventcount[i] += 1
expand_times[i].append(ev_lt)
bubInfo.append([n,Q,bl,light,ev_z])
if abs(centersp[i]-pset)<preq/2:
LT[i] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
for j in range(len(Qbins)-1):
if Q >= Qbins[j] and Q <= Qbins[j+1]:
LT_by_Q[j] += times[i]*(1-LED_INDUCED_DEAD_TIME_FRACTION)
#if (ev_z > z_low and ev_z < z_high):
except Exception as x:
print(x)
#break
blockedEvents = [x for x in bubInfo if x[2] == 1]
print("fraction of LED-blocked bubbles: "+str(len(blockedEvents)/len([x for x in bubInfo if x[0]>0])))
print("Number of single-bubble zero phe non-blocked events:" + str(len([x for x in bubInfo if x[0]==1 and x[2] == 0 and (x[3]>0 and x[3] <1)])))
print("Number of single-bubble one phe non-blocked events:" + str(len([x for x in bubInfo if x[0]==1 and x[2] == 0 and (x[3]>1 and x[3] <2)])))
print("Number of single-bubble two phe non-blocked events:" + str(len([x for x in bubInfo if x[0]==1 and x[2] == 0 and (x[3]>2 and x[3] <3)])))
rateList1 = [onebubcount[i]/LT[i] for i in range(len(onebubcount))]
rateErrList1h = [(0.5+np.sqrt(onebubcount[i]+0.25))/LT[i] for i in range(len(onebubcount))]
rateErrList1l = [(-0.5+np.sqrt(onebubcount[i]+0.25))/LT[i] for i in range(len(onebubcount))]
standard_error1 = [np.sqrt(onebubcount[i])/LT[i] for i in range(len(onebubcount))]
rateList2 = [twobubcount[i]/LT[i] for i in range(len(twobubcount))]
rateErrList2h = [(0.5+np.sqrt(twobubcount[i]+0.25))/LT[i] for i in range(len(twobubcount))]
rateErrList2l = [(-0.5+np.sqrt(twobubcount[i]+0.25))/LT[i] for i in range(len(twobubcount))]
rateList3 = [threebubcount[i]/LT[i] for i in range(len(threebubcount))]
rateErrList3h = [(0.5+np.sqrt(threebubcount[i]+0.25))/LT[i] for i in range(len(threebubcount))]
rateErrList3l = [(-0.5+np.sqrt(threebubcount[i]+0.25))/LT[i] for i in range(len(threebubcount))]
rateListE = [eventcount[i]/LT[i] for i in range(len(eventcount))]
rateErrListEh = [(0.5+np.sqrt(eventcount[i]+0.25))/LT[i] for i in range(len(eventcount))]
rateErrListEl = [(-0.5+np.sqrt(eventcount[i]+0.25))/LT[i] for i in range(len(eventcount))]
"""
plt.figure()
q = [bub[1] for bub in bubInfo]
plt.hist(q,int(np.ceil(np.sqrt(len(q)))))
plt.xlabel('Seitz Threshold')
plt.ylabel('Count')
plt.show()
#Threshold:
plt.figure()
plt.errorbar(centers,rateList1,[rateErrList1l,rateErrList1h],fmt='ro',label='Single Bubbles')
plt.errorbar(centers,rateList2,[rateErrList2l,rateErrList2h],fmt='go',label='Double Bubbles')
plt.errorbar(centers,rateList3,[rateErrList3l,rateErrList3h],fmt='bo',label='Triple Bubbles')
plt.errorbar(centers,rateListE,[rateErrListEl,rateErrListEh],fmt='ko',label='All Events')
#plt.yscale('log')
plt.ylim([1e-4,0.1])
plt.xlabel('Seitz Threshold [keV]',fontsize=18)
plt.ylabel('Rate [Hz]', fontsize=18)
plt.legend(fontsize=18)
plt.grid()
plt.show
#single bubbles
def line(x,m,b):
return m*x + b
QForFit = []
RForFit = []
errForFit = []
for i in range(len(rateList1)):
if (not np.isnan(rateList1[i])) and (not np.isinf(rateList1[i])) and rateList1[i] != 0:
QForFit.append(centers[i])
RForFit.append(rateList1[i])
errForFit.append(standard_error1[i])
popt,pcov = scipy.optimize.curve_fit(line,QForFit,RForFit,p0=[0.005,0.01],sigma=errForFit)
plt.figure()
plt.errorbar(QForFit,RForFit,yerr=errForFit,fmt="ro")
xfine = np.linspace(min(centers),3,50)
y1 = line(xfine,popt[0]+pcov[0,0]**0.5, popt[1]-pcov[1,1]**0.5)
y2 = line(xfine,popt[0]-pcov[0,0]**0.5, popt[1]+pcov[1,1]**0.5)
plt.plot(xfine,line(xfine,popt[0],popt[1]),'k-')
plt.plot(xfine,y1,'k--')
plt.plot(xfine,y2,'k--')
plt.plot([0,5],[0,0],'b-')
plt.fill_between(xfine,y1,y2,facecolor='gray',alpha=0.1)
plt.ylabel('Rate [Hz]',fontsize=18)
plt.xlabel('Seitz Threshold [keV]',fontsize=18)
plt.title('Crosses x-axis at %f'%(-popt[1]/popt[0]))
plt.show
"""
totbub = len(nbubs)
print("total number of bubbles: %d"%totbub)
print("total number of events: %d" %len(counts))
print("didn't pass: %d"%didntpass)
m = max(nbubs)
for i in range(len(nbubs)):
if nbubs[i]>3:
nbubs[i] = 3
binedges = [0.5,1.5,2.5,3.5] #bins for bubble multiplicity
