function ani_opt_3d_case2_fitting_pnorm()
nx=60;
ny=20;
nz=20;
volfrac=0.5;
rmin=1.5;
[Hs,H]=filter_coef_3D(nx,ny,nz,rmin);

a(1:nz,1:ny,1:nx) = 1.0;
b(1:nz,1:ny,1:nx) = 1.0;
c(1:nz,1:ny,1:nx) = 0;
aPhys = a;
bPhys = b;
cPhys = c;
% -1+a+b-c>=0
%  1-a+b-c>=0
%  1+a-b-c>=0

%OPTIMIZE a
% a>=max(1-b+c,-1+b+c)
% a<=1+b-c
%OPTIMIZE b
% b>=max(1-a+c,-1+a+c)
% b<=1+a-c
%OPTIMIZE c
% c<=min(-1+a+b,1-a+b,1+a-b)
nele     = nx * ny * nz;

m     = 4 + 1;                % The number of general constraints.
n     = 3 * nx * ny * nz; % The number of design variables x_j.
         
xmin  = [ones(nele,1).*0.6;...
         ones(nele,1).*0.6;...
         ones(nele,1).*(-4.9)];
    % Column vector with the lower bounds for the variables x_j.
xmax  = [ones(nele,1).*1.9;...
         ones(nele,1).*1.9;...
         ones(nele,1).*0.9];
     
xold1 = [ a(:); b(:);c(:)]; % xval, one iteration ago (provided that iter>1).
xold2 = [ a(:); b(:);c(:)]; % xval, two iterations ago (provided that iter>2).
low   = ones(n,1);        % Column vector with the lower asymptotes from the previous iteration (provided that iter>1).
upp   = ones(n,1);        % Column vector with the upper asymptotes from the previous iteration (provided that iter>1).
a0    = 1;                % The constants a_0 in the term a_0*z.
a1    = zeros(m,1);       % Column vector with the constants a_i in the terms a_i*z.
c_MMA = 1e3.*ones(m,1);   % Column vector with the constants c_i in the terms c_i*y_i.
% c_MMA = [0.5e3.*ones(m-1,1);1e3];   % Column vector with the constants c_i in the terms c_i*y_i.
d     = zeros(m,1);       % Column vector with the constants d_i in the terms 0.5*d_i*(y_i)^2.


% aold1 = a(:);             % xval, one iteration ago (provided that iter>1).
% aold2 = a(:);             % xval, two iterations ago (provided that iter>2).
% bold1 = b(:);
% bold2 = b(:);
% cold1 = c(:);
% cold2 = c(:);
% 
% low   = ones(n,1);        % Column vector with the lower asymptotes from the previous iteration (provided that iter>1).
% upp   = ones(n,1);        % Column vector with the upper asymptotes from the previous iteration (provided that iter>1).
% alow=low;aupp=upp;
% blow=low;bupp=upp;
% clow=low;cupp=upp;

maxloop = 300;
a_log = cell(maxloop,2);
b_log = cell(maxloop,2);
c_log = cell(maxloop,2);
tim=zeros(maxloop,1);
sumCompliance=zeros(maxloop,1);
volfraction = zeros(maxloop,1);
loop = 0;
change = 1.;
while change > 0.001 && loop < maxloop
    loop = loop + 1;
    tic
    [ch,ch_da,ch_db,ch_dc]=fitting_val(aPhys,bPhys,cPhys);
    ke_all=lk_all(ch);
    U=FEM(nx,ny,nz,ke_all);
    
    ke_da=lk_all(ch_da);
ke_db=lk_all(ch_db);
ke_dc=lk_all(ch_dc);
[~,~,dcdb] = COMP(U,ke_all,ke_db,nx,ny,nz);
[~,~,dcda] = COMP(U,ke_all,ke_da,nx,ny,nz);
[comp,compliance,dcdc] = COMP(U,ke_all,ke_dc,nx,ny,nz);
    
[dvda]=interp_dvda(aPhys(:),bPhys(:),cPhys(:));
[dvdb]=interp_dvdb(aPhys(:),bPhys(:),cPhys(:));
[dvdc]=interp_dvdc(aPhys(:),bPhys(:),cPhys(:));

dv=[dvda;dvdb;dvdc];
xval=[aPhys(:);bPhys(:);cPhys(:)];
f0val = compliance;
df0dx = [dcda(:);dcdb(:);dcdc(:)];

vol=interp_v(aPhys(:),bPhys(:),cPhys(:));

