Nothing
tests/testthat/test_get_k_best.R
In muRty: Murty's Algorithm for k-Best Assignments
############################################
#
# Test script for Murty's algorithm
#
# Updated on 29/02/2020
#
############################################
context("get_k_best")
# LP
test_that("muRty::get_k_best functions as expected with data frames and matrices (LP)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 5, algo = 'lp')
expectedOutput1 <- list(solutions = list(structure(c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3L,3L)),
structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 0, 1, 0, 1, 0, 0), .Dim = c(3L, 3L))),
costs = list(3, 7, 13, 15, 107))
expect_equal(matTest, expectedOutput1)
expect_warning(muRty::get_k_best(mat, 5, algo = 'lp'),
"You haven't provided an object of class matrix. Attempting to convert to matrix ..")
matLarger <- as.matrix(
read.table(
text = "7 51 52 87 38 60 74 66 0 20
50 12 0 64 8 53 0 46 76 42
27 77 0 18 22 48 44 13 0 57
62 0 3 8 5 6 14 0 26 39
0 97 0 5 13 0 41 31 62 48
79 68 0 0 15 12 17 47 35 43
76 99 48 27 34 0 0 0 28 0
0 20 9 27 46 15 84 19 3 24
56 10 45 39 0 93 67 79 19 38
27 0 39 53 46 24 69 46 23 1",
header = FALSE
)
)
attr(matLarger, "dimnames") <- NULL
matSolLarger <- muRty::get_k_best(matLarger, 70, algo = 'lp')
expectedOutput2 <- 12L
expect_equal(length(matSolLarger$costs[matSolLarger$costs == 29]), expectedOutput2)
})
test_that("muRty::get_k_best functions as expected with objective max and n_possible < k_best (also for by_rank), no warning for n_possible == k_best (LP)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 10, objective = 'max', algo = 'lp')
matTest <- unlist(matTest$costs)
expectedOutput3 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput3)
matTestRank <- muRty::get_k_best(mat, 6, objective = 'max', algo = 'lp', by_rank = TRUE)
matTest <- unlist(matTestRank$costs)
expectedOutput4 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput4)
expect_warning(muRty::get_k_best(mat, 10, objective = 'max', algo = 'lp'),
paste0("There are only ", factorial(nrow(mat)), " possible solutions - terminating earlier.")
)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, objective = 'max', algo = 'lp', by_rank = TRUE), regexp = NULL)
expect_warning(muRty::get_k_best(as.matrix(mat), 6, objective = 'max', algo = 'lp'), regexp = NA)
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1, but no error for 2x2 (LP)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp'),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp'),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'lp'), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'lp'), "You have provided an invalid value for k_best.")
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1, but no error for 2x2 (LP, by rank)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp', by_rank = TRUE),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp', by_rank = TRUE),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'lp', by_rank = TRUE), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'lp', by_rank = TRUE), "You have provided an invalid value for k_best.")
})
test_that("by_rank argument functions as expected (LP)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
test_by_rank <- muRty::get_k_best(mat, k_best = 3, by_rank = TRUE, algo = 'lp')
expect_error(muRty::get_k_best(mat, 0, algo = 'lp', by_rank = TRUE), "You have provided an invalid value for k_best.")
