Renv = new.env(parent = globalenv())
Renv$RoundingTimes <- matrix(c(5.40, 5.50, 5.55,
5.85, 5.70, 5.75,
5.20, 5.60, 5.50,
5.55, 5.50, 5.40,
5.90, 5.85, 5.70,
5.45, 5.55, 5.60,
5.40, 5.40, 5.35,
5.45, 5.50, 5.35,
5.25, 5.15, 5.00,
5.85, 5.80, 5.70,
5.25, 5.20, 5.10,
5.65, 5.55, 5.45,
5.60, 5.35, 5.45,
5.05, 5.00, 4.95,
5.50, 5.50, 5.40,
5.45, 5.55, 5.50,
5.55, 5.55, 5.35,
5.45, 5.50, 5.55,
5.50, 5.45, 5.25,
5.65, 5.60, 5.40,
5.70, 5.65, 5.55,
6.30, 6.30, 6.25),
nrow = 22,
byrow = TRUE,
dimnames = list(1 : 22,
c("Round Out", "Narrow Angle", "Wide Angle")))
Renv$flv <- 1:6
FLenv <- as.FL(Renv)
Renv$wb <- aggregate(warpbreaks$breaks,
by = list(w = warpbreaks$wool,
t = warpbreaks$tension),
FUN = mean)
FLenv$wb <- as.FLTable(Renv$wb)
test_that("Friedman Test on FLMatrix: R example: checking Result Equality without data.name:",{
result = eval_expect_equal({
fit <- friedman.test(RoundingTimes)
},Renv,FLenv,
expectation=c("fit"))
})
## ## Replicate same data and then subset
## Renv$wb <- rbind(Renv$wb,Renv$wb)
## FLenv$wb <- as.FLTable(Renv$wb,
## tableName="ARBaseTestTempTable",
## drop=TRUE)
## test_that("Friedman Test on FLTable: R example: checking Result Equality without data.name:",{
## result = eval_expect_equal({
## fit <- friedman.test(x~w|t, data = wb, subset=flv)
## fit$data.name <- NULL
## class(fit) <- "list"
## },Renv,FLenv,
## verbose=F,
## expectation=c("fit"))
## })
fltMD <- FLTableMD("tblFriedmanTest","datasetid","obsid","groupid","num_val")
data1 <- FLTable("tblFriedmanTest","obsid","groupid","num_val", "datasetid = 1")
data2 <- FLTable("tblFriedