def draw_classes(inputfile,data):
pathname,filename = os.path.split(inputfile)
# last subdir is for well
## TODO ## support multiple plates, read plate and well from csv
well = os.path.basename(pathname)
# create output directory
outputdir = os.path.join(OUTPUTROOT,well)
if not os.path.isdir(outputdir):
os.makedirs(outputdir)
# create output filename
head,tail = os.path.splitext(filename)
outputfilename = head + "_classes" + tail
outputfilename = os.path.join(outputdir,outputfilename)
print outputfilename
imp = IJ.openImage(inputfile).duplicate()
IJ.run(imp,"RGB Color","")
for d in data:
x = int(float(d[0]))
y = int(float(d[1]))
c = int(float(d[2]))
classname = classes[str(c)]
colorname = colors[classname]
color = colormap[colorname]
#print colorname
roi = PointRoi(x,y)
roi.setDefaultMarkerSize("Large")
roi.setStrokeColor(colormap[colorname])
imp.getProcessor().drawRoi(roi)
IJ.saveAs(imp,"png",outputfilename)
def draw_centers(data):
pathname = data[1]
filename = data[2]
platename = data[3]
print data[4]
nx = int(data[4])
ny = int(data[5])
nx_com = int(data[6])
ny_com = int(data[7])
ax = int(data[8])
ay = int(data[9])
orientation = 2*math.pi * float(data[10]) / 360.0
line_dy = int(round(math.atan(orientation) * LINE_DX))
ax2 = ax - LINE_DX
ay2 = ay - line_dy
orientation_avg = 2*math.pi * float(data[11]) / 360.0
line_dy = int(round(math.atan(orientation_avg) * LINE_DX))
ax3 = ax - LINE_DX
ay3 = ay - line_dy
imp = IJ.openImage(os.path.join(pathname,filename))
roi_nucleus = PointRoi(nx,ny)
roi_nucleus.setDefaultMarkerSize("Large")
roi_nucleus.setStrokeColor(Color.CYAN)
roi_nucleus_com = PointRoi(nx_com,ny_com)
roi_nucleus_com.setDefaultMarkerSize("Large")
roi_nucleus_com.setStrokeColor(Color.GREEN)
roi_anchor = PointRoi(ax,ay)
roi_anchor.setDefaultMarkerSize("Large")
imp.getProcessor().drawRoi(roi_nucleus)
imp.getProcessor().drawRoi(roi_nucleus_com)
imp.getProcessor().drawRoi(roi_anchor)
imp.setColor(Color.RED)
imp.getProcessor().drawLine(ax,ay,ax2,ay2)
imp.setColor(Color.WHITE)
imp.getProcessor().drawLine(ax,ay,ax3,ay3)
IJ.saveAsTiff(imp,os.path.join(pathname,filename))
def processOneImage(inputDir):
tmp = glob.glob(os.path.join(inputDir, "fibrone*"))
fibronectin = tmp[0]
tmp = glob.glob(os.path.join(inputDir, "nucleus*"))
nucleus = tmp[0]
tmp = glob.glob(os.path.join(inputDir, "actin*"))
actin = tmp[0]
# read sample name
head,tail = os.path.split(inputDir)
sample = tail.replace(".tif_Files","")
# original images
imp_fn_orig = IJ.openImage(fibronectin)
imp_nuc_orig = IJ.openImage(nucleus)
# work copies
imp_fn = imp_fn_orig.duplicate()
imp_nuc = imp_nuc_orig.duplicate()
IJ.run(imp_fn,"Set Scale...", "distance=1 known=1 pixel=1 unit=pixels")
IJ.run(imp_fn,"Gaussian Blur...","sigma=5")
IJ.run(imp_fn,"Make Binary","")
IJ.run(imp_nuc,"Set Scale...", "distance=1 known=1 pixel=1 unit=pixels")
IJ.run(imp_nuc,"Gaussian Blur...","sigma=5")
IJ.run(imp_nuc,"Make Binary","")
# get moments of the fibronectin image
moments_file = os.path.join(OUTPUT, sample + " moments.txt")
printMoments(fibronectin, moments_file)
moments = readMoments(moments_file)
print moments.m00
sys.exit()
# centroid of fibronectin anchor
centers = getParticleCenters(imp_fn)
cxfn = int(round(centers[0][0]))
cyfn = int(round(centers[1][0]))
fn_centroid_roi = PointRoi(cxfn,cyfn)
fn_centroid_roi.setDefaultMarkerSize("Large")
fn_centroid_roi.setStrokeColor(Color.CYAN)
# center of mass of nucleus
centers = getParticleCenters(imp_nuc)
cxnuc = int(round(centers[2][0]))
cynuc = int(round(centers[3][0]))
nuc_com_roi = PointRoi(cxnuc,cynuc)
nuc_com_roi.setDefaultMarkerSize("Large")
# skeletonize fibronectin anchor to find its orientation
IJ.run(imp_fn,"Skeletonize","")
skel = AnalyzeSkeleton_()
skel.setup("",imp_fn)
skelResult = skel.run(skel.NONE, False, True, None, True, True)
graph = skelResult.getGraph()
print len(graph)
print skelResult.getNumOfTrees()
# find the longest graph
graph = sorted(graph, key=lambda g: getGraphLength(g), reverse=True)
graph = graph[0]
edges = graph.getEdges()
# find longest edge, the main axis of the anchor
edges = sorted(edges, key=lambda edge: edge.getLength(), reverse=True)
#for e in edges:
# print e.getLength()
v1long = edges[0].getV1()
v2long = edges[0].getV2()
x1 = v1long.getPoints()[0].x
y1 = v1long.getPoints()[0].y
x2 = v2long.getPoints()[0].x
y2 = v2long.getPoints()[0].y
anchor_roi = PointRoi(x1,y1)
anchor_roi = anchor_roi.addPoint(x2,y2)
# find top and bottom vertices of the graph
vertices = graph.getVertices()
vertices = sorted(vertices, key=lambda vertex: vertex.getPoints()[0].y)
v1short = vertices[len(vertices)-1]
v2short = vertices[0]
x3 = v1short.getPoints()[0].x
y3 = v1short.getPoints()[0].y
x4 = v2short.getPoints()[0].x
y4 = v2short.getPoints()[0].y
anchor_roi = anchor_roi.addPoint(x3,y3)
anchor_roi = anchor_roi.addPoint(x4,y4)
# calculate angles
a1 = math.atan(abs(float(y2-y1)/float(x2-x1))) / math.pi * 360
a2 = math.atan(abs(float(x4-x3)/float(y4-y3))) / math.pi * 360
amean = float((a1+a2)/2)
dx = cxfn-cxnuc
print sample,cxfn,cyfn,cxnuc,cynuc,dx,math.cos(amean)*dx,x1,y1,x2,y2,x3,y3,x4,y4,a1,a2
# create composite
comp = ImagePlus("composite",imp_nuc_orig.getProcessor().convertToColorProcessor())
comp.getProcessor().setChannel(2,imp_fn_orig.getProcessor())
comp.getProcessor().setChannel(3,imp_fn.getProcessor())
comp.show()
comp.getProcessor().drawRoi(fn_centroid_roi)
comp.getProcessor().drawRoi(nuc_com_roi)
comp.getProcessor().drawRoi(anchor_roi)
comp.repaintWindow()
IJ.saveAsTiff(comp, os.path.join(OUTPUT,sample + ".tif"))