library(MixMatrix)
context("Testing input type integrity")
test_that("trying wrong type of input", {
expect_error(rmatrixnorm(n = 1, mean = matrix(c("A", 1))), "numeric")
expect_error(rmatrixt(n = 1, df = 1, mean = matrix(c("A", 1))), "numeric")
expect_error(rmatrixinvt(n = 1, df = 1, mean = matrix(c("A", 1))), "numeric")
expect_error(dmatrixnorm(x = matrix(c("A", 1))), "numeric")
expect_error(dmatrixt(x = matrix(c("A", 1)), df = 1), "numeric")
expect_error(dmatrixinvt(x = matrix(c("A", 1)), df = 1), "numeric")
expect_error(rmatrixnorm(
n = 1, mean = matrix(c(0, 0)),
U = matrix(c("A", 0, 0, 1), nrow = 2)
), "non-numeric", ignore.case = TRUE)
expect_error(rmatrixt(
n = 1, df = 1, mean = matrix(c(0, 0)),
U = matrix(c("A", 0, 0, 1), nrow = 2)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(rmatrixinvt(
n = 1, df = 1, mean = matrix(c(0, 0)),
U = matrix(c("A", 0, 0, 1), nrow = 2)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixnorm(
x = matrix(c(0, 0)),
U = matrix(c("A", 0, 0, 1), nrow = 2)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixt(
x = matrix(c(0, 0)), df = 1,
U = matrix(c("A", 0, 0, 1), nrow = 2)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixinvt(
x = mean(matrix(c(0, 0))), df = 1,
U = matrix(c("A", 0, 0, 1), nrow = 2)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(rmatrixnorm(
n = "A", mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
list = FALSE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(rmatrixnorm(
n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = "A"),
L = matrix(c(2, 1, 0, .1), nrow = 2),
R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
list = FALSE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(rmatrixnorm(
n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c("A", 1, 0, .1), nrow = 2),
R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
list = FALSE
))
expect_error(rmatrixnorm(
n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
R = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
list = FALSE
))
expect_error(rmatrixnorm(
n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
R = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
list = TRUE
))
expect_error(rmatrixnorm(
n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
U = matrix(c("A", 1, 0, .1), nrow = 2),
R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
list = FALSE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixnorm(matrix(c("A", 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
log = TRUE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = "A"),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
log = TRUE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c("A", 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
log = TRUE
))
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c("A", 1, 0, .1), nrow = 2),
log = TRUE
))
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = "A"),
log = TRUE
))
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
R = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
log = TRUE
))
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
U = matrix(c("A", 1, 0, .1), nrow = 2),
log = TRUE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
L = matrix(c(2, 1, 0, .1), nrow = 2),
V = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
log = TRUE
),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)), tol = "Q"),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)),
max.iter = "Q"
),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)),
U = matrix("Q", nrow = 5, ncol = 5)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)),
V = matrix("Q", nrow = 5, ncol = 5)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)), tol = "Q"),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)), max.iter = "Q"),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)), df = "Q"),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)),
U = matrix("Q", nrow = 5, ncol = 5)
),
"non-numeric",
ignore.case = TRUE
)
expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)),
V = matrix("Q", nrow = 5, ncol = 5)
),
"non-numeric",
ignore.case = TRUE
)
})
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