def setChannelInvisible(project,channel): layerset = project.getRootLayerSet() layers = layerset.getLayers() for l,layer in enumerate(layers): patches = layer.getDisplayables(Patch) for patch in patches: patchName = nameFromPath(patch.getImageFilePath()) if patchName[0:len(channel)] == channel: patch.setVisible(False, True) Display.getFront().updateVisibleTabs()
def toggleChannel(project,channel):
layerset = project.getRootLayerSet()
layers = layerset.getLayers()
for l,layer in enumerate(layers):
patches = layer.getDisplayables(Patch)
for patch in patches:
# IJ.log('thepatch' + str(patch))
patchName = nameFromPath(patch.getImageFilePath())
# IJ.log(str(patchName[0:len(channel)]) + '=' + str(channel) + ' value' + str(patchName[0:len(channel)] == channel) )
if patchName[0:len(channel)] == channel:
# IJ.log(str(patch) + ' toggled')
patch.setVisible((not patch.visible), True)
Display.getFront().updateVisibleTabs()
def setChannelVisible(project,channel):
layerset = project.getRootLayerSet()
layers = layerset.getLayers()
for l,layer in enumerate(layers):
patches = layer.getDisplayables(Patch)
for patch in patches:
patchName = nameFromPath(patch.getImageFilePath())
if patchName[0:len(channel)] == channel:
patch.setVisible(True, True)
# else:
# patch.setVisible(False, True)
try:
Display.getFront().updateVisibleTabs()
except Exception, e:
IJ.log('Did not succeed in updating the visible tabs')
pass
def exportSegmentation(evt=None):
display = Display.getFront()
canvas = display.getCanvas()
numLayer = display.getLayerSet().size();
exportMask(evt)
files = []
for l in display.getLayerSet().getLayers():
for p in l.getDisplayables(Patch):
files.append(p.getFilePath())
# Create virtual stack 'vs'
vs = None
for f in files:
# if first image...
if vs is None:
imp = IJ.openImage(f)
vs = VirtualStack(imp.width, imp.height, None, "/")
vs.addSlice(f)
ImagePlus("VSeg", vs).show()
IJ.run("Duplicate...", "title=Segmentation duplicate range=1-30");
WindowManager.getImage("VSeg").close()
ic = ImageCalculator()
ic.run("Multiply stack", WindowManager.getImage("Segmentation"), WindowManager.getImage("Labels"));
WindowManager.getImage("Labels").close()
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 getTheTag(tagString):
# find one tag with tagString
areatrees = Display.getFront().getLayerSet().getZDisplayables(AreaTree)
connectors = Display.getFront().getLayerSet().getZDisplayables(Connector)
for tree in itertools.chain(areatrees, connectors):
root = tree.getRoot()
if root is None:
break
for node in root.getSubtreeNodes():
tags = node.getTags()
if tags is None:
continue
for tag in tags:
if tagString in tag.toString():
return tag
return None
def getBranches(tree):
tree = Display.getFront().getLayerSet().findById(tree)
""" Return a list of remaining branch vertices and lists of lists of Point3f, each inner list representing a branch with Point3d. """
m = tree.asVertices() # map of Node keys vs. Vertex values
steps = Centrality.branchWise(m.values(), 2)
branches = []
for step in steps:
s = []
for branch in step.branches:
nds = [vertex.data for vertex in branch]
b = []
for nd in asSequence(nds):
# transfrom nd to Point3d
calibration = tree.getLayerSet().getCalibration()
affine = tree.getAffineTransform()
fp = array([nd.getX(), nd.getY()], 'f')
affine.transform(fp, 0, fp, 0, 1)
x = fp[0] * calibration.pixelWidth
y = fp[1] * calibration.pixelHeight
z = nd.getLayer().getZ() * calibration.pixelWidth
tfm = correct([x, y, z])
p = Point3d(tfm[0], tfm[1], tfm[2]) #and transform in new coordinates
b.append(p)
s.append(b)
branches.append([step.remaining_branch_vertices, s])
return branches
def getTheTag(tagString):
# find one tag with tagString
areatrees = Display.getFront().getLayerSet().getZDisplayables(AreaTree)
connectors = Display.getFront().getLayerSet().getZDisplayables(Connector)
for tree in itertools.chain(areatrees, connectors):
root = tree.getRoot()
if root is None:
break
for node in root.getSubtreeNodes():
tags = node.getTags()
if tags is None:
continue
for tag in tags:
if tagString in tag.toString():
return tag
return None
def extract_stack_under_arealist():
# Check that a Display is open
display = Display.getFront()
if display is None:
IJ.log("Open a TrakEM2 Display first!")
return
# Check that an AreaList is selected and active:
ali = display.getActive()
if ali is None or not isinstance(ali, AreaList):
IJ.log("Please select an AreaList first!")
