def load_coincidences_from_events(self):
for (path, dirs, files) in os.walk(self.ldesrcdir):
for fn in files:
if self.fnpattern in fn and fn[0] != "." and fn[-4:] == ".npz":
print os.path.join(path, fn)
d = np.load(os.path.join(path, fn))
data = d["hhdata"]
d.close()
data = hht3.filter_timewindow(data, 0, mintime=0, maxtime=2400)
data = hht3.filter_timewindow(data, 1, mintime=0, maxtime=2400)
d, c = tpqi.coincidence_times(data, self.deltas)
self.coincidences = tpqi.add_coincidence_times(self.coincidences, c)
def get_double_clicks(data,ch0_start=0, ch0_stop=700,
ch1_start=0, ch1_stop=700):
clicks=hht3.get_allclicks(data)
clicks=hht3.filter_timewindow(clicks,0,ch0_start,ch0_stop)
clicks=hht3.filter_timewindow(clicks,1,ch1_start,ch1_stop)
clicks=np.vstack((clicks,np.zeros(4,dtype=np.uint32)))
clicks=np.vstack((np.zeros(4,dtype=np.uint32),clicks))
delta_marker=clicks[1:,0]-clicks[:-1,0]
double_click_idx=np.ravel(np.where(delta_marker==1))
triple_click_idx=np.ravel(np.where(delta_marker==0))
bad_idx=np.append(triple_click_idx,\
[triple_click_idx-np.ones(len(triple_click_idx),dtype=np.uint),\
triple_click_idx+np.ones(len(triple_click_idx),dtype=np.uint)])
valid_double_click_idx=np.setdiff1d(double_click_idx,bad_idx)
valid_double_click_idx=np.sort(np.append(valid_double_click_idx,valid_double_click_idx+np.ones(len(valid_double_click_idx),dtype=np.uint)))
return clicks[valid_double_click_idx]
def get_double_clicks(data,ch0_start=0, ch0_stop=700,
ch1_start=0, ch1_stop=700):
clicks=hht3.get_allclicks(data)
clicks=hht3.filter_timewindow(clicks,0,ch0_start,ch0_stop)
clicks=hht3.filter_timewindow(clicks,1,ch1_start,ch1_stop)
clicks=np.vstack((clicks,np.zeros(4,dtype=np.uint32)))
clicks=np.vstack((np.zeros(4,dtype=np.uint32),clicks))
delta_marker=clicks[1:,0]-clicks[:-1,0]
double_click_idx=np.ravel(np.where(delta_marker==1))
triple_click_idx=np.ravel(np.where(delta_marker==0))
bad_idx=np.append(triple_click_idx,\
[triple_click_idx-np.ones(len(triple_click_idx),dtype=np.uint),\
triple_click_idx+np.ones(len(triple_click_idx),dtype=np.uint)])
valid_double_click_idx=np.setdiff1d(double_click_idx,bad_idx)
valid_double_click_idx=np.sort(np.append(valid_double_click_idx,valid_double_click_idx+np.ones(len(valid_double_click_idx),dtype=np.uint)))
return clicks[valid_double_click_idx]
def get_double_clicks_slow(hhdata, ch0_start=0, ch0_stop=700,
ch1_start=0, ch1_stop=700):
noof_double = 0
double_clicks = np.zeros(4,dtype=np.uint32)
hhdata=hht3.get_allclicks(hhdata)
hhdata=hht3.filter_timewindow(hhdata,0,ch0_start,ch0_stop)
hhdata=hht3.filter_timewindow(hhdata,1,ch1_start,ch1_stop)
for i in np.arange(len(hhdata)):
try:
if (hhdata[i,0]+1==(hhdata[i+1,0])):
if (len(hhdata[np.where(hhdata[:,0]==hhdata[i,0])])==1 and\
len(hhdata[np.where(hhdata[:,0]==hhdata[i+1,0])])==1):
double_clicks=np.vstack((double_clicks,hhdata[i]))
double_clicks=np.vstack((double_clicks,hhdata[i+1]))
except IndexError:
pass
if (len(np.shape(double_clicks))>1):
double_clicks=double_clicks[1:]
return double_clicks
def get_double_clicks_slow(hhdata, ch0_start=0, ch0_stop=700,
ch1_start=0, ch1_stop=700):
noof_double = 0
double_clicks = np.zeros(4,dtype=np.uint32)
hhdata=hht3.get_allclicks(hhdata)
hhdata=hht3.filter_timewindow(hhdata,0,ch0_start,ch0_stop)
hhdata=hht3.filter_timewindow(hhdata,1,ch1_start,ch1_stop)
for i in np.arange(len(hhdata)):
try:
if (hhdata[i,0]+1==(hhdata[i+1,0])):
if (len(hhdata[np.where(hhdata[:,0]==hhdata[i,0])])==1 and\
len(hhdata[np.where(hhdata[:,0]==hhdata[i+1,0])])==1):
double_clicks=np.vstack((double_clicks,hhdata[i]))
double_clicks=np.vstack((double_clicks,hhdata[i+1]))
except IndexError:
pass
if (len(np.shape(double_clicks))>1):
double_clicks=double_clicks[1:]
return double_clicks
def load_coincidences_from_events(self):
for (path,dirs,files) in os.walk(self.ldesrcdir):
for fn in files:
if self.fnpattern in fn and fn[0] != '.' and fn[-4:] == '.npz':
print os.path.join(path,fn)
d = np.load(os.path.join(path, fn))
data = d['hhdata']
d.close()
data = hht3.filter_timewindow(data, 0,
mintime=0,
maxtime=2400)
data = hht3.filter_timewindow(data, 1,
mintime=0,
maxtime=2400)
d,c = tpqi.coincidence_times(data, self.deltas)
self.coincidences = tpqi.add_coincidence_times(
self.coincidences, c)
def coincidences_from_folder(path, ch0window=(0,500), ch1window=(0,500), *arg, **kw):
npzfiles = [ f for f in os.listdir(os.path.join(workingpath, path)) \
if ( os.path.splitext(f)[1] == '.npz' and 'alldata' in f and f[:1] != '.') ]
sync_range = kw.pop('sync_range', range(1, 301))
ret = kw.pop('ret', True)
totalhist=np.array([0,0], dtype=np.uint32)
#totalhist = np.array([], dtype=int)
for i,f in enumerate(npzfiles):
print ''
