Nothing
# library(testthat)
context("Cophenetic correlation between two trees")
test_that("cor_cophenetic works", {
suppressWarnings(RNGversion("3.5.0"))
set.seed(23235)
ss <- sample(1:150, 10)
hc1 <- iris[ss, -5] %>%
dist() %>%
hclust("com")
hc2 <- iris[ss, -5] %>%
dist() %>%
hclust("single")
dend1 <- as.dendrogram(hc1)
dend2 <- as.dendrogram(hc2)
# cutree(dend1)
# cophenetic(hc1)
# cophenetic(hc2)
# # notice how the dist matrix for the dendrograms have different orders:
# cophenetic(dend1)
# cophenetic(dend2)
# just taking the cor of two cophenetic treess
# will NOT give the same result for hclust and dendrogram
# (due to the different order of matrices)
expect_false(
cor(cophenetic(hc1), cophenetic(hc2)) == # 0.874
cor(cophenetic(dend1), cophenetic(dend2)) # 0.16
)
# the difference is becasue the order of the distance table in the case of
# stats:::cophenetic.dendrogram will change between dendrograms!
# however, the following numbers are consistant (since I force-sort the rows/columns):
expect_equal(
cor_cophenetic(hc1, hc2),
cor_cophenetic(dend1, dend2)
)
# Let's see that dendlist works
expect_equal(
cor_cophenetic(dendlist(dend1, dend2)),
cor_cophenetic(dend1, dend2)
)
})
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