% cnstrt1 = -1-aPhys(:)-bPhys(:)-cPhys(:);
% cnstrt2 = -(-1+aPhys(:)+bPhys(:)-cPhys(:));
% cnstrt3 = -(1-aPhys(:)+bPhys(:)-cPhys(:));
% cnstrt4 = -(1+aPhys(:)-bPhys(:)-cPhys(:));
% cnstrt1 =cnstrt1./6;
% cnstrt2 =cnstrt2./8;
% cnstrt3 =cnstrt3./6;
% cnstrt4 =cnstrt4./6;
p=32;
cnstrt1 = mean((5-aPhys(:)-bPhys(:)-cPhys(:)).^p).^(1/p)-6;
    cnstrt2 = mean((9-aPhys(:)-bPhys(:)+cPhys(:)).^p).^(1/p)-8;
    cnstrt3 = mean((5+aPhys(:)-bPhys(:)+cPhys(:)).^p).^(1/p)-6;
    cnstrt4 = mean((5-aPhys(:)+bPhys(:)+cPhys(:)).^p).^(1/p)-6;
    
fval = [cnstrt1;cnstrt2;cnstrt3;cnstrt4;...
            sum(vol)/(volfrac*nele)-1];   
disp('fval: ')
disp(fval.')

[num_unconnect,cnstrt1,cnstrt2,cnstrt3,cnstrt4]=connect_check(a,b,c);
disp(num_unconnect.')

% % EYES=eye(nele);
% EYES=sparse(1:nele,1:nele,1);
% dfdx  = [EYES.*(-1)./6,EYES.*(-1)./6,EYES.*(-1)./6;
%              EYES.*(-1)./8,EYES.*(-1)./8,EYES.*( 1)./8;
%              EYES.*( 1)./6,EYES.*(-1)./6,EYES.*( 1)./6;
%              EYES.*(-1)./6,EYES.*( 1)./6,EYES.*( 1)./6;
%              dv(:)' / (volfrac*nele)]; % m X n
dc1da=-sum((5-aPhys(:)-bPhys(:)-cPhys(:)).^p).^(1/p-1).*((5-aPhys(:)-bPhys(:)-cPhys(:)).^(p-1));

dc2da=-sum((9-aPhys(:)-bPhys(:)+cPhys(:)).^p).^(1/p-1).*(9-aPhys(:)-bPhys(:)+cPhys(:)).^(p-1);
dc2dc= -dc2da;

dc3da= sum((5+aPhys(:)-bPhys(:)+cPhys(:)).^p).^(1/p-1).*(5+aPhys(:)-bPhys(:)+cPhys(:)).^(p-1);
dc3db=-dc3da;

dc4da=-sum((5-aPhys(:)+bPhys(:)+cPhys(:)).^p).^(1/p-1).*(5-aPhys(:)+bPhys(:)+cPhys(:)).^(p-1);
dc4db= -dc4da;

% EYES=eye(nele);
dfdx  = [dc1da.',dc1da.',dc1da.';
         dc2da.',dc2da.',dc2dc.';
         dc3da.',dc3db.',dc3da.';
         dc4da.',dc4db.',dc4db.';
         dv(:)' / (volfrac*nele)]; % m X n
[xmma, ~, ~, ~, ~, ~, ~, ~, ~, low,upp] = ...
    mmasub(m, n, loop, xval, xmin, xmax, xold1, xold2, ...
    f0val,df0dx,fval,dfdx,low,upp,a0,a1,c_MMA,d);
    a = reshape(xmma(1:nele),nz,ny,nx);
    b = reshape(xmma((nele+1):2*nele),nz,ny,nx);
    c = reshape(xmma((2*nele+1):n),nz,ny,nx);
    aPhys(:) = (double(H)*double(a(:)))./double(Hs);
    bPhys(:) = (double(H)*double(b(:)))./double(Hs);
    cPhys(:) = (double(H)*double(c(:)))./double(Hs);

    xold2    = xold1(:);
    xold1    = xval(:);
    change = max(max(abs([a(:);b(:);c(:)]-xval)));
    
    sumCompliance(loop,1)=compliance;
    volfraction(loop,1) = mean(vol);
    disp([' It.: ' sprintf('%4i',loop)...
      ' compliance.: ' sprintf('%10.10f',compliance)...
      ' volfrac:' sprintf('%10.10f',mean(vol))...
      '  change.: ' sprintf('%6.3f',change )]);
  a_log{loop,1}=a;a_log{loop,2}=aPhys;  
  b_log{loop,1}=b;b_log{loop,2}=bPhys;
  c_log{loop,1}=c;c_log{loop,2}=cPhys;
  
  plot_convergence_all(loop,maxloop,sumCompliance,volfraction);