return
# Get the range of layers to which ali paints:
ls = display.getLayerSet()
ifirst = ls.indexOf(ali.getFirstLayer())
ilast = ls.indexOf(ali.getLastLayer())
layers = display.getLayerSet().getLayers().subList(ifirst, ilast + 1)
# Create a stack with the dimensions of ali
bounds = ali.getBoundingBox()
stack = ImageStack(bounds.width, bounds.height)
# Using 16-bit. To change to 8-bit, use GRAY8 and ByteProcessor in the two lines below:
type = ImagePlus.GRAY16
ref_ip = ShortProcessor(bounds.width, bounds.height)
for layer in layers:
area = ali.getArea(layer)
z = layer.getZ()
ip = ref_ip.createProcessor(bounds.width, bounds.height)
if area is None:
stack.addSlice(str(z), bp)
continue
# Create a ROI from the area of ali at layer:
aff = ali.getAffineTransformCopy()
aff.translate(-bounds.x, -bounds.y)
roi = ShapeRoi(area.createTransformedArea(aff))
# Create a cropped snapshot of the images at layer under ali:
flat = Patch.makeFlatImage(type, layer, bounds, 1.0,
layer.getDisplayables(Patch), Color.black)
b = roi.getBounds()
flat.setRoi(roi)
ip.insert(flat.crop(), b.x, b.y)
# Clear the outside of ROI (ShapeRoi is a non-rectangular ROI type)
bimp = ImagePlus("", ip)
bimp.setRoi(roi)
ip.setValue(0)
ip.setBackgroundValue(0)
IJ.run(bimp, "Clear Outside", "")
# Accumulate slices
stack.addSlice(str(z), ip)
imp = ImagePlus("AreaList stack", stack)
imp.setCalibration(ls.getCalibrationCopy())
imp.show()
def extract_stack_under_arealist():
# Check that a Display is open
display = Display.getFront()
if display is None:
IJ.log("Open a TrakEM2 Display first!")
return
# Check that an AreaList is selected and active:
ali = display.getActive()
if ali is None or not isinstance(ali, AreaList):
IJ.log("Please select an AreaList first!")
return
# Get the range of layers to which ali paints:
ls = display.getLayerSet()
ifirst = ls.indexOf(ali.getFirstLayer())
ilast = ls.indexOf(ali.getLastLayer())
layers = display.getLayerSet().getLayers().subList(ifirst, ilast +1)
# Create a stack with the dimensions of ali
bounds = ali.getBoundingBox()
stack = ImageStack(bounds.width, bounds.height)
# Using 16-bit. To change to 8-bit, use GRAY8 and ByteProcessor in the two lines below:
type = ImagePlus.GRAY16
ref_ip = ShortProcessor(bounds.width, bounds.height)
for layer in layers:
area = ali.getArea(layer)
z = layer.getZ()
ip = ref_ip.createProcessor(bounds.width, bounds.height)
if area is None:
stack.addSlice(str(z), bp)
continue
# Create a ROI from the area of ali at layer:
aff = ali.getAffineTransformCopy()
aff.translate(-bounds.x, -bounds.y)
roi = ShapeRoi(area.createTransformedArea(aff))
# Create a cropped snapshot of the images at layer under ali:
flat = Patch.makeFlatImage(type, layer, bounds, 1.0, layer.getDisplayables(Patch), Color.black)
b = roi.getBounds()
flat.setRoi(roi)
ip.insert(flat.crop(), b.x, b.y)
# Clear the outside of ROI (ShapeRoi is a non-rectangular ROI type)
bimp = ImagePlus("", ip)
bimp.setRoi(roi)
ip.setValue(0)
ip.setBackgroundValue(0)
IJ.run(bimp, "Clear Outside", "")
# Accumulate slices
stack.addSlice(str(z), ip)
imp = ImagePlus("AreaList stack", stack)
imp.setCalibration(ls.getCalibrationCopy())
imp.show()
def run():
front = Display.getFront()
if front is None:
print "No displays open!"
return
sel = front.getSelection().getSelected(Profile)
if sel.isEmpty():
print "No profiles selected!"
return
svg = export(sel.get(0))
tw = TextWindow("Profile as SVG", svg, 500, 500)
GUI.center(tw)
def exportMask(evt=None):
display = Display.getFront()
arealists = display.getSelection().getSelected(AreaList)
canvas = display.getCanvas()
numLayer = display.getLayerSet().size();
if arealists.isEmpty():
IJ.log("No arealists selected -- I just take the FIRST ONE!!")
#IJ.showMessage("No arealists selected -- select one!")
zDispList = display.getLayerSet().getDisplayableList()
if len(zDispList) > 0:
arealists = zDispList
else:
IJ.log("Project does not contain any AreaLists!")
IJ.showMessage("Project does not contain any AreaLists!")
return
AreaList.exportAsLabels(arealists, canvas.getFakeImagePlus().getRoi(), 1.0, 0, numLayer-1, False, False, False);
def getNodes(tree):
"""Return a list of remaining vertices and lists of lists of all nodes representing a branch"""
tree = Display.getFront().getLayerSet().findById(tree)
m = tree.asVertices() # map of Node keys vs. Vertex values
steps = Centrality.branchWise(m.values(), 2)
branches = []
saveNodes = []
for step in steps:
for branch in step.branches:
b = []
branchNodes = []
for vertex in branch:
nd = vertex.data
branchNodes.append(nd)
saveNodes.append([step.remaining_branch_vertices, branchNodes])
return saveNodes
def openStack(evt=None):
display = Display.getFront()
canvas = display.getCanvas()
numLayer = display.getLayerSet().size();
files = []
for l in display.getLayerSet().getLayers():
for p in l.getDisplayables(Patch):
files.append(p.getFilePath())
# Create virtual stack 'vs'
vs = None
for f in files:
