def test1():
s1 = SigProc(nSamples=16384, nAdcCh=20, nSdmCh=19, adcSdmCycRatio=5)
# data1 = s1.generate_adcDataBuf()
# data2 = s1.generate_sdmDataBuf()
# data1 = ((s1.ANALYSIS_WAVEFORM_BASE_TYPE * s1.nSamples) * s1.nAdcCh)()
data1 = (s1.ANALYSIS_WAVEFORM_BASE_TYPE * (s1.nSamples * s1.nAdcCh))()
# data1 = ((s1.ANALYSIS_WAVEFORM_BASE_TYPE * s1.nSamples) * s1.nAdcCh)()
# print len(data1[0])
print type(data1)
# print type(byref(data1[0]))
print type(pointer(data1))
data1 = array('f', [0] * (16384 * 20))
inRoot = 'data/fpgaLin/Feb09b_data_581.root'
fout1 = TFile(inRoot, 'read')
tree1 = fout1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
i = 37
tree1.GetEntry(i)
# print data1[3]
sp1 = SignalProcessor()
sp1.nAdcCh = 20
# sp1.sRanges.clear()
# sp1.sRanges.push_back((0,3000))
# sp1.sRanges.push_back((3000,8000))
# sp1.sRanges.push_back((8000,15000))
# sp1.measure_pulse(byref(data1))
# sp1.measure_pulse(pointer(data1))
# sp1.measure_pulse(data1)
print sp1.nMeasParam
f = 1000
a = 16384 * 0.2 * f * 0.000001
print 16384 * 0.2 * f * 0.000001
n1 = int(1 / (0.2 * f * 0.000001))
print n1
sp1.sRanges.clear()
ip = 0
while ip + n1 < sp1.nSamples:
iq = ip + n1
# if iq > sp1.nSamples: iq = sp1.nSamples
# a = (ip, iq)
sp1.sRanges.push_back((ip, iq))
ip = iq
#
sp1.measure_pulse(data1)
for i in range(sp1.nAdcCh):
# print i, sp1.measParam[sp1.nMeasParam*i], sp1.measParam[sp1.nMeasParam*i+1], sp1.measParam[sp1.nMeasParam*i+2], sp1.measParam[sp1.nMeasParam*i+3]
print i,
for j in range(sp1.nMeasParam):
print sp1.measParam[sp1.nMeasParam * i + j],
print
sp1.test2()
def test3a():
'''To test the event reconstruction'''
data1 = array('f', [0] * (16384 * 20))
inRoot = 'data/fpgaLin/Feb27a_data_40.root'
fout1 = TFile(inRoot, 'read')
tree1 = fout1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
i = 81
tree1.GetEntry(i)
### here comes the constructor
sp1 = SignalProcessor()
sp1.nAdcCh = 20
sp1.IO_adcData = data1
sp1.fltParam.clear()
for x in [30, 100, 300, -1]:
sp1.fltParam.push_back(x)
thre = [0.001] * sp1.nAdcCh
thre[19] = 0.02
sp1.ch_thre.clear()
for x in thre:
sp1.ch_thre.push_back(x)
sp1.reco()
Unit = 0.2
h3 = TH3F('h3', 'h3;x [cm];y [cm];t [ps]', 9, -1.8, 1.8, 9, -1.8, 1.8, 100,
-1. * Unit * sp1.CF_uSize, Unit * sp1.CF_dSize)
# for e in sp1.IO_evts:
for e in sp1.get_events():
print e.trigID, len(e.sigs)
h3.Reset()
showEvent(e, h3, h2)
h3.Draw('BOX2Z')
waitRootCmdX()
# for j in range(sp1.nAdcCh): print j, e.sigs[j].im
# d = [e.sigs[j].Q for j in range(sp1.nAdcCh)]
# print d
# showA(d)
e1 = sp1.IO_evts[0]
print dir(e1)
print dir(e1.sigs[0])
print '****', e1.sigs[0].im
showEvents(sp1.IO_evts)
def readSignal(inRoot, outText, freq=1000):
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
sp1.fltParam.clear()
for x in [50, 150, 200, -1.]:
sp1.fltParam.push_back(x)
n1 = int(1 / (0.2 * freq * 0.000001))
sp1.sRanges.clear()
ip = 0
dn = 2500 % n1 ## 2500 is the expected position of the signal
# while ip+dn < sp1.nSamples:
# sp1.sRanges.push_back((ip, min(ip+n1, sp1.nSamples)))
# ip += n1
sp1.sRanges.push_back((0, 400))