skip_on_cran()
expectedOutput4 <- list(solutions = list(list(structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)))), costs = list(c(31, 31), c(32, 32, 32, 32, 32), c(33, 33,
33, 33, 33, 33, 33)))
expect_equal(test_by_rank, expectedOutput4)
})
test_that("muRty::get_k_best functions as expected with matrices (LP)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 35, algo = 'lp')
matTest <- sum(unlist(matTest$costs) == 32)
expectedOutput5 <- 5L
expect_equal(matTest, expectedOutput5)
})
test_that("muRty::get_k_best functions as expected with decimal weights (LP)", {
mat <- read.table(
text = "0.5 5 0.5
3 1 3
2.5 4 2.5",
header = FALSE)
matTest <- muRty::get_k_best(mat, 3, by_rank = TRUE, algo = 'lp')
expectedOutput6 <- list(solutions = list(list(structure(c(0, 0, 1, 0, 1, 0, 1, 0,
0), .Dim = c(3L, 3L)), structure(c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3L,
3L))), list(structure(c(0, 1, 0, 0, 0, 1, 1, 0, 0), .Dim = c(3L,
3L)), structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L
))), list(structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L,
3L)), structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L
)))), costs = list(c(4, 4), c(7.5, 7.5), c(10.5, 10.5)))
expect_equal(matTest, expectedOutput6)
})
# Hungarian
test_that("muRty::get_k_best functions as expected with data frames and matrices (Hungarian, by rank for conversion)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 5, algo = 'hungarian')
expectedOutput1 <- list(solutions = list(structure(c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3L,3L)),
structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 0, 1, 0, 1, 0, 0), .Dim = c(3L, 3L))),
costs = list(3, 7, 13, 15, 107))
expect_equal(matTest, expectedOutput1)
expect_warning(muRty::get_k_best(mat, 5, algo = 'hungarian'),
"You haven't provided an object of class matrix. Attempting to convert to matrix ..")
expect_warning(muRty::get_k_best(mat, 5, algo = 'hungarian', by_rank = TRUE),
"You haven't provided an object of class matrix. Attempting to convert to matrix ..")
matLarger <- as.matrix(
read.table(
text = "7 51 52 87 38 60 74 66 0 20
50 12 0 64 8 53 0 46 76 42
27 77 0 18 22 48 44 13 0 57
62 0 3 8 5 6 14 0 26 39
0 97 0 5 13 0 41 31 62 48
79 68 0 0 15 12 17 47 35 43
76 99 48 27 34 0 0 0 28 0
0 20 9 27 46 15 84 19 3 24
56 10 45 39 0 93 67 79 19 38
27 0 39 53 46 24 69 46 23 1",
header = FALSE
)
)
attr(matLarger, "dimnames") <- NULL
matSolLarger <- muRty::get_k_best(matLarger, 70, algo = 'hungarian')
expectedOutput2 <- 12L
expect_equal(length(matSolLarger$costs[matSolLarger$costs == 29]), expectedOutput2)
})
test_that("muRty::get_k_best functions as expected with objective max and n_possible < k_best (also for by_rank), no warning for n_possible == k_best (Hungarian)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 10, objective = 'max', algo = 'hungarian')
matTest <- unlist(matTest$costs)
expectedOutput3 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput3)
matTestRank <- muRty::get_k_best(mat, 6, objective = 'max', algo = 'hungarian', by_rank = TRUE)
matTest <- unlist(matTestRank$costs)
expectedOutput4 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput4)
expect_warning(muRty::get_k_best(mat, 10, objective = 'max', algo = 'hungarian'),
paste0("There are only ", factorial(nrow(mat)), " possible solutions - terminating earlier.")
)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, objective = 'max', algo = 'hungarian', by_rank = TRUE), regexp = NULL)
expect_warning(muRty::get_k_best(as.matrix(mat), 6, objective = 'max', algo = 'hungarian'), regexp = NA)
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1 but no error for 2x2 (Hungarian)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian'),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian'),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'hungarian'), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'hungarian'), "You have provided an invalid value for k_best.")
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1 but no error for 2x2 (Hungarian, by rank)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian', by_rank = TRUE),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian', by_rank = TRUE),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'hungarian', by_rank = TRUE), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'hungarian', by_rank = TRUE), "You have provided an invalid value for k_best.")