# if first image...
if vs is None:
imp = IJ.openImage(f)
vs = VirtualStack(imp.width, imp.height, None, "/")
vs.addSlice(f)
layerset = display.getLayerSet()
p = layerset.getProject()
ImagePlus("VSeg", vs).show()
IJ.run("Duplicate...", "title=" + p.getTitle() + " duplicate range=1-30");
WindowManager.getImage("VSeg").close()
return p.getTitle()
def importMask(evt=None):
display = Display.getFront()
# Obtain an image stack
#imp = IJ.getImage()
imp = WindowManager.getImage("Labels")
layerset = display.getLayerSet()
p = layerset.getProject()
ali = AreaList(p, "", 0, 0)
layerset.add(ali)
p.getProjectTree().insertSegmentations([ali])
# Obtain the image stack
stack = imp.getImageStack()
# Iterate every slice of the stack
for i in range(1, imp.getNSlices() + 1):
ip = stack.getProcessor(i) # 1-based
# Extract all areas (except background) into a map of value vs. java.awt.geom.Area
m = AreaUtils.extractAreas(ip)
# Report progress
if len(m) > 0:
IJ.log(str(i) + ":" + str(len(m)))
# Get the Layer instance at the corresponding index
layer = layerset.getLayers().get(i-1) # 0-based
# Add the first Area instance to the AreaList at the proper Layer
if ( m.values().iterator().hasNext() ):
ali.addArea(layer.getId(), m.values().iterator().next())
# Change the color of the AreaList
ali.setColor(Color.red)
ali.adjustProperties()
# Ensure bounds are as constrained as possible
ali.calculateBoundingBox(None)
# Repaint
Display.repaint()
# Create a snapshot of the images under the area:
imp = loader.getFlatImage(layer, box, 1, 0xffffffff,
ImagePlus.GRAY8, Patch, False)
# Set the area as a roi
imp.setRoi(ShapeRoi(area))
# Perform measurements (uncalibrated)
# (To get the calibration, call layerset.getCalibrationCopy())
stats = ByteStatistics(imp.getProcessor(), moptions,
calibration)
table.incrementCounter()
table.addLabel("Name", ali.getTitle())
table.addValue(0, ali.getId())
table.addValue(1, index) # the layer index
table.addValue(2, layer.getZ())
table.addValue(3, stats.area)
table.addValue(4, stats.mean)
# Update and show the table
table.show("AreaLists")
# Get the front display, if any:
display = Display.getFront()
if display is not None:
# Obtain the LayerSet of the current Display canvas:
layerset = Display.getFront().getLayer().getParent()
# Measure!
measureCustom(display.getFront().getLayer().getParent())
else:
IJ.showMessage("Open a TrakEM2 display first!")
def getDendriticProfiles(ID, biniter):
tree = Display.getFront().getLayerSet().findById(ID)
coords = Matrix(getNodeCoordinates(tree))
# Define axis vectors and origin
xnorm = Matrix([[1, 0, 0]])
ynorm = Matrix([[0, 1, 0]])
znorm = Matrix([[0, 0, 1]])
center = Matrix([[0, 0, 0]])
# Project nodes onto axis
dpx = []
dpy = []
dpz = []
m = coords.getRowDimension()
for i in range(0, m):
xstore = Matrix([coords.getRow(i)]) * xnorm.transpose()
ystore = Matrix([coords.getRow(i)]) * ynorm.transpose()
zstore = Matrix([coords.getRow(i)]) * znorm.transpose()
dpx.append(xstore.getRow(0))
dpy.append(ystore.getRow(0))
dpz.append(zstore.getRow(0))
# Count number of nodes which fall in defined interval of pca projection
xhistovector = []
yhistovector = []
zhistovector = []
# get it back in array form (get rid of list in list of Jarray)
dpx = [x[0] for x in dpx]
dpy = [x[0] for x in dpy]
dpz = [x[0] for x in dpz]
# Initialize interval size and fix iterations to a specific number
xbinleft = -34600.0
ybinleft = -24200.0
zbinleft = 0
# --------PARAMETER FOR MACHINE LEARNING-----
iterations = biniter
# -------------------------------------------
xlength = int((35600.0 + 34600.0) / iterations + 0.5)
ylength = int((21300.0 + 24200.0) / iterations + 0.5)
zlength = int((22500) / iterations + 0.5)
xbinright = xbinleft + xlength
ybinright = ybinleft + ylength
zbinright = zbinleft + zlength
# Count elements in bins
xaxis = []
# Count lengths in bins
xdist = []
ydist = []
zdist = []
for i in range(0, iterations):
counter = 0
xdiff = 0
for i in range(0, len(dpx)):
if dpx[i] <= xbinright and dpx[i] >= xbinleft:
counter += 1
xdiff += sqrt(dpy[i] ** 2 + dpz[i] ** 2) # sqrt(dpy[i]**2) xdist is yvalue
if counter != 0:
xdiff /= counter
xdist.append(xdiff)
xhistovector.append(counter)
xaxis.append(xbinleft)
xbinleft += xlength
xbinright += xlength
yaxis = []
for i in range(0, iterations):
counter = 0
ydiff = 0
for i in range(0, len(dpy)):
if dpy[i] <= ybinright and dpy[i] >= ybinleft:
counter += 1
ydiff += sqrt(dpx[i] ** 2 + dpz[i] ** 2)
if counter != 0:
ydiff /= counter
ydist.append(ydiff)
yhistovector.append(counter)
yaxis.append(ybinleft)
ybinleft += ylength
ybinright += ylength
zaxis = []
for i in range(0, iterations):
counter = 0
zdiff = 0
for i in range(0, len(dpz)):
if dpz[i] <= zbinright and dpz[i] >= zbinleft:
counter += 1
zdiff += sqrt(dpx[i] ** 2 + dpy[i] ** 2)
if counter != 0:
zdiff /= counter
zdist.append(zdiff)
zhistovector.append(counter)
zaxis.append(zbinleft)
zbinleft += zlength
zbinright += zlength
# print xdist
# print ydist
# print zdist
"""
#Normalize
for i in range(0, iterations):
xhistovector[i]/=float(xlength)
yhistovector[i]/=float(ylength)
zhistovector[i]/=float(zlength)
"""
return xhistovector, yhistovector, zhistovector, xdist, ydist, zdist
affines = {}
for line in fobj:
affineline = line.split()
affines[affineline[0]] = [affineline[1],affineline[2],affineline[3],affineline[4],affineline[5],affineline[6]]
fobj.close()