# while ip+n1<sp1.nSamples:
# sp1.sRanges.push_back((ip, ip+n1))
# ip += n1
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
# inRoot = 'data/fpgaLin/Jan21b_C2_100mV_f1000.root'
fout1 = TFile(inRoot, 'read')
tree1 = fout1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
with open(outText, 'w') as fout:
fout.write(':'.join(
['sID/I', 'ch/I', 'B/F', 'dB/F', 'im/I', 'idx/I', 'A/F']))
for ievt in range(tree1.GetEntries()):
tree1.GetEntry(ievt)
sp1.measure_pulse(data1)
for i in range(sp1.nAdcCh):
itmp = sp1.nMeasParam * i
for j in range(sp1.nMeasParam / 2 - 1):
fout.write('\n' + ' '.join([
str(ievt),
str(i),
str(sp1.measParam[itmp]),
str(sp1.measParam[itmp + 1]),
str(j),
str(int(sp1.measParam[itmp + 2 * j + 2])),
str(sp1.measParam[itmp + 2 * j + 3])
]))
def overlayFilters(inRoot):
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
sp1.fltParam.clear()
sp1.x_thre = 0.1
# sp3a
for x in [30, 15, 50, 2500]:
sp1.fltParam.push_back(x)
# for x in [50, 5, 15, 2500]: sp1.fltParam.push_back(x)
# sp3b
# for x in [50, 500, 700, 2500]: sp1.fltParam.push_back(x)
run = int(inRoot.rstrip('.root').split('_')[-1])
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
dataT = array('i', [0])
fin1 = TFile(inRoot, 'read')
tree1 = fin1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
tree1.SetBranchAddress('T', dataT)
oTag = 'flt_'
fout1 = TFile(
os.path.dirname(inRoot) + '/' + oTag + os.path.basename(inRoot),
'recreate')
tup1 = TNtuple('flt', "filter analysis tuple", 'run:evt:ch:ip:V')
NPOINTS = 200
ch = 19
NEVT = tree1.GetEntries()
for ievt in range(NEVT):
tree1.GetEntry(ievt)
sp1.measure_pulse2(data1, ch)
for ip in range(NPOINTS):
tup1.Fill(run, ievt, ch, ip, sp1.scrAry[ip])
tup1.Write()
fout1.Close()
def check_calib():
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
### setup the calibration file
fin1 = TFile('fout_calib.root')
sp1.corr_spine.clear()
sp1.corr_TF1.clear()
sp1.corr_spine.reserve(sp1.nAdcCh)
sp1.corr_TF1.reserve(sp1.nAdcCh)
for i in range(sp1.nAdcCh - 1):
sp1.corr_spine.push_back(fin1.Get('gr_calib_ch' + str(i)))
sp1.corr_TF1.push_back(sp1.corr_spine[i].GetFunction('pol1'))
## run a test
for x in sp1.corr_spine[5].GetX():
t = 1
print sp1.correction(1, x) * t, sp1.correction(
1, x, 1) * t, '|', sp1.correction(5, x) * t, sp1.correction(
5, x, 1) * t
def display_test(inRoot='data/fpgaLin/Feb27a_data_40.root', ievt=0):
'''To test the event reconstruction'''
gStyle.SetOptStat(0)
gROOT.ProcessLine('.L Pal.C')
gStyle.SetPalette(55)
gStyle.SetPadRightMargin(0.15)
# from ROOT import Pal2
# Pal2()
data1 = array('f', [0] * (16384 * 20))
fout1 = TFile(inRoot, 'read')
tree1 = fout1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
### here comes the constructor
sp1 = SignalProcessor()
sp1.nAdcCh = 20
sp1.IO_adcData = data1
sp1.CF_chan_en.clear()
for i in range(20):
sp1.CF_chan_en.push_back(1)
sp1.fltParam.clear()
for x in [30, 100, 300, -1]:
sp1.fltParam.push_back(x)
thre = [0.001] * sp1.nAdcCh
thre[19] = 0.02
sp1.ch_thre.clear()
for x in thre:
sp1.ch_thre.push_back(x)