bincenters = [1,2,3]
plt.figure()
ns, _ = np.histogram(nbubs,binedges)
print("bubble counts: ")
print(ns)
plt.errorbar(bincenters,ns,np.sqrt(ns),fmt='o')
plt.yscale('log')
plt.title("Max Nbub: %d"%int(m),fontsize=20)
plt.xlabel("Nbub",fontsize=18)
plt.ylabel("counts",fontsize=18)
plt.xlim(0.5,3.5)
plt.grid()
plt.show
f = [ns[i]/totbub for i in range(len(ns))]
ferrh = [(0.5+np.sqrt(ns[i]+0.25))/totbub for i in range(len(ns))]
ferrl = [(-0.5+np.sqrt(ns[i]+0.25))/totbub for i in range(len(ns))]
plt.figure()
plt.errorbar(bincenters,f,[ferrl,ferrh],fmt='o')
plt.xlabel("Nbub",fontsize=18)
plt.ylabel("fraction of bubbles",fontsize=18)
plt.xlim([0.5,3.5])
plt.grid()
plt.show
"""
#Pressure
plt.figure()
plt.errorbar(centersp,rateList1,[rateErrList1l,rateErrList1h],fmt='ro',label='Single Bubbles')
plt.errorbar(centersp,rateList2,[rateErrList2l,rateErrList2h],fmt='go',label='Double Bubbles')
plt.errorbar(centersp,rateList3,[rateErrList3l,rateErrList3h],fmt='bo',label='Triple Bubbles')
plt.errorbar(centersp,rateListE,[rateErrListEl,rateErrListEh],fmt='ko',label='All Events')
plt.yscale('log')
plt.xlabel('Pressure [psia]',fontsize=18)
plt.ylabel('Rate [Hz]', fontsize=18)
plt.legend(fontsize=18)
plt.grid()
plt.show
plt.figure()
hy = []
hx = []
for i in range(len(expand_times)):
if len(expand_times[i])>0:
for j in range(len(expand_times[i])):
hx.append(centersp[i])
hy.append(expand_times[i][j])
plt.hist2d(hx,hy,bins=(len(centers),30),cmap='magma')
plt.colorbar()
plt.xlabel('PT6 [psia]',fontsize=18)
plt.ylabel('Total time since expansion [s]',fontsize=18)
plt.show
hy = []
hx = []
for i in range(len(expand_times)):
if len(spectra[i])>0:
for j in range(len(spectra[i])):
hx.append(centersp[i])
hy.append(spectra[i][j])
plt.figure()
plt.hist2d(hx,hy,bins=(40,int(max(hy))),cmap='Greys')
plt.colorbar()
plt.xlabel('PT6 [psia]',fontsize=18)
plt.ylabel('Light collected [phe]',fontsize=18)
plt.yscale('symlog',linthreshy = 0.9)
plt.show
xedges = np.arange(88)
#yedges = np.arange(int(max(hy))+1)
bins = [10**i+0.5 for i in range(5)] # light bins
#bins = np.arange(0.5,1+np.ceil(max(spect)))
bins = np.insert(bins,0,0.5)
bins=np.insert(bins,0,-0.5)
bins=np.insert(bins,0,-1.5)
H, xedges, yedges = np.histogram2d(hx,hy,bins=(xedges,bins))
for i in range(len(xedges)-1):
for j in range(len(H[i,:])):
#print(LT[i])
H[i,j] = H[i,j]/LT[i]
print("max rate: %f"%np.amax(H))
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
X,Y = np.meshgrid(xedges,yedges)
im=ax.pcolormesh(X,Y,H.T,cmap="magma")
plt.yscale('symlog',linthreshy = 0.9)
fig.colorbar(im,ax=ax)
plt.show()
"""
hy = []
hx = []
hy_multi = []
hx_multi = []
for bubble in bubInfo:
if bubble[0]==1 and bubble[2] == 0:
#if bubble[0]==1:
hx.append(bubble[1]) # Seitz threshold
hy.append(bubble[3]) # phe
elif (bubble[0] == 2 or bubble[0] == 3):
hx_multi.append(bubble[1])
hy_multi.append(bubble[3])
plt.figure()
plt.hist2d(hx,hy,bins=(40,int(max(hy))),cmap='Greys')
plt.colorbar()
plt.xlabel('Q [keV]',fontsize=18)
plt.ylabel('Light collected [phe]',fontsize=18)
plt.yscale('symlog',linthreshy = 0.9)
plt.show
#print(temps)
xedges = edges
Qedges = np.zeros(np.shape(xedges))
for i in range(1,len(xedges)):
SM = SeitzModel(float(xedges[i]),np.mean(temps),'xenon')
if SM is not None:
Qedges[i]=SM.Q
OArateQ = [(Qbins[i]+Qbins[i+1])/2 for i in range(len(Qbins)-1)]
OArate_multi = []
OArateErr_multi = []
OArate_singles = []
OArateErr_singles = []
Qedges = Qbins
#print(Qbins)
#yedges = np.arange(int(max(hy))+1)
bins = lightBins # light bins
#bins = np.arange(1,int(1+np.ceil(max(spect))))
bins = np.insert(bins,0,0.5)
bins=np.insert(bins,0,-0.5)
#bins=np.insert(bins,0,-1.5)
#bins = [-0.5, 2**9+0.5, 2**13+0.5]
binc=[(bins[i+1]+bins[i])/2 for i in range(len(bins)-1)]
binwidths = [bins[i+1]-bins[i] for i in range(len(bins)-1)]
print(binwidths)
H, Qedges, yedges = np.histogram2d(hx,hy,bins=(Qedges,bins)) # using hx and hy defined a few lines above in the previous plot section