# ...
# ...
# Apply the affine to every Patch
from ini.trakem2.display import Display, Patch
from java.awt.geom import AffineTransform
for layer in Display.getFront().getLayerSet().getLayers():
for patch in layer.getDisplayables(Patch):
filepath = patch.getImageFilePath()
print ("filepath\n")
affine = affines.get(filepath, None) #filepath statt affines eingefuegt
if affine:
for index in range (0,6):
affine[index] = float(affine[index])
print ("affine[index]", index, affine[index])
patch.setAffineTransform(AffineTransform(affine[0], affine[1],affine[2], affine[3], (affine[4]), affine[5]))
else:
print "No affine for filepath:", filepath
print ("done\n")
# For output a list of tagged nodes in currently active TrakEM2 project
# Change output filename at the bottom
from ini.trakem2.display import AreaList, Display, AreaTree, Connector
import csv
header = ["type", "parentId", "nodeDegree", "layer", "x", "y", "z", "parentName", "shortMeaningfulTitle", "tag"]
foundtags = [header]
areatrees = Display.getFront().getLayerSet().getZDisplayables(AreaTree)
for areatree in areatrees:
root = areatree.getRoot()
if root is None:
continue
for node in root.getSubtreeNodes():
tags = node.getTags()
if tags is None:
continue
for tag in tags:
foundtags.append(
[
"areatrea",
areatree.getId(),
node.computeDegree(),
node.getLayer().getId(),
node.getX(),
node.getY(),
node.getLayer(),
areatree.getTitle(),
def pca(ID, biniter):
tree = Display.getFront().getLayerSet().findById(ID)
#Calculate the center of mass
center = Matrix( [[0,0,0]] )
coords = Matrix(getNodeCoordinates(tree))
m=coords.getRowDimension()
for i in range(0, coords.getRowDimension()):
center += Matrix([coords.getRow( i )])
center /= float(m)
#print center
"""
x, y, z = 0, 0, 0
nc = getNodeCoordinates(tree)
for c in nc:
x += c[0]
y += c[1]
z += c[2]
print "center:", x/len(nc), y/len(nc), z/len(nc)
"""
#Define covvariance matrix
cova = Matrix([[0,0,0],[0,0,0],[0,0,0]])
diff= Matrix ( [[0,0,0]])
for i in range(0, m):
diff = Matrix([coords.getRow( i )]) - center
cova += diff.transpose() * diff
cova /= float(m)
#Evaluedecomposition
evaluedecomp = cova.eig()
evalues = evaluedecomp.getRealEigenvalues()
evectors = evaluedecomp.getV() # is a Matrix instance
#Find maximum Eigenvector for maximal Eigenvalue
maxevaluepos = -1
maxevalue = 0
for i in range(0, len(evalues)):
if evalues[i] > maxevalue or maxevaluepos==-1:
maxevalue=evalues[i]
maxevaluepos=i
maxevector=evectors.getColumn(maxevaluepos) #HAVE TO GET VALUES OF COLUMN of evector matrix i NOT ROW
#--------------------TEST if Eigenvaluedecomposition is correct-----------
#vectormatrix=Matrix([evectors.getColumn(maxevaluepos)])
#test=cova * vectormatrix.transpose()
#test2=vectormatrix*maxevalue
#print test
#print test2
#-------------------------------------------------------------------------
#Define a vector over the point cloud and count points in defined interval
#Normalize vector
length=sqrt(maxevector[0]**2 + maxevector[1]**2 + maxevector[2]**2)
normvector = map(lambda x: x / length, maxevector)
normvectormatrix = Matrix([normvector])
pca=[]
m=coords.getRowDimension()
for i in range(0, m):
pcastore = (Matrix([coords.getRow( i )]) - center ) * normvectormatrix.transpose()
pca.append(pcastore.getRow(0))
#Count number of nodes which fall in defined interval of pca projection -> has to be fixed globally when to compare PCAs!
