/usr/lib/R/site-library/igraph/tests/test_evcent.R is in r-cran-igraph 0.7.1-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | context("evcent")
test_that("evcent works", {
library(igraph)
kite <- graph.formula(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(evcent(kite)$vector, 3)
expect_that(evc, equals(structure(c(0.732, 0.732, 0.594, 1, 0.827,
0.594, 0.827, 0.407, 0.1, 0.023), .Names =
c("Andre", "Beverly", "Carol", "Diane",
"Fernando", "Ed", "Garth", "Heather", "Ike",
"Jane"))))
## Eigenvector-centrality, small stress-test
is.principal <- function(M, lambda, eps=1e-12) {
abs(eigen(M)$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 <- erdos.renyi.game(10, sample(1:20, 1), type="gnm")
ev <- evcent(G)
expect_that(is.good(get.adjacency(G, sparse=FALSE), ev$vector,
ev$value), is_true())
}
})
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