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Copy pathPlot3d_pure_column_Radius_Of_Curvature.m
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Plot3d_pure_column_Radius_Of_Curvature.m
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clear all
dt_path_wt={ '../data/Nuclei_and_Cells_DT_S18_m6_wt/', '../data/Nuclei_and_Cells_DT_S17_m2_wt/',...
'../data/Nuclei_and_Cells_DT_S84_m3_wt/', '../data/Nuclei_and_Cells_DT_S51_m2_wt/',...
'../data/Nuclei_and_Cells_DT_S84_m4_wt/'};
pt_path_wt = { '../data/Nuclei_and_Cells_PT_S18_m6_wt/','../data/Nuclei_and_Cells_PT_S17_m2_wt/',...
'../data/Nuclei_and_Cells_PT_S84_m3_wt/','../data/Nuclei_and_Cells_PT_S51_m2_wt/',...
'../data/Nuclei_and_Cells_PT_S84_m4_wt/'};
dt_path_mut= {'../data/Nuclei_and_Cells_DT_S17_m1_mut/', '../data/Nuclei_and_Cells_DT_S18_m2_mut/' ,...
'../data/Nuclei_and_Cells_DT_S84_m1_mut/', '../data/Nuclei_and_Cells_DT_S84_m5_mut/'};
pt_path_mut = {'../data/Nuclei_and_Cells_PT_S17_m1_mut/', '../data/Nuclei_and_Cells_PT_S18_m2_mut/',...
'../data/Nuclei_and_Cells_PT_S84_m1_mut/', '../data/Nuclei_and_Cells_PT_S84_m5_mut/', };
du_path_wt={'../data/Nuclei_and_Cells_DU_S51_m2_wt/','../data/Nuclei_and_Cells_DU_S84_m2_wt/','../data/Nuclei_and_Cells_DU_S84_m3_wt/'};
allpath={dt_path_wt; pt_path_wt; dt_path_mut; pt_path_mut; du_path_wt};
%allpath={du_path_wt};
% the columns contains the individual nuclei features
% 1 - stack id
% 2 - volume
% 3 - surface area
% 4 - sphericity
% 5-7 - centroid x,y,z coordinates
% 8-10 - PC1 x,y,z orientation
% 11-13 - PC2 x,y,z orientation
% 14-16 - PC3 x,y,z orientation
% 17-19 - PC1,PC2,PC3 latent coefficient
% 20 - Delaunay density
mycolor={'r.','b.','g.','m.','k.'};
nucallcolor={'r--','b--','g--','m--','k--'};
fcelallcolor={'ro-','bo-','go-','mo-','ko-'};
fnucallcolor={'ro--','bo--','go--','mo--','ko--'};
meanOfAllCelltemp=load('meanOfAllCell.dat');
count=1;
for gi=1:length(allpath)
for gj=1:length(allpath{gi})
GlobalCenter{gi}{gj}=meanOfAllCelltemp(count,1:3);
count=count+1;
end
end
data=[];
for gi=1:length(allpath)
bonetype=gi;
for gj=1:length(allpath{gi})
h=figure;
path=allpath{gi}{gj}
s=strsplit(path,'Nuclei_and_Cells_');
input1=strcat('MakeListColumnarStructurePrediction/',s{2});
input2=strcat('Cluster_Structure_Prediction/',s{2});
% if bonetype==5
% ns=strsplit(path,'U_');
% else
% ns=strsplit(path,'T_');
% end
%outputpath=strcat('Columnar_Structure_Prediction_8_100/',s{2});
load(['MakeListColumnarStructurePrediction/',s{2},'centroid_and_surface_cells.mat'],'centroid','nuc');
a1=load([input1,'NeighboringCell_in_20_micron_cube.dat']);
edges=a1(:,[1,2]); [~,ia]=unique(edges,'rows');
edges=edges(ia,:);
disp('start LCC')
LCCall=LargestConnectedComponents(edges);
pureColumn=load(['degree_of_the_column/StraightLine/pureColum_',s{2}(1:strlength(s{2})-1),'.dat']);