Unit = 0.2
h3 = TH3F('h3', 'h3;x [cm];y [cm];t [ps]', 9, -1.8, 1.8, 9, -1.8, 1.8, 100,
-1. * Unit * sp1.CF_uSize, Unit * sp1.CF_dSize)
h2 = TH2F('h2', 'h2;t [ps];Channel;Q', (sp1.CF_uSize + sp1.CF_dSize),
-1. * Unit * sp1.CF_uSize, Unit * sp1.CF_dSize, 20, 0, 20)
cx = TCanvas('cx', 'cx', 1500, 700)
cx.Divide(2, 1)
# for i in range(tree1.GetEntries()):
while ievt >= 0:
tree1.GetEntry(ievt)
sp1.reco()
for e in sp1.IO_evts:
print e.trigID, len(e.sigs)
h3.Reset()
h2.Reset()
showEvent(e, h3, h2)
cx.cd(1)
# h3.Draw('BOX2')
# h3.Draw()
# h3.SetMarkerStyle(20)
# h3.SetMarkerSize(1)
h3.Draw('COLZ')
cx.cd(2)
t = h2.GetBinContent(h2.GetMaximumBin()) * 1.06
h2.GetZaxis().SetRangeUser(-0.05 * t, t * 0.95)
h2.Draw('colz')
# h2.Draw('axis same')
cx.cd(0)
# gPad.Update()
# a = raw_input("x:")
waitRootCmdX(cx)
ievt += 1
def readSignal4a(argX, runPattern='.*_data_(\d+).root'):
'''Use non default time window'''
args = argX.split(';')
inRoot = args[0]
oTag = args[1]
print "Starting", inRoot, oTag
### pulse test
dV = -1
dvPattern = '.*_(\d+)mV_f\d+.root'
m = re.match(dvPattern, inRoot)
if m:
try:
dV = int(m.group(1))
except ValueError:
print "Failed to get the dV in file:", iRoot
### data check
run = -1
if runPattern is not None:
m = re.match(runPattern, inRoot)
if m:
try:
run = int(m.group(1))
except ValueError:
print "Run number not exatracted for file", iRoot
return
else:
if dV < 0:
print "Run number not exatracted for file", iRoot
return
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
sp1.fltParam.clear()
# for i in range(sp1.nAdcCh): sp1.ch_thre[i] = 0.002
# sp1.ch_thre[19] = 0.05
thre = [0.002] * sp1.nAdcCh
thre[2] = 0.0008
thre[4] = 0.001
thre[6] = 0.001
thre[7] = 0.001
thre[10] = 0.001
thre[11] = 0.0007
thre[14] = 0.0007
thre[17] = 0.001
thre[19] = 0.05
sp1.CF_uSize = 600
sp1.CF_dSize = 1100
sp1.ch_thre.clear()
for x in thre:
sp1.ch_thre.push_back(x)
sp1.CF_chan_en.clear()
for i in range(20):
sp1.CF_chan_en.push_back(1)
flt = [50, 100, 500, -1] # dp01a
for x in flt:
sp1.fltParam.push_back(x)
fin1 = TFile(inRoot, 'read')
tree1 = fin1.Get('tree1')
tree2 = 0
outRoot = os.path.dirname(inRoot) + '/' + oTag + os.path.basename(inRoot)
tf = sp1.processFile(tree1, tree2, outRoot, run)
tf.Close()
def readSignal2(inRoot, oTag=None, freq=1000, runPattern='.*_data_(\d+).root'):
if oTag is None:
oTag = readSignal2.oTag
print "Starting", inRoot, oTag
# return
run = -1
if runPattern is not None:
m = re.match(runPattern, inRoot)
if m:
run = int(m.group(1))
print run
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
sp1.fltParam.clear()
for x in [50, 150, 250, 2500]:
sp1.fltParam.push_back(x)
# for x in [50, 150, 200, -1.]: sp1.fltParam.push_back(x)
# for x in [50, 150, 200, 2500]: sp1.fltParam.push_back(x)
# for x in [50, 15, 50, 2500]: sp1.fltParam.push_back(x)
# for x in [500, 450, 800, 2500]: sp1.fltParam.push_back(x)
n1 = int(1 / (0.2 * freq * 0.000001))
sp1.sRanges.clear()
ip = 0
dn = 2500 % n1 ## 2500 is the expected position of the signal