H_multi, Qedges, yedges_multi = np.histogram2d(hx_multi, hy_multi, bins=(Qedges, bins))
multi_ns = H_multi.copy()
ns = H.copy()
errorbararray_upper = np.zeros_like(H)
errorbararray_lower = np.zeros_like(H)
errorbararray_multi_upper = np.zeros_like(H_multi)
errorbararray_multi_lower = np.zeros_like(H_multi)
print("total number of events in H: %d"%np.sum(H))
print("total number of multiples in H_multi: %d"%np.sum(H_multi))
for i in range(len(LT_by_Q)):
OArate_singles.append(sum(H[i,:])/LT_by_Q[i])
OArateErr_singles.append(np.sqrt(sum(H[i,:]))/LT_by_Q[i])
for j in range(len(H[i,:])):
H[i,j] = H[i,j]/LT_by_Q[i]
if ns[i,j] > 10:
errorbararray_upper[i,j]= np.sqrt(ns[i,j])/LT_by_Q[i]
errorbararray_lower[i,j]= np.sqrt(ns[i,j])/LT_by_Q[i]
else:
errorbararray_upper[i,j]= (0.5+np.sqrt(ns[i,j]+0.25))/LT_by_Q[i]
errorbararray_lower[i,j]= (-0.5+np.sqrt(ns[i,j]+0.25))/LT_by_Q[i]
#print(H[i,j])
#print(errorbararray[i,j])
if np.isnan(H[i,j]):
H[i,j]=0
errorbararray_upper[i,j] = 0
errorbararray_lower[i,j] = 0
OArate_multi.append(sum(H_multi[i,:])/LT_by_Q[i])
OArateErr_multi.append(np.sqrt(sum(H_multi[i,:]))/LT_by_Q[i])
for j in range(len(H_multi[i,:])):
H_multi[i,j] = H_multi[i,j]/LT_by_Q[i]
if multi_ns[i,j] > 10:
errorbararray_multi_upper[i,j]= np.sqrt(multi_ns[i,j])/LT_by_Q[i]
errorbararray_multi_lower[i,j]= np.sqrt(multi_ns[i,j])/LT_by_Q[i]
else:
errorbararray_multi_upper[i,j]= (0.5+np.sqrt(multi_ns[i,j] + 0.25))/LT_by_Q[i]
errorbararray_multi_lower[i,j]= (-0.5+np.sqrt(multi_ns[i,j] + 0.25))/LT_by_Q[i]
#print(H[i,j])
#print(errorbararray[i,j])
if np.isnan(H_multi[i,j]):
H_multi[i,j]=0
errorbararray_multi_upper[i,j] = 0
errorbararray_multi_lower[i,j] = 0
#print(sum(H))
#print(OArate)
print("singles:")
print(ns)
print("multiples:")
print(multi_ns)
plt.figure()
plt.errorbar(OArateQ,OArate_singles,OArateErr_singles,marker='v',linestyle='')
plt.grid()
plt.xlabel('Seitz Threshold [keV]')
plt.ylabel('Rate [Hz]')
plt.show()
print("max rate: %f"%np.amax(H))
print("number in onebubcount: %f"%np.sum(onebubcount))
print(np.sum([rateList1[i] * LT[i] for i in range(len(rateList1)) if not np.isnan(rateList1[i])]))
fig = plt.figure()
ax = fig.add_subplot(1,2,1)
ax.title.set_text('Rates [Hz/bin]')
X,Y = np.meshgrid(Qedges,yedges)
im=ax.pcolormesh(X,Y,H.T,cmap="Greys")
plt.yscale('symlog',linthreshy = 0.9)
plt.ylabel("Collected light [phe]")
plt.xlabel("Seitz Threshold [keV]")
fig.colorbar(im,ax=ax)
ax2 = fig.add_subplot(1,2,2)
ax2.title.set_text('Number of bubbles in each bin')
im2=ax2.pcolormesh(X,Y,ns.T,cmap="Blues")
plt.yscale('symlog',linthreshy = 0.9)
plt.ylabel("Collected light [phe]")
plt.xlabel("Seitz Threshold [keV]")
fig.colorbar(im2,ax=ax2)
#plt.show()
fig = plt.figure()
ax3 = fig.add_subplot(1,1,1)
ax3.title.set_text("Rates per Scintillation: fraction")
for k in range(len(Qedges)-1):
print("%f-%f keV: %f bubbles in %f seconds"%(Qedges[k],Qedges[k+1],sum(ns[k,:]),LT_by_Q[k]))
if LT_by_Q[k]>100:
ax3.errorbar(binc,H[k,:]/OArate_singles[k],[(errorbararray_upper[k,:]/OArate_singles[k]),(errorbararray_lower[k,:]/OArate_singles[k])],marker='.',markersize=7,
linestyle='none',label="%f-%f keV"%(Qedges[k],Qedges[k+1]))
for l in range(len(bins)-1):
fractionFile.write("%.1f-%.1fphe\t"%(bins[l],bins[l+1]))
for k in range(len(Qedges)-1):
fractionFile.write("%f,%f,%f\t"%(H[k,l]/OArate_singles[k], errorbararray_upper[k,l]/OArate_singles[k], errorbararray_lower[k,l]/OArate_singles[k]))
fractionFile.write('\n')
plt.xscale('symlog',linthreshx=0.5)
#plt.yscale('symlog',linthreshy=0.0001)
plt.legend(fontsize=15)
plt.xlabel("collected light [phe]")
plt.ylabel("Fraction")
#plt.ylim([0,0.1])
plt.grid(which='both',axis='both')
plt.show()
fig = plt.figure()
ax3 = fig.add_subplot(1,2,1)
#ax3.title.set_text("Rates per Scintillation")
ax4 = fig.add_subplot(1,2,2)
for k in range(len(Qedges)-1):
print("%f-%f keV: %f seconds"%(Qedges[k],Qedges[k+1],LT_by_Q[k]))
if LT_by_Q[k]>100:
ax3.errorbar(binc,H[k,:],[errorbararray_upper[k,:], errorbararray_lower[k,:]],marker='.',markersize=7,
linestyle='none',label="%f-%f keV"%(Qedges[k],Qedges[k+1]))