a1=load(['./../../',path,'all_cells_nuclei.mat']);
nucleiFeatures=a1.all_cells_nuclei;
nuccent=nucleiFeatures(:,5:7);
C=mean(nuccent); zgap=max(nuccent(:,3))-min(nuccent(:,3));
s=strsplit(path,'Nuclei_and_Cells_');
outputpath=strcat('Columnar_Structure_Prediction_8_100/',s{2});
if (bonetype==3)|(bonetype==1)
%zmin=-zmin; zmax=-zmax;
bonetypeMatrix=[1,0,0;0 1 0;0, 0,-1];
nuccent1=(nuccent-C)*bonetypeMatrix;
GlobCent=GlobalCenter{gi}{gj};
nuccent2=(nuccent-GlobCent*bonetypeMatrix)*bonetypeMatrix;
else
%zmin=zmin+70; zmax=zmax+70;
bonetypeMatrix=[1,0,0;0 1 0;0, 0,1];
nuccent1=(nuccent-C)*bonetypeMatrix;
GlobCent=GlobalCenter{gi}{gj};
nuccent2=(nuccent-GlobCent*bonetypeMatrix)*bonetypeMatrix;
end
%[C, GlobalCenter{gi}{gj}]
%[min(nuccent1(:,3)), min(nuccent2(:,3)), max(nuccent1(:,3)), max(nuccent2(:,3))]
[CurvatureAxisLine,~]=movingMeanAverage(nuccent2);
%dlmwrite(['Curvature/CurvLine_',s{2}(1:strlength(s{2})-1),'.dat'],CurvatureAxisLine,'\t');
bone_curvature=CurvatureAxisLine;
CC=plotClusterFigure(bone_curvature, pureColumn,LCCall,centroid,nuc, C, bonetypeMatrix,'r.');
%save(['Curvature/Column_curvature_',s{2}(1:strlength(s{2})-1),'.mat'], 'CurvatureOfColumn');
dlmwrite(['RadiusOfCurvature/ROC_',s{2}(1:strlength(s{2})-1),'.dat'], [CC.RadiusOfCurvature,CC.sphFit(:,[2]),CC.ColumnPos_PDaxis],'\t');
RadOfCurv=CC.sphFit; t=find(~isnan(RadOfCurv(:,4)));
method1=corrcoef(RadOfCurv(t,1),RadOfCurv(t,2));
method2=corrcoef(RadOfCurv(t,3),RadOfCurv(t,4));
[gi,gj,method1(1,2),method2(1,2)]
shp = alphaShape(nuccent1);
[tetrahedron,V] = alphaTriangulation(shp);
trep = triangulation(tetrahedron, V);
[tri, V] = freeBoundary(trep);
plot3( V(:,1), V(:,2), V(:,3),'b.','markersize',0.01);
hold on
plot3( CurvatureAxisLine(:,1), CurvatureAxisLine(:,2), CurvatureAxisLine(:,3),'r.-');
title('Curvature axis line','fontweight','normal')
axis image
xlabel('X')
ylabel('Y')
zlabel('P-D axis')
view(-38,30)
savefolder='Curvature/figure_Curvature_column/';
if ~exist([savefolder],'dir')
mkdir([savefolder]);
end
saveas(h,[savefolder,'curvatureAxisLine_',s{2}(1:strlength(s{2})-1),'.png'])
saveas(h,[savefolder,'curvatureAxisLine_',s{2}(1:strlength(s{2})-1),'.fig'])
close all
end
end
function [CurvatureAxisLine,dd]=movingMeanAverage(nuccent)
zmin=min(nuccent(:,3)); zmax=max(nuccent(:,3));
interval=zmin-0.001:1:zmax+0.001;
count=1;
for i=1:length(interval)
left=interval(i)-100;
right=interval(i)+100;
index=find((nuccent(:,3)>=left) & (nuccent(:,3)<right));
if length(index)>=100
CurvatureAxisLine(count,:)=mean(nuccent(index,:));
count=count+1;
end
end
% d=CurvatureAxisLine;
% CS = cat(1,0,cumsum(sqrt(sum(diff(d,[],1).^2,2))));
% dd = interp1(CS, d, unique([CS(:)' linspace(0,CS(end),100)]),'pchip');
dd=[];
end
function output=plotClusterFigure(bone_curv,pureColumn,LCCall,centroid,csurfVertices,globalCenter, bonetypeMatrix,mycolor)