counter = 0
histovector = []
pca=[ x[0] for x in pca] #get it back in array form (get rid of list in list)
binleft = -12500 #binleft = min(pca)
iterations = biniter
length = int(25000/iterations + 0.5) #int((max(pca)-min(pca))/iterations + 0.5)
binright = binleft + length
for i in range(0,iterations):
for i in range(0, len(pca)):
if pca[i] <= binright and pca[i] >= binleft:
counter += 1
histovector.append(counter)
counter=0
binleft+=length
binright+=length
#print "The histogram vector is:", histovector
return histovector
# For output a list of tagged nodes in currently active TrakEM2 project
# Change output filename at the bottom
from ini.trakem2.display import AreaList, Display, AreaTree, Connector
import csv
header = [
'type', 'parentId', 'nodeDegree', 'layer', 'x', 'y', 'z', 'parentName',
'shortMeaningfulTitle', 'tag'
]
foundtags = [header]
areatrees = Display.getFront().getLayerSet().getZDisplayables(AreaTree)
for areatree in areatrees:
root = areatree.getRoot()
if root is None:
continue
for node in root.getSubtreeNodes():
tags = node.getTags()
if tags is None:
continue
for tag in tags:
foundtags.append([
'areatrea',
areatree.getId(),
node.computeDegree(),
node.getLayer().getId(),
node.getX(),
node.getY(),
elem = l[:-1].split(" ")
fname = elem[0]
xloc = int(elem[1])
yloc = int(elem[2])
zloc = int(elem[3])
z_list.append(zloc)
imp = IJ.openImage(os.path.join(img_dir, fname))
patch = Patch(project, imp.title, xloc, yloc, imp)
patch.project.loader.addedPatchFrom(os.path.join(img_dir, fname),
patch)
layer = layerset.getLayer(zloc, 1, True)
layer.add(patch)
f.close()
front = Display.getFront()
bounds = Rectangle(x=0, y=0, width=20000, height=20000)
front.resizeCanvas(bounds)
z_list.sort()
if z_list[0] != 0:
layer = layerset.getLayer(0, 1, False)
layer.remove(False)
# Save project
project.saveAs(os.path.join(proj_dir, "montage_v1.xml"), False)
front.close(project)
from ini.trakem2.display import Display, Treeline
from java.lang import Math
from jarray import array
def longJumps(t, mindist):
for nd in t.getRoot().getSubtreeNodes():
if nd.parent is None:
continue
d = Math.sqrt(Math.pow(nd.x - nd.parent.x, 2) + Math.pow(nd.y - nd.parent.y, 2))
if d > mindist:
print nd.x, nd.y
p = array([nd.x, nd.y], 'f')
aff = t.affineTransform
aff.transform(p, 0, p, 0, 1)
cal = t.layerSet.getCalibration()
print "Off:", p[0] * cal.pixelWidth, p[1] * cal.pixelHeight, (nd.layer.getParent().indexOf(nd.layer) + 1)
for t in Display.getFront().getLayerSet().getZDisplayables(Treeline):
print t
longJumps(t, 500)
def sumDist(id1, biniter):
distance=profileDistances(id1, biniter)
xdistance=distance[0]
ydistance=distance[1]
zdistance=distance[2]
tree = Display.getFront().getLayerSet().findById(id1)
coords = Matrix(getNodeCoordinates(tree))
m=coords.getRowDimension()
xdist=[]
ydist=[]
zdist=[]
#Initialize interval size and fix iterations to a specific coordinate position
xbinleft = -34600.0
ybinleft = -24200.0
zbinleft = 0
#----------PARAMETER FOR MACHINE LEARNING-----
iterations =biniter
#---------------------------------------------
xlength = int((35600.0+34600.0)/iterations + 0.5)
ylength = int((21300.0+24200.0)/iterations + 0.5)
zlength = int((22500)/iterations + 0.5)
xbinright = xbinleft + xlength
ybinright = ybinleft + ylength
zbinright = zbinleft + zlength
sumdist=0.0
for i in range(0, iterations):
for i in range(0, len(xdistance)):
if xdistance[i] <= xbinright and xdistance[i] >= xbinleft:
sumdist += xdistance[i]
xdist.append(sumdist)
sumdist=0.0
xbinleft += xlength
xbinright += xlength
for i in range(0, iterations):
for i in range(0, len(ydistance)):
if ydistance[i] <= ybinright and ydistance[i] >= ybinleft:
sumdist += ydistance[i]
ydist.append(sumdist)
sumdist=0.0
ybinleft += ylength
ybinright += ylength
for i in range(0, iterations):
for i in range(0, len(zdistance)):
if zdistance[i] <= zbinright and zdistance[i] >= zbinleft:
sumdist += zdistance[i]
zdist.append(sumdist)
sumdist=0.0
zbinleft += zlength
zbinright += zlength
sumdistance=[]
sumdistance= [xdist, ydist, zdist]
return sumdistance
from mpicbg.trakem2.transform import ExportUnsignedShort
from mpicbg.ij.util import Filter
from net.imglib2.img import ImagePlusAdapter
from net.imglib2.type.numeric.integer import UnsignedShortType
