pacManPipelines/Daniel7050AlPowder-AnalysisV2.py at main · sinclai3/pacManPipelines · GitHub

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""" 2021-09-03 @EG
Main code for the individual segmentation of particles - FGM datasets

This code uses the Segment module to convert the binary data to labelled map

The input needs to be in tiff format, preferably 8 bit
The output will be in tiff as well - labelled map

The particles will be analyzed

"""

#Imports
import tifffile as tf
from pac import Segment
from pac import Measure
from pac import Plot
import matplotlib

# Input and output locations (don't change):


ifl = '/home/chawlahpc2adm/Desktop/Daniel/RAMpowder/Input/'
ofl = '/home/chawlahpc2adm/Desktop/Daniel/RAMpowder/Output/'


# Change name of the file here
dataFile = ifl + 'Binarized AA7050RAM2 Powder Large Area 643x643x969.tif'
dataName = 'Al_643x643x(200-400)zyx_8h_rr09' # Change this to have different output file names

#Reading binary data
#binMap = tf.imread(dataFile)[800:1000]
binMap = tf.imread(dataFile) [200:400]

# Getting EDM
edmMap = Segment.obtainEuclidDistanceMap( binaryMapForEDM=binMap,
	                                   scaleUp = int(1),
	                                   saveImg=True,
	                                   sampleName=dataName,
	                                   outputDir=ofl )

# Getting peaks of EDM
edmPeaksMap = Segment.obtainLocalMaximaMarkers( edMapForPeaks=edmMap,
	                                         h=5, # Decrease this to capture more ptcls
	                                         sampleName=dataName,
	                                         saveImg=True,
	                                         outputDir=ofl )

# Watershed segmentation (without segmentation line)
labMap = Segment.segmentUsingWatershed( binaryMapToSeg=binMap,
	                                 edmMapForTopo=edmMap,
	                                 edmPeaksForSeed=edmPeaksMap,
	                                 sampleName=dataName,
	                                 saveImg=True,
	                                 outputDir=ofl)
	                                 #addWatershedLine=False)

# Correcting watershed segmentation
corLabMap = Segment.fixErrorsInSegmentation( labelledMapForOSCorr=labMap,
	                                      pad=int(2),
	                                      areaLimit=700,
	                                      considerEdgeLabels=True,
	                                      checkForSmallParticles=True,
	                                      radiusCheck=True,
	                                      radiusRatioLimit=0.95, # Lower - more aggressive merging
	                                      sampleName=dataName,
	                                      saveImg=True,
	                                      outputDir=ofl )

noEdgeCorLabMap = Segment.removeEdgeLabels( labelledMapForEdgeLabelRemoval=corLabMap,
					       pad=0,
					       sampleName=dataName,
					       saveImg=True,
					       outputDir=ofl)

# Particle size anaysis on corlabMap
Measure.getParticleSizeArray( labelledMapForParticleSizeAnalysis = noEdgeCorLabMap,
				calibrationFactor=1,	# mm per voxel
				saveData=True,
				sampleName=dataName,
				outputDir=ofl)

# Orientation of major axis of particle
ortsTable = Measure.getPrincipalAxesOrtTable( labelMapForParticleOrientation = noEdgeCorLabMap,
						saveData=True,
					    	sampleName=dataName,
						outputDir=ofl)

# Plot orientations
Plot.plotOrientationsSPAM(ortsTable[:,1:],
                         projection="lambert",
                         plot="both",
                         binValueMin=0,
                         binValueMax=20,
                         binNormalisation = False,
                         numberOfRings = 9,
                         # the size of the dots in the points plot (5 OK for many points, 25 good for few points/debugging)
                         pointMarkerSize = 8,
                         cmap = matplotlib.pyplot.cm.Reds,
                         title = "",
                         subtitle = {"points":"","bins":""},
                         saveFigPath = ofl,
                         sampleName=dataName,
                         figXSize = 12,
                         figYSize = 4.8,
                         figFontSize = 15,
                         labelName = 'Number of particles')