scripts to generate figures, fig. 5 (top), supp. fig. (algofig)

code/spatialstats/norms.m

@@ -0,0 +1,8 @@
+function [Xn,nmz] = norms(X)
+
+% normalize the columns of X
+nmz = sqrt(sum(X.^2));
+Xn = X./repmat(nmz,size(X,1),1);
+
+
+end

code/spatialstats/script_fig5.m

@@ -0,0 +1,61 @@
+% script_fig5
+% creates top panel of Figure 5
+
+load('finalresults-cell2vesseldist.mat')
+load('centroids_rfr1.mat')
+
+dist_vessel = nndist; clear nndist
+out = knnsearch(Centroids(:,1:3),Centroids(:,1:3),'K',2);
+nncell = out(:,2)';
+dist_cell = sqrt(sum(((Centroids(:,1:3)-Centroids(nncell,1:3))').^2))';
+
+% compute cell density (nn approach)
+k=5; % dvec = cell density estimates over volume
+[pout,pts,volvox,dvec,numvox] = knndensityest(Centroids(:,1:3),k);
+
+%%
+figure;
+subplot(131);
+hist(dvec,linspace(0,6e5))
+axis tight
+title('Distribution of cell density over volume')
+xlabel('cell density (x 10^5 cells/cubic mm)')
+ylabel('counts')
+
+subplot(132);
+hist(dist_cell*0.65,linspace(0,140,100))
+axis tight
+title('Distances from cell centers to closest cell center')
+xlabel('cubic microns')
+ylabel('neurons')
+
+
+subplot(133);
+hist(dist_vessel*0.65,linspace(0,140,100))
+axis tight
+title('Distances from cell centers to closest vessel voxel')
+xlabel('cubic microns')
+ylabel('neurons')
+
+sample_stats.celldensity_mean = mean(dvec);
+sample_stats.celldensity_var = var(dvec);
+
+sample_stats.ccdist_mean = mean(dist_cell);
+sample_stats.ccdist_var = var(dist_cell);
+
+sample_stats.cvdist_mean = mean(dist_vessel);
+sample_stats.cvdist_var = var(dist_vessel);
+
+sample_stats.totstats = [mean(dvec),var(dvec),mean(dist_cell), var(dist_cell), mean(dist_vessel),var(dist_vessel)];
+
+
+%%
+% visualize density
+figure; 
+for i=1:size(pout,3); 
+    imagesc(log(pout(:,:,i)),[min(log(pout(:))),max(log(pout(:)))]), 
+    pause, 
+end
+
+
+

code/spatialstats/script_stats_fig4.m

@@ -1,4 +1,6 @@
-%
+
+load('centroids_rfr1.mat') % in /xbrain/results
+load('traindata-celldetect-V1.mat') % /xbrain/data/groundtruth/V1
 
 id1 = find((Centroids(:,4)<0.9).*(Centroids(:,4)>=0.7));
 id2 = find((Centroids(:,4)<0.7).*(Centroids(:,4)>=0.5));
@@ -31,9 +33,9 @@
 x0 = [x0; [xx1(:), yy1(:), zz1(:)]];
 
 clear C1
-C1(:,1) = Centroids_ed0(1,:)+xmin; 
-C1(:,2) = Centroids_ed0(2,:)+ymin; 
-C1(:,3) = Centroids_ed0(3,:)+zmin;
+C1(:,1) = Centroids_gt(1,:)+xmin; 
+C1(:,2) = Centroids_gt(2,:)+ymin; 
+C1(:,3) = Centroids_gt(3,:)+zmin;
 
 %%
 

code/spatialstats/script_statsnviz.m

@@ -3,7 +3,7 @@
 minsz = 500; % minimum number of voxels for conn comps (set rest to zero)
 
 %% Load nii file (with segmentation)
-Gt = load_nii('proj4_x1351-1650_y1851-2150_z395-495_r0_cube1_eva5.nii');
+Gt = load_nii('proj4_x1351-1650_y1851-2150_z395-495_r0_cube1_anno_eva8.nii');
 
 % neuron and vessel segmentation
 Nmap = (Gt.img==1);
@@ -16,11 +16,23 @@
 % (3) distance from centroid of cell to closest vessel
 % (4) 
 
-Results = computedensitystats(Nmap,Vmap,minsz,erodesz,maxdist);
+maxdist=10;
+Results = computedensitystats(Nmap,Vmap,maxdist);
 
 corr = visualizecorrelations(Results);
 
+
 %%
+
+
+
+
+
+
+
+
+%% this part isnt working.
+
 % cluster cells based upon their size
 labels = kmeans(numvox_nb,numclust);
 [val,id] = sort(labels);