from net.imglib2.type.numeric.real import FloatType
import os
import time
display = Display.getFront()
shape = (3, 3)
subscriptToIndex = [None] * (shape[0]*shape[1])
helperIndex = 0
for x in xrange(shape[0]):
for y in xrange(shape[1]):
subscriptToIndex[helperIndex] = (x, y)
helperIndex += 1
# use coordinate transform folder to specify output folder
ctsFolder = display.project.getLoader().getCoordinateTransformsFolder().rstrip('/')
lastFolderIdx = len(ctsFolder.split('/')) - 1
itsFolder = '/'.join(ctsFolder.split('/')[:-1]) + '/trakem2.its/'
if tags is None:
return False
for tag in tags:
if string in tag.toString():
return True
return False
def unsetTagWithString(node, string):
tags = node.getTags()
if tags is None:
return
for tag in tags:
if string in tag.toString():
node.removeTag(tag)
theTag = Tag('EC-link', KeyEvent.VK_C)
connectors = Display.getFront().getLayerSet().getZDisplayables(Connector)
for connector in connectors:
root = connector.getRoot()
if root is None:
continue
if not containsTag(root, 'EC-link'):
continue
# wrong tag position, move to child node
for childnode in root.getChildrenNodes():
if not containsTag(childnode, 'EC-link'):
childnode.addTag(theTag)
print 'set new tag on', connector.getId()
unsetTagWithString(root, 'EC-link')
from mpicbg.trakem2.transform import ExportUnsignedByte
from ini.trakem2 import Project
from ini.trakem2.display import Display
from ij import ImagePlus
project = Project.getProjects()[0]
layers = project.getRootLayerSet().getLayers()
bounds = Display.getFront().getRoi().getBounds()
pair = ExportUnsignedByte.makeFlatImageFromMipMaps(layers[1].getDisplayables(),
bounds, 0, 1.0)
bp = pair.a
mask = pair.b
ImagePlus("bp", bp).show()
ImagePlus("mask", mask).show()
for tag in tags:
if string in tag.toString():
return True
return False
def unsetTagWithString(node, string):
tags = node.getTags()
if tags is None:
return
for tag in tags:
if string in tag.toString():
node.removeTag(tag)
theTag = Tag('EC-link', KeyEvent.VK_C)
connectors = Display.getFront().getLayerSet().getZDisplayables(Connector)
for connector in connectors:
root = connector.getRoot()
if root is None:
continue
if not containsTag(root, 'EC-link'):
continue
# wrong tag position, move to child node
for childnode in root.getChildrenNodes():
if not containsTag(childnode, 'EC-link'):
childnode.addTag(theTag)
print 'set new tag on', connector.getId()
unsetTagWithString(root, 'EC-link')
from java.lang.reflect import Field
from ini.trakem2.persistence import FSLoader
from ini.trakem2.display import Display
loader = Display.getFront().getProject().getLoader()
f = FSLoader.getDeclaredField("cannot_regenerate")
f.setAccessible(True)
f.get(loader).clear()
affine = tree.getAffineTransform()
coords = []
for nd in root.getSubtreeNodes():
fp = array([nd.getX(), nd.getY()], 'f')
affine.transform(fp, 0, fp, 0, 1)
x = fp[0] * calibration.pixelWidth
y = fp[1] * calibration.pixelHeight
z = nd.getLayer().getZ() * calibration.pixelWidth # a TrakEM2 oddity
# data may be a radius or a java.awt.geom.Area
coords.append(Matrix([[x, y, z]]))
return coords
tree = Display.getFront().getActive()
m = Matrix( [ [1, 2, 3], [4, 5, 6], [ 7, 8, 10 ] ] )
print "m is:", m
m= m.append( [1,1,1] )
print m
#Calculate the center of mass
center = Matrix([[0,0,0]])
coords = getNodeCoordinates(tree)
for coord in coords:
center += coord
center /= float(len(coords))
print center
#Define covvariance matrix
from ini.trakem2 import Project
from ini.trakem2.display import AreaList, Display, AreaTree, Connector, Coordinate
from ini.trakem2.display.Tree import MeasurePathDistance
from fiji.geom import AreaCalculations
import csv
from jarray import array
from java.awt.geom import Area
from java.awt import Rectangle
import re
project = Project.getProjects().get(0)
projectRoot = project.getRootProjectThing()
display = Display.getFront(project)
neurites = projectRoot.findChildrenOfTypeR("neurite")
notDrawnCo = []
notDrawn = [['layer', 'neurite', 'node']]
for neurite in neurites:
if re.match(r"^apl", neurite.getTitle()) is None:
continue
areatrees = neurite.findChildrenOfTypeR("areatree")
for areatree in areatrees:
areatree = areatree.getObject()
root = areatree.getRoot()
if root is None:
