Commit 3a339480 authored by Argyris Kalogeratos's avatar Argyris Kalogeratos
Browse files

minor code improvements

parent cae19c5c

DRAsimulator.m

+15 −9
Original line number Diff line number Diff line
@@ -40,17 +40,23 @@ rngInfo = rng; 
    

    % a. Generate graph

        graphPars.N         = 100;           % the size of graph to generate

        graphPars.graphType = 'erdosRenyi';    % available: 'erdosRenyi', 'preferentialAttachment', 'smallWorld', 'adjacencyMatrix'

        graphPars.graphType = 'preferentialAttachment';  % available: 'erdosRenyi', 'preferentialAttachment', 'smallWorld', 'adjacencyMatrix'

        

        if (strcmp(graphPars.graphType, 'erdosRenyi') == 1)

            graphPars.prob_arete_graph = 0.1;  % only for erdosRenyiGraph() generation

        switch graphPars.graphType,  % specific parameters needed for some random graph models

        case 'erdosRenyi'

            graphPars.edge_prob = 0.1;

        case 'preferentialAttachment'

            graphPars.edge_num = 5;

            graphPars.delta = 0.01;

        case 'smallWorld'

            graphPars.edge_num  = 5;  

            graphPars.edge_prob = 0.05;                

        end 

        

    % b. Use an input graph

    %  - enter 'adjacencyMatrix' in graphPars.graphType

    %  - include the following:

    %  - load or create your graph G 

        %    G = erdosRenyiGraph(graphPars.N, graphPars.prob_arete_graph);   % this is just an example

    %  - load your graph G or create it include the following:

        %    G = erdosRenyiGraph(graphPars.N, graphPars.edge_prob);   % this is just an example

        %    graphPars.adjacencyMatrix = G;

        %    graphPars.N = size(G,1);

EvalMetrics/showMeasures.m

+2 −2
Original line number Diff line number Diff line
@@ -18,8 +18,8 @@ 
function showMeasures (fRresults, varargin)



methodNames = fieldnames(fRresults);

numMeasures = length(varargin);

numMethods  = length(methodNames);

numMeasures = numel(varargin);

numMethods  = numel(methodNames);



measures = cell(numMeasures, 1);

for j=1:numMeasures

GraphModels/erdosRenyiGraph.m

+6 −6
Original line number Diff line number Diff line 
%erdosRenyiGraph - A generator for Erdos Renyi graphs.

%

% function G = erdosRenyiGraph (N, p)

% function G = erdosRenyiGraph (N, edge_num)

%

% Input:

%   - N: the size of the graph to generate.

%   - p: the probability of creating each edge (i,j).

%   - edge_prob: the probability of creating each edge (i,j).

%

% Output:

%   - G: the generated graph.
@@ -17,14 +17,14 @@ 
% Copyright (c) by Argyris Kalogeratos and Kevin Scaman, 2015.

%---



function G = erdosRenyiGraph (N, p)

function G = erdosRenyiGraph (N, edge_num)



G = rand(N);

G = G + G';

if (p <= 0.5)

    G = G < sqrt(2 * p);

if (edge_num <= 0.5)

    G = G < sqrt(2 * edge_num);

else

    G = G >= sqrt(2 * (1 - p));

    G = G >= sqrt(2 * (1 - edge_num));

end

G = G - diag(diag(G));

G = sparse(G);

GraphModels/preferentialAttachmentGraph.m

+5 −5
Original line number Diff line number Diff line 
%preferentialAttachmentGraph - A generator for Preferential Attachment graphs.

%

% function G = preferentialAttachmentGraph (N, M, delta)

% function G = preferentialAttachmentGraph (N, num_edges, delta)

%

% Input:

%   - N: the size of the graph to generate.

%   - M: is the number of esges to generate.

%   - num_edges: is the number of edges to generate.

%   - delta: is an extra additive weight that increases the probability of 

%     creating an edge, for each node.

%
@@ -19,19 +19,19 @@ 
% Copyright (c) by Argyris Kalogeratos and Kevin Scaman, 2015.

%---



function G = preferentialAttachmentGraph (N, M, delta)

function G = preferentialAttachmentGraph (N, num_edges, delta)



if (nargin < 3)

    delta = 0;

end



G = spalloc(N, N, N*M);

G = spalloc(N, N, N*num_edges);

G(1, 2) = 1;

G(2, 1) = 1;



for i = 3:N

    numNeighbors = full(sum(G,1));

    newNeighbors = randp(max(0, numNeighbors + delta), [M 1]);

    newNeighbors = randp(max(0, numNeighbors + delta), [num_edges 1]);

    G(i, newNeighbors) = 1;

    G(newNeighbors, i) = 1;

end

GraphModels/smallWorldGraph.m

+9 −9
Original line number Diff line number Diff line 
%smallWorldGraph - A generator for Small World graphs.

%

% function G = smallWorldGraph (N, k, p)

% function G = smallWorldGraph (N, edge_num, edge_prob)

%

% Input:

%   - N: the size of the graph to generate.

%   - k: the size of the neighbors to connect each node (it assumes that 

%   - edge_num: the size of the neighbors to connect each node (it assumes that 

%     each node is located on the periphery of a ring, then k is the number 

%     of nearest neighbors to connect with each node)

%   - p: the probability of creating each edge (i,j) of the Erdos Renyi model.

%   - edge_prob: the probability of creating each edge (i,j) of the Erdos Renyi model.

%     the generator makes an OR between the graph generated with the ring

%     layout and an Erdos Renyi graph.

%
@@ -22,18 +22,18 @@ 
% Copyright (c) by Argyris Kalogeratos and Kevin Scaman, 2015.

%---



function G = smallWorldGraph (N, k, p)

function G = smallWorldGraph (N, edge_num, edge_prob)



G = zeros(N,N);

for i = 1:k

for i = 1:edge_num

    G = G + diag(ones(N - i, 1), i);

end



G = G + G';

G = max(G, erdosRenyiGraph(N, p));

p = randperm(N);

G = G(p,:);

G = G(:,p);

G = max(G, erdosRenyiGraph(N, edge_prob));

edge_prob = randperm(N);

G = G(edge_prob,:);

G = G(:,edge_prob);

G = sparse(G);



end