Update scripts w/ references to old SkeletonConverter

Author: tferr

src/main/resources/script_templates/Neuroanatomy/Boilerplate/PY.py

@@ -17,7 +17,8 @@
 from sc.fiji.snt import Path, PathAndFillManager, SNT, SNTUI, Tree
 from sc.fiji.snt.analysis import GroupedTreeStatistics, MultiTreeStatistics, NodeStatistics, TreeStatistics,\
             ConvexHullAnalyzer, PersistenceAnalyzer, ShollAnalyzer, StrahlerAnalyzer, NodeColorMapper,\
-            TreeColorMapper, PathProfiler, PathStraightener, RoiConverter, SkeletonConverter, SNTChart, SNTTable
+            TreeColorMapper, PathProfiler, PathStraightener, RoiConverter, SNTChart, SNTTable
+from sc.fiji.snt.tracing.auto import BinaryTracer
 from sc.fiji.snt.analysis.graph import DirectedWeightedGraph
 from sc.fiji.snt.analysis.sholl.parsers import TreeParser
 from sc.fiji.snt.annotation import AllenCompartment, AllenUtils, VFBUtils, ZBAtlasUtils

src/main/resources/script_templates/Neuroanatomy/Skeletons_and_ROIs/Reconstruction_From_Segmented_Image.py

@@ -21,7 +21,7 @@
 import os
 from ij import IJ
 from sc.fiji.snt import Tree
-from sc.fiji.snt.analysis import SkeletonConverter
+from sc.fiji.snt.tracing.auto import BinaryTracer
 from sc.fiji.snt.viewer import Viewer3D
 
 # Documentation Resources: https://imagej.net/plugins/snt/scripting
@@ -39,7 +39,7 @@ def main():
 		skeletonizeImp = True
 	# Use the image to create the reconstructions, first skeletonizing 
 	# if it is not already a skeleton.
-	converter = SkeletonConverter(imp, skeletonizeImp)
+	converter = BinaryTracer(imp, skeletonizeImp)
 	converter.setPruneByLength(pruneByLength)
 	converter.setLengthThreshold(lengthThreshold)
 	converter.setConnectComponents(connectComponents)

src/main/resources/script_templates/Neuroanatomy/Tracing/Fully_Automated_Tracing_Demo_(Interactive).py

@@ -10,7 +10,7 @@
             instance of SNT to perform automated (unsupervised) tracing
 """
 
-from sc.fiji.snt.analysis import SkeletonConverter
+from sc.fiji.snt.tracing.auto import BinaryTracer
 from ij.gui import Roi
 
 def run():
@@ -39,18 +39,18 @@ def run():
     # use the Estimate Radii (Local Thickness).. command directly on the image)
     snt.getUI().runSecondaryLayerWizard("Frangi Vesselness (Multi-scale filter)", [0.56, 0.74, 0.98])
 
-    # the SkeletonConverter class is the workhorse class for the conversion. We'll
+    # the BinaryTracer class is the workhorse class for the conversion. We'll
     # use it to skeletonize the Frangi image, thresholding out the voxels with
     # low 'vesselness scores' (here, we'll only consider values above 0.005..
     # NB: The last boolean argument in the skeletonize() method specifies whether
     # isolated voxels that may exist should be eroded
     filtered_img = snt.getPlugin().getSecondaryDataAsImp()
     #filtered_img.duplicate().show() # display copy
-    SkeletonConverter.skeletonize(filtered_img, 0.45, 1, True)
+    BinaryTracer.skeletonize(filtered_img, 0.45, 1, True)
     #filtered_img.show() # display skeletonized image
 
     # We can now initialize the converter and specify some tweaks:
-    converter = SkeletonConverter(filtered_img)
+    converter = BinaryTracer(filtered_img)
     converter.setPruneByLength(False) # Discard smaller disconnected branches?
     converter.setLengthThreshold(1) # Discard only branches smaller than 1um
     converter.setConnectComponents(True) # Attempt to bridge gaps in the structure?

src/main/resources/script_templates/Neuroanatomy/Tracing/Fully_Automated_Tracing_Timelapse_Demo.groovy

@@ -33,7 +33,7 @@ imp = snt.getImagePlus()
 	println("Processing frame #" + frame)
 
 	// Assemble a converter for extraction of paths from this frame. API:
-	// https://javadoc.scijava.org/SNT/index.html?sc/fiji/snt/analysis/SkeletonConverter.html
+	// https://javadoc.scijava.org/SNT/index.html?sc/fiji/snt/tracing/auto/BinaryTracer.html
 	converter = new BinaryTracer(imp, frame) // image and frame to be parsed
 	converter.setPruneByLength(false) // Don't ignore small components...
 	converter.setConnectComponents(false) // Don't merge neighboring components..