Hnew = []
errorbarnew_upper = []
errorbarnew_lower = []
for l in range(len(binwidths)):
Hnew.append(np.divide(H[k,l],binwidths[l]))
errorbarnew_upper.append(np.divide(errorbararray_upper[k,l],binwidths[l]))
errorbarnew_lower.append(np.divide(errorbararray_lower[k,l],binwidths[l]))
ax4.errorbar(binc, Hnew, [errorbarnew_upper, errorbarnew_lower],
marker='.', markersize=7, linestyle='none',
label='%f-%f keV'%(Qedges[k],Qedges[k+1]))
for l in range(len(bins)-1):
spectrumFile.write("%.1f-%.1fphe\t"%(bins[l],bins[l+1]))
for k in range(len(Qedges)-1):
spectrumFile.write("%f,%f,%f\t"%(H[k,l],errorbararray_upper[k,l], errorbararray_lower[k,l]))
spectrumFile.write('\n')
ax3.set_xscale('symlog',linthreshx=0.5)
ax4.set_xscale('symlog',linthreshx=0.5)
ax3.set_yscale('log')
ax4.set_yscale('log')
#plt.yscale('symlog',linthreshy=0.0001)
ax3.legend(fontsize=15)
ax4.legend(fontsize=15)
plt.xlabel("collected light [phe]")
ax3.set_ylabel("Rate per bin [Hz]")
ax4.set_ylabel("rate per phe [Hz/phe]")
#plt.ylim([0,0.1])
ax3.grid(which='both',axis='both')
ax4.grid(which='both',axis='both')
plt.show()
fig = plt.figure()
ax3 = fig.add_subplot(1,2,1)
ax3.title.set_text("Rates per Scintillation, multiples")
ax4 = fig.add_subplot(1,2,2)
for k in range(len(Qedges)-1):
print("%f-%f keV: %f seconds"%(Qedges[k],Qedges[k+1],LT_by_Q[k]))
if LT_by_Q[k]>100:
ax3.errorbar(binc,H_multi[k,:],[errorbararray_multi_upper[k,:], errorbararray_multi_upper[k,:]],marker='.',markersize=7,
linestyle='none',label="%f-%f keV"%(Qedges[k],Qedges[k+1]))
Hnew_multi = []
errorbarnew_multi_upper = []
errorbarnew_multi_lower = []
for l in range(len(binwidths)):
Hnew_multi.append(np.divide(H_multi[k,l],binwidths[l]))
errorbarnew_multi_upper.append(np.divide(errorbararray_multi_upper[k,l],binwidths[l]))
errorbarnew_multi_lower.append(np.divide(errorbararray_multi_lower[k,l],binwidths[l]))
ax4.errorbar(binc, Hnew_multi, [errorbarnew_multi_upper, errorbarnew_multi_lower],
marker='.', markersize=7, linestyle='none',
label='%f-%f keV'%(Qedges[k],Qedges[k+1]))
for l in range(len(bins)-1):
spectrumFile_multiples.write("%.1f-%.1fphe\t"%(bins[l],bins[l+1]))
for k in range(len(Qedges)-1):
spectrumFile_multiples.write("%f,%f,%f\t"%(H_multi[k,l],errorbararray_multi_upper[k,l], errorbararray_multi_lower[k,l]))
spectrumFile_multiples.write('\n')
ax3.set_xscale('symlog',linthreshx=0.5)
ax4.set_xscale('symlog',linthreshx=0.5)
ax3.set_yscale('log')
ax4.set_yscale('log')
#plt.yscale('symlog',linthreshy=0.0001)
ax3.legend(fontsize=15)
ax4.legend(fontsize=15)
plt.xlabel("collected light [phe]")
ax3.set_ylabel("Rate per bin [Hz]")
ax4.set_ylabel("rate per phe [Hz/phe]")
#plt.ylim([0,0.1])
ax3.grid(which='both',axis='both')
ax4.grid(which='both',axis='both')
plt.show()
plt.figure()
plt.scatter([x[1] for x in bubInfo],[x[3] for x in bubInfo])
plt.yscale('symlog',linthreshy=0.5)
plt.xlabel('Seitz Threshold [keV]')
plt.ylabel('collected light [phe]')
plt.show
fig,ax1 = plt.subplots()
ax2 = ax1.twinx()
ax1.set_xlabel('Seitz Threshold (keV)',fontsize=18)
ax1.set_ylabel('Live time (s)',fontsize=18)
ax2.set_ylabel('Number of bubbles',fontsize=18)
ax1.scatter(centers,LT,20,'r')
ax2.scatter(centers,onebubcount,20,'b')
plt.show
spectrumFile.close()
spectrumFile_multiples.close()
fractionFile.close()
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 11 10:29:20 2019
@author: bressler
"""
from PICOcode.REFPROP.SeitzModel import SeitzModel
import numpy as np
T = np.arange(-180,-150,5)
print(T)
for t in T:
print(t)
m=SeitzModel(30,float(t),'argon')
print(m.Q[0])
def xeSoundSpeed(runs, mergedfilename, Qbins, FeedbackTransducer):
if FeedbackTransducer == "PT4":
pt = 3
elif FeedbackTransducer == "PT6":
pt = 5
#with open("/nashome/b/bressler/sbcoutput/%s_merged_oldPMT.txt"%mergedfilename,"r") as fin:
with open("/nashome/b/bressler/sbcoutput/%s_merged.txt" % mergedfilename,
"r") as fin:
data = fin.readlines()
headers = data[0].split()
runind = headers.index("run")
eventind = headers.index("event")
