# Simulate a feature vector whose components (columns)
# are on different scales
query <- matrix(c(
# k a t
1, -10, -100, # time step 1
-1, 10, -100, # time step 2
-1, -10, 100), # time step 3
ncol = 3,
nrow = 3,
byrow = TRUE
)
test_that("Calculating standardised Euclidean distances works", {
# There should only be 2 unique values when calculating a
# standardised Euclidean distance between the query and itself
expect_equal(
unique(round(dist_stdeuc(query, query), 8)),
c(0.00000000, 2.44948974)
)
})
test_that("Normalising matrix according using Rodriguez-Fuentes et al. (2014) procedure works", {
# The procedure range-normalises the matrix by columns (i.e. feature components)
# yielding 1 where the max value occurs in that column (i.e. 100 for third column)
# and 0 where the min value occurs (i.e. -100 for the third column)
expect_equal(
norm_rf2014(query)[ , 3],
c(0, 0, 1)
)
})
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