18_06_06

In the program PoreSizeDistriution_(ErosionDiltation)_Python.py
I realized I ccould eliminate the loop for the erosion
Time of the execution was reduced to a little more of 50% of the last
version

In Segmentation_Hashemi.py
I just added some coments on how to produce the inputs of the function
bu using some commands in ImageJ

PoreSizeDistriution_(ErosionDiltation)_Jython.py

@@ -9,7 +9,7 @@ def Pore_Size_Distribution(Dir, FileName):
 
 	from os import path, chdir
 	assert (path.isdir(Dir)) , "Folder IS NOT A FOLDER: " + folder
-	assert (path.exists(FileName)) , "FILE DOES NOT EXIST: " + File_Top_Image
+	assert (path.exists(FileName)) , "FILE DOES NOT EXIST: " + FileName
 	
 	# Reading Segmented Image
 	# Imp is the air-phase (this is the result of the Hashemi's segmentation, by Hashemi's method normally)
@@ -37,18 +37,15 @@ def Pore_Size_Distribution(Dir, FileName):
 	print('Max Radius:', Max_radius)
 	
 	from ij import ImagePlus
+	Erosion = ImagePlus('Erosion', Imp_Air.getImageStack())
+	Erosion.show()
 	for Radius in range(1,Max_radius):
 	    print('Step: Radius of erosion (in pixels) = ', Radius)
 	    
 	    # Computing erosions
-	    Erosion = ImagePlus('Erosion', Imp_Air.getImageStack())
-	    Erosion.show()
-	    for repeat in range(Radius):
-	        IJ.run(Erosion, "Erode (3D)", "iso=255")
-	
+	    IJ.run(Erosion, "Erode (3D)", "iso=255") # IJ.run("Erode 3D") is a change in place method (there is no need to reasign the result of the Erosion)
 	    # Computing dilations  
 	    Dilation = ImagePlus('Dilation', Erosion.getImageStack())
-	    Dilation.show()
 	    for repeat in range(Radius):
 	        IJ.run(Dilation, "Dilate (3D)", "iso=255")
 	
@@ -62,7 +59,6 @@ def Pore_Size_Distribution(Dir, FileName):
 	    Volume = Initial - Remaining
 	    Cum_Volumes.append(Volume)
 	    # Breaking if procedure completed
-	    Erosion.close()
 	    Dilation.close()
 	    if Remaining == 0:
 	        break
@@ -75,8 +71,13 @@ def Pore_Size_Distribution(Dir, FileName):
 		File.write(str(Radii[i]) + ',' + str(Cum_Volumes[i]) + '\n')
 	File.close()
 	print("Finished !")    
-    
+
+
+
 # MAIN
+# Report start-time of the execution
+import datetime
+Start = datetime.datetime.today() 
 # Directory and File Name
 Dir  = '/home/german.martinez-carvajal/Desktop/2018/Pore_Size_Distribution/Test'
 #Dir  = '/home/german.martinez-carvajal/Desktop/2017/Tomographie/170411COP/Segmentation(Hashemi)'
@@ -84,4 +85,12 @@ FileName = Dir + "/" + "Binary.tif"
 #FileName = Dir + "/" + "Air.tif"
 # Calling the function
 Pore_Size_Distribution(Dir, FileName)
-    
\ No newline at end of file
+# Report end-time of the execution
+End = datetime.datetime.today()
+# Saving report
+from os import chdir
+chdir (Dir)
+File = open('Time_Report.txt', mode = 'w')
+File.write('Start time: ' + str(Start) + '\n')
+File.write('End   time: ' + str(End  ) + '\n')
+File.close()
\ No newline at end of file

Segmentation_Hashemi.py

@@ -9,6 +9,8 @@ def Segmentation_Hashemi(Dir, Scan_File,PVE_File, Mu = None):
     Dir       : The directory were the files are read and written
     Scan_File : .tif  3D-image in 8-bit or 16-bit. It should be filtered before (Use 3D median filter in ImageJ)
     PVE_File  : .tif  3D-image in 8-bit (same size as Scan_File). It is binary, white pixels (255 in 8-bit) represent pixels of the Partial Volume Effect
+                In imageJ Use the command: Process-Find Edges (Warning, this is a 2D operation)
+                Then binarize using the defalut ImageJ thresholding method
     Mu        : a list with three integers values that will be the initialisation in the fitting of gaussians of the gray value histogram , if None, they
                 will be initialised by some values depending our experience