A condor script for filtering and thresholding a given image using a number of different parameters

batchimage.condor

##################################################################
##
## Run a parameter sweep with threshold and filter using condor
##	Filename: batchimage.condor
##
##################################################################


universe	= vanilla
getenv		= True		# MATLAB needs local environment

#initialdir	= /home/foo/src/matlab
my_prefix	= FilterTest

#
# Seek max floating point performance
#
Rank		= Kflops

#
# Filter and Threshold Settings
#
thresh_count= 30
filter_count = 1
job_count	= $(thresh_count) * $(filter_count)
threshold_start	= 0.25
threshold_end	= 0.75

#
# MATLAB does all the math there,
# Condor just does string substitution
#
cur_threshold	= ( $(threshold_start) + ($(threshold_end) - $(threshold_start))*$(Process)/$(thresh_count) )
cur_filter = 1

#
# The name of the image file we want MATLAB to write
#
my_file		= $(my_prefix).t.$(Process).csv

#
# For MATLAB and other SEPP packages, the executable must be a script wrapper.
#
executable	= filterandthreshold.sh
arguments	= saveresults('input_image.jpg',$(cur_threshold), '$(my_file)')

#
# To redirect stdout and/or stderr to /dev/null, comment these out.
#
log		= $(my_prefix).log
output		= $(my_prefix).$(Process).out
error		= $(my_prefix).$(Process).err

#
# Lastly, tell condor how many jobs to queue up.
#
queue $(job_count)

ellipsoid_analysis.m

% this function (will) performs the ellipsoid based shape analysis on a 3D image
% the input is a labeled image probably from the bwlabel function
% the output is an array formatted like such
% labelId, volume, centerX, centerY, centerZ, extentsX, extentsY, extentsZ, pca1X, pca1Y, pca1Z, score1, score2, score3
function [out_table]=ellipsoid_analysis(in_image,out_file)
% create an array the same size as the image of x,y, and z points. This way we can calculate
% center of volume and other parameters by using multiplication
[xgrid,ygrid,zgrid]=meshgrid(1:size(in_image,1),1:size(in_image,2),1:size(in_image,3));

num_of_obj=max(in_image(:));

% assign the columns to the output table

col_names={'label','volume','cov_x','cov_y','cov_z','ext_x','ext_y','ext_z','pca1_x','pca1_y','pca1_z','score_1','score_2','score_3'};

num_of_outputs=length(col_names);
% initialize the output array
out_table=zeros(num_of_obj,num_of_outputs);

for cur_obj = 1 : num_of_obj
    % save the label and the volume
    out_table(cur_obj,getnameidx(col_names,'label'))=cur_obj;
    out_table(cur_obj,getnameidx(col_names,'volume'))=sum(in_image(:)==cur_obj);
    
    % get the x,y, and z positions of each voxel
    xpts=xgrid(in_image==cur_obj);
    ypts=ygrid(in_image==cur_obj);
    zpts=zgrid(in_image==cur_obj);
    
    out_table(cur_obj,getnameidx(col_names,'cov_x'))=mean(xpts);
    out_table(cur_obj,getnameidx(col_names,'cov_y'))=mean(ypts);
    out_table(cur_obj,getnameidx(col_names,'cov_z'))=mean(zpts);
    
    % extents analysis
    out_table(cur_obj,getnameidx(col_names,'ext_x'))=range(xpts);
    out_table(cur_obj,getnameidx(col_names,'ext_y'))=range(ypts);
    out_table(cur_obj,getnameidx(col_names,'ext_z'))=range(zpts);
    
    % shape tensor analysis
    covar_pts=cov([xpts(:) ypts(:) zpts(:)]);
    % in case it is only one point
    if (prod(size(covar_pts))<9)
        covar_pts=ones(3);
    end
 
    
    % save the first (largest) eigenvector as pca1, 
    % and the scores (eigenvalues) as score1...
    [evec,evals]=eig(covar_pts);
    evals=diag(evals); % scores are in a diagonal matrix
    first_comp=evec(:,3);
    out_table(cur_obj,getnameidx(col_names,'pca1_x'))=first_comp(1);
    out_table(cur_obj,getnameidx(col_names,'pca1_y'))=first_comp(2);
    out_table(cur_obj,getnameidx(col_names,'pca1_z'))=first_comp(3);
    
    out_table(cur_obj,getnameidx(col_names,'score_1'))=evals(3);
    out_table(cur_obj,getnameidx(col_names,'score_2'))=evals(2);
    out_table(cur_obj,getnameidx(col_names,'score_3'))=evals(1);
    
end
% make and write the header
header_txt=sprintf('%s,',col_names{:});
header_txt(end)=''; % delete the last comma
dlmwrite(out_file,header_txt,'');
% write the table
dlmwrite(out_file,out_table,'-append','delimiter',',');

filterandthreshold.m

%
%	Filename: filterandthreshold.m
% Performs the filtering, thresholding and component labeling
%
function [label_img]=filterandthreshold(in_image,threshold_value)
filt_image=medfilt2(in_image,[3,3]);
thresh_img=filt_image<=threshold_value;
label_img=bwlabel(thresh_img);

filterandthreshold.sh

#!/bin/sh
#
#	Filename: mandelbrot.sh

#
# We use a shell wrapper for two reasons:
#
#   1)	By using "$*" we ensure that the matlab command string is
#	passed as a single argument even if it contains spaces.
#
#   2)	Condor changes argv[0], which causes problems for SEPP.  Hence,
#	whenever we run a program from /usr/sepp/bin/* we must use a
#	shell script wrapper.
#
exec /usr/sepp/bin/matlab  -nojvm -nodisplay -nodesktop -nosplash -r "$*"

input_image.jpg

saveresults.m

%
%	Filename: saveresults.m
%
function saveresults(im_name,threshold_value,filename)
gray_img=imread(im_name);
% run the filter / threshold
lab_img=filterandthreshold(gray_img,threshold_value);
% run shape analysis
ellipsoid_analysis(lab_img,filename);