def getLongestPathNodes(areatree):
# requires ini.trakem2.display.Tree.MeasurePathDistance
root = areatree.getRoot()
endNodes = set([nd for nd in areatree.getEndNodes()])
branchNodes = set([nd for nd in areatree.getBranchNodes()])
if 2 == root.getChildrenCount():
branchNodes.discard(root)
# case 0. root is the only node
if 0 == root.getChildrenCount():
print 'root singleton'
return
# case 1. else
else:
# get longest path from each 'lobe'
ndVsLen = {}
ndVsLen[root] = 0.0 # compatibility when root children count is 1
for loberoot in root.getChildrenNodes():
lbEndNodes = [nd for nd in loberoot.getEndNodes()]
lbBranchNodes = [nd for nd in loberoot.getBranchNodes()]
lbMaxLen = 0.0
lbMaxPM = None
lbMaxNd = lbEndNodes[0]
for nd in lbEndNodes:
pm = MeasurePathDistance(areatree, nd, root)
if lbMaxLen <= pm.getDistance():
lbMaxLen = pm.getDistance()
lbMaxPM = pm
lbMaxNd = nd
ndVsLen[lbMaxNd] = lbMaxLen
# print 'lobe max', nd, lbMaxLen
longestNodes = sorted(ndVsLen, key=ndVsLen.get, reverse=True)
nda = longestNodes[0]
ndb = longestNodes[1]
if nda.getLayer().getParent().indexOf(nd.getLayer()) >= ndb.getLayer().getParent().indexOf(nd.getLayer()):
ndtop = nda
ndbottom = ndb
else:
ndtop = ndb
ndbottom =nda
return [ndtop, ndbottom]
for areatree in areatrees:
areatree = areatree.getObject()
layerset = areatree.getLayerSet()
calibration = layerset.getCalibration()
affine = areatree.getAffineTransform()
print areatree
root = areatree.getRoot()
endNodes = set([nd for nd in areatree.getEndNodes()])
branchNodes = set([nd for nd in areatree.getBranchNodes()])
if 2 == root.getChildrenCount():
branchNodes.discard(root)
cutNodes = getCutNodes(areatree)
dt = getTreeDistanceTable(areatree)
topnd, bottomnd = getLongestPathNodes(areatree)
mnds = set(MeasurePathDistance(areatree, topnd, bottomnd).getPath())
connectedTrees = findConnectedTree(areatree)
inputs = connectedTrees['inputs']
outputs = connectedTrees['outputs']
# output tree connections
dtext = {'inputs':'input', 'outputs':'output'}
for d, cn in connectedTrees.iteritems():
# d for direction, cn for connection dict
for nd, targets in cn.iteritems():
for tree in targets:
neuriteConnection.append([neurite.getParent().getTitle(), neurite.getTitle(), areatree.getId(), dtext[d], tree.getId(), treeVsNeurite[tree].getTitle(), treeVsNeurite[tree].getParent().getTitle()])
markings = markTreeSegment(areatree)
for i, nds in markings.iteritems():
# case 0. root is the only node
if 0 == root.getChildrenCount():
print 'root singleton'
else:
# get longest path from each half
ndVsLen = {}
ndVsLen[root] = 0.0 # compatibility when root children count is 1
for loberoot in root.getChildrenNodes():
lbEndNodes = [nd for nd in loberoot.getEndNodes()]
lbBranchNodes = [nd for nd in loberoot.getBranchNodes()]
lbMaxLen = 0.0
lbMaxPM = None
lbMaxNd = lbEndNodes[0]
for nd in lbEndNodes:
pm = MeasurePathDistance(areatree, nd, root)
if lbMaxLen <= pm.getDistance():
lbMaxLen = pm.getDistance()
lbMaxPM = pm
lbMaxNd = nd
ndVsLen[lbMaxNd] = lbMaxLen
# print 'lobe max', nd, lbMaxLen
longestNodes = sorted(ndVsLen, key=ndVsLen.get, reverse=True)
nda = longestNodes[0]
ndb = longestNodes[1]
if nda.getLayer().getParent().indexOf(
nd.getLayer()) >= ndb.getLayer().getParent().indexOf(
nd.getLayer()):
ndtop = nda
ndbottom = ndb
else:
layerset = areatree.getLayerSet()