# while ip+dn < sp1.nSamples:
# sp1.sRanges.push_back((ip, min(ip+n1, sp1.nSamples)))
# ip += n1
# sp1.sRanges.push_back((0, 400))
sp1.sRanges.push_back((0, 3000))
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
dataT = array('i', [0])
fin1 = TFile(inRoot, 'read')
tree1 = fin1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
tree1.SetBranchAddress('T', dataT)
fout1 = TFile(
os.path.dirname(inRoot) + '/' + oTag + os.path.basename(inRoot),
'recreate')
tup1 = TNtuple('tup1', "filter analysis tuple",
'run:sID:ch:B:dB:im:idx:A:T')
for ievt in range(tree1.GetEntries()):
tree1.GetEntry(ievt)
sp1.measure_pulse(data1)
for i in range(sp1.nAdcCh):
itmp = sp1.nMeasParam * i
for j in range(sp1.nMeasParam / 2 - 1):
tup1.Fill(run, ievt, i, sp1.measParam[itmp],
sp1.measParam[itmp + 1], j,
sp1.measParam[itmp + 2 * j + 2],
sp1.measParam[itmp + 2 * j + 3],
dataT[0] - 788947200)
tup1.Write()
fout1.Close()
def readSignal3(argX, runPattern='.*_data_(\d+).root'):
args = argX.split(';')
inRoot = args[0]
oTag = args[1]
print "Starting", inRoot, oTag
### pulse test
dV = -1
dvPattern = '.*_(\d+)mV_f\d+.root'
m = re.match(dvPattern, inRoot)
if m:
try:
dV = int(m.group(1))
except ValueError:
print "Failed to get the dV in file:", iRoot
### data check
run = -1
if runPattern is not None:
m = re.match(runPattern, inRoot)
if m:
try:
run = int(m.group(1))
except ValueError:
print "Run number not exatracted for file", iRoot
return
else:
if dV < 0:
print "Run number not exatracted for file", iRoot
return
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
sp1.fltParam.clear()
# for i in range(sp1.nAdcCh): sp1.ch_thre[i] = 0.002
# sp1.ch_thre[19] = 0.05
thre = [0.002] * sp1.nAdcCh
thre[2] = 0.0008
thre[4] = 0.001
thre[6] = 0.001
thre[7] = 0.001
thre[10] = 0.001
thre[11] = 0.0007
thre[14] = 0.0007
thre[17] = 0.001
thre[19] = 0.05
sp1.ch_thre.clear()
for x in thre:
sp1.ch_thre.push_back(x)
# sp3a
# for x in [30, 15, 50, 2500]: sp1.fltParam.push_back(x)
# flt = [50, 50, 250, 2500]
# flt = [50, 50, 150, -1]
flt = [50, 100, 500, -1] # dp01a
# flt = [30, 250, 350, 2500]
# flt = [50, 10, 150, 2500]
# flt = [50, 500, 600, 2500]
# flt = [50, 5, 100, 2500]
for x in flt:
sp1.fltParam.push_back(x)
# sp3b
# for x in [50, 500, 700, 2500]: sp1.fltParam.push_back(x)
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
dataT = array('i', [0])
fin1 = TFile(inRoot, 'read')
tree1 = fin1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
tree1.SetBranchAddress('T', dataT)
fout1 = TFile(
os.path.dirname(inRoot) + '/' + oTag + os.path.basename(inRoot),
'recreate')
tup1 = TNtuple('tup1', "filter analysis tuple",
'run:evt:ch:B:dB:iA:imean:imax:A:w0:w1:w2:T:dV')
a = TObjString("filter:" + str(flt))
a.Write('Info')
### for background subtraction
be1 = bkgEstimator()
# chs = [19]
chs = None
for ievt in range(tree1.GetEntries()):
tree1.GetEntry(ievt)
# apply_wiener_filter(data1, ich=19)
# be1.correct(data1, 19)
sp1.measure_pulse2(data1)
for ich in range(sp1.nAdcCh):
if chs and (ich not in chs): continue
# print "processing channle", ich
ss = sp1.signals[ich]
itmp = sp1.nMeasParam * ich
