Tests for spam.label.moveLabels()

tests/test_label.py

@@ -11,6 +11,7 @@ import spam.label
 import spam.kalisphera
 import spam.label.contacts as con
 import spam.plotting
+import skimage.morphology
 VERBOSE = True
 
 # small labelled volume is a 3x3x3 with a single 1 in the middle
@@ -638,6 +639,74 @@ class TestFunctionLabel(unittest.TestCase):
         im = im.astype('<u4')
         convexVol = spam.label.convexVolume(im)
         self.assertEqual(0, convexVol[-1])
-
+        
+    def test_moveLabels(self):
+        # Create the sphere
+        imLab = skimage.morphology.ball(20)
+        # Pad with zero at each boundaries
+        imLab = numpy.pad(imLab, (10), 'constant', constant_values=(0))
+        # Compute initial volume
+        iniVol = spam.label.volumes(imLab)[-1]
+        # Compute initial COM
+        iniCOM = spam.label.centresOfMass(imLab)[-1]
+        # Compute boundingBoxes
+        boundingBoxes = spam.label.boundingBoxes(imLab)
+        # Compute centre of Mass
+        centresOfMass = spam.label.centresOfMass(imLab)
+        # Create empty PhiField
+        PhiField = numpy.zeros((2, 4, 4))
+
+        # Test #1 -> COM=iniCOM, vol = iniVol for no dilate and Phi = I
+        transformation = {'t': [0, 0, 0]}
+        PhiField[1] = spam.deformation.computePhi(transformation)
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass)
+        # Compute Volume and COM
+        newVol = spam.label.volumes(imLab2)[-1]
+        newCOM = spam.label.centresOfMass(imLab2)[-1]
+        self.assertEqual(0, numpy.sum(iniVol - newVol))
+        self.assertEqual(0, numpy.sum(iniCOM - newCOM))
+        # Test #2 -> COM=iniCOM, vol = +10% volIni for a dilation of 10%
+        transformation = {'z': [1.1, 1, 1]}
+        PhiField[1] = spam.deformation.computePhi(transformation)
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass)
+        # Compute Volume and COM
+        newVol = spam.label.volumes(imLab2)[-1]
+        newCOM = spam.label.centresOfMass(imLab2)[-1]
+        self.assertEqual(0, numpy.sum(iniCOM - newCOM))
+        self.assertAlmostEqual(1.1, newVol/iniVol, places = 1)
+        # Test #3 -> COM=iniCOM and vol/ iniVol > 1 for dilate = 1 and Phi = I
+        transformation = {'t': [0, 0, 0]}
+        PhiField[1] = spam.deformation.computePhi(transformation)
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass, labelDilate=1)
+        # Compute Volume and COM
+        newVol = spam.label.volumes(imLab2)[-1]
+        newCOM = spam.label.centresOfMass(imLab2)[-1]
+        self.assertEqual(0, numpy.sum(iniCOM - newCOM))
+        self.assertGreater(newVol/iniVol, 1.0)
+        # Test#4 -> vol=iniVol and COM follows the 5vox displacement
+        transformation = {'t': [5, 5, 5]}
+        PhiField[1] = spam.deformation.computePhi(transformation)
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass)
+        # Compute Volume and COM
+        newVol = spam.label.volumes(imLab2)[-1]
+        newCOM = spam.label.centresOfMass(imLab2)[-1]
+        self.assertEqual(0, numpy.sum(iniVol - newVol))
+        self.assertTrue(((newCOM - iniCOM) == 5).all())
+        # Test 5 -> move grain half out and check volume is near 0.5
+        transformation = {'t': [30, 0, 0,]}
+        PhiField[1] = spam.deformation.computePhi(transformation)
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass)
+        # Compute Volume and COM
+        newVol = spam.label.volumes(imLab2)[-1]
+        newCOM = spam.label.centresOfMass(imLab2)[-1]
+        self.assertAlmostEqual(0.5, newVol/iniVol, places = 1)
+        # Test 6A -> Check that it runs when the PhiField has less labels than the labelled image
+        PhiField = numpy.zeros((1, 4, 4))
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass)
+        self.assertIsNotNone(imLab2)
+        # Test 6B -> Check that it runs when the PhiField has more labels than the labelled image
+        PhiField = numpy.zeros((3, 4, 4))
+        imLab2 = spam.label.moveLabels(imLab, PhiField, boundingBoxes = boundingBoxes, centresOfMass = centresOfMass)
+        self.assertIsNotNone(imLab2)
 if __name__ == '__main__':
     unittest.main()

tools/label/label.py

@@ -32,6 +32,7 @@ import math
 import progressbar
 import spam.filters
 import multiprocessing
+import spam.DIC
 
 # Define a random colourmap for showing labels
 #   This is taken from https://gist.github.com/jgomezdans/402500
@@ -1789,12 +1790,13 @@ def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin
     #Create output label image
     labOut = numpy.zeros_like(lab, dtype=spam.label.labelType)
     #Get number of labels
-    numberOfLabels = min(lab.max(), PhiField.shape[0])
+    numberOfLabels = min(lab.max()+1, PhiField.shape[0])
+    
     #Setting up queues
     q_jobs    = multiprocessing.Queue()
     q_results = multiprocessing.Queue()
     #Adding jobs to queues
-    for label in range(1, numberOfLabels+1):
+    for label in range(1, numberOfLabels):
         q_jobs.put(label)
 
     for i in range(NumberOfThreads):  q_jobs.put("STOP")
@@ -1802,7 +1804,7 @@ def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin
     for i in range(NumberOfThreads):
         p = multiprocessing.Process( target=work_on_one_job, args=(i, q_jobs, q_results,))
         p.start()
-        
+
     finished_threads  = 0
     nodes_processed   = 0
     #Waiting for results
@@ -1822,6 +1824,4 @@ def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin
             nodes_processed += 1
             widgets[0] = progressbar.FormatLabel("{}/{} ".format(nodes_processed, numberOfLabels))
             pbar.update(nodes_processed)
-
-            
     return labOut