possible incorrect calculation of initial prox_vector when using Tau

[dkainer]

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I think that the calculation of the starting prox_vector may be incorrect when the values of Tau are not 1. I am using the two small example networks (m1 and m2) from the Testthat tests to form a 2 layer multiplex network with an 8x8 super-adjacency matrix.

If I use only one Seed node (node 2) and set Tau = c(1.5, 0.5), then the initial prox_vector looks correct:

prox_vector [,1] [1,] 0.00 [2,] 0.75 [3,] 0.00 [4,] 0.00 [5,] 0.00 [6,] 0.25 [7,] 0.00 [8,] 0.00

However, if i use TWO seed nodes (nodes 2 and 3) and set Tau= c(1.5, 0.5) then the initial prox_vector looks wrong:

prox_vector [,1] [1,] 0.000 [2,] 0.375 [3,] 0.125 [4,] 0.000 [5,] 0.000 [6,] 0.375 [7,] 0.125 [8,] 0.000

It appears to be weighting each seed node WITHIN layers rather than across the layers. Is this an error or am i misunderstanding the use of Tau?

If it is an error i believe it is in the get.seed.scoresMultiplex function.

[alberto-valdeolivas]

Hi there,

Yeah, it looks like you are right. I will take a deeper look.