iA = 0
for ii in ss:
tup1.Fill(run, ievt, ich, sp1.measParam[itmp],
sp1.measParam[itmp + 1], iA, ii.im, ii.idx, ii.Q,
ii.w0, ii.w1, ii.w2, dataT[0] - 788947200, dV)
iA += 1
tup1.Write()
fout1.Close()
def main():
inRoot = sys.argv[1] if len(sys.argv) > 1 else "test.root"
ich = int(sys.argv[2]) if len(sys.argv) > 2 else 0
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
sp1.fltParam.clear()
for x in [50, 150, 200, -1.]:
sp1.fltParam.push_back(x)
freq = 1000
n1 = int(1 / (0.2 * freq * 0.000001))
sp1.sRanges.clear()
ip = 0
dn = 2500 % n1 ## 2500 is the expected position of the signal
while ip + dn < sp1.nSamples:
sp1.sRanges.push_back((ip, min(ip + n1, sp1.nSamples)))
ip += n1
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
fout1 = TFile(inRoot, 'read')
tree1 = fout1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
### range
eRange = None
if len(sys.argv) > 3:
lx = []
r = sys.argv[3].split(',')
for ri in r:
si = ri.find('-')
if si == -1:
lx.append(int(ri))
else:
end = tree1.GetEntries() if si == len(ri) - 1 else int(ri[si +
1:])
lx += range(int(ri[:si]), end)
eRange = lx
else:
eRange = range(tree1.GetEntries())
### plotting
plt.ion()
plt.show()
fig, ax1 = plt.subplots()
ax1.set_xlabel('time (s)')
# Make the y-axis label, ticks and tick labels match the line color.
ax1.set_ylabel('exp', color='b')
ax1.tick_params('y', colors='b')
ax2 = ax1.twinx()
ax2.set_ylabel('sin', color='r')
ax2.tick_params('y', colors='r')
# for i in range(10):
for i in eRange:
print i
tree1.GetEntry(i)
sp1.measure_pulse(data1, ich)
ax1.clear()
ax1.plot(data1[sp1.nSamples * ich:sp1.nSamples * (ich + 1)])
ax2.clear()
ax2.plot([sp1.scrAry[i] for i in range(sp1.nSamples)], 'r.')
fig.tight_layout()
plt.draw()
plt.pause(0.001)
x = raw_input("Press [enter] to continue.")
if x == 'q': break
def check1b(argX,
chs=None,
nEvt=None,
runPattern='.*_data_(\d+).root',
step2=False):
'''Use various filters to extract the results'''
args = argX.split(';')
inRoot = args[0]
oTag = args[1]
outRoot = os.path.dirname(inRoot) + '/' + oTag + os.path.basename(inRoot)
# outRoot = inRoot.rstrip('.root')+oTag+'.root'
print "Starting", inRoot, '->', outRoot
if os.path.exists(outRoot):
print "has:", inRoot, outRoot
return
run = -1
if runPattern is not None:
m = re.match(runPattern, inRoot)
if m: run = int(m.group(1))
else: print "Run number not exatracted for file", iRoot
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
testPulseOnly = False
### look for signal peak in the expected regions only
if testPulseOnly:
freq = 1000
n1 = int(1 / (0.2 * freq * 0.000001))
sp1.sRanges.clear()
ip = 0
dn = 2500 % n1 ## 2500 is the expected position of the signal
while ip + dn < sp1.nSamples:
sp1.sRanges.push_back((ip, min(ip + n1, sp1.nSamples)))
ip += n1
### for storing data
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
dataT = array('i', [0])
fin1 = TFile(inRoot, 'read')
tree1 = fin1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
tree1.SetBranchAddress('T', dataT)
if nEvt is None: nEvt = tree1.GetEntries()