calibration = layerset.getCalibration()
affine = areatree.getAffineTransform()
# for calculating subtree length
dt = getTreeDistanceTable(areatree)
print areatree
root = areatree.getRoot()
endNodes = set([nd for nd in areatree.getEndNodes()])
branchNodes = set([nd for nd in areatree.getBranchNodes()])
if 2 == root.getChildrenCount():
branchNodes.discard(root)
# finding the primary 'stem'
topnd, bottomnd = getLongestPathNodes(areatree)
mnds = set(MeasurePathDistance(areatree, topnd, bottomnd).getPath())
synapses = findConnectorsInTree(areatree)
inputs = synapses['incoming']
outputs = synapses['outgoing']
for direction, ndVsConnector in synapses.iteritems():
print direction, ndVsConnector.values()
cutNodes = set(ndVsConnector.keys())
if not cutNodes:
continue
markings = markTreeSegment(areatree, cutNodes)
for i, nds in markings.iteritems():
# for each segment
length = sum([d for nd, d in dt.iteritems() if nd in nds])
mainSegNds = nds.intersection(mnds)
for nd, connectors in inputs.iteritems():
for c in connectors:
p = [
c.getId(),
neurite.getParent().getTitle(),
neurite.getTitle(),
areatree.getId(),
nd.getId(), 'incoming'
]
connectorProfile.append(p)
# calculate distance for each input
for nd in ndIn:
ds = []
for tnd in ndOut:
# from output
d = MeasurePathDistance(areatree, nd, tnd).getDistance()
nodeData = [
neurite.getParent().getTitle(),
neurite.getTitle(),
areatree.getId(),
nd.getId(), 'incoming', 'outgoing', d
]
foundNeuriteNodes.append(nodeData)
# for min
ds.append(d)
# for connectors with id
for toCt in inputs[nd]:
for fromCt in outputs[tnd]:
connectorData = [
neurite.getParent().getTitle(),
neurite.getTitle(),
# case 0. root is the only node
if 0 == root.getChildrenCount():
print 'root singleton'
else:
# get longest path from each half
ndVsLen = {}
ndVsLen[root] = 0.0 # compatibility when root children count is 1
for loberoot in root.getChildrenNodes():
lbEndNodes = [nd for nd in loberoot.getEndNodes()]
lbBranchNodes = [nd for nd in loberoot.getBranchNodes()]
lbMaxLen = 0.0
lbMaxPM = None
lbMaxNd = lbEndNodes[0]
for nd in lbEndNodes:
pm = MeasurePathDistance(areatree, nd, root)
if lbMaxLen <= pm.getDistance():
lbMaxLen = pm.getDistance()
lbMaxPM = pm
lbMaxNd = nd
ndVsLen[lbMaxNd] = lbMaxLen
# print 'lobe max', nd, lbMaxLen
longestNodes = sorted(ndVsLen, key=ndVsLen.get, reverse=True)
nda = longestNodes[0]
ndb = longestNodes[1]
if nda.getLayer().getParent().indexOf(nd.getLayer()) >= ndb.getLayer().getParent().indexOf(nd.getLayer()):
ndtop = nda
ndbottom = ndb
else:
ndtop = ndb
ndbottom =nda
if 'input_' in tag.toString():
posN = tag.toString().find('_')
nInputs = int(tag.toString()[posN + 1:])
ndIn.append(nd)
ndIn = set(ndIn)
ndOut = set(ndOut)
if 0 == len(ndIn) or 0 == len(ndOut):
continue
# calculate shortest distance for each input
ndInDistance = {}
for nd in ndIn:
d = []
for tnd in ndOut:
d.append(MeasurePathDistance(areatree, nd, tnd).getDistance())
ndInDistance[nd] = min(d)
# calculate shortest distance for each out
ndOutDistance = {}
for nd in ndOut:
d = []
for tnd in ndIn:
d.append(MeasurePathDistance(areatree, nd, tnd).getDistance())
ndOutDistance[nd] = min(d)
# input synapses
for nd, d in ndInDistance.iteritems():
# get node coordinates, from tut on web
fp = array([nd.getX(), nd.getY()], 'f')
affine.transform(fp, 0, fp, 0, 1)
