imagesc(matrix)
Plotting the correlation distribution:
degree = sum(matrix_thresh);
% plot the correlation distribution
figure;
hist(degree,20);
xlabel('Degree')
ylabel('Frequency')
Calculating the mean shortest path length L and the clustering coefficient C, for your thresholded, binarized network:
C = mean(clustering_coef_bu(matrix_thresh));
L = charpath(distance_bin(matrix_thresh));
% Values for C and L: C = 0.49, L = 2.93
Generating null networks:
randmatrix = cell(1,100);
for ind = 1:100
[R,eff] = randmio_und_connected(matrix_thresh, 10);
randmatrix{1,ind} = R;
end
Calculating Cr and Lr:
for ind = 1:100
C_rand(ind) = mean(clustering_coef_bu(randmatrix{1,ind}));
L_rand(ind) = charpath(distance_bin(randmatrix{1,ind}));
end
mean(C_rand) % = 0.25
mean(L_rand) % = 2.3
σ=0.49/0.252.9/2.3=1.6>1
→ We have a small-world network!