Network modeling, Problem Set #03-4.

PS03_Woo_facebook.m

% Data info: 
%   Each of the school .mat files has an A matrix (sparse) and a
%   "local_info" variable, one row per node: a student/faculty status
%   flag, gender, major, second major/minor (if applicable), dorm/house,
%   year, and high school. Missing data is coded 0.

% datdir = '/Users/clinpsywoo/Documents/2011-2016yr/2014_2015_4th_GS/Network_modeling/Problem_sets/facebook100';
datdir = '/Volumes/engram/Users/wani/Documents/Network_modeling/Problem_sets/facebook100';
fnames = filenames(fullfile(datdir, '*mat'));

% the assortativity patterns for:
%   1) student/faculty status (row:1)
%   2) major (row:3)
%   3) vertex degree
% x axis: network size n
% y axis-1: modularity q for each
% y axis-2: relative gender modularity, q/q_rand

for i = 1:numel(fnames)
    
    t = tic;
    load(fnames{i});
    [~, res.name{i}] = fileparts(fnames{i});
    
    fprintf('\nWorking on.. %s (%d/%d).', res.name{i}, i, numel(fnames));

    % calculate the modularity for ***student/faculty status***
    fprintf('\n\t1) student/faculty...     ');
    stu_fac = local_info(:,1);
    missing = find(stu_fac==0);
    if ~isempty(missing)
        A = A'; A(:,missing) = [];
        A = A'; A(:,missing) = [];
        stu_fac(missing) = [];
    end
    
    n = length(stu_fac);
    res.stu_fac{i} = modularity_wani(A,stu_fac);

    % random permutation
    for iter = 1:100
        fprintf('\b\b\b\b%04d', iter);
        res.rand_stu_fac{i}(iter) = modularity_wani(A, stu_fac(randperm(n)));
    end
    
    load(fnames{i});
    % calculate the modularity for ***major***
    fprintf('\n\t2) major...     ');
    major = local_info(:,3);
    missing = find(major==0);
    if ~isempty(missing)
        A = A'; A(:,missing) = [];
        A = A'; A(:,missing) = [];
        major(missing) = [];
    end
    
    n = length(major);
    res.major{i} = modularity_wani(A,major);
    
    % random permutation
    for iter = 1:100
        fprintf('\b\b\b\b%04d', iter);
        res.rand_major{i}(iter)= modularity_wani(A,major(randperm(n)));
    end

    load(fnames{i});
    % calculate the assortativity coefficient for ***vertex degree***
    fprintf('\n\t3) vertex degree...     ');
    degree_k = sum(A,1);
    res.degree{i} = modularity_wani(A, [], 'degree');
    
    for iter = 1:100
        fprintf('\b\b\b\b%04d', iter);
        A = configuration_model(degree_k, 'sparse');
        res.rand_degree{i}(iter) = modularity_wani(A, [], 'degree');
    end
    fprintf('\n');
    toc(t);
end

savedir = '/Volumes/engram/Users/wani/Documents/Network_modeling/Problem_sets/PS03';
savename = fullfile(savedir, 'PS03_results.mat');
save(savename, 'res');