xind = headers.index("x")
yind = headers.index("y")
zind = headers.index("z")
lagind = headers.index("lag")
spectind = headers.index("PMTphe")
blockedind = headers.index('isBlocked')
nbubind = headers.index('nbub')
x = []
y = []
z = []
evid = []
lag = []
spect = []
isblocked = []
nbub = []
i = 0
for line in data:
if i > 0:
split_line = line.split()
evid.append(split_line[runind] + "-" + split_line[eventind])
isblocked.append(float(split_line[blockedind]))
x.append(float(split_line[xind]))
y.append(float(split_line[yind]))
z.append(float(split_line[zind]))
lag.append(float(split_line[lagind]))
spect.append(float(split_line[spectind]))
nbub.append(float(split_line[nbubind]))
i += 1
counts = []
nbubs = []
didntpass = 0
bubInfo = []
eventcount = np.zeros(87)
spectra = [[] for i in range(87)]
LT = np.zeros(87)
LT_by_Q = np.zeros(len(Qbins) - 1)
expand_times = [[] for i in range(87)]
totbub = 0
onebubcount = np.zeros(87)
twobubcount = np.zeros(87)
threebubcount = np.zeros(87)
setpoints = []
elt = 0
temps = []
passing_lag = []
passing_z = []
for run in runs:
print(run)
tcut = 0 # was 20
z_low = -4
z_high = 0
preq = 1
runrawpath = '/bluearc/storage/SBC-17-data/' + run
events = [
evnt for evnt in listdir(runrawpath)
if not isfile(join(runrawpath, evnt))
]
Nevents = len(events)
runreconpath = "/pnfs/coupp/persistent/grid_output/SBC-17/output/%s/" % run
historyfilename = runreconpath + "HistoryAnalysis_%s.bin" % run
history = sbc.DataHandling.ReadBinary.ReadBlock(historyfilename)
getbubfile = "/coupp/data/home/coupp/HumanGetBub_output_SBC-17/HumanGetBub_%s.bin" % run
c = sbc.DataHandling.ReadBinary.ReadBlock(getbubfile)
eventn = c["ev"]
count = Counter(eventn)
edges = history["PressureEdge"][pt]
centersp = [(edges[i] + edges[i + 1]) / 2
for i in range(len(edges) - 1)]
#centers = Qvals
e0 = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath, 0, "slowDAQ")
T = np.mean(e0["slowDAQ"]["T1"])
temps.append(T)
sm = SeitzModel(list(edges), T, 'xenon')
edges_by_Q = sm.Q
centers = [(edges_by_Q[i] + edges_by_Q[i + 1]) / 2
for i in range(len(edges_by_Q) - 1)]
print("T=%f C" % T)
for c in count:
N = count[c]
counts.append(N)
"""
if N%2 != 0 and N != 1:
print("lines isn't even")
print(c)
print(N)
elif N%2 == 0:
n = N/2
nbubs.append(n)
"""
for eventn in range(Nevents):
try:
indices_back = 30
event_ID = run + "-" + str(eventn)
mergedind = evid.index(event_ID)
bl = isblocked[mergedind]
light = spect[mergedind]
ev_z = z[mergedind]
if np.isnan(light):
light = 0
ev_z = z[mergedind]
ev_lag = lag[mergedind]
#onebub = not np.isnan(runposreco["z"][0][int(eventn)])
n_from_merged = nbub[mergedind]
n = 0
N = count[eventn]
if N % 2 == 0:
n = N / 2
nbubs.append(n)
if n_from_merged != n:
print('n and merged n dont match')
print("n here: %d" % n)
print("n from merged: %d" % n_from_merged)
e = sbc.DataHandling.GetSBCEvent.GetEvent(
runrawpath, eventn, "slowDAQ", "event")
t = e["slowDAQ"]["elapsed_time"]
tcenters = [(t[i + 1] + t[i]) / 2 for i in range(len(t) - 1)]
trig_time = t[list(e["slowDAQ"]["TriggerOut"]).index(1.0) -
indices_back]
pslope = np.diff(e["slowDAQ"][FeedbackTransducer])
expstartind = list(pslope).index(min(list(pslope)))
exp_start = tcenters[expstartind]
trig_pressure = e["slowDAQ"][FeedbackTransducer][
list(e["slowDAQ"]["TriggerOut"]).index(1.0) - indices_back]
T = np.mean(e["slowDAQ"]["T1"])
#print(Q[0])
pset = e["event"]["Pset"]
ev_lt = e["event"]['livetime']
elt += ev_lt
if pset not in setpoints:
setpoints.append(pset)
#print(pset)
#print(len(history["PressureBins"][eventn]))
"""
plt.figure()
plt.plot([trig_time,trig_time],[0,200],label="Bubble time")
plt.plot([exp_start,exp_start],[0,200],label="Expansion start")
plt.plot([0,max(t)],[trig_pressure,trig_pressure],label="Bubble pressure")
plt.plot(t,e["slowDAQ"]["PT6"],label="PT6")
plt.plot(tcenters,pslope,label="Pressure slope")
plt.xlabel("time",fontsize=18)
plt.ylabel("signal",fontsize=18)
plt.legend(fontsize=18)
plt.show
"""
if n == 1 and ev_lt > 20 and pset == 25:
totbub += 1
