calculate the distances instead of starting from a table

calculate_hist_and_eCDF.py

@@ -1,15 +1,14 @@
+from ij import IJ
 from fr.cnrs.mri.cialib.stats import Histogram 
+from fr.cnrs.mri.cialib.spatialstats import NearestNeighborEmpiricalCDF
 from ij.measure import ResultsTable
 from jarray import array
 
-COLUMN = "V2"
-TABLE = "ClosestDistanceCCUnit"
+image = IJ.getImage()
+nn = NearestNeighborEmpiricalCDF(image)
+nn.calculateDistances()
 
-table = ResultsTable.getResultsTable(TABLE)
-data = table.getColumn(COLUMN)
-data = array(list(data), 'f')
-
-hist = Histogram(data, start=0, end=8, nBins=100)
+hist = Histogram(nn.distances, start=0, end=max(nn.distances) + 1, nBins=12)
 hist.autoBinning = False
 hist.calculate()
 hist.getPlot().show()

db_scan.py

@@ -1,7 +1,7 @@
 '''
 DBSCAN-clustering of 3D-points. 
 
-(c) 2019-2022, INSERM
+(c) 2019-2023, INSERM
 written by Volker Baecker at Montpellier Ressources Imagerie, Biocampus Montpellier, INSERM, CNRS, University of Montpellier (www.mri.cnrs.fr)
 
 The points must be in the X, Y, Z and NR columns
@@ -27,10 +27,10 @@
 
 
 def main():
-    XColumn = 'X'
-    YColumn = 'Y'
-    ZColumn = 'Z'
-    NRColumn = 'NR'
+    XColumn = 'Centroid.X'
+    YColumn = 'Centroid.Y'
+    ZColumn = 'Centroid.Z'
+    NRColumn = 'Label'
     minPts = 4
     maxDist = 3
     run(maxDist, minPts, XColumn, YColumn, ZColumn, NRColumn)
@@ -58,7 +58,7 @@ def pointList3DFromRT(XColumn='X', YColumn='Y', ZColumn='Z'):
     '''
     Create a list of 3D-coordinates from the ImageJ system results table and return it.
     '''
-    rt = ResultsTable.getResultsTable()
+    rt = ResultsTable.getActiveTable()
     xIndex = getColumnIndex(XColumn)
     yIndex = getColumnIndex(YColumn)
     zIndex = getColumnIndex(ZColumn)
@@ -82,25 +82,23 @@ def reportClustersAsTable(clusters, allPoints, XColumn='X', YColumn='Y', ZColumn
     '''
     Report the clustered and unclustered points in the tables 'clusters' and 'unclustered'.
     '''
-    rt = ResultsTable()
+    rt_clustered = ResultsTable()
     counter = 1;
     clusterCounter = 1
     clusteredPoints = []
     for c in clusters:
         for dp in c.getPoints():
-            rt.incrementCounter()
+            rt_clustered.incrementCounter()
             p = dp.getPoint()
-            rt.addValue(NRColumn, counter)
-            rt.addValue(XColumn, p[0])
-            rt.addValue(YColumn, p[1])
-            rt.addValue(ZColumn, p[2])
-            rt.addValue("C", clusterCounter)
+            rt_clustered.addValue(NRColumn, counter)
+            rt_clustered.addValue(XColumn, p[0])
+            rt_clustered.addValue(YColumn, p[1])
+            rt_clustered.addValue(ZColumn, p[2])
+            rt_clustered.addValue("C", clusterCounter)
             counter = counter + 1;
             clusteredPoints.append([p[0], p[1], p[2]])
         clusterCounter = clusterCounter + 1
-    rt.show("clusters")
-    win = WindowManager.getWindow("Results")
-    rt = win.getResultsTable()
+    rt = ResultsTable.getActiveTable()
     X, Y, Z  = getColumns(XColumn, YColumn, ZColumn)
     if not rt.columnExists(NRColumn):
         for i in range(0, len(X)):
@@ -118,13 +116,14 @@ def reportClustersAsTable(clusters, allPoints, XColumn='X', YColumn='Y', ZColumn
         rt.addValue(ZColumn, p[2])
         counter = counter + 1;    
     rt.show("unclustered")
-    WindowManager.setWindow(win)
+    rt_clustered.show("clusters")
+    WindowManager.getWindow("Results").close()
 
