fixing numberOfThreads typo

tools/filters/morphologicalOperations.py

@@ -308,7 +308,7 @@ def reconstructionFromOppositeFaces(im, dmax=None, verbose=False):
 
     return rec1  # send the reconstructed image
 
-def directionalErosion(bwIm, vect, a, c, NumberOfThreads=1, verbose = False):
+def directionalErosion(bwIm, vect, a, c, numberOfThreads=1, verbose = False):
     """
     This functions performs direction erosion over the binarized image using
     an ellipsoidal structuring element over a range of directions. It is highly
@@ -329,7 +329,7 @@ def directionalErosion(bwIm, vect, a, c, NumberOfThreads=1, verbose = False):
         c : int or float
             Lenght of the principal semi-axis of the structuring element in px
             
-        NumberOfThreads : integer, optional
+        numberOfThreads : integer, optional
             Number of Threads for multiprocessing.
             Default = 1
 
@@ -379,11 +379,11 @@ def directionalErosion(bwIm, vect, a, c, NumberOfThreads=1, verbose = False):
         # qJobs.put( contactList[x,0] )
         qJobs.put(x)
     
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         qJobs.put("STOP")
         
     # print "Master: Launching workers"
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         p = multiprocessing.Process(target=worker, args=(i, qJobs, qResults, ))
         p.start()
         
@@ -392,7 +392,7 @@ def directionalErosion(bwIm, vect, a, c, NumberOfThreads=1, verbose = False):
     finishedThreads = 0
     finishedJobs = 0
     # print "Master: Waiting for results"
-    while finishedThreads < NumberOfThreads:
+    while finishedThreads < numberOfThreads:
         result = qResults.get()
 
         if result == "STOP":

tools/label/contacts.py

@@ -859,7 +859,7 @@ def _markerCorrection(markers, numMarkers, distanceMap, volBin, peakDistance=5,
     return markers
 
 
-def localDetectionAssembly(volLab, volGrey, contactList, localThreshold, boundingBoxes=None, NumberOfThreads=1, radiusThresh=4):
+def localDetectionAssembly(volLab, volGrey, contactList, localThreshold, boundingBoxes=None, numberOfThreads=1, radiusThresh=4):
     """
     Local contact refinement of a set of contacts
     checks whether two particles are in contact with a local threshold using ``localDetection()``
@@ -883,7 +883,7 @@ def localDetectionAssembly(volLab, volGrey, contactList, localThreshold, boundin
             Bounding boxes in format returned by ``boundingBoxes``.
             If not defined (Default = None), it is recomputed by running ``boundingBoxes``
 
-        NumberOfThreads : integer, optional
+        numberOfThreads : integer, optional
             Number of Threads for multiprocessing
             Default = 1
 
@@ -948,12 +948,12 @@ def localDetectionAssembly(volLab, volGrey, contactList, localThreshold, boundin
     for x in range(numberOfJobs):
         qJobs.put( x )
 
-    for i in range( NumberOfThreads ):
+    for i in range( numberOfThreads ):
         qJobs.put( "STOP" )
 
 
     #print ("Master: Launching workers")
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         p = multiprocessing.Process( target=worker, args=( i, qJobs, qResults, ) )
         p.start()
 
@@ -961,7 +961,7 @@ def localDetectionAssembly(volLab, volGrey, contactList, localThreshold, boundin
     finishedThreads = 0
     finishedJobs = 0
     #print ("Master: Waiting for results")
-    while finishedThreads < NumberOfThreads:
+    while finishedThreads < numberOfThreads:
         result = qResults.get()
 
         if result == "STOP":
@@ -980,7 +980,7 @@ def localDetectionAssembly(volLab, volGrey, contactList, localThreshold, boundin
     return numpy.asarray(contactListRefined)
 
 
-def contactOrientationsAssembly(volLab, volGrey, contactList, watershed="ITK", peakDistance=5, boundingBoxes=None, NumberOfThreads=1, verbose=False):
+def contactOrientationsAssembly(volLab, volGrey, contactList, watershed="ITK", peakDistance=5, boundingBoxes=None, numberOfThreads=1, verbose=False):
     """
     Determines contact normal orientation in an assembly of touching particles
     uses either directly the labelled image or the random walker implementation from skimage
@@ -1012,7 +1012,7 @@ def contactOrientationsAssembly(volLab, volGrey, contactList, watershed="ITK", p
             Bounding boxes in format returned by ``boundingBoxes``.
             If not defined (Default = None), it is recomputed by running ``boundingBoxes``
 
-        NumberOfThreads : integer, optional
+        numberOfThreads : integer, optional
             Number of Threads for multiprocessing.
             Default = 1
             
@@ -1078,11 +1078,11 @@ def contactOrientationsAssembly(volLab, volGrey, contactList, watershed="ITK", p
         # qJobs.put( contactList[x,0] )
         qJobs.put(x)
 
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         qJobs.put("STOP")
 
     # print "Master: Launching workers"
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         p = multiprocessing.Process(target=worker, args=(i, qJobs, qResults, ))
         p.start()
 