for i in range(len(centers)):
if trig_time > exp_start + tcut:
#print(trig_pressure)
#print(pset)
if (trig_pressure >= edges[i]
and trig_pressure <= edges[i + 1]
) and abs(trig_pressure - pset) < preq / 2:
onebubcount[i] += 1
eventcount[i] += 1
if not bl and not np.isnan(light):
if light > 0:
spectra[i].append(light)
passing_lag.append(ev_lag)
passing_z.append(ev_z)
except Exception as x:
print(x)
plt.figure()
plt.scatter(passing_z, passing_lag, 20)
plt.xlabel('z [cm]', fontsize=19)
plt.ylabel('lag [microseconds]', fontsize=19)
plt.show()
def gaussian(x, mu, sigma, amplitude):
return amplitude * np.exp(-((x - mu) / (np.sqrt(2) * sigma))**2)
def lin(x, m, b):
return m * x + b
zbinedges = np.arange(-2.75, 0.25, 0.25)
zpts = [(zbinedges[i] + zbinedges[i + 1]) / 2
for i in range(len(zbinedges) - 1)]
zbinlags = [[] for i in range(len(zbinedges) - 1)]
print(zbinlags)
for j in range(len(passing_lag)):
for i in range(len(zbinedges) - 1):
if passing_z[j] >= zbinedges[i] and passing_z[j] < zbinedges[
i + 1] and passing_lag[j] > -275:
zbinlags[i].append(passing_lag[j])
"""
params, params_cov = scipy.optimize.curve_fit(fit_fun, ch1zs, ch1lags)
fitx = np.arange(-3,0,0.1)
ft = [fit_fun(fitx[i], params[0], params[1], params[2],
params[3], params[4]) for i in range(len(fitx))]
ss = (-1/params[3])*10000
"""
avgs = []
avgs_std = []
gausfitx = np.arange(-400, 0, 0.1)
for j in range(len(zpts)):
Nbins = int(np.ceil(np.sqrt(len(zbinlags[j]))))
print(Nbins)
if Nbins == 0:
Nbins = 1
if len(zbinlags[j]) > 0:
print(zbinlags[j])
#avgs.append(np.mean(zbinlags[j]))
gparams = [np.mean(zbinlags[j]), np.std(zbinlags[j]), 10]
"""
dat,bins = np.histogram(zbinlags[j],Nbins)
bincenters = [(bins[i]+bins[i+1])/2 for i in range(len(bins)-1)]
try:
gparams,gparams_cov = scipy.optimize.curve_fit(gaussian,bincenters,dat,
p0=(-250,50,10))
except Exception as ex:
print(ex)
gparams = [np.mean(zbinlags[j]), np.std(zbinlags[j]), 10]
print("bin centered on z=%.2f uses numpy mean and std"%zpts[j])
print(gparams)
"""
avgs.append(gparams[0])
avgs_std.append(gparams[1])
gausfit = [
gaussian(gausfitx[i], gparams[0], gparams[1], gparams[2])
for i in range(len(gausfitx))
]
lfitx = np.arange(-3, 0, 0.1)
print(zpts)
print(avgs)
print(avgs_std)
lparams, lparams_cov = scipy.optimize.curve_fit(lin,
zpts[:-1],
avgs[:-1],
sigma=avgs_std[:-1],
p0=[50, -50])
ss = (1 / abs(lparams[0])) * 10000
ss_err = 10000 * max(
abs(1 / abs(lparams[0]) - 1 /
(abs(lparams[0]) + np.sqrt(lparams_cov[0][0]))),
abs(1 / abs(lparams[0]) - 1 /
(abs(lparams[0]) - np.sqrt(lparams_cov[0][0]))))
plt.figure()
plt.grid()
plt.scatter(passing_z, passing_lag)
plt.plot(
lfitx,
lparams[0] * lfitx + lparams[1],
color="g",
linewidth=4,
label=r"fit line: $\Delta t_0 = (%.2f \pm %.2f)z +(%.2f \pm %.2f)$" %
(lparams[0], np.sqrt(
lparams_cov[0][0]), lparams[1], np.sqrt(lparams_cov[1][1])))
#plt.plot(fitx,params[3]*fitx + params[4],color = 'g',linewidth=4,
# label = "Linear part of fit, dt = %fz+%f"%(params[3],params[4]))
#plt.plot(fitx,ft,color='r',linewidth=5,
# label = "Fit: dt = %fcos(%fz+%f) + %fz +%f"%(params[0],
# params[1],params[2],params[3],params[4]))
plt.errorbar(zpts,
avgs,
avgs_std,
color='c',
marker='o',
markersize=10,
linestyle='none')
plt.xlabel("z position [cm]", fontsize=20)
plt.ylabel(r"$\Delta t_0 = t_{PMT} - t_{Piezo}$ [$\mu$s]", fontsize=20)
plt.title(r"Channel 0, $v_s=%.2f \pm %.2f$ m/s" % (ss, ss_err),
fontsize=20)
plt.legend(fontsize=18)
plt.show
plt.figure()
plt.hist(spect, int(np.floor(np.sqrt(len(spect)))))
plt.show
def getRate(xyzf, runs, LTpreq, PT):
LT = []
totbub = 0
bubperpset = []
doublesperpset = []
triplesperpset = []
setpoints = []
elt = 0
feedbackTransducer = int(PT[-1]) - 1
temperatures = []
counts = []
event_livetimes = []
event_counter = 0
for run in runs:
runpath = '/bluearc/storage/SBC-17-data/' + run + '/'
events = [
evnt for evnt in listdir(runpath)
if not isfile(join(runpath, evnt))
]
Nevents = len(events)
print("run " + run + ": %d events" % Nevents)
indices = [
i for i, x in enumerate(xyzf["runid"])