%     [c,cPhys,cold1,cold2,change,compliance,vol,clow,cupp,comp]=...
%         optimizeC(a,b,c,aPhys,bPhys,cPhys,cold1,cold2,Hs,H,volfrac,clow,cupp,nx,ny,nz,loop);
%     sumCompliance(loop,1)=compliance;
%     volfraction(loop,1) = mean(vol);
%     disp([' c-It.: ' sprintf('%4i',loop)...
%       ' compliance.: ' sprintf('%10.10f',compliance)...
%       ' volfrac:' sprintf('%10.10f',mean(vol))...
%       '  change.: ' sprintf('%6.3f',change )]);
%    c_log{loop,1}=c;c_log{loop,2}=cPhys;   
% %     plot_comp(comp);
% 
%     [a,aPhys,aold1,aold2,change,compliance,vol,alow,aupp,comp]=...
%         optimizeA(a,b,c,aPhys,bPhys,cPhys,aold1,aold2,Hs,H,volfrac,alow,aupp,nx,ny,nz,loop);
%     sumCompliance(loop,2)=compliance;
%     volfraction(loop,2) = mean(vol);
%     disp([' a-It.: ' sprintf('%4i',loop)...
%       ' compliance.: ' sprintf('%10.10f',compliance)...
%       ' volfrac:' sprintf('%10.10f',mean(vol))...
%       '  change.: ' sprintf('%6.3f',change )]);
%   a_log{loop,1}=a;a_log{loop,2}=aPhys;    
% %     plot_comp(comp);
%     
%     [b,bPhys,bold1,bold2,change,compliance,vol,blow,bupp,comp]=...
%         optimizeB(a,b,c,aPhys,bPhys,cPhys,bold1,bold2,Hs,H,volfrac,blow,bupp,nx,ny,nz,loop);
%     sumCompliance(loop,3)=compliance;
%     volfraction(loop,3) = mean(vol);
%     disp([' b-It.: ' sprintf('%4i',loop)...
%       ' compliance.: ' sprintf('%10.10f',compliance)...
%       ' volfrac:' sprintf('%10.10f',mean(vol))...
%       '  change.: ' sprintf('%6.3f',change )]);
%   b_log{loop,1}=b;b_log{loop,2}=bPhys;
%     plot_comp(comp);
    
%     plot_distributions(aPhys,bPhys,cPhys);
%     plot_convergence(loop,maxloop,sumCompliance,volfraction);
    
    tim(loop)=toc;
    save('ani_rmin1.5_Beam3d_Case2_fitting_pnorm.mat','aPhys','bPhys','cPhys',...
    'sumCompliance','volfraction','a_log','b_log','c_log','tim');
end
end

