Examples

BoneJ Module

import numpy as np
import nrrd
import os
import subprocess
import tempfile
import sys
import matplotlib.pyplot as plt
import tifffile as tiff
from contextlib import contextmanager
import sys, os

from BoneJ_Module import Thickness
from BoneJ_Module import Spacing
from BoneJ_Module import Area_VolumeFraction
from BoneJ_Module import Connectivity
from BoneJ_Module import Anisotropy
from BoneJ_Module import Ellipsoid_Factor

array,array1header = nrrd.read(volume)
voxel_size = [51.29980, 51.29980, 51.29980] #microns
fiji_path = "~/Fiji.app/ImageJ-linux64"

if __name__ == "__main__":
     Thickness_result = Thickness(array,voxel_size,fiji_path,showMaps = True, maskArtefacts = True)
     Spacing_result = Spacing(array,voxel_size,fiji_path,showMaps = True, maskArtefacts = True)
     Area_VolumeFraction_result = Area_VolumeFraction(array,voxel_size,fiji_path)
     Connectivity_result = Connectivity(array,voxel_size,fiji_path)
     Anisotropy_result = Anisotropy(array,voxel_size,fiji_path,NDirs = 2000, nLines = 10000, samplingincrement = 1.73,
     radii = False, eigens = False)
     Ellipsoid_Factor(array, voxel_size, fiji_path,nVectors = 100,vectorIncrement =.435,skipRatio =1,contactSensitivity = 1
     ,maxIterations = 100,maxDrift = .4,runs = 1,seedOnDistanceRidge = True,distanceThreshold = .6,seedOnTopologyPreserving = True
     ,showFlinnPlots = True,showConvergence = True,showSecondaryImages = True,showMaps = True)

BoneJ Secondary Module

import numpy as np
import nrrd
import csv
import os
import subprocess
from glob import glob
import tempfile
import sys
import matplotlib.pyplot as plt
import tifffile as tiff
from contextlib import contextmanager
import sys, os

from BoneJ_Module import Fractal_Dimension
from BoneJ_Module import Surface_Area
from BoneJ_Module import Analyze_Skeleton
from BoneJ_Module import Intertrabecular_Angles
from BoneJ_Module import Skeletonise

array,array1header = nrrd.read(volume)
voxel_size = [51.29980, 51.29980, 51.29980] #microns
fiji_path = "~/Fiji.app/ImageJ-linux64"

if __name__ == "__main__":
    Fractal_Dimension_Results = Fractal_Dimension(array,voxel_size,fiji_path,startBoxSize=48,smallestBoxSize=6,scaleFactor=1.2,autoParam=False)
    Surface_Area_Result= Surface_Area(array,voxel_size,fiji_path)
    Analzye_Skeleton_Result = Analyze_Skeleton(array,voxel_size,fiji_path,pruneCycleMethod=None,pruneEnds=True,excludeRoi=False,calculateShortestPaths=True,verbose=True,displaySkeletons=True)
    Intertrabecular_Angles_Result =                 Intertrabecular_Angles(array,voxel_size,fiji_path,minimumValence=3,maximumValence=50,marginCutOff=10,minimumTrabecularLength=0,iteratePruning=False,printCentroids=False,useClusters=False,printCulledEdgePercentages=False)
    Skeletonise_Result=Skeletonise(array,voxel_size,fiji_path)

Anisotropy Parameter Convergence

import numpy as np
import nrrd
import csv
import os
import subprocess
from glob import glob
import tempfile
import sys
import matplotlib.pyplot as plt
from contextlib import contextmanager
import sys, os


array,array1header = nrrd.read(volume)  # should be a numpy array
voxel_size = [51.29980, 51.29980, 51.29980] #microns
fiji_path = "~/Fiji.app/ImageJ-linux64"


# feed in numpy array

nLines_list = [1,2,4,8,16,32,64,128,256,512,1024,2048,4096,8192,16384]
NDirs_list = [16,32,64,128,256,512,1024,2048,4096,8192]
csv_dir = "/BoneJ_Headless/Anisotropy_Convergence_Test.csv" #location of csv file storing anisotropy convergence measurements
from Anisotropy_Parameter_Convergence import Anisotropy_Convergence

if __name__ == "__main__":
  Anisotropy_convergence_result=Anisotropy_Convergence(array,voxel_size,fiji_path,NDirs=NDirs_list, nLines=nLines_list, samplingincrement=1.73, radii=False, eigens=False,csv_dir=csv_dir)

Ellipsoid Factor Convergence

import numpy as np
import nrrd
import csv
import os
import subprocess
from glob import glob
import tempfile
import sys
import matplotlib.pyplot as plt
from contextlib import contextmanager
import sys, os


array,array1header = nrrd.read(volume)  # should be a numpy array
voxel_size = [51.29980, 51.29980, 51.29980] #microns
fiji_path = "~/Fiji.app/ImageJ-linux64"


# feed in numpy array

nLines_list = [1,2,4,8,16,32,64,128,256,512,1024,2048,4096,8192,16384]
NDirs_list = [16,32,64,128,256,512,1024,2048,4096,8192]
csv_dir = "/BoneJ_Headless/Ellipsoid_Factor_Convergence_Test.csv" #location of csv file storing anisotropy convergence measurements

from Ellipsoid_Factor_Convergence import Ellipsoid_Factor_Convergence

if __name__ == "__main__":
    Ellipsoid_Factor_result = Ellipsoid_Factor_Convergence(array,voxel_size,fiji_path,csv_dir=csv_dir,nVectors = nVectors_list,
    vectorIncrement = VectorIncrement_list,
    skipRatio = skipRatio_list,
    contactSensitivity = contactSensitivity_list,
    maxIterations = maxIterations_list,
    maxDrift = maxDrift_list,
    runs = 1,
    seedOnDistanceRidge = True,
    distanceThreshold = .8,
    seedOnTopologyPreserving = True,
    showFlinnPlots = False,
    showConvergence = False)