continue
nEmpty = 0
nNodes = 0
# <graph>
# <edge id="[the connector id]" origin="[the origin Treeline id]" target="[the target Treeline id]" />
# ...
# </graph>
#
# The XML opens in a TextWindow
#
# While at it, will generate a .sif file for importing the networt into cytoscape
# as well as a list of id vs name.
from ini.trakem2.display import Display, Connector, Treeline
from java.lang import StringBuilder
from ij.text import TextWindow
layerset = Display.getFront().getLayerSet()
xml = StringBuilder("<graph>\n")
sif = StringBuilder()
names = StringBuilder()
indent = ' '
type = Treeline
alltargets = set()
for con in layerset.getZDisplayables(Connector):
print "Processing Connector", con
origins = con.getOrigins(type)
if origins.isEmpty():
print "Connector without origins:", con
continue
from __future__ import with_statement
from ini.trakem2.display import Display
from ini.trakem2.utils import Utils
from java.io import File
import os
pps = "/home/albert/Desktop/0111-8/scripts/bzip2-decompress_preprocessor.py"
loader = Display.getFront().getProject().getLoader()
for layer in Display.getFront().getLayerSet().getLayers():
for patch in layer.getDisplayables():
loader.setPreprocessorScriptPathSilently(patch, pps)
# Translate any selected Displayable objects
dx = -90
dy = 129
from ini.trakem2.display import Display
# For any selected objected
for displ in Display.getFront().getSelected():
displ.getAffineTransform().translate(dx, dy)
Display.repaint()
from ini.trakem2 import Project
from ini.trakem2.display import AreaList, Display, AreaTree, Connector, Coordinate
from ini.trakem2.display.Tree import MeasurePathDistance
from fiji.geom import AreaCalculations
import csv
from jarray import array
from java.awt.geom import Area
from java.awt import Rectangle
import re
project = Project.getProjects().get(0)
projectRoot = project.getRootProjectThing()
display = Display.getFront(project)
neurites = projectRoot.findChildrenOfTypeR("neurite")
notDrawnCo = []
notDrawn = [['layer', 'neurite', 'node']]
for neurite in neurites:
if re.match(r"^apl", neurite.getTitle()) is None:
continue
areatrees = neurite.findChildrenOfTypeR("areatree")
for areatree in areatrees:
areatree = areatree.getObject()
root = areatree.getRoot()
if root is None:
continue
nEmpty = 0
nNodes = 0
def timeIt(fn, n_iterations=10):
elapsed_times = []
for i in range(n_iterations):
t0 = System.nanoTime()
fn()
t1 = System.nanoTime()
elapsed_times.append(t1 - t0)
smallest = min(elapsed_times)
largest = max(elapsed_times)
average = sum(elapsed_times) / float(n_iterations)
print "Elapsed time: min", smallest, "max", largest, "average", average
return elapsed_time
layer = Display.getFront().getLayer()
patch = layer.getDisplayables().get(0)
print patch
pai = patch.createTransformedImage()
print pai
print patch.hasCoordinateTransform()
print patch.getImageProcessor()
first_level_mipmaps_saved = 0
def testCascade():
global patch, pai, first_level_mipmaps_saved
print pai
b = DownsamplerMipMaps.create(
patch,
patch.getType(),
pai.target,
from ini.trakem2.display import Display, Patch
unique = set()
for patch in Display.getFront().getLayer().getDisplayables(Patch):
path = patch.getImageFilePath()
if path in unique:
patch.remove(False)
else:
unique.add(path)
Display.repaint()
# Create a snapshot of the images under the area:
imp = loader.getFlatImage(layer, box, 1, 0xffffffff,
ImagePlus.GRAY8, Patch, False)
# Set the area as a roi
imp.setRoi(ShapeRoi(area))
# Perform measurements (uncalibrated)
# (To get the calibration, call layerset.getCalibrationCopy())
stats = ByteStatistics(imp.getProcessor(), moptions, calibration)
table.incrementCounter()
table.addLabel("Name", ali.getTitle())
table.addValue(0, ali.getId())
table.addValue(1, index) # the layer index
table.addValue(2, layer.getZ())
table.addValue(3, stats.area)
table.addValue(4, stats.mean)
# Update and show the table
table.show("AreaLists")
# Get the front display, if any:
display = Display.getFront()
if display is not None:
# Obtain the LayerSet of the current Display canvas:
layerset = Display.getFront().getLayer().getParent()
# Measure!
measureCustom(display.getFront().getLayer().getParent())
else:
IJ.showMessage("Open a TrakEM2 display first!")
def injectNordenTools(display):
tabs = display.getTabbedPane()
# Check that it's not there already
title = "Norden Tools"
for i in range(tabs.getTabCount()):
if tabs.getTitleAt(i) == title:
tabs.remove(i)
#IJ.showMessage("Norden Tools have already been injected!")
#return
# Otherwise, add it new:
from javax.swing import JPanel, JButton
panel = JPanel()
btnExportMask = JButton("Export mask", actionPerformed=nt.exportMask)
panel.add(btnExportMask)
btnImportMask = JButton("Import mask", actionPerformed=nt.importMask)
panel.add(btnImportMask)
btnOpenStack = JButton("Open Stack", actionPerformed=nt.openStack)
panel.add(btnOpenStack)
btnExportSegmentation = JButton("Export segmentation",
actionPerformed=nt.exportSegmentation)
panel.add(btnExportSegmentation)
tabs.add(title, panel)
tabs.setSelectedComponent(panel)
# MAIN
display = Display.getFront()
if display is not None:
injectNordenTools(display)
else:
IJ.showMessage("No active TrackEM2-project found. Open one!")
def sphereCount(ID, biniter):
#find center of mass
tree = Display.getFront().getLayerSet().findById(ID)
coords = Matrix(getNodeCoordinates(tree))
center = Matrix( [[0,0,0]] )
m=coords.getRowDimension()
for i in range(0, m):
center += Matrix([coords.getRow( i )])
center /= float(m)
#calculate all distances of all points to center of mass and put them in a list
xdist=[]
ydist=[]
zdist=[]
for i in range(0, m):
xdiff=[]
if coords.get(i,0) > center.get(0,0):
xdiff = coords.get(i,0) - center.get(0,0)
else:
xdiff = center.get(0,0) - coords.get(i,0)
xdist.append(xdiff)
for i in range(0, m):
ydiff=[]
if coords.get(i,1) > center.get(0,1):
ydiff = coords.get(i,1) - center.get(0,1)
else:
ydiff = center.get(0,1) - coords.get(i,1)
ydist.append(ydiff)
for i in range(0, m):
zdiff=[]
if coords.get(i,2) > center.get(0,2):
zdiff = coords.get(i,2) - center.get(0,2)
else:
zdiff = center.get(0,2) - coords.get(i,2)
zdist.append(zdiff)
nodeDist=[]
dist=[]
for i in range(0, m):
dist=sqrt(xdist[i]**2 + ydist[i]**2 + zdist[i]**2)
nodeDist.append(dist)
iterations=biniter
Ri=0 #inner radius
"""
The maximum distance can only be achieved in the xy-plane
With "fixed" coordinates this will approx. be 35000nm
To make the scholl-profiles comparable this length has to be used.