if str(x[0]) + "_" + str(x[1]) == run
]
runposreco = {
"ev": [xyzf["ev"][indices]],
"x": [xyzf["bubX"][indices]],
"y": [xyzf["bubY"][indices]],
"z": [xyzf["bubZ"][indices]]
}
runrawpath = '/bluearc/storage/SBC-17-data/' + run
runreconpath = "/pnfs/coupp/persistent/grid_output/SBC-17/output/%s/" % run
historyfilename = runreconpath + "HistoryAnalysis_%s.bin" % run
history = sbc.DataHandling.ReadBinary.ReadBlock(historyfilename)
getbubfile = "/coupp/data/home/coupp/HumanGetBub_output_SBC-17/HumanGetBub_%s.bin" % run
c = sbc.DataHandling.ReadBinary.ReadBlock(getbubfile)
#print(c.keys())
evn = c["ev"]
#print(evn)
#print(c["nbubimage"])
count = Counter(evn)
#print(count)
nbubs = np.zeros(Nevents)
#print(len(nbubs))
for c in count:
#print(c)
N = count[c]
#print(N)
counts.append(N)
if N % 2 != 0 and N != 1:
print("lines isn't even")
print(c)
print(N)
elif N % 2 == 0:
n = N / 2
nbubs[c] = n
e0 = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath, 0, "slowDAQ",
"event")
T25 = np.mean(e0["slowDAQ"]["T1"])
seitz25 = SeitzModel(25, T25, 'xenon')
Q25 = seitz25.Q
#print(nbubs)
for eventn in range(Nevents):
try:
nobub = np.isnan(runposreco["z"][0][int(eventn)])
n = nbubs[int(eventn)]
#print("n=%d"%n)
if nobub and n == 1:
print("nobub and n=1: " + run + '-' + str(eventn))
"""
elif (not nobub) and n==1:
print("(not nobub) and n = 1: " + run + '-'+str(eventn))
elif n != 1 and nobub:
print("nobub and n != 1: "+run+'-'+str(eventn))
elif n !=1 and not nobub:
print("not nobub and n != 1: "+run+'-'+str(eventn))
"""
#print(n==1)
e = sbc.DataHandling.GetSBCEvent.GetEvent(
runrawpath, eventn, "slowDAQ", "event")
lt_event = e["event"]["livetime"]
if (lt_event > 800):
if run + '-' + str(eventn) not in OKLONGEVENTS:
print("check long event, excluding now: " + run + "-" +
str(eventn))
continue
event_livetimes.append(lt_event)
event_counter += 1
if lt_event < 20:
#print("short event excluded")
continue
T = np.mean(e["slowDAQ"]["T1"])
#print(T)
if T > -1000:
temperatures.append(T)
else:
print("Not including unpysical temperature %f C" % T)
pset = e["event"]["Pset"]
#seitz = SeitzModel(pset,T,'xenon')
#Q = seitz.Q
elt += e["event"]["livetime"]
if pset not in setpoints:
setpoints.append(pset)
LT.append(0)
bubperpset.append(0)
doublesperpset.append(0)
triplesperpset.append(0)
ind = setpoints.index(pset)
indices_back = 30
trig_pressure = e["slowDAQ"][PT][
list(e["slowDAQ"]["TriggerOut"]).index(1.0) - indices_back]
#if not nobub:
#print("adding bubble at P = %f"%trig_pressure)
if n > 0:
totbub += 1
if (np.abs(trig_pressure - pset) < LTpreq / 2):
if n == 1: bubperpset[ind] += 1
elif n == 2: doublesperpset[ind] += 1
elif n == 3: triplesperpset[ind] += 1
edges = history["PressureEdge"][feedbackTransducer]
times = history["PressureBins"][eventn][feedbackTransducer][:]
centers = [(edges[i] + edges[i + 1]) / 2
for i in range(len(edges) - 1)]
#print(edges)
for i in range(len(centers)):
if abs(centers[i] - pset) < LTpreq / 2:
LT[ind] += times[i]
except Exception as x:
print(x)
break
totlt = sum(LT)
r = totbub / totlt
rerr = np.sqrt(totbub) / totlt
rperpset = np.divide(bubperpset, LT)
r_err_perpset = np.divide(np.sqrt(bubperpset), LT)
for i in range(len(rperpset)):
if LT[i] > 50:
seitz = SeitzModel(setpoints[i], np.mean(temperatures), 'xenon')
#print(setpoints[i])
#print(min(temperatures))
#print(temperatures)
#print(seitz)
print("@@@@@@@@@@@@@@@@@@@@@@@@@@")
print("Pressure bin: " + str(setpoints[i]))
print("Live Time: " + str(LT[i]))
print("Single Bubbles: " + str(bubperpset[i]))
print("Singles Rate: " + str(rperpset[i]) + "+/-" +
str(r_err_perpset[i]))
print("Double Bubbles: %d" % doublesperpset[i])
print("Doubles Rate: %.2e" % (doublesperpset[i] / LT[i]))
print("Triple Bubbles: %d" % triplesperpset[i])
print("Triples Rate: %.2e" % (triplesperpset[i] / LT[i]))
print("Seitz Threshold: %f keV" % seitz.Q)
print("Temperature: %.2fC" % np.mean(temperatures))
print("\n")
if 25.0 in setpoints:
print("!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!")
