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#' Test for select_h
#'
#'
#'
#' @srrstats {G5.1, G5.5} data sets are generated using simple functions with
#' fixed seed
#' @srrstats {G5.2,G5.2a,G5.2b} all the error and warning messages are tested
#' @srrstats {G5.8, G5.8a,G5.8b,G5.8c} edge conditions
#'
#' @noRd
library(testthat)
## "Tests for select_h function"
# Test 1: Verify Error on Invalid Input
test_that("Error on invalid method input", {
expect_error(select_h(x = matrix(rnorm(100), ncol = 2),
alternative = "location", n_cores = "invalid"),
"n_cores must be a numeric value", fixed=TRUE)
set.seed(123)
expect_error(select_h(x = matrix(rnorm(100), ncol = 2),
alternative = "invalid"),
"The alternative argument should be one of 'location', 'scale' or
'skewness'", fixed=TRUE)
# x is not numeric
expect_error(select_h(x = "invalid", alternative="skewness"),
"x must be numeric", fixed=TRUE)
x <- matrix(rnorm(100), ncol = 2)
x[1,] <- NA
expect_error(select_h(x = x, alternative="skewness"),
"There are missing values in x!", fixed=TRUE)
x[1,] <- Inf
expect_error(select_h(x = x, alternative="skewness"),
"There are undefined values in x, that is Nan, Inf, -Inf", fixed=TRUE)
x <- matrix(rnorm(100), ncol = 2)
y <- matrix(rnorm(100), ncol = 2)
y[1,] <- NA
expect_error(select_h(x = x, y = y, alternative="skewness"),
"There are missing values in y!", fixed=TRUE)
y[1,] <- Inf
expect_error(select_h(x = x, y = y, alternative="skewness"),
"There are undefined values in y, that is Nan, Inf, -Inf", fixed=TRUE)
x <- matrix(rnorm(100), ncol = 2)
y <- matrix(rnorm(90), ncol = 3)
expect_error(select_h(x, y, alternative="skewness"),
"'x' and 'y' must have the same number of columns.",
fixed=TRUE)
x <- matrix(rnorm(100), ncol = 2)
y <- rep(c(1,2), each=20)
expect_error(select_h(x, y, alternative="skewness"),
"'x' and 'y' must have the same number of rows.", fixed=TRUE)
y <- rep(c(1,2), each=25)
expect_error(select_h(x, y, alternative="skewness", delta_dim=c(1,2,1)),
"delta_dim must be 1 or a numeric vector of length equal to the
number of columns of pooled.", fixed=TRUE)
x <- rnorm(50)
y <- rnorm(50, 10)
expect_error(select_h(x, y, alternative="skewness",
h_values = c("a","b","c")),
"h_values must be a numeric vector", fixed=TRUE)
expect_error(select_h(x, y, alternative="skewness",
delta = c("a","b","c")),
"delta must be a numeric vector", fixed=TRUE)
})
## # Test 1: test for select_h
test_that("Select h", {
set.seed(123)
# normality
result <- select_h(x = as.data.frame(matrix(rnorm(20),ncol=2)),
alternative="location")
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
result <- select_h(x = as.data.frame(matrix(rnorm(20),ncol=2)),
alternative="scale", n_cores = 2)
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
# two-sample
result <- select_h(x = matrix(rnorm(20),ncol=2),
y = as.data.frame(matrix(rnorm(20),ncol=2)), alternative="location")
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
result <- select_h(x = matrix(rnorm(20),ncol=2),
y = matrix(rnorm(20),ncol=2), alternative="skewness")
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
result <- select_h(x = matrix(rnorm(20),ncol=2),
y = matrix(rnorm(20),ncol=2), alternative="scale")
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
# k-sample
result <- select_h(x = matrix(rnorm(30),ncol=2), y = rep(c(1,2,3),each=5),
alternative="scale")
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
result <- select_h(x = matrix(rnorm(30),ncol=2), y = rep(c(1,2,3),each=5),
alternative="location")
expect_equal(class(result$h_sel), "numeric")
expect_equal(class(result$power), "data.frame")
})
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