@@ -1090,7 +1090,7 @@ def contactOrientationsAssembly(volLab, volGrey, contactList, watershed="ITK", p
     finishedThreads = 0
     finishedJobs = 0
     # print "Master: Waiting for results"
-    while finishedThreads < NumberOfThreads:
+    while finishedThreads < numberOfThreads:
         result = qResults.get()
 
         if result == "STOP":

tools/label/label.py

@@ -1331,7 +1331,7 @@ class Spheroid:
         x = numpy.mgrid[slices]
         return self.criterion(x)<=1.0
 
-def fixUndersegmentation(imLab, imGrey, listLabels, a, c, numVect = 100, vect = None, boundingBoxes = None, centresOfMass = None, NumberOfThreads = 1, verbose = False):
+def fixUndersegmentation(imLab, imGrey, listLabels, a, c, numVect=100, vect=None, boundingBoxes=None, centresOfMass=None, numberOfThreads=1, verbose=False):
     """
     This function fix undersegmented particles using directional erosion over the particle
     to get the seed for a new localized watershed. 
@@ -1361,7 +1361,7 @@ def fixUndersegmentation(imLab, imGrey, listLabels, a, c, numVect = 100, vect =
         c : int or float
             Lenght of the principal semi-axis of the structuring element
 
-        NumberOfThreads : integer (optional, default = 1)
+        numberOfThreads : integer (optional, default = 1)
             Number of Threads for multiprocessing of the directional erosion.
             Default = 1
 
@@ -1435,7 +1435,7 @@ def fixUndersegmentation(imLab, imGrey, listLabels, a, c, numVect = 100, vect =
         while Continue == False:
             #Directional Erosion
             imEroded = spam.filters.morphologicalOperations.directionalErosion(bwIm, vect, 
-                                                                               a, c, NumberOfThreads = NumberOfThreads, 
+                                                                               a, c, numberOfThreads = numberOfThreads, 
                                                                                verbose = verbose)
             #Label the markers
             markers, num_seeds = scipy.ndimage.label(imEroded)
@@ -1536,7 +1536,7 @@ def fixUndersegmentation(imLab, imGrey, listLabels, a, c, numVect = 100, vect =
     return imLab
 
 
-def convexVolume(lab, boundingBoxes = None, centresOfMass = None, volumes = None, NumberOfThreads = 1, verbose = True):
+def convexVolume(lab, boundingBoxes=None, centresOfMass=None, volumes=None, numberOfThreads=1, verbose=True):
     """
     This function compute the convex hull of each label of the labelled image and return a 
     list with the convex volume of each particle. 
@@ -1558,7 +1558,7 @@ def convexVolume(lab, boundingBoxes = None, centresOfMass = None, volumes = None
             Volumes in format returned by ``volumes``
             If not defined (Default = None), it is recomputed by running ``volumes``
 
-        NumberOfThreads : integer (optional, default = 1)
+        numberOfThreads : integer (optional, default = 1)
             Number of Threads for multiprocessing
             Default = 1
 
@@ -1622,11 +1622,11 @@ def convexVolume(lab, boundingBoxes = None, centresOfMass = None, volumes = None
     # print "Master: Adding jobs to queues"
     for x in range(1,numberOfJobs+1):
         qJobs.put(x)
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         qJobs.put("STOP")
         
     # print "Master: Launching workers"
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         p = multiprocessing.Process(target=worker, args=(i, qJobs, qResults, ))
         p.start()
     
@@ -1635,7 +1635,7 @@ def convexVolume(lab, boundingBoxes = None, centresOfMass = None, volumes = None
     finishedThreads = 0
     finishedJobs = 0
     # print "Master: Waiting for results"
-    while finishedThreads < NumberOfThreads:
+    while finishedThreads < numberOfThreads:
         result = qResults.get()
 
         if result == "STOP":
@@ -1653,7 +1653,7 @@ def convexVolume(lab, boundingBoxes = None, centresOfMass = None, volumes = None
 
     return convexVolume
 
-def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin = 3, PhiCOM = True, threshold = 0.5, labelDilate = 0, NumberOfThreads = 1):
+def moveLabels(lab, PhiField, boundingBoxes=None, centresOfMass=None, margin=3, PhiCOM=True, threshold=0.5, labelDilate=0, numberOfThreads=1):
     """
     This function applies a discrete Phi field (from DDIC?) over a labelled image.
 
@@ -1690,7 +1690,7 @@ def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin
             If ``labelDilate > 0`` a dilated label is returned, while ``labelDilate < 0`` returns an eroded label.
             Default = 0
             
-        NumberOfThreads : int, optional
+        numberOfThreads : int, optional
             Number of Threads for multiprocessing
             Default = 1
             
@@ -1799,9 +1799,9 @@ def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin
     for label in range(1, numberOfLabels):
         q_jobs.put(label)
 
-    for i in range(NumberOfThreads):  q_jobs.put("STOP")
+    for i in range(numberOfThreads):  q_jobs.put("STOP")
     #Launching workers
-    for i in range(NumberOfThreads):
+    for i in range(numberOfThreads):
         p = multiprocessing.Process( target=work_on_one_job, args=(i, q_jobs, q_results,))
         p.start()
 
@@ -1812,7 +1812,7 @@ def moveLabels(lab, PhiField, boundingBoxes = None, centresOfMass = None, margin
     pbar = progressbar.ProgressBar(widgets=widgets, maxval=numberOfLabels)
     pbar.start()
 
-    while finished_threads < NumberOfThreads:
+    while finished_threads < numberOfThreads:
         result = q_results.get()
 
         if result == "STOP":