function [A,C,fval] = mylpm(h)
%global A0
global nstate
m = nstate;
% box constraints
LB = zeros(m,1);
UB = ones(m,1);
% normalization constraints
Aeq = zeros(m+1,m^2+m);
for i=1:m+1
  for j=1:m
    Aeq(i,m*(i-1)+j) = 1;
  end
end
Beq = ones(m+1,1);
% stricture constraints
%% nevermind for now -- a bit cumbersome...
%% though still linear, i'm pretty sure
%% let's cheat
% not cheating, doing this right
SIGNS = 2*list_all_ind(repmat([2],[1 m]))-3;
Ain = zeros(size(SIGNS,1)*m*(m-1)/2,m^2+m);
rind = 0;
for i1 = 1:m
  for i2 = i1+1:m
    for s = 1:size(SIGNS,1)
      rind = rind+1;
      ss = SIGNS(s,:);
      for j=1:m
        ind1 = coord2ind([j i1],[m m]);
        ind2 = coord2ind([j i2],[m m]);
        Ain(rind,ind1) =  ss(j);
        Ain(rind,ind2) = -ss(j);
      end
    end
  end
end
Bin = ones(size(SIGNS,1),1)*h*2;
A1 = pnormdim(rand(m,m),1);
C1 = pnormdim(rand(m,1),1);
x0 = [A1(:);C1]
options = optimset('TolCon',1e-12,'TolFun',1e-12)
[x,fval] = fmincon(@myobjm,x0,Ain,Bin,Aeq,Beq,LB,UB,[],options);
A = reshape(x(1:nstate^2),[nstate nstate]);
C = x(end-nstate+1:end);
return

%function nonlcon(x)
%global curH
%
%return


%function [h,i1,i2] = strict(A)
function h = strict(x)
A = reshape(x(1:nstate^2),[nstate nstate]);
[n,n,T] = size(A);
h = 0;
i1 = 0;
i2 = 0;
for t=1:T
  for i=1:n
  %for i=1
    for j=i+1:n
      x = A(:,i);
      y = A(:,j);
      d = .5*sum(abs(x-y));
      if d>h
        i1=i;
        i2=j;
        h=d;
      end
    end
  end
end
return