% function [c,cPhys,cold1,cold2,change,compliance,vol,clow,cupp,comp]=...
%         optimizeC(a,b,c,aPhys,bPhys,cPhys,cold1,cold2,Hs,H,volfrac,clow,cupp,nx,ny,nz,loop)
% m     = 1;                % The number of general constraints.
% n     = nx * ny * nz;     % The number of design variables x_j.
% nele  = nx * ny * nz;
% a0    = 1;                % The constants a_0 in the term a_0*z.
% a1    = zeros(m,1);       % Column vector with the constants a_i in the terms a_i*z.
% x_MMA = 1e1.*ones(m,1);   % Column vector with the constants c_i in the terms c_i*y_i.
% d     = zeros(m,1);       % Column vector with the constants d_i in the terms 0.5*d_i*(y_i)^2.
% 
%     ch=interp_ch(aPhys,bPhys,cPhys);
%     ke_all=lk_all(ch);
%     U=FEM(nx,ny,nz,ke_all);
% 
%     
%     %OPTIMIZE c
%     % c<=min(-1+a+b,1-a+b,1+a-b)
% %     c_min = max(1-a+c,-1+a+c);
%     c_min = -1-aPhys-bPhys;
%     c_max = min(min(-1+aPhys+bPhys,1-aPhys+bPhys),1+aPhys-bPhys);
%     xmin  = max(c_min(:),-5.00);% Column vector with the lower bounds for the variables x_j.
%     xmax  = min(c_max(:),1.00);
% 
%     [ch_dc]=interp_ch_dc(aPhys,bPhys,cPhys);
%     ke_dc=lk_all(ch_dc);
%     [comp,compliance,dcdc] = COMP(U,ke_all,ke_dc,nx,ny,nz);
%     [dvdc]=interp_dvdc(aPhys(:),bPhys(:),cPhys(:));
%     dv=dvdc;
%     xval=cPhys(:);
%     f0val = compliance;
%     df0dx = dcdc(:);
%     vol=interp_v(aPhys(:),bPhys(:),cPhys(:));
%     fval = sum(vol)/(volfrac*nele)-1;
%     dfdx  = dv(:)' / (volfrac*nele);
%     [xmma, ~, ~, ~, ~, ~, ~, ~, ~, clow,cupp] = ...
%     mmasub(m, n, loop, xval, xmin, xmax, cold1, cold2, ...
%     f0val,df0dx,fval,dfdx,clow,cupp,a0,a1,x_MMA,d);
%     c = reshape(xmma,nz,ny,nx);
%     cPhys(:) = (double(H)*double(c(:)))./double(Hs);
%     cold2    = cold1(:);
%     cold1    = xval(:);
%     change = max(max(abs(c(:)-xval)));
%     vol=interp_v(aPhys(:),bPhys(:),cPhys(:));
% end

% function [b,bPhys,bold1,bold2,change,compliance,vol,blow,bupp,comp]=...
%         optimizeB(a,b,c,aPhys,bPhys,cPhys,bold1,bold2,Hs,H,volfrac,blow,bupp,nx,ny,nz,loop)
% m     = 1;                % The number of general constraints.
% n     = nx * ny * nz;     % The number of design variables x_j.
% nele  = nx * ny * nz;
% a0    = 1;                % The constants a_0 in the term a_0*z.
% a1    = zeros(m,1);       % Column vector with the constants a_i in the terms a_i*z.
% x_MMA = 0.8e1.*ones(m,1);   % Column vector with the constants c_i in the terms c_i*y_i.
% d     = zeros(m,1);       % Column vector with the constants d_i in the terms 0.5*d_i*(y_i)^2.
% 
%     ch=interp_ch(aPhys,bPhys,cPhys);
%     ke_all=lk_all(ch);
%     U=FEM(nx,ny,nz,ke_all);
%     
%     %OPTIMIZE b
%     % b>=max(1-a+c,-1+a+c)
%     % a<=1+a-c
%     b_min = max(max(1-aPhys+cPhys,-1+aPhys+cPhys),-1-aPhys-cPhys);
%     b_max = 1+aPhys-cPhys;
%     xmin  = max(b_min(:),0.52);% Column vector with the lower bounds for the variables x_j.
%     xmax  = min(b_max(:),1.98);
%       
%     [ch_db]=interp_ch_db(aPhys,bPhys,cPhys);
%     ke_db=lk_all(ch_db);
%     [comp,compliance,dcdb] = COMP(U,ke_all,ke_db,nx,ny,nz);
%     [dvdb]=interp_dvdb(aPhys(:),bPhys(:),cPhys(:));
%     dv=dvdb;
%     xval=bPhys(:);
%     f0val = compliance;
%     df0dx = dcdb(:);
%     vol=interp_v(aPhys(:),bPhys(:),cPhys(:));
%     fval = sum(vol)/(volfrac*nele)-1;
%     dfdx  = dv(:)' / (volfrac*nele);
%     [xmma, ~, ~, ~, ~, ~, ~, ~, ~, blow,bupp] = ...
%     mmasub(m, n, loop, xval, xmin, xmax, bold1, bold2, ...
%     f0val,df0dx,fval,dfdx,blow,bupp,a0,a1,x_MMA,d);
%     b = reshape(xmma,nz,ny,nx);
%     bPhys(:) = (double(H)*double(b(:)))./double(Hs);
%     bold2    = bold1(:);
%     bold1    = xval(:);
%     change = max(max(abs(b(:)-xval)));
%     vol=interp_v(aPhys(:),bPhys(:),cPhys(:));
% end