if chs is None: chs = range(sp1.nAdcCh)
ch = chs[0] if len(chs) == 1 else -1
fout1 = TFile(outRoot, 'recreate')
# tup1 = TNtuple('tup1',"filter analysis tuple",'evt:fR:fW:ich:b:bE:im:idx:A')
tup1 = TNtuple('tup1', "filter analysis tuple",
'run:evt:fR:fW:ch:B:dB:iA:imean:imax:A:w0:w1:w2:T')
chs = [19]
rRange = range(10, 200, 20)
wRange = range(50, 300, 20)
### start processing
INTV = 1000 if nEvt > 10000 else max(nEvt / 10, 1)
for ievt in range(nEvt):
tree1.GetEntry(ievt)
if ievt % INTV == 0: print ievt, ' events processed'
for R in rRange:
for W in wRange:
sp1.fltParam.clear()
for x in [500, R, W, 2500.]:
sp1.fltParam.push_back(x)
sp1.measure_pulse2(data1, ch)
for ich in chs:
ss = sp1.signals[ich]
iA = 0
for ii in ss:
tup1.Fill(run, ievt, R, W, ich, 0, 0, iA, ii.im,
ii.idx, ii.Q, ii.w0, ii.w1, ii.w2,
dataT[0] - 788947200)
iA += 1
tup1.Write()
### save the ENC results
tup2 = TNtuple('tup2', "filter analysis tuple enc",
'ich:fR:fW:m:mE:sigma:sigmaE:fq:fStatus')
for R in rRange:
for W in wRange:
for ich in chs:
gDirectory.Delete('h1*')
tup1.Draw(
'A>>h1',
'int(fW)=={0:d}&&int(fR)=={1:d}&&ch=={2:d}'.format(
W, R, ich), 'goff')
h1 = gDirectory.Get('h1')
r = h1.Fit('gaus', 'S0')
fun1 = h1.GetFunction('gaus')
tup2.Fill(ich, R, W, fun1.GetParameter(1), fun1.GetParError(1),
fun1.GetParameter(2), fun1.GetParError(2), r.Prob(),
r.Status())
tup2.Write()
fout1.Close()
def check0():
inRoot = sys.argv[1] if len(sys.argv) > 1 else "test.root"
ich = int(sys.argv[2]) if len(sys.argv) > 2 else 0
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
freq = 1000
n1 = int(1 / (0.2 * freq * 0.000001))
sp1.sRanges.clear()
ip = 0
dn = 2500 % n1 ## 2500 is the expected position of the signal
while ip + dn < sp1.nSamples:
sp1.sRanges.push_back((ip, min(ip + n1, sp1.nSamples)))
ip += n1
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
fout1 = TFile(inRoot, 'read')
tree1 = fout1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
### range
eRange = None
if len(sys.argv) > 3:
lx = []
r = sys.argv[3].split(',')
for ri in r:
si = ri.find('-')
if si == -1:
lx.append(int(ri))
else:
end = tree1.GetEntries() if si == len(ri) - 1 else int(ri[si +
1:])
lx += range(int(ri[:si]), end)
eRange = lx
else:
eRange = range(tree1.GetEntries())
### plotting
plt.ion()
plt.show()
fig, ax1 = plt.subplots()
ax1.set_xlabel('time (s)')
# Make the y-axis label, ticks and tick labels match the line color.
ax1.set_ylabel('exp', color='b')
ax1.tick_params('y', colors='b')
ax2 = ax1.twinx()
ax2.set_ylabel('sin', color='r')
ax2.tick_params('y', colors='r')
# fl1 = Filter_ibl(sp1.nSamples)
# fl1.setup(2,3e-3)
fl1 = Filter_ibb(sp1.nSamples)
fl1.setup(4, 2e-3, 5e-3)
# for i in range(10):
for i in eRange:
print i
tree1.GetEntry(i)
ax1.clear()
ax1.plot(data1[sp1.nSamples * ich:sp1.nSamples * (ich + 1)])
ax2.clear()
sp1.fltParam.clear()
# for x in [500, 150, 200, 2500]: sp1.fltParam.push_back(x)
for x in [500, 800, 2000, 2500]:
sp1.fltParam.push_back(x)
sp1.measure_pulse(data1, ich)
ax2.plot([sp1.scrAry[i] for i in range(sp1.nSamples)], 'r.')