})
test_that("by_rank argument functions as expected (Hungarian)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
test_by_rank <- muRty::get_k_best(mat, k_best = 3, by_rank = TRUE, algo = 'hungarian')
expect_error(muRty::get_k_best(mat, 0, algo = 'hungarian', by_rank = TRUE), "You have provided an invalid value for k_best.")
expectedOutput4 <- list(solutions = list(list(structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)))), costs = list(c(31, 31), c(32, 32, 32, 32, 32), c(33, 33,
33, 33, 33, 33, 33)))
expect_equal(test_by_rank, expectedOutput4)
})
test_that("muRty::get_k_best functions as expected with matrices (Hungarian)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 35, algo = 'hungarian')
matTest <- sum(unlist(matTest$costs) == 32)
expectedOutput5 <- 5L
expect_equal(matTest, expectedOutput5)
})
test_that("muRty::get_k_best functions as expected with decimal weights (Hungarian)", {
mat <- read.table(
text = "0.5 5 0.5
3 1 3
2.5 4 2.5",
header = FALSE)
matTest <- muRty::get_k_best(mat, 3, objective = 'max', algo = 'hungarian')
expectedOutput6 <- list(solutions = list(structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L,
3L)), structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L
)), structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L))),
costs = list(10.5, 10.5, 7.5))
expect_equal(matTest, expectedOutput6)
})
test_that("muRty::get_k_best functions as expected with objective max and by_rank (Hungarian & LP)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'hungarian', by_rank = TRUE)
matTestLP <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'lp', by_rank = TRUE)
expectedOutput7 <- list(c(135, 135), 134, c(133, 133, 133, 133, 133), c(132, 132,
132, 132, 132), c(131, 131, 131, 131, 131, 131, 131))
expect_equal(expectedOutput7, matTest$costs)
expect_equal(expectedOutput7, matTestLP$costs)
expectedOutput8 <- list(list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L))), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L
)), list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L))), list(structure(c(0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))))
expect_equal(matTest$solutions, expectedOutput8)
})
test_that("muRty::get_k_best functions as expected with negative values, objective max and by_rank (Hungarian & LP)", {
mat <- structure(c(-9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, -10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, -6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, -9L, 7L, 14L, 4L, 7L, -13L, -13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'hungarian', by_rank = TRUE)
matTestLP <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'lp', by_rank = TRUE)
expectedOutput9 <- list(135, 134, c(133, 133, 133), c(132, 132, 132, 132), c(131,
131, 131, 131))
expect_equal(expectedOutput9, matTest$costs)
expect_equal(expectedOutput9, matTestLP$costs)
expectedOutput10 <- list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L)), list(structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L))))
expect_equal(matTest$solutions, expectedOutput10)
})
test_that("muRty::get_k_best functions as expected with negative values and by_rank (Hungarian & LP)", {
mat <- structure(c(-9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, -10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, -6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, -9L, 7L, 14L, 4L, 7L, -13L, -13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 5, algo = 'hungarian', by_rank = TRUE)
matTestLP <- muRty::get_k_best(mat, 5, algo = 'lp', by_rank = TRUE)
expectedOutput11 <- list(-29, -28, c(-27, -27), c(-26, -26), c(-25, -25, -25, -25,
-25))
expect_equal(expectedOutput11, matTest$costs)
expect_equal(expectedOutput11, matTestLP$costs)
expectedOutput12 <- list(structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), list(structure(c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L))), list(structure(c(1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))))
expect_equal(matTest$solutions, expectedOutput12)
})
test_that("muRty::get_k_best functions as expected with negative values without rank (Hungarian & LP)", {
mat <- structure(c(-9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, -10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, -6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, -9L, 7L, 14L, 4L, 7L, -13L, -13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 3, algo = 'hungarian')
matTestLP <- muRty::get_k_best(mat, 3, algo = 'lp')
expectedOutput13 <- list(solutions = list(structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)),
structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))), costs = list(
-29L, -28L, -27L))
expect_equal(expectedOutput13, matTest)
expect_equal(expectedOutput13, matTestLP)
})
test_that("muRty::get_k_best functions as expected with k_best > n_possible and number of ranks (additional tests; both LP and Hungarian)", {
mat <- read.table(
text = "1 1 1
6 1 3
7 4 2",
header = FALSE)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, algo = 'lp', by_rank = TRUE),
"There are 6 possible solutions. Final solution has been found at rank number 4 which is lower than the k_best specified; terminating here."