% function [a,aPhys,aold1,aold2,change,compliance,vol,alow,aupp,comp]=...
%         optimizeA(a,b,c,aPhys,bPhys,cPhys,aold1,aold2,Hs,H,volfrac,alow,aupp,nx,ny,nz,loop)
% m     = 1;                % The number of general constraints.
% n     = nx * ny * nz;     % The number of design variables x_j.
% nele  = nx * ny * nz;
% 
% a0    = 1;                % The constants a_0 in the term a_0*z.
% a1    = zeros(m,1);       % Column vector with the constants a_i in the terms a_i*z.
% x_MMA = 0.8e1.*ones(m,1);   % Column vector with the constants c_i in the terms c_i*y_i.
% d     = zeros(m,1);       % Column vector with the constants d_i in the terms 0.5*d_i*(y_i)^2.
% 
%     ch=interp_ch(aPhys,bPhys,cPhys);
%     ke_all=lk_all(ch);
%     U=FEM(nx,ny,nz,ke_all);
%     
%     a_min = max(max(1-bPhys+cPhys,-1+bPhys+cPhys),-1-bPhys-cPhys);
%     a_max = 1+bPhys-cPhys;
%     xmin  = max(a_min(:),0.52);% Column vector with the lower bounds for the variables x_j.
%     xmax  = min(a_max(:),1.98);
% 
%     [ch_da]=interp_ch_da(aPhys,bPhys,cPhys);
%     ke_da=lk_all(ch_da);
%     [comp,compliance,dcda] = COMP(U,ke_all,ke_da,nx,ny,nz);
%     
%     [dvda]=interp_dvda(aPhys(:),bPhys(:),cPhys(:));
%     dv=dvda;
%     xval=aPhys(:);
%     f0val = compliance;
%     df0dx = dcda(:);
%     vol=interp_v(aPhys(:),bPhys(:),cPhys(:));
%     fval = sum(vol)/(volfrac*nele)-1;
%     dfdx  = dv(:)' / (volfrac*nele);
%     [xmma, ~, ~, ~, ~, ~, ~, ~, ~, alow,aupp] = ...
%     mmasub(m, n, loop, xval, xmin, xmax, aold1, aold2, ...
%     f0val,df0dx,fval,dfdx,alow,aupp,a0,a1,x_MMA,d);
%     a = reshape(xmma,nz,ny,nx);
%     aPhys(:) = (double(H)*double(a(:)))./double(Hs);
%     aold2    = aold1(:);
%     aold1    = xval(:);
%     change = max(max(abs(a(:)-xval)));
%     vol=interp_v(aPhys(:),bPhys(:),cPhys(:));
% end


%%%%%%%%%% 3D FEM with brick element %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [U]=FEM(nx,ny,nz,ke_all)
N = 3*(nx+1)*(ny+1)*(nz+1);
% K = sparse(N, N);
nele=nx*ny*nz;
si=zeros(1,nele*24^2);
sj=zeros(1,nele*24^2);
sv=zeros(1,nele*24^2);

for elx = 1:nx
    for ely = 1:ny
        for elz = 1:nz
%             n1 = (nz+1)*(ny+1)*elx + (nz+1)*(ely-1) + elz;
%             n2 = n1 - (nz+1)*(ny+1);
            n2 = (nz+1)*(ny+1)*elx + (nz+1)*(ely-1) + elz;
            n1 = n2-(nz+1)*(ny+1);
            n3 = n1 + (nz+1);
            n4 = n2 + (nz+1);
            n5 = n1 + 1;
            n6 = n2 + 1;
            n7 = n3 + 1;
            n8 = n4 + 1;
            edof = [3*n1-2; 3*n1-1; 3*n1;
                    3*n2-2; 3*n2-1; 3*n2;
                    3*n3-2; 3*n3-1; 3*n3;
                    3*n4-2; 3*n4-1; 3*n4;
                    3*n5-2; 3*n5-1; 3*n5;
                    3*n6-2; 3*n6-1; 3*n6;
                    3*n7-2; 3*n7-1; 3*n7;
                    3*n8-2; 3*n8-1; 3*n8];
            ne=(elx-1)*ny*nz+(ely-1)*nz+elz;
            si((ne-1)*24^2+1:ne*24^2)=kron(ones(1,24),edof.');
            sj((ne-1)*24^2+1:ne*24^2)=kron(edof.',ones(1,24));
            ke=ke_all(:,:,elz,ely,elx);
            sv((ne-1)*24^2+1:ne*24^2)=ke(:);
%             K(edof,edof) = K(edof,edof) + ke_all(:,:,elz,ely,elx);
        end
    end
end
K = sparse(si,sj,sv,N,N);