 
 def getColumnIndex(column):
-    rt = ResultsTable.getResultsTable()
+    rt = ResultsTable.getActiveTable()
     headings = rt.getHeadings()
-    for i, heading in enumerate(headings, start=1):
+    for i, heading in enumerate(headings, start=0):
         if heading==column:
             return i
     return None

tools/draw_clusters.ijm

@@ -0,0 +1,33 @@
+var IS_SCALED = true;
+var X_COLUMN = "Centroid.X";
+var Y_COLUMN = "Centroid.Y";
+var Z_COLUMN = "Centroid.Z";
+var CLUSTER_COLUMN = "C";
+var TABLE = "clusters"
+
+run("Duplicate...", "duplicate");
+run("Select All");
+setBackgroundColor(0, 0, 0);
+run("Clear", "stack");
+run("Select None");
+
+X = Table.getColumn(X_COLUMN, TABLE);
+Y = Table.getColumn(Y_COLUMN, TABLE);
+Z = Table.getColumn(Z_COLUMN, TABLE);
+C = Table.getColumn(CLUSTER_COLUMN, TABLE);
+for (i = 0; i < Table.size(TABLE); i++) {
+    x = X[i];
+    y = Y[i];
+    z = Z[i];
+    if (IS_SCALED) {
+        toUnscaled(x, y, z);
+    }
+    setSlice(z+1);
+    setPixel(x, y, C[i]);
+}
+setOption("ScaleConversions", false);
+run("16-bit");
+run("glasbey on dark");
+run("Morphological Filters (3D)", "operation=Dilation element=Cube x-radius=2 y-radius=2 z-radius=2");
+ setSlice(1);
+resetMinAndMax();

tools/draw_nearest_neighbors.ijm

@@ -1,11 +1,14 @@
 var MAX_DIST = 999999;
-var IS_SCALED = false;
-var X_COLUMN = "axis-2";
-var Y_COLUMN = "axis-1";
-var Z_COLUMN = "axis-0";
+var IS_SCALED = true;
+var X_COLUMN = "Centroid.X";
+var Y_COLUMN = "Centroid.Y";
+var Z_COLUMN = "Centroid.Z";
+var LABEL_COLUMN = "Label";
+
 
 drawNearestNeighborConnections();
 
+
 function drawNearestNeighborConnections() {
     inputStackID = getImageID();
     Stack.getDimensions(width, height, channels, slices, frames);
@@ -14,19 +17,17 @@ function drawNearestNeighborConnections() {
 
     table = Table.title;
     duplicateTable(table, "green")
-    Table.applyMacro("Label = index + 1", "green");
     duplicateTable("green", "red")
-    Table.applyMacro("Label = index + 1", "red");
 
     run("3D Distances Closest", "image_a="+title+" image_b="+title+" number=2 distance=DistCenterCenterUnit distance_maximum="+MAX_DIST);
     Table.rename("ClosestDistanceCCUnit", "neighbors");
 
-    labelRed = Table.getColumn("Label", "red");
+    labelRed = Table.getColumn(LABEL_COLUMN, "red");
     xRed = Table.getColumn(X_COLUMN, "red");
     yRed = Table.getColumn(Y_COLUMN, "red");
     zRed = Table.getColumn(Z_COLUMN, "red");
 
-    labelGreen = Table.getColumn("Label", "green");
+    labelGreen = Table.getColumn(LABEL_COLUMN, "green");
     xGreen = Table.getColumn(X_COLUMN, "green");
     yGreen = Table.getColumn(Y_COLUMN, "green");
     zGreen = Table.getColumn(Z_COLUMN, "green");