)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, algo = 'hungarian', by_rank = TRUE),
"There are 6 possible solutions. Final solution has been found at rank number 4 which is lower than the k_best specified; terminating here."
)
})
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############################################
#
# Test script for Murty's algorithm
#
# Updated on 29/02/2020
#
############################################
context("get_k_best")
# LP
test_that("muRty::get_k_best functions as expected with data frames and matrices (LP)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 5, algo = 'lp')
expectedOutput1 <- list(solutions = list(structure(c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3L,3L)),
structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 0, 1, 0, 1, 0, 0), .Dim = c(3L, 3L))),
costs = list(3, 7, 13, 15, 107))
expect_equal(matTest, expectedOutput1)
expect_warning(muRty::get_k_best(mat, 5, algo = 'lp'),
"You haven't provided an object of class matrix. Attempting to convert to matrix ..")
matLarger <- as.matrix(
read.table(
text = "7 51 52 87 38 60 74 66 0 20
50 12 0 64 8 53 0 46 76 42
27 77 0 18 22 48 44 13 0 57
62 0 3 8 5 6 14 0 26 39
0 97 0 5 13 0 41 31 62 48
79 68 0 0 15 12 17 47 35 43
76 99 48 27 34 0 0 0 28 0
0 20 9 27 46 15 84 19 3 24
56 10 45 39 0 93 67 79 19 38
27 0 39 53 46 24 69 46 23 1",
header = FALSE
)
)
attr(matLarger, "dimnames") <- NULL
matSolLarger <- muRty::get_k_best(matLarger, 70, algo = 'lp')
expectedOutput2 <- 12L
expect_equal(length(matSolLarger$costs[matSolLarger$costs == 29]), expectedOutput2)
})
test_that("muRty::get_k_best functions as expected with objective max and n_possible < k_best (also for by_rank), no warning for n_possible == k_best (LP)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 10, objective = 'max', algo = 'lp')
matTest <- unlist(matTest$costs)
expectedOutput3 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput3)
matTestRank <- muRty::get_k_best(mat, 6, objective = 'max', algo = 'lp', by_rank = TRUE)
matTest <- unlist(matTestRank$costs)
expectedOutput4 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput4)
expect_warning(muRty::get_k_best(mat, 10, objective = 'max', algo = 'lp'),
paste0("There are only ", factorial(nrow(mat)), " possible solutions - terminating earlier.")
)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, objective = 'max', algo = 'lp', by_rank = TRUE), regexp = NULL)
expect_warning(muRty::get_k_best(as.matrix(mat), 6, objective = 'max', algo = 'lp'), regexp = NA)
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1, but no error for 2x2 (LP)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp'),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp'),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'lp'), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'lp'), "You have provided an invalid value for k_best.")
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1, but no error for 2x2 (LP, by rank)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp', by_rank = TRUE),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'lp', by_rank = TRUE),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'lp', by_rank = TRUE), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'lp', by_rank = TRUE), "You have provided an invalid value for k_best.")
})
test_that("by_rank argument functions as expected (LP)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
test_by_rank <- muRty::get_k_best(mat, k_best = 3, by_rank = TRUE, algo = 'lp')
expect_error(muRty::get_k_best(mat, 0, algo = 'lp', by_rank = TRUE), "You have provided an invalid value for k_best.")
