lacan · March 16, 2018 20:56 · Jun 21, 2017 · Jun 21, 2017 · Jun 16, 2017 · Jul 12, 2016
diff --git a/simpleKNN.py b/simpleKNN.py
@@ -1,5 +1,6 @@
-# @ImagePlus imp
-# @Integer(label="Number of Neighbors") k
+#@ImagePlus imp
+#@Integer(label="Number of Neighbors") k
+#@Boolean(label="Give Each Neighbor's Distance") is_show_each
 
 '''
 Simple 2D KNN script
@@ -83,7 +84,13 @@ def showKNNResults(frt, the_knn, label):
 		frt.addValue("Average distance [px]", the_avg[i])
 		if( cal.scaled() ):
 			frt.addValue("Average distance ["+cal.getXUnit()+"]", cal.getX(the_avg[i]))
-
+		if is_show_each:
+			for j in range(k):
+				if( cal.scaled() ):
+					frt.addValue("Distance Neighbor "+str(j+1)+" ["+cal.getXUnit()+"]", cal.getX(the_knn[i][j][1]))
+				else:
+					frt.addValue("Distance Neighbor "+str(j+1)+" [px]", the_knn[i][j][1])
+
 	frt.show(str(k)+" Nearest Neightbors Average Distances")
 	imp.setOverlay(ov)
 

diff --git a/simpleKNN.py b/simpleKNN.py
@@ -11,11 +11,12 @@
 http://imagej.1557.x6.nabble.com/distance-between-adjacent-particles-td3699485.html#a5016864
 '''
 
-from ij.gui import Overlay,  Line, OvalRoi
+from ij.gui import Overlay,  Line, OvalRoi, Roi
 from ij import IJ
 from ij.measure import ResultsTable
 from ij.measure import Calibration
 from java.awt import Color
+from ij.plugin.frame import RoiManager
 import math
 
 ### Some functions ###
@@ -42,12 +43,12 @@ def dist(p0, p1):
     return math.sqrt((p0[0] - p1[0])**2 + (p0[1] - p1[1])**2)
 
 # Convenience function to go from a ROI to points
-def roiToPointList(image):
-	p = [image.getRoi().getFloatPolygon().xpoints, image.getRoi().getFloatPolygon().ypoints]
+def roiToPointList(roi):
+	p = [roi.getFloatPolygon().xpoints, roi.getFloatPolygon().ypoints]
 	points = map(list, zip(*p))
 	return points
 
-def showKNNResults(the_knn):
+def showKNNResults(frt, the_knn, label):
 
 	# Overlay
 	ov = Overlay()
@@ -74,10 +75,10 @@ def showKNNResults(the_knn):
 
 	# Build Results Table
 	cal = imp.getCalibration()
-	frt = ResultsTable()
 
 	for i in range(len(the_knn)):
 		frt.incrementCounter()
+		frt.addValue("Label", label);
 		frt.addValue("Point", i)
 		frt.addValue("Average distance [px]", the_avg[i])
 		if( cal.scaled() ):
@@ -90,11 +91,38 @@ def showKNNResults(the_knn):
 
 ### Starting the script ###
 
-# Get Coordinates
-points = roiToPointList(imp)
+# Get a new Results Table
+rt = ResultsTable()
 
-# Compute K Nearest Neighbors
-the_knn = knn(points,k)
+# Get the ROI manager
+rm = RoiManager().getInstance2();
 
-# Display the result table and an overlay
-showKNNResults(the_knn)
+n_rois = rm.getCount();
+
+# Work either on the image alone
+if n_rois == 0:
+	roi = imp.getRoi()
+	label = imp.getTitle()
+	# Get Coordinates
+	points = roiToPointList(imp.getRoi())
+
+
+	# Compute K Nearest Neighbors
+	the_knn = knn(points,k)
+
+	# Display the result table and an overlay
+	showKNNResults(rt,the_knn,label)
+
+# Or on each ROI of the ROI manager
+else:
+	for i in range(n_rois):
+		roi = rm.getRoi(i)
+		label = roi.getName()
+		# Get Coordinates
+		points = roiToPointList(roi)
+
+		# Compute K Nearest Neighbors
+		the_knn = knn(points,k)
+
+		# Display the result table and an overlay
+		showKNNResults(rt,the_knn,label)
diff --git a/simpleKNN.py b/simpleKNN.py
@@ -0,0 +1,100 @@
+# @ImagePlus imp
+# @Integer(label="Number of Neighbors") k
+
+'''
+Simple 2D KNN script
+Olivier Burri, BioImaging & Optics Platform
+Ecole Polytechnique Fédérale de Lausanne
+July 12th 2016
+
+Code provided as-is in reply to an ImageJ mailing list question
+http://imagej.1557.x6.nabble.com/distance-between-adjacent-particles-td3699485.html#a5016864
+'''
+
+from ij.gui import Overlay,  Line, OvalRoi
+from ij import IJ
+from ij.measure import ResultsTable
+from ij.measure import Calibration
+from java.awt import Color
+import math
+
+### Some functions ###
+
+# Brute-Force KNN
+def knn(data, k):
+	# Just take the data, find the K nearest neighbors to each point
+
+	the_knn=[]
+
+	for i in range(len(data)):
+		d = []
+		for j in range(len(data)):
+			d.append([j, dist(data[i], data[j])])
+
+		# Sort
+		d_sort = sorted(d, key=lambda thed: thed[1])
+		# Keep only the k nearest
+		the_knn.append(d_sort[1:(k+1)])
+	return the_knn
+
+# Euclidean Distance 2D
+def dist(p0, p1):
+    return math.sqrt((p0[0] - p1[0])**2 + (p0[1] - p1[1])**2)
+
+# Convenience function to go from a ROI to points
+def roiToPointList(image):
+	p = [image.getRoi().getFloatPolygon().xpoints, image.getRoi().getFloatPolygon().ypoints]
+	points = map(list, zip(*p))
+	return points
+
+def showKNNResults(the_knn):
+
+	# Overlay
+	ov = Overlay()
+	the_avg = []
+
+	# Draw each neighbor as a line and draw the average as a circle
+	for i in range(len(the_knn)):
+		avg =  sum([d[1] for d in the_knn[i]]) / k
+		the_avg.append(avg)
+
+		o = OvalRoi(points[i][0] - avg, points[i][1] - avg, 2*avg, 2*avg)
+		o.setStrokeColor(Color.decode("#00FFFF"))
+		ov.add(o)
+
+		for j in range(k):
+			# XY Coordinates of current point
+			a = points[i];
+			b = points[the_knn[i][j][0]]
+			# XY Coordinates of neighbor k
+			l = Line(a[0], a[1], b[0], b[1])
+			l.setStrokeColor(Color.decode("#FF00FF"))
+			ov.add(l)
+
+
+	# Build Results Table
+	cal = imp.getCalibration()
+	frt = ResultsTable()
+
+	for i in range(len(the_knn)):
+		frt.incrementCounter()
+		frt.addValue("Point", i)
+		frt.addValue("Average distance [px]", the_avg[i])
+		if( cal.scaled() ):
+			frt.addValue("Average distance ["+cal.getXUnit()+"]", cal.getX(the_avg[i]))
+
+	frt.show(str(k)+" Nearest Neightbors Average Distances")
+	imp.setOverlay(ov)
+
+
+
+### Starting the script ###
+
+# Get Coordinates
+points = roiToPointList(imp)
+
+# Compute K Nearest Neighbors
+the_knn = knn(points,k)
+
+# Display the result table and an overlay
+showKNNResults(the_knn)
No results found