'B': -1,
}
prob = {
'A': 0.,
'B': 0.,
}
allOffs = {}
OffsRaw = {}
print 'enter DB'
for rec in db.iteritems():
# Gambi pra verificar se o spike ja foi classificado
off, bindata = rec
read_data = recogdb.parseDBHeader(bindata)
offraw, direction, distA, distB, distAB, SaturationFlag, svm, pairsvm, prob[
'A'], prob['B'], fishwins = recogdb.fishrec(rec)
off = offraw / 4 / NumChannels
for PIdx in fishwins.keys():
if PIdx == 'A':
f.write('%d %d\n' % (1, off + fishwins[PIdx][0]))
if PIdx == 'B':
f.write('%d %d\n' % (-1, off + fishwins[PIdx][0]))
f.flush()
'''correctedPosA = read_data[ recogdb.dicFields['correctedPosA'] ]
correctedPosB = read_data[ recogdb.dicFields['correctedPosB'] ]
if (correctedPosA != -1) and (correctedPosB != -1):
f.write( '%d\t%d\n'%(1, correctedPosA) )
f.write( '%d\t%d\n'%(-1, correctedPosB) )
continue
import scipy.signal as sig
NumChannels = 7
db = bsddb3.btopen(sys.argv[1], 'r')
winfile = open(sys.argv[2], 'rb')
checkfish = sys.argv[3]
checkfile = open(sys.argv[4], 'rb')
threshold = float(sys.argv[5])
assert (checkfish in ('A', 'B'))
filt = sig.firwin(100, .1)
for rec in db.iteritems():
off, distA, distB, distAB, fishwins = recogdb.fishrec(rec)
wlastlen, = struct.unpack('i', winfile.read(4))
woff, wsamples, wchannels = struct.unpack('qii', winfile.read(8 + 4 * 2))
winfile.seek(wchannels * (4 + wsamples * 4), 1)
assert (off == woff)
checkoff = off / NumChannels
checkfile.seek(checkoff)
buf = np.frombuffer(checkfile.read(wsamples * 4), dtype=np.float32)
buf = np.convolve(filt, buf)
fishexists = 1 if abs(buf).max() >= threshold else 0
fishdetected = 1 if checkfish in fishwins else 0
if fishexists ^ fishdetected == 1:
}
flag = { 'A': 1,
'B': -1,
}
prob = { 'A': 0.,
'B': 0.,
}
allOffs = {}
OffsRaw = {}
print 'enter DB'
for rec in db.iteritems():
# Gambi pra verificar se o spike ja foi classificado
off, bindata = rec
read_data = recogdb.parseDBHeader(bindata)
offraw, direction, distA, distB, distAB, SaturationFlag, svm, pairsvm, prob['A'], prob['B'], fishwins = recogdb.fishrec(rec)
off = offraw/4/NumChannels
for PIdx in fishwins.keys():
if PIdx == 'A':
f.write('%d %d\n'%(1, off + fishwins[PIdx][0]))
if PIdx == 'B':
f.write('%d %d\n'%(-1, off + fishwins[PIdx][0]))
f.flush()
'''correctedPosA = read_data[ recogdb.dicFields['correctedPosA'] ]
correctedPosB = read_data[ recogdb.dicFields['correctedPosB'] ]
if (correctedPosA != -1) and (correctedPosB != -1):
f.write( '%d\t%d\n'%(1, correctedPosA) )
f.write( '%d\t%d\n'%(-1, correctedPosB) )
NumChannels = 11
db = bsddb3.btopen(sys.argv[1], 'r')
searchoff = np.inf
if len(sys.argv) >= 3:
searchoff = int(sys.argv[2])
A = [list([]) for i in xrange(NumChannels)]
B = [list([]) for i in xrange(NumChannels)]
mark = None
for rec in db.iteritems():
off, distA, distB, distAB, fishwins = recogdb.fishrec(rec)
if mark == None and off >= searchoff:
print(repr(('mark', off, distA, distB, distAB)))
mark = sum(map(len,A[0]))
dataA = fishwins['A'][1] if 'A' in fishwins else np.zeros((NumChannels,0))
dataB = fishwins['B'][1] if 'B' in fishwins else np.zeros((NumChannels,0))
arrsz = max(dataA.shape[1], dataB.shape[1]) + 2
apszA = arrsz - dataA.shape[1]
apszB = arrsz - dataB.shape[1]
dataA = np.concatenate((dataA, np.nan*np.ones((NumChannels,apszA))),1)
dataB = np.concatenate((dataB, np.nan*np.ones((NumChannels,apszB))),1)
for i in xrange(NumChannels):
A[i].append(dataA[i,:])
B[i].append(dataB[i,:])
A = map(np.concatenate, A)
