function process_corr_p_a(conff,nlin,ncol,listlinf,listcolf,tit);
%
% M-function for processing of confusion matrix
%
% Syntax process_corr_p_a(conff,nlin,ncol,listlinf,listcolf,tit);
%
%   conf   - filename of confusion matrix (text)
%   nlin   - number of its lines 
%   ncol   - number of its columns
%   listlin - labels for lines (filename)
%   listcol - labels for columns (filename)
%   title   - title for plot

%disp(['>' conff '<'])
ff=fopen(conff,'r')
conf=fscanf(ff, '%f', [ncol nlin]);      %columnwise
%conf=fscanf(ff, '%f', [nlin ncol]);      %columnwise
fclose(ff);
conf=conf';

%%% in columns and rows, the sums should be 1...
disp('sum of cols'); sum (conf)    % - not really ones ...
disp('sum of rows'); sum (conf')   % this is ok 

%%% look at max and min

disp('min'); min(min(conf))  %... 0
disp('max'); max(max(conf))  %... 0.8063    

%%% visualize it 
figure(1); colormap(gray); imagesc(1-conf)
ylabel ('phonetic classes'); xlabel ('alisp units'); title('not sorted');

%%%  should sort it 
% construct "ideal diagonal matrix" - allow only one 1 per column
ratio=(nlin-1)/(ncol-1);
pos_in_cols=round((0:ncol-1)*ratio)+1;
idig=zeros(nlin,ncol); 
for i=1:ncol,
  idig(pos_in_cols(i), i)=1;
end
% see ideal matrix
figure(2); colormap(gray); imagesc(1-idig)
ylabel ('phonetic classes'); xlabel ('alisp units'); title('ideal');

%%% now sort - go from best to worst column in conf (best
%%% means with the clearest maximum.
%%% thanks to V. Sebesta for this idea !!!

% sort maxima of columns:
[dummy, imaxcol]=sort(max(conf));  % this is ascending, wants desc.
imaxcol=imaxcol(ncol:-1:1);

% create empty matrix and vector with new indices. 0 will mean that 
% the position if free 

newconf=zeros(nlin,ncol);
newind=zeros(1,ncol);

% go from the best maxima, and put the vector where it best coincides 
% with the ideal pseudo-diagonal

for ii=1:ncol,
  col_to_put=conf(:,imaxcol(ii));

  % retrieve free positions
  free_pos=find(newind==0);

  % compute euclidian distance of vector with all columns on free
  % positions  
  aux=idig(:,free_pos);
  eucl=sqrt(sum( (col_to_put*ones(1,length(free_pos))-aux).^2 ));
  
  % put the vector where we've minimal eucl distance
  [dummy, mini] = min(eucl);
  index_to_put=free_pos(mini);
  newconf(:, index_to_put) = col_to_put;
  newind(index_to_put) = ii;
end


%%% visualize sorted matrix 
figure(3); colormap(gray); imagesc(1-newconf); 
ylabel ('phonetic classes'); xlabel ('alisp units'); title(tit);

%%% should put labels on axes. 
% read the two lists:
list_lin=[];
ff=fopen(listlinf,'r');
for ii=1:nlin, 
  str=fscanf(ff,'%s',[1 1]); 
  if ii==1,
    list_lin=str;
  else
    list_lin=str2mat(list_lin, str);
  end
end
fclose(ff);

list_col=[];
ff=fopen(listcolf,'r');
for ii=1:ncol, 
  str=fscanf(ff,'%s',[1 1]); 
  if ii==1,
    list_col=str;
  else
    list_col=str2mat(list_col, str);
  end
end
fclose(ff);

%%% put them on axis 

h=gca;
set (h,'fontsize',15);
set (h,'fontweight','bold');

% with deletion of 1st char 
 set(h,'xtick', 1:ncol); set (h,'xticklabel', list_col(imaxcol(newind),2))

% without deleteion of 1st char:
%set(h,'xtick', 1:ncol); set (h,'xticklabel', list_col(imaxcol(newind),:))

set(h,'ytick', 1:nlin); set (h,'yticklabel', list_lin)
%grid;          % no - its not nice