sp1.fltParam.clear()
for x in [500, 15, 50, 2500]:
sp1.fltParam.push_back(x)
# for x in [500, 150, 200, 2500]: sp1.fltParam.push_back(x)
sp1.measure_pulse(data1, ich)
# ax2.plot([sp1.scrAry[i] for i in range(sp1.nSamples)], 'g.')
vx = np.array([sp1.scrAry[i] for i in range(sp1.nSamples)])
ax2.plot(vx, 'g.')
fl1.apply(sp1.scrAry)
vf1 = np.array([fl1.outWav[i] for i in range(sp1.nSamples)])
ax2.plot(vf1, 'm.')
# peakind = find_peaks_cwt(vx, np.arange(1,100))
# peaks = find_peaks_cwt(vx, np.array([5, 10, 20,30,50,100,200,350]), min_snr=50)
# print peaks, vx[peaks]
# peaks, properties = signal.find_peaks(vx, prominence=1, width=20)
# plt.plot(peaks, vx[peaks], "x")
fig.tight_layout()
plt.draw()
plt.grid(True)
plt.pause(0.001)
x = raw_input("Press [enter] to continue.")
if x == 'q': break
def check1(inRoot, chRange=None, nEvt=None, oTag='_tt'):
'''Use various filters to extract the results'''
if os.path.exists(inRoot.rstrip('.root') + oTag + '.root'):
print "has:", inRoot
return
# print inRoot
# return
sp1 = SignalProcessor()
sp1.nSamples = 16384
sp1.nAdcCh = 20
freq = 1000
n1 = int(1 / (0.2 * freq * 0.000001))
sp1.sRanges.clear()
ip = 0
dn = 2500 % n1 ## 2500 is the expected position of the signal
while ip + dn < sp1.nSamples:
sp1.sRanges.push_back((ip, min(ip + n1, sp1.nSamples)))
ip += n1
data1 = array('f', [0] * (sp1.nSamples * sp1.nAdcCh))
fin1 = TFile(inRoot, 'read')
tree1 = fin1.Get('tree1')
tree1.SetBranchAddress('adc', data1)
if nEvt is None: nEvt = tree1.GetEntries()
if chRange is None: chRange = range(sp1.nAdcCh)
fout1 = TFile(inRoot.rstrip('.root') + oTag + '.root', 'recreate')
tup1 = TNtuple('tup1', "filter analysis tuple",
'evt:fR:fW:ich:b:bE:im:idx:A')
### start processing
INTV = 1000 if nEvt > 10000 else max(nEvt / 10, 1)
for ievt in range(nEvt):
tree1.GetEntry(ievt)
if ievt % INTV == 0: print ievt, ' events processed'
for R in range(50, 300, 50):
for W in range(50, 600, 50):
sp1.fltParam.clear()
for x in [500, R, W, -1.]:
sp1.fltParam.push_back(x)
sp1.measure_pulse(data1)
for ich in chRange:
itmp = sp1.nMeasParam * ich
for j in range(sp1.nMeasParam / 2 - 1):
tup1.Fill(ievt, R, W, ich, sp1.measParam[itmp],
sp1.measParam[itmp + 1], j,
sp1.measParam[itmp + 2 * j + 2],
sp1.measParam[itmp + 2 * j + 3])
tup1.Write()
### save the ENC results
tup2 = TNtuple('tup2', "filter analysis tuple enc",
'ich:fR:fW:m:mE:sigma:sigmaE:fq:fStatus')
for R in range(50, 300, 50):
for W in range(50, 600, 50):
for ich in chRange:
gDirectory.Delete('h1*')
tup1.Draw(
'A>>h1',
'int(fW)=={0:d}&&int(fR)=={1:d}&&ich=={2:d}'.format(
W, R, ich), 'goff')
h1 = gDirectory.Get('h1')
r = h1.Fit('gaus', 'S0')
fun1 = h1.GetFunction('gaus')
tup2.Fill(ich, R, W, fun1.GetParameter(1), fun1.GetParError(1),
fun1.GetParameter(2), fun1.GetParError(2), r.Prob(),
r.Status())
tup2.Write()
fout1.Close()