function [U,w,MU] = trainptonsample(M,X)

alf = M.ALF;

X = lensort(X);

U = {};
MU = {};
w = [];

w(1) = b2y(run_dfsa(M,''));
U{1} = '';
MU{1} = shuf2dfsa('',alf);

PROGstart(length(X),'training');
for i=1:length(X)
  x = X{i};
  %fprintf('main loop: x = [%s] \n',x);
  [U,w,MU,b] = add_feature(U,w,MU,M,x);
  PROGupdate(i);
end
PROGend;
return

function [U,w,MU,b] = add_feature(U,w,MU,M,x)
xi = embedX(x,MU);
yh = sign(xi*w);
yt = b2y(run_dfsa(M,x));
b = (yh == yt);
if ~b
  % signs disagree
  N = length(U)+1;
  U{N,1} = x;
  %fprintf('processing x = %s \n',x);
  %MU{N,1} = bool2fsa_pt(['(' x ')'],M.ALF);
  MU{N,1} = shuf2dfsa(x,M.ALF);
  w(N,1) = yt * (1+abs(xi*w));
  %%w(N,1) = yt * (1+sum(abs(w)));
  %w(N,1) = yt * 1.01 * abs(xi*w);
end
return