print("25 psia bin: ")
print(str(LT[setpoints.index(25.0)]) + "s")
print(str(bubperpset[setpoints.index(25.0)]) + " bubbles")
print(str(Q25) + " keV")
print(str(T25) + " Celsius")
print("rate: " + str(rperpset[setpoints.index(25.0)]) + "+/-" +
str(r_err_perpset[setpoints.index(25.0)]) + " Hz")
print("\n")
print("overall rate: " + str(r) + "+/-" + str(rerr) + "Hz")
print("total events: %d" % event_counter)
print("total bubbles: " + str(totbub))
print("fraction of events with bubbles: %f" % (totbub / event_counter))
print("total live time: " + str(totlt))
print("total live time from events: " + str(elt))
print("mean live time: %f sec" % np.mean(event_livetimes))
print("trigger rate: %f Hz" % (1 / float(np.mean(event_livetimes))))
print("bubble rate from bub fraction and LT: %f Hz" % (float(
(totbub / event_counter)) / float(np.mean(event_livetimes))))
print("\n")
plt.figure()
plt.scatter(np.arange(event_counter),
event_livetimes,
facecolor='none',
edgecolor='b')
plt.grid()
plt.xlabel('event count')
plt.ylabel('event livetime (s)')
plt.show()
plt.figure()
plt.hist(event_livetimes, int(np.ceil(np.sqrt(len(event_livetimes)))))
plt.show()
return [totbub, totlt, rperpset, r_err_perpset, r, rerr, setpoints]
LTpreq=5
indices_back=30
triggerp = []
for run in runs:
runrawpath = '/bluearc/storage/SBC-17-data/'+run
runreconpath = "/pnfs/coupp/persistent/grid_output/SBC-17/output/%s/"%run
historyfilename = runreconpath+"HistoryAnalysis_%s.bin"%run
history = sbc.DataHandling.ReadBinary.ReadBlock(historyfilename)
for eventn in range(10):
try:
e = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath,eventn,"slowDAQ","event")
T = np.mean(e["slowDAQ"]["T1"])
t = e["slowDAQ"]["elapsed_time"]
print(T)
pset = e["event"]["Pset"]
seitz = SeitzModel(pset,T,'xenon')
Q = seitz.Q
PT6 = e["slowDAQ"]["PT6"]
PT5 = e["slowDAQ"]["PT5"]
plt.figure()
PT4 = e["slowDAQ"]["PT4"]
plt.plot(t,PT6,label="PT6")
plt.plot(t,PT5,label="PT5")
plt.plot(t,PT4,label="PT4")
plt.plot([t[0],t[-1]],[pset,pset],label="pset")
plt.legend()
print("event livetime: "+str(e["event"]["livetime"]))
trig_pressure = e["slowDAQ"]["PT6"][list(e["slowDAQ"]["TriggerOut"]).index(1.0)-indices_back]
edges = history["PressureEdge"][5]
times = history["PressureBins"][eventn][5][:]
for run in runs:
print(run)
tcut = 0
runrawpath = '/bluearc/storage/SBC-17-data/' + run
runreconpath = "/pnfs/coupp/persistent/grid_output/SBC-17/output/%s/" % run
historyfilename = runreconpath + "HistoryAnalysis_%s.bin" % run
history = sbc.DataHandling.ReadBinary.ReadBlock(historyfilename)
edges = history["PressureEdge"][5]
centersp = [(edges[i] + edges[i + 1]) / 2 for i in range(len(edges) - 1)]
#centers = Qvals
e0 = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath, 0, "slowDAQ")
T = np.mean(e0["slowDAQ"]["T1"])
temps.append(T)
sm = SeitzModel(list(edges), T, 'xenon')
edges_by_Q = sm.Q
centers = [(edges_by_Q[i] + edges_by_Q[i + 1]) / 2
for i in range(len(edges_by_Q) - 1)]
print("T=%f C" % T)
for eventn in range(101):
try:
indices_back = 30
event_ID = run + "-" + str(eventn)
e = sbc.DataHandling.GetSBCEvent.GetEvent(runrawpath, eventn)
acousticfilename = runreconpath + "AcousticAnalysis_%s.bin" % run
a = sbc.DataHandling.ReadBinary.ReadBlock(acousticfilename)
bubt0 = a["bubble_t0"]
@author: bressler
"""
from PICOcode.REFPROP.SeitzModel import SeitzModel
import numpy as np
import matplotlib.pyplot as plt
T = np.arange(-153, -138, 1)
#T=[-143]
print(T)
P = np.arange(15, 382, 2)
QperT = [[] for i in range(len(T))]
RperT = [[] for i in range(len(T))]
for i in range(len(T)):
print(T[i])
for j in range(len(P)):
m = SeitzModel(float(P[j]), float(T[i]), 'argon')
QperT[i].append(m.Q[0])
RperT[i].append(m.Rc[0])
plt.figure()
for i in range(len(T)):
plt.plot(QperT[i], RperT[i], label="T=%f K" % (T[i] + 273.15))
plt.xlim([0.01, 0.5])
plt.ylim([0, 15])
plt.xlabel("Seitz Threshold [keV]")
plt.ylabel("Critical Radius [nm]")
plt.legend()
plt.show()