%loadnid = nz+1:nz+1:(nx+1)*(ny+1)*(nz+1);
% loadnid = (nx/2+1)*(ny+1)*(nz+1) - nz/2;
loadnid = nx*(ny+1)*(nz+1) + (nz+1)*ny/2 + nz/2 + 1;
loaddof = 3.*loadnid(:);
F = sparse(N,1);  F(loaddof)=-1;

fixednid=[1:(nz+1)*6,(ny+1-6)*(nz+1)+1:(ny+1)*(nz+1)];
%fixednid=[1,(ny+1)*(nz+1)-nz,nx*(ny+1)*(nz+1)+1,(nx+1)*(ny+1)*(nz+1)-nz];
fixeddofs = [3*fixednid(:); 3*fixednid(:)-1; 3*fixednid(:)-2];
alldofs     = [1:N];
freedofs    = setdiff(alldofs,fixeddofs);
U = zeros(N,1);
U(freedofs,:) = K(freedofs,freedofs) \ F(freedofs,:);   
end


function plot_comp(comp)
figure(1)
set(gcf,'position',[100 650 300 300])
cc = squeeze(comp(:,1,:));
colormap(1-gray); imagesc(cc);
axis equal; axis tight; axis off;
title('Compliance Distribution')
set(gca,'YDir','normal')
pause(1e-6);
end

function plot_distributions(aPhys,bPhys,cPhys)
figure(2)
set(gcf,'position',[410 650 1200 300])
subplot(1,3,1)
colormap(gray); imagesc(squeeze(aPhys(:,1,:)));
axis equal; axis tight; axis off;
title('a Distribution')
set(gca,'YDir','normal')
subplot(1,3,2)
colormap(gray); imagesc(squeeze(bPhys(:,1,:)));
axis equal; axis tight; axis off;
title('b Distribution')
set(gca,'YDir','normal')
subplot(1,3,3)
colormap(gray); imagesc(squeeze(cPhys(:,1,:)));
axis equal; axis tight; axis off;
title('c Distribution')
set(gca,'YDir','normal')
pause(1e-6);
end

% function [comp,compliance,dcdx] = COMP(U,ke_all,ke_dx,nx,ny,nz)
% comp =zeros(nz,ny,nx);
% compliance = 0.;
% dcdx=zeros(nz,ny,nx);
% for elz = 1:nz
%     %       z = nz*h - (elz-1)*h;
%     for ely = 1:ny
%         %           y = (ely-1)*h + 0.5*h;
%         for elx = 1:nx
%             %              x = (elx-1)*h + 0.5*h;
%             n2 = (nz+1)*(ny+1)*elx + (nz+1)*(ely-1) + elz;
%             n1 = n2-(nz+1)*(ny+1);
%             n3 = n1 + (nz+1);
%             n4 = n2 + (nz+1);
%             n5 = n1 + 1;
%             n6 = n2 + 1;
%             n7 = n3 + 1;
%             n8 = n4 + 1;
%             Ue = U([3*n1-2; 3*n1-1; 3*n1;
%                 3*n2-2; 3*n2-1; 3*n2;
%                 3*n3-2; 3*n3-1; 3*n3;
%                 3*n4-2; 3*n4-1; 3*n4;
%                 3*n5-2; 3*n5-1; 3*n5;
%                 3*n6-2; 3*n6-1; 3*n6;
%                 3*n7-2; 3*n7-1; 3*n7;
%                 3*n8-2; 3*n8-1; 3*n8]);
%             
%             comp(elz,ely,elx) = Ue'* ke_all(:,:,elz,ely,elx)*Ue;
%             compliance = compliance +  comp(elz,ely,elx);
%             dcdx(elz,ely,elx) =-Ue'*ke_dx(:,:,elz,ely,elx)*Ue;
%         end
%     end
% end
% end

function plot_convergence_all(loop,maxloop,sumCompliance,volfraction)
figure(3)
% figure()
% loop=75;maxloop=loop;
set(gcf,'position',[100 100 1200 400])
subplot(2,1,1)
plotC=sumCompliance.';
plot([1:loop].',plotC(1:loop))
xlim([0 maxloop])
subplot(2,1,2)
plotV=volfraction.';
plot([1:loop].',plotV(1:loop))
xlim([0 maxloop])
pause(1e-6);
end