test_that("eigen_centrality works", {
  kite <- graph_from_literal(
    Andre - Beverly:Carol:Diane:Fernando,
    Beverly - Andre:Diane:Ed:Garth,
    Carol - Andre:Diane:Fernando,
    Diane - Andre:Beverly:Carol:Ed:Fernando:Garth,
    Ed - Beverly:Diane:Garth,
    Fernando - Andre:Carol:Diane:Garth:Heather,
    Garth - Beverly:Diane:Ed:Fernando:Heather,
    Heather - Fernando:Garth:Ike,
    Ike - Heather:Jane,
    Jane - Ike
  )
  evc <- round(eigen_centrality(kite)$vector, 3)
  expect_equal(evc, structure(c(0.732, 0.732, 0.594, 1, 0.827, 0.594, 0.827, 0.407, 0.1, 0.023), .Names = c("Andre", "Beverly", "Carol", "Diane", "Fernando", "Ed", "Garth", "Heather", "Ike", "Jane")))


  ## Eigenvector-centrality, small stress-test

  is.principal <- function(M, lambda, eps = 1e-12) {
    abs(eigen(M)$values[1] - lambda) < eps
  }

  is.ev <- function(M, v, lambda, eps = 1e-12) {
    max(abs(M %*% v - lambda * v)) < eps
  }

  is.good <- function(M, v, lambda, eps = 1e-12) {
    is.principal(M, lambda, eps) && is.ev(M, v, lambda, eps)
  }

  for (i in 1:1000) {
    G <- sample_gnm(10, sample(1:20, 1))
    ev <- eigen_centrality(G)
    expect_true(is.good(as_adjacency_matrix(G, sparse = FALSE), ev$vector, ev$value))
  }
})