compareAlgorithm=[];
RadiusOfCurvature=[];
for k=1:length(LCCall)
LCC=LCCall{k};
if length(LCC)>=3
mu=(centroid(LCC,:)-globalCenter)* bonetypeMatrix;
%plot3(mu(:,1),mu(:,2),mu(:,3),'bo-');
hold on
clear csurf
for i=1:size(LCC,1)
%plot_cube(t(i,[3,4,1,2,5,6]).*voxelimit);
V=(csurfVertices{LCC(i)}-globalCenter)* bonetypeMatrix;
csurf{i}=V;
%plot3(V(:,1),V(:,2),V(:,3),mycolor,'markersize',0.5);
%text(mu(i,1),mu(i,2),mu(i,3),num2str(LCC(i)),'fontsize',16);
hold on
end
curv_column1=findCurvatureUsingCentroid_method1(mu);
curv_column2=findCurvatureUsingCentroid_method2(mu);
RadiusOfCurvature=[ RadiusOfCurvature;[k,length(LCC), curv_column1]];
for i=1:length(pureColumn)
if k==pureColumn(i)
if curv_column1>5
plot3(mu(:,1),mu(:,2),mu(:,3),'k.-','linewidth',1);
else
plot3(mu(:,1),mu(:,2),mu(:,3),'m.-','linewidth',1);
end
end
end
Z=mu(:,3);
ColumnPos_PDaxis(k,:)=[min(Z),max(Z)];
boneCurvIndex=[];
for j=1:length(bone_curv)-1
if (bone_curv(j,3)<=min(Z) & min(Z)<=bone_curv(j+1,3))
boneCurvIndex=[boneCurvIndex;(j:j+1)'];
end
if (bone_curv(j,3)<=max(Z) & max(Z)<=bone_curv(j+1,3))
boneCurvIndex=[boneCurvIndex;(j:j+1)'];
end
end
bone_curv_along_col=bone_curv(unique(boneCurvIndex),:);
if size(bone_curv_along_col,1)>2
curv_bone1=findCurvatureUsingCentroid_method1(bone_curv_along_col);
curv_bone2=findCurvatureUsingCentroid_method2(bone_curv_along_col);
else
curv_bone1=0; curv_bone2=0;
end
compareAlgorithm=[ compareAlgorithm;[ curv_column1, curv_bone1,curv_column2, curv_bone2]];
smoothline{k}=smoothUsingAverage(csurf,'g.-',0);
columnCentroid{k}=mu;
%smoothUsingEllipsoid(csurf,'b.-');
end
end
output.CurvatureOfColumn=smoothline;
output.NormalizedColumnCentroid=columnCentroid;
output.sphFit=compareAlgorithm;
output.RadiusOfCurvature=RadiusOfCurvature;
output.ColumnPos_PDaxis=ColumnPos_PDaxis;
end
function Bone_curvature_def=findCurvatureUsingCentroid_method1(mu)
[rcol1,a,b,c]=sphereFit_Prem(mu);
clear theta
for i=1:size(mu,1)
vec1=mu(i,:)-[a,b,c];
for j=i+1:size(mu,1)
vec2=mu(j,:)-[a,b,c];
theta(i,j)=angleCompute(vec1', vec2');
end
end
[sa,sb]=sort(theta(:),'descend');
%[size(mu,1), size(theta)]
[x,y] = ind2sub(size(theta),sb(1:2));
PlanePoints=mu(unique([x;y]),:);
P1=PlanePoints(1,:); P2=PlanePoints(2,:); P3=PlanePoints(3,:);
points=mu(unique([x;y]),:)';
% % figure
% % plot3(mu(:,1),mu(:,2),mu(:,3),'k.','linewidth',1);
% % hold on
% % plot3(a,b,c,'bo','linewidth',1);
% % plot3(mu([x;y],1),mu([x;y],2),mu([x;y],3),'ro','linewidth',1);
% %
% % [X,Y,Z] = sphere; radius=rcol1;
% % X = X * radius; Y = Y * radius; Z = Z * radius;
% % surf(X+a,Y+b,Z+c, 'edgecolor','none','facealpha',0.1)
% % fill3(points(1,:),points(2,:),points(3,:),'r'); alpha(0.2)
normal = cross(P1-P2, P1-P3);
d=point_to_plane_distance( [a,b,c], normal, P1 );
Bone_curvature_def= rcol1-d; %1/rcol1;
end