"""
scholl=[]
xaxis=[]
counter=0
length= int(35000 / biniter + 0.5)
Ra=length #outer radius
for i in range(0, biniter):
for i in range(0, len(nodeDist)):
if nodeDist[i] <= Ra and nodeDist[i] >= Ri:
counter += 1
scholl.append(counter)
counter=0
xaxis.append(Ri) # adapt THIS position in all other scripts! Otherwise 1 datapoint is missing!!
Ri += length
Ra += length
return scholl, xaxis
from __future__ import with_statement
from ini.trakem2.display import Display
paths = []
for layer in Display.getFront().getLayerSet().getLayers():
for patch in layer.getDisplayables():
if patch.isVisible():
paths.append(patch.getImageFilePath())
print "Number of image paths:", len(paths)
with open("/home/albert/shares/cardona_nearline/Albert/0111-8_whole_L1_CNS/visible_image_filepaths.txt", "w") as f:
f.write("\n".join(paths))
for nd in root.getSubtreeNodes():
fp = array([nd.getX(), nd.getY()], 'f')
affine.transform(fp, 0, fp, 0, 1)
x = fp[0] * calibration.pixelWidth
y = fp[1] * calibration.pixelHeight
z = nd.getLayer().getZ() * calibration.pixelWidth # a TrakEM2 oddity
# data may be a radius or a java.awt.geom.Area
coords.append( correct([x, y, z]) )
#print coords[len(coords)-1]
return coords
#---------Select tree-----------------
#tree = Display.getFront().getActive()
ID = 74329
tree = Display.getFront().getLayerSet().findById(ID)
#-------------------------------------
#Calculate the center of mass
center = Matrix( [[0,0,0]] )
coords = Matrix(getNodeCoordinates(tree))
m=coords.getRowDimension()
for i in range(0, coords.getRowDimension()):
center += Matrix([coords.getRow( i )])
center /= float(m)
print center
"""
from ini.trakem2.display import Display
from mpicbg.trakem2.transform import ExportBestFlatImage
from ij import ImagePlus
patches = Display.getFront().getLayer().getDisplayables()
bounds = Display.getFront().getRoi().getBounds()
backgroundValue = 0
scale = 0.25
e = ExportBestFlatImage(patches, bounds, backgroundValue, scale)
print e.canUseAWTImage()
print e.isSmallerThan2GB()
e.printInfo()
p = e.makeFlatFloatGrayImageAndAlpha()
ImagePlus("grey", p.a).show()
ImagePlus("mask", p.b).show()
def getDendriticProfiles(ID):
tree = Display.getFront().getLayerSet().findById(ID)
coords = Matrix(getNodeCoordinates(tree))
#Define axis vectors and origin
xnorm = Matrix([[1,0,0]])
ynorm = Matrix([[0,1,0]])
znorm = Matrix([[0,0,1]])
center= Matrix([[0,0,0]])
#Project nodes onto axis
dpx=[]
dpy=[]
dpz=[]
m=coords.getRowDimension()
for i in range(0, m):
xstore = Matrix([coords.getRow( i )]) * xnorm.transpose()
ystore = Matrix([coords.getRow( i )]) * ynorm.transpose()
zstore = Matrix([coords.getRow( i )]) * znorm.transpose()
dpx.append(xstore.getRow(0))
dpy.append(ystore.getRow(0))
dpz.append(zstore.getRow(0))
#Count number of nodes which fall in defined interval of pca projection
counter = 0
xhistovector = []
yhistovector = []
zhistovector = []
#get it back in array form (get rid of list in list of Jarray)
dpx=[ x[0] for x in dpx]
dpy=[ x[0] for x in dpy]
dpz=[ x[0] for x in dpz]
#Initialize interval size and fix iterations to a specific number
xbinleft = min(dpx)
ybinleft = min(dpy)
zbinleft = min(dpz)
#-------PARAMETER FOR MACHINE LEARNING--------------
iterations =100
#---------------------------------------------------
xlength = int((max(dpx)-min(dpx))/iterations + 0.5)
ylength = int((max(dpy)-min(dpy))/iterations + 0.5)
zlength = int((max(dpz)-min(dpz))/iterations + 0.5)
xbinright = xbinleft + xlength
ybinright = ybinleft + ylength
zbinright = zbinleft + zlength
#Count elements in bins
xaxis=[]
for i in range(0,iterations):
for i in range(0, len(dpx)):
if dpx[i] <= xbinright and dpx[i] >= xbinleft:
counter += 1
xhistovector.append(counter)
counter=0
xbinleft += xlength
xbinright += xlength
xaxis.append(xbinleft)
yaxis=[]
for i in range(0,iterations):
for i in range(0, len(dpy)):
if dpy[i] <= ybinright and dpy[i] >= ybinleft:
counter += 1
yhistovector.append(ylength)
counter=0
ybinleft += ylength
ybinright += ylength
yaxis.append(ybinleft)
zaxis=[]
for i in range(0,iterations):
for i in range(0, len(dpz)):
if dpz[i] <= zbinright and dpz[i] >= zbinleft:
counter += 1
zhistovector.append(counter)
counter=0
zbinleft += zlength
zbinright += zlength
zaxis.append(zbinleft)
#Normalize bin-count by division through length
for i in range(0, iterations):
xhistovector[i]/=float(xlength)
yhistovector[i]/=float(ylength)
zhistovector[i]/=float(zlength)
return xhistovector, yhistovector, zhistovector