def rawFeatureVector(id2, id1, biniter):
if not id1 in iddict:
iddict[id1]=getDendriticProfiles(id1, biniter)
if not id2 in iddict:
iddict[id2]=getDendriticProfiles(id2, biniter)
histo1=iddict[id1]
histo2=iddict[id2]
xhisto1=histo1[0]
yhisto1=histo1[1]
zhisto1=histo1[2]
xhisto2=histo2[0]
yhisto2=histo2[1]
zhisto2=histo2[2]
#Calculation of sum of distances in bin is now included in
#getDendriticProfiles function to reduce runtime
xsumDist1 = histo1[3]
ysumDist1 = histo1[4]
zsumDist1 = histo1[5]
xsumDist2 = histo2[3]
ysumDist2 = histo2[4]
zsumDist2 = histo2[5]
rawVector = xhisto1 + xhisto2 + yhisto1 + yhisto2 + zhisto1 + zhisto2 + xsumDist1 +xsumDist2 + ysumDist1 + ysumDist2 + zsumDist1 + zsumDist2
return rawVector
def featureVector(id1, id2, biniter):
if not id1 in iddict:
iddict[id1]=getDendriticProfiles(id1, biniter)
if not id2 in iddict:
iddict[id2]=getDendriticProfiles(id2, biniter)
histo1=iddict[id1]
histo2=iddict[id2]
trainingvector =feature1(histo1,histo2, biniter) + feature2(histo1, histo2, biniter) + feature3(histo1, histo2, biniter) + feature4(histo1, histo2, biniter)
return trainingvector
def profileDistances(ID, biniter):
histo=getDendriticProfiles(ID, biniter)
xhisto=histo[0]
yhisto=histo[1]
zhisto=histo[2]
xdistance=[]
ydistance=[]
zdistance=[]
tree = Display.getFront().getLayerSet().findById(ID)
coords = Matrix(getNodeCoordinates(tree))
m=coords.getRowDimension()
for i in range(0, m):
xdist = coords.get(i, 1 )
if xdist > 0 :
xdistance.append(xdist)
else:
xdistance.append((-1)*xdist)
for i in range(0, m):
ydist = coords.get(i, 0 )
if ydist > 0 :
ydistance.append(ydist)
else:
ydistance.append((-1)*ydist)
for i in range(0, m):
zdist = sqrt(coords.get(i, 0)**2 + coords.get(i,1)**2)
zdistance.append(zdist)
return xdistance, ydistance, zdistance
def rawHistogramVector(id1, id2, biniter):
if not id1 in iddict:
iddict[id1]=getDendriticProfiles(id1, biniter)
if not id2 in iddict:
iddict[id2]=getDendriticProfiles(id2, biniter)
histo1=iddict[id1]
histo2=iddict[id2]
xhisto1=histo1[0]
yhisto1=histo1[1]
zhisto1=histo1[2]
xhisto2=histo2[0]
xhisto2=reversing(xhisto2)
yhisto2=histo2[1]
zhisto2=histo2[2]
trainingvector = []
trainingvector = xhisto1 + yhisto1 + zhisto1 + xhisto2 + yhisto2 + zhisto2
return trainingvector