tests/testthat/test-authority.score.R

In igraph: Network Analysis and Visualization

test_that("authority score works", {
  ashs <- function(graph, as = TRUE) {
    mscale <- function(x) {
      if (sd(x) != 0) {
        x <- scale(x)
      }
      if (x[1] < 0) {
        x <- -x
      }
      x
    }
    A <- as_adj(graph, sparse = FALSE)
    if (as) {
      s1 <- eigen(t(A) %*% A)$vectors[, 1]
      s2 <- authority_score(graph)$vector
    } else {
      s1 <- eigen(A %*% t(A))$vectors[, 1]
      s2 <- hub_score(graph)$vector
    }
    expect_that(mscale(s1), is_equivalent_to(mscale(s2)))
  }

  g1 <- sample_pa(100, m = 10)
  ashs(g1)
  ashs(g1, as = FALSE)

  g2 <- sample_gnp(100, 2 / 100)
  ashs(g2)
  ashs(g2, as = FALSE)
})

test_that("authority scores of a ring are all one", {
  g3 <- make_ring(100)
  expect_that(authority_score(g3)$vector, equals(rep(1, vcount(g3))))
  expect_that(hub_score(g3)$vector, equals(rep(1, vcount(g3))))
})

test_that("authority_score survives stress test", {
  skip_on_cran()

  set.seed(42)

  is.principal <- function(M, lambda) {
    expect_that(eigen(M)$values[1], equals(lambda))
  }

  is.ev <- function(M, v, lambda) {
    expect_that(as.vector(M %*% v), equals(lambda * v))
  }

  is.good <- function(M, v, lambda) {
    is.principal(M, lambda)
    is.ev(M, v, lambda)
  }

  for (i in 1:100) {
    G <- sample_gnm(10, sample(1:20, 1))
    as <- authority_score(G)
    M <- as_adj(G, sparse = FALSE)
    is.good(t(M) %*% M, as$vector, as$value)
  }

  for (i in 1:100) {
    G <- sample_gnm(10, sample(1:20, 1))
    hs <- hub_score(G)
    M <- as_adj(G, sparse = FALSE)
    is.good(M %*% t(M), hs$vector, hs$value)
  }
})