function Bone_curvature_def=findCurvatureUsingCentroid_method2(mu)
warning 'off';
[center,rcol1]=sphereFit_Alan(mu); a=center(1);b=center(2);c=center(3);
clear theta
for i=1:size(mu,1)
vec1=mu(i,:)-[a,b,c];
for j=i+1:size(mu,1)
vec2=mu(j,:)-[a,b,c];
theta(i,j)=angleCompute(vec1', vec2');
end
end
[sa,sb]=sort(theta(:),'descend');
[x,y] = ind2sub(size(theta),sb(1:2));
PlanePoints=mu(unique([x;y]),:);
P1=PlanePoints(1,:); P2=PlanePoints(2,:); P3=PlanePoints(3,:);
points=mu(unique([x;y]),:)';
normal = cross(P1-P2, P1-P3);
d=point_to_plane_distance( [a,b,c], normal, P1 );
Bone_curvature_def= rcol1-d; %1/rcol1;
end
function dd=smoothUsingAverage(surface,color,plotfig)
csurf=[];
for i=1:length(surface)
csurf=[csurf;surface{i}];
end
z=min(csurf(:,3)):2:max(csurf(:,3));
for i=1:length(z)-1
index=find( (csurf(:,3)>z(i)) & (csurf(:,3)<=z(i+1)));
d(i,:)=mean(csurf(index,:));
end
%plot3(d(:,1),d(:,2),d(:,3),'kx-')
d = d( ~any( isnan( d ) | isinf( d ), 2 ),: );
CS = cat(1,0,cumsum(sqrt(sum(diff(d,[],1).^2,2))));
dd = interp1(CS, d, unique([CS(:)' linspace(0,CS(end),100)]),'pchip');
if plotfig==1
plot3(dd(:,1),dd(:,2),dd(:,3),color,'linewidth',5)
end
end
function value=angleCompute(u,v)
value=atan2(norm(cross(u,v)),dot(u,v));
value=180/pi*value;
end
function [data,centroidZ,Xinterval,youtput]= makeProfile(centroidZ,data,profilesize)
%centroidZ=centroid(:,3);
minl=min(centroidZ); maxl=max(centroidZ);
Yinterval=linspace(minl-0.00001,maxl+0.00001,profilesize);
Xinterval=zeros(1,length(Yinterval));
binsize=Yinterval(2)-Yinterval(1);
horizontalCount=cell(1,length(Yinterval));
for k=1:length(Yinterval)
horizontalCount{k}=[];
for tt=1:length(centroidZ)
if (centroidZ(tt) > Yinterval(k)) & (centroidZ(tt) <= Yinterval(k+1))
horizontalCount{k}=[horizontalCount{k},tt];
end
end
Xinterval(k)=sum(data(horizontalCount{k}));
end
youtput=Yinterval+binsize/2;
end
function b=binarySum(a)
for i=1:size(a,1)
if ((a(i,1)==1) & (a(i,2)==1))
b(i)=1;
elseif ((a(i,1)==0) & (a(i,2)==1))
b(i)=2;
elseif ((a(i,1)==0) & (a(i,2)==0))
b(i)=3;
elseif ((a(i,1)==1) & (a(i,2)==0))
b(i)=4;
end
end
end
function LCC=LargestConnectedComponents(edges)
cellIds=unique(edges(:));
for j=1:length(cellIds)
old2new(cellIds(j),1)=j;
new2old(j,1)=cellIds(j);
end
[length(old2new),length(new2old),length(cellIds)];
for i=1:length(edges)
for j=1:2
newedgename(i,j)= old2new(edges(i,j));
end
end
G=graph(newedgename(:,1),newedgename(:,2));
bins=conncomp(G);
% number of connected components
nocomp=unique(bins);
disp(['# of connected components ', num2str(length(nocomp))]);
for i=1:length(nocomp)
numberOfObjectsInConnectedComponents(i)=sum(nocomp(i)==bins);
end
[sa,sb]=sort(numberOfObjectsInConnectedComponents,'descend');
index=1;
for i=1:length(sa)
if sa(i)>1
LCCIds=find(bins==nocomp(sb(i)));
LCC{index}=new2old(LCCIds);
index=index+1;
end
end
end