skip_on_cran()
expectedOutput4 <- list(solutions = list(list(structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)))), costs = list(c(31, 31), c(32, 32, 32, 32, 32), c(33, 33,
33, 33, 33, 33, 33)))
expect_equal(test_by_rank, expectedOutput4)
})
test_that("muRty::get_k_best functions as expected with matrices (LP)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 35, algo = 'lp')
matTest <- sum(unlist(matTest$costs) == 32)
expectedOutput5 <- 5L
expect_equal(matTest, expectedOutput5)
})
test_that("muRty::get_k_best functions as expected with decimal weights (LP)", {
mat <- read.table(
text = "0.5 5 0.5
3 1 3
2.5 4 2.5",
header = FALSE)
matTest <- muRty::get_k_best(mat, 3, by_rank = TRUE, algo = 'lp')
expectedOutput6 <- list(solutions = list(list(structure(c(0, 0, 1, 0, 1, 0, 1, 0,
0), .Dim = c(3L, 3L)), structure(c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3L,
3L))), list(structure(c(0, 1, 0, 0, 0, 1, 1, 0, 0), .Dim = c(3L,
3L)), structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L
))), list(structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L,
3L)), structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L
)))), costs = list(c(4, 4), c(7.5, 7.5), c(10.5, 10.5)))
expect_equal(matTest, expectedOutput6)
})
# Hungarian
test_that("muRty::get_k_best functions as expected with data frames and matrices (Hungarian, by rank for conversion)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 5, algo = 'hungarian')
expectedOutput1 <- list(solutions = list(structure(c(1, 0, 0, 0, 1, 0, 0, 0, 1), .Dim = c(3L,3L)),
structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L)),
structure(c(0, 0, 1, 0, 1, 0, 1, 0, 0), .Dim = c(3L, 3L))),
costs = list(3, 7, 13, 15, 107))
expect_equal(matTest, expectedOutput1)
expect_warning(muRty::get_k_best(mat, 5, algo = 'hungarian'),
"You haven't provided an object of class matrix. Attempting to convert to matrix ..")
expect_warning(muRty::get_k_best(mat, 5, algo = 'hungarian', by_rank = TRUE),
"You haven't provided an object of class matrix. Attempting to convert to matrix ..")
matLarger <- as.matrix(
read.table(
text = "7 51 52 87 38 60 74 66 0 20
50 12 0 64 8 53 0 46 76 42
27 77 0 18 22 48 44 13 0 57
62 0 3 8 5 6 14 0 26 39
0 97 0 5 13 0 41 31 62 48
79 68 0 0 15 12 17 47 35 43
76 99 48 27 34 0 0 0 28 0
0 20 9 27 46 15 84 19 3 24
56 10 45 39 0 93 67 79 19 38
27 0 39 53 46 24 69 46 23 1",
header = FALSE
)
)
attr(matLarger, "dimnames") <- NULL
matSolLarger <- muRty::get_k_best(matLarger, 70, algo = 'hungarian')
expectedOutput2 <- 12L
expect_equal(length(matSolLarger$costs[matSolLarger$costs == 29]), expectedOutput2)
})
test_that("muRty::get_k_best functions as expected with objective max and n_possible < k_best (also for by_rank), no warning for n_possible == k_best (Hungarian)", {
mat <- read.table(
text = "0 5 99
6 1 3
7 4 2",
header = FALSE)
matTest <- muRty::get_k_best(mat, 10, objective = 'max', algo = 'hungarian')
matTest <- unlist(matTest$costs)
expectedOutput3 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput3)
matTestRank <- muRty::get_k_best(mat, 6, objective = 'max', algo = 'hungarian', by_rank = TRUE)
matTest <- unlist(matTestRank$costs)
expectedOutput4 <- c(109, 107, 15, 13, 7, 3)
expect_equal(matTest, expectedOutput4)
expect_warning(muRty::get_k_best(mat, 10, objective = 'max', algo = 'hungarian'),
paste0("There are only ", factorial(nrow(mat)), " possible solutions - terminating earlier.")