print 'file', f
# brute force for now: ignore the first file of each measurement.
# if os.path.splitext(f)[0][-3:] == '-0':
# print 'IGNORED; FIND BETTER WAY...'
# continue
base = path
d = np.load(os.path.join(workingpath, path, f))
raw = d['data'].astype(np.uint)
d.close()
data = hht3.decode(raw)
data, ofls = hht3.filter_overflows(data)
# print 'filter on timewindow'
data = hht3.filter_timewindow(data, 0, mintime=ch0window[0], maxtime=ch0window[1])
data = hht3.filter_timewindow(data, 1, mintime=ch1window[0], maxtime=ch1window[1])
if len(data) == 0:
continue
data = hht3.filter_decreasing_syncs(data)
if len(data) == 0:
continue
# print 'filter counts on markers'
data = filter_markers(data, sync_range=sync_range)
if len(data) == 0:
continue
t0, t1 = hht3.get_clicks(data)
# print 'extract coincidences'
#deltas, c = coincidences(data, *arg, **kw)
#print '* Coincidences for %s:' % f, [ len(_c) for _c in c ]
#print ''
totalhist= totalhist+np.array([len(t0),len(t1)])
print totalhist
#totalhist = add_coincidences(totalhist, c)
p = os.path.join(workingpath, '%s_coincidences_syncs_%d-%d_ch0_%d-%d_ch1_%d-%d' % \
(base, sync_range[0], sync_range[-1], ch0window[0], ch0window[1], ch1window[0], ch1window[1]))
np.savez(p, deltas=deltas, coincidences=totalhist)
plot_g2(deltas, totalhist, savepath=p+'.png',
title='%s; windows: %d-%d, %d-%d; syncs: %d-%d' % (path,
ch0window[0], ch0window[1], ch1window[0], ch1window[1], sync_range[0], sync_range[-1]))
if ret:
return deltas, totalhist
def coincidences_from_folder(path, ch0window=(0,500), ch1window=(0,500), *arg, **kw):
npzfiles = [ f for f in os.listdir(os.path.join(workingpath, path)) \
if ( os.path.splitext(f)[1] == '.npz' and 'alldata' in f and f[:1] != '.') ]
sync_range = kw.pop('sync_range', range(1, 301))
ret = kw.pop('ret', True)
totalhist=np.array([0,0], dtype=np.uint32)
#totalhist = np.array([], dtype=int)
for i,f in enumerate(npzfiles):
print ''
print 'file', f
# brute force for now: ignore the first file of each measurement.
# if os.path.splitext(f)[0][-3:] == '-0':
# print 'IGNORED; FIND BETTER WAY...'
# continue
base = path
d = np.load(os.path.join(workingpath, path, f))
raw = d['data'].astype(np.uint)
d.close()
data = hht3.decode(raw)
data, ofls = hht3.filter_overflows(data)
# print 'filter on timewindow'
data = hht3.filter_timewindow(data, 0, mintime=ch0window[0], maxtime=ch0window[1])
data = hht3.filter_timewindow(data, 1, mintime=ch1window[0], maxtime=ch1window[1])
if len(data) == 0:
continue
data = hht3.filter_decreasing_syncs(data)
if len(data) == 0:
continue
# print 'filter counts on markers'
data = filter_markers(data, sync_range=sync_range)
if len(data) == 0:
continue
t0, t1 = hht3.get_clicks(data)
# print 'extract coincidences'
#deltas, c = coincidences(data, *arg, **kw)
#print '* Coincidences for %s:' % f, [ len(_c) for _c in c ]
#print ''
totalhist= totalhist+np.array([len(t0),len(t1)])
print totalhist
#totalhist = add_coincidences(totalhist, c)
p = os.path.join(workingpath, '%s_coincidences_syncs_%d-%d_ch0_%d-%d_ch1_%d-%d' % \
(base, sync_range[0], sync_range[-1], ch0window[0], ch0window[1], ch1window[0], ch1window[1]))
np.savez(p, deltas=deltas, coincidences=totalhist)
plot_g2(deltas, totalhist, savepath=p+'.png',
title='%s; windows: %d-%d, %d-%d; syncs: %d-%d' % (path,
ch0window[0], ch0window[1], ch1window[0], ch1window[1], sync_range[0], sync_range[-1]))
if ret:
return deltas, totalhist
