readCoronet.m

clc;
clear;
close all;

%% Import data from spreadsheet
% Script for importing data from the following spreadsheet:
%
%    Workbook: /home/li/Desktop/ProbabilisticModel/CORONET_CONUS_Topology.xls
%    Worksheet: Nodes
%
% To extend the code for use with different selected data or a different
% spreadsheet, generate a function instead of a script.

% Auto-generated by MATLAB on 2017/04/06 09:42:43

%% Import the data
[~, ~, raw] = xlsread('/home/li/Desktop/ProbabilisticModel/CORONET_CONUS_Topology.xls','Nodes');
raw = raw(6:end,:);
stringVectors = string(raw(:,[1,2]));
stringVectors(ismissing(stringVectors)) = '';
raw = raw(:,[3,4]);

%% Create output variable
data = reshape([raw{:}],size(raw));

%% Create table
nodes = table;

%% Allocate imported array to column variable names
nodes.City = stringVectors(:,1);
nodes.State = stringVectors(:,2);
nodes.Latitude = data(:,1);
nodes.Longitude = data(:,2);

%% Clear temporary variables
clearvars data raw stringVectors;

%% Import data from spreadsheet
% Script for importing data from the following spreadsheet:
%
%    Workbook: /home/li/Desktop/ProbabilisticModel/CORONET_CONUS_Topology.xls
%    Worksheet: Links
%
% To extend the code for use with different selected data or a different
% spreadsheet, generate a function instead of a script.

% Auto-generated by MATLAB on 2017/04/06 10:39:06

%% Import the data
[~, ~, raw] = xlsread('/home/li/Desktop/ProbabilisticModel/CORONET_CONUS_Topology.xls','Links');
raw = raw(6:end,:);
stringVectors = string(raw(:,[1,2]));
stringVectors(ismissing(stringVectors)) = '';
raw = raw(:,3);

%% Create output variable
data = reshape([raw{:}],size(raw));

%% Create table
links = table;

%% Allocate imported array to column variable names
links.NodeA = stringVectors(:,1);
links.NodeZ = stringVectors(:,2);
links.Distancekm = data(:,1);

%% Clear temporary variables
clearvars data raw stringVectors;

%% Construct adjacent matrix, cost matrix, and topology matrix
NodeNames = cell(75, 1);
for i=1:75
    NodeNames{i} = nodes.City{i};
end
networkCostMatrix = inf(75);

for i=1:size(links, 1)
    src = find(contains(NodeNames, links{i, 1}));
    dst = find(contains(NodeNames, links{i, 2}));
    distance = ceil(links{i, 3}/100);
    networkCostMatrix(src, dst) = distance;
end

for i=1:75
    for j=i+1:75
        if ~isinf(networkCostMatrix(i, j))
            networkCostMatrix(j, i) = networkCostMatrix(i, j);
        end
    end
end

networkAdjacentMatrix = double(~(isinf(networkCostMatrix)));

networkTopology = zeros(sum(networkAdjacentMatrix(:)), 1);
n=1;
for i=1:75
    for j=1:75
        if ~isinf(networkCostMatrix(i, j))
            networkTopology(n, 1) = i;
            networkTopology(n, 2) = j;
            networkTopology(n, 3) = networkCostMatrix(i, j);
            n = n+1;
        end
    end
end

locations = [nodes.Latitude, nodes.Longitude];

save('CoronetTopology.mat', 'networkCostMatrix', ...
    'networkAdjacentMatrix', 'networkTopology', 'locations')