function h=plotLRcont(w,xrange,yrange,n,k,lw,v,col)
% h=plotLRcont(w,xrange,yrange,n,k,lw,v,col)
% 
% Plot contour of logistic regression likelihood in 2D 
% Arguments:
% w: the weights of LR
% xrange,yrange: either vectors of x and y values, or just the limits
% n: if xrange and/or yrange are given in the form [min max] n is the
% number of steps on the grid between those limits (i.e., the resolution
% of the plot). Default 300.
% k: number of contour lines. Default 20
% lw: line width for the contour. Default 3.
% v: if given, contour for these values is plotted (in which case k is
% ignored). To plot decision boundary, pass v=0.5
% col: color of the contour (default used in contour.m is green).
% Returns:
% handle to the contour plot.

if (nargin < 4)
  n=300;
end

if (nargin < 5)
  k=20;
end
if (nargin < 6)
  lw=3;
end

if (length(xrange)==2)
  xrange=xrange(1):(xrange(2)-xrange(1))/n:xrange(2);
  yrange=yrange(1):(yrange(2)-yrange(1))/n:yrange(2);
end

[xx,yy]=meshgrid(xrange,yrange);
xy=[reshape(xx,1,[]);reshape(yy,1,[])];

if (length(w)>2)
  M=(length(w)-1)/2;
  XY=degexpandScale(xy,M,ones(1,length(w)));
end

fvalue=g(XY*w);
fvalue=reshape(fvalue,size(xx));

if (nargin < 7)
  step=(.99-0.03)/(k-1);
  v=(0.03:step:.99)*(max(fvalue(:))-min(fvalue(:)))+min(fvalue(:))
else
  if (length(v)==1)
    v=[v v];
  end
end

[c,h]=contour(xrange,yrange,fvalue,v);
set(h,'LineWidth',lw);
if (nargin >= 8)
  set(h,'Color',col);
end
hold on;