)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, objective = 'max', algo = 'hungarian', by_rank = TRUE), regexp = NULL)
expect_warning(muRty::get_k_best(as.matrix(mat), 6, objective = 'max', algo = 'hungarian'), regexp = NA)
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1 but no error for 2x2 (Hungarian)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian'),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian'),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'hungarian'), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'hungarian'), "You have provided an invalid value for k_best.")
})
test_that("muRty::get_k_best throws errors with 1x1 matrices, unequal dimensions, k best < 1 but no error for 2x2 (Hungarian, by rank)", {
mat <- matrix(3, ncol = 1, nrow = 1)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian', by_rank = TRUE),
"Have you provided an empty set or matrix with only a single value? Your matrix should have at least 2 rows and 2 columns.",
fixed = TRUE
)
mat <- matrix(3, ncol = 5, nrow = 7)
expect_error(
muRty::get_k_best(mat, 2, algo = 'hungarian', by_rank = TRUE),
"Number of rows and number of columns are not equal. You need to provide a square matrix (N x N).",
fixed = TRUE
)
mat <- matrix(3, ncol = 2, nrow = 2)
expect_error(muRty::get_k_best(mat, 1, algo = 'hungarian', by_rank = TRUE), regexp = NA)
expect_error(muRty::get_k_best(mat, 0, algo = 'hungarian', by_rank = TRUE), "You have provided an invalid value for k_best.")
})
test_that("by_rank argument functions as expected (Hungarian)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
test_by_rank <- muRty::get_k_best(mat, k_best = 3, by_rank = TRUE, algo = 'hungarian')
expect_error(muRty::get_k_best(mat, 0, algo = 'hungarian', by_rank = TRUE), "You have provided an invalid value for k_best.")
expectedOutput4 <- list(solutions = list(list(structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0), .Dim = c(10L, 10L
)))), costs = list(c(31, 31), c(32, 32, 32, 32, 32), c(33, 33,
33, 33, 33, 33, 33)))
expect_equal(test_by_rank, expectedOutput4)
})
test_that("muRty::get_k_best functions as expected with matrices (Hungarian)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 35, algo = 'hungarian')
matTest <- sum(unlist(matTest$costs) == 32)
expectedOutput5 <- 5L
expect_equal(matTest, expectedOutput5)
})
test_that("muRty::get_k_best functions as expected with decimal weights (Hungarian)", {
mat <- read.table(
text = "0.5 5 0.5
3 1 3
2.5 4 2.5",
header = FALSE)
matTest <- muRty::get_k_best(mat, 3, objective = 'max', algo = 'hungarian')
expectedOutput6 <- list(solutions = list(structure(c(0, 1, 0, 1, 0, 0, 0, 0, 1), .Dim = c(3L,
3L)), structure(c(0, 0, 1, 1, 0, 0, 0, 1, 0), .Dim = c(3L, 3L
)), structure(c(1, 0, 0, 0, 0, 1, 0, 1, 0), .Dim = c(3L, 3L))),
costs = list(10.5, 10.5, 7.5))
expect_equal(matTest, expectedOutput6)
})
test_that("muRty::get_k_best functions as expected with objective max and by_rank (Hungarian & LP)", {
mat <- structure(c(9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, 10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, 6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, 9L, 7L, 14L, 4L, 7L, 13L, 13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'hungarian', by_rank = TRUE)
matTestLP <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'lp', by_rank = TRUE)
expectedOutput7 <- list(c(135, 135), 134, c(133, 133, 133, 133, 133), c(132, 132,
132, 132, 132), c(131, 131, 131, 131, 131, 131, 131))
expect_equal(expectedOutput7, matTest$costs)
expect_equal(expectedOutput7, matTestLP$costs)
expectedOutput8 <- list(list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L))), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L
)), list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L))), list(structure(c(0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))))
expect_equal(matTest$solutions, expectedOutput8)
})
test_that("muRty::get_k_best functions as expected with negative values, objective max and by_rank (Hungarian & LP)", {
mat <- structure(c(-9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, -10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, -6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, -9L, 7L, 14L, 4L, 7L, -13L, -13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'hungarian', by_rank = TRUE)
matTestLP <- muRty::get_k_best(mat, 5, objective = 'max', algo = 'lp', by_rank = TRUE)
expectedOutput9 <- list(135, 134, c(133, 133, 133), c(132, 132, 132, 132), c(131,
131, 131, 131))
expect_equal(expectedOutput9, matTest$costs)
expect_equal(expectedOutput9, matTestLP$costs)
expectedOutput10 <- list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L)), list(structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))), list(structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1), .Dim = c(10L, 10L)), structure(c(0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L))))
expect_equal(matTest$solutions, expectedOutput10)
})
test_that("muRty::get_k_best functions as expected with negative values and by_rank (Hungarian & LP)", {
mat <- structure(c(-9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, -10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, -6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, -9L, 7L, 14L, 4L, 7L, -13L, -13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 5, algo = 'hungarian', by_rank = TRUE)
matTestLP <- muRty::get_k_best(mat, 5, algo = 'lp', by_rank = TRUE)
expectedOutput11 <- list(-29, -28, c(-27, -27), c(-26, -26), c(-25, -25, -25, -25,
-25))
expect_equal(expectedOutput11, matTest$costs)
expect_equal(expectedOutput11, matTestLP$costs)
expectedOutput12 <- list(structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), list(structure(c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L))), list(structure(c(1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
))), list(structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0), .Dim = c(10L, 10L)), structure(c(1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 10L
)), structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0), .Dim = c(10L, 10L)), structure(c(1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))))
expect_equal(matTest$solutions, expectedOutput12)
})
test_that("muRty::get_k_best functions as expected with negative values without rank (Hungarian & LP)", {
mat <- structure(c(-9L, 4L, 7L, 1L, 2L, 13L, 7L, 11L, 14L, 2L, 11L, 3L,
1L, 5L, 5L, 10L, 6L, 14L, 10L, 7L, 9L, 15L, 5L, 5L, 9L, 9L, 14L,
5L, 5L, 2L, 10L, 14L, 9L, 12L, 15L, 1L, 4L, 3L, 6L, 10L, 10L,
6L, 15L, 4L, 12L, 4L, -10L, 12L, 9L, 7L, 6L, 9L, 8L, 12L, 9L,
7L, 8L, 6L, 10L, 7L, 3L, 10L, 6L, 8L, 14L, 2L, 13L, 2L, 6L, 14L,
6L, 1L, 3L, 3L, 8L, 6L, 7L, 15L, 12L, -6L, 8L, 7L, 11L, 1L, 4L,
13L, 8L, 9L, -9L, 7L, 14L, 4L, 7L, -13L, -13L, 12L, 6L, 13L, 12L,
12L), .Dim = c(10L, 10L))
matTest <- muRty::get_k_best(mat, 3, algo = 'hungarian')
matTestLP <- muRty::get_k_best(mat, 3, algo = 'lp')
expectedOutput13 <- list(solutions = list(structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)), structure(c(1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L)),
structure(c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0), .Dim = c(10L, 10L))), costs = list(
-29L, -28L, -27L))
expect_equal(expectedOutput13, matTest)
expect_equal(expectedOutput13, matTestLP)
})
test_that("muRty::get_k_best functions as expected with k_best > n_possible and number of ranks (additional tests; both LP and Hungarian)", {
mat <- read.table(
text = "1 1 1
6 1 3
7 4 2",
header = FALSE)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, algo = 'lp', by_rank = TRUE),
"There are 6 possible solutions. Final solution has been found at rank number 4 which is lower than the k_best specified; terminating here."
)
expect_warning(muRty::get_k_best(as.matrix(mat), 10, algo = 'hungarian', by_rank = TRUE),
"There are 6 possible solutions. Final solution has been found at rank number 4 which is lower than the k_best specified; terminating here."
)
})
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