function [prob term_prob] = transProbEXAMPLE(filename, leader, follower)
%
% function [prob term_prob] = transProbEXAMPLE(filename, leader, follower)
%
% 'filename' is plain text file containing matrix
% will compute transition probability from 'leader' to 'follower'
% i.e. how often 'leader' is immediately followed by 'follower'
%
% returns 'prob'      - 'leader' -> 'follower' transition probability
%         'term_prob' - probability that 'leader' is last element
%                       in its row

data = dlmread(filename); % pass info in 'filename' to variable 'data'
                          % dlmread will store ASCII file in matrix 
                          %
                          % could also have used load(), which is meant
                          % for .mat (MATLAB file format) files, but will
                          % store contents of ASCII files in a matrix also

                    % initialize empty counting vectors
                    % would be best to preallocate vector lengths 
                    % but we don't really know how long these vectors
                    % will be
track_trans = [];      % for tracking instances when 'leader' is
                       % followed by 'follower'
                       
track_terms = [];      % for tracking instances when 'leader' 
                       % terminates the line

[data_row, data_col] = size(data); % save dimensions of 'data'
                                   % to use for looping

% loop over 'data' rows
for row = 1:data_row
    
    % loop over 'data' columns
    for col = 1:data_col
        
        % look for instances of 'leader' 
        if data(row, col) == leader     
            
            % check if 'leader' terminates line
            if col == data_col
                
                % if yes, add 1 to counting vector
                track_terms = [track_terms 1];      % grow vector by
                                                    % redefining it as
                                                    % itself appended with
                                                    % a 1 (remember these
                                                    % counting vectors
                                                    % start out empty)
            
            % see if next element is 'follower'
            elseif data(row, col + 1) == follower
                
                % if yes, add 1 to counting vector
                track_trans = [track_trans 1]; 
   
            end
        end
    end
end

% count total number of instances of 'leader'

% find() will return indices of 'data' that contain 'leader'
% thus, the length of the vector returned by find() gives the total
% number of 'leader's in 'data'
% could also have used:
% total_leader = sum(sum(data == leader));
% but find() is a very useful function to know about

total_leader = length(find(data == leader));

% count number of times 'follower' followed 'leader' 
count_trans = sum(track_trans);

% calculate probability that 'follower' follows 'leader'
prob = count_trans/total_leader;

% count number of times 'leader' terminated line
terminations = sum(track_terms);

% calculate probability that 'leader' terminates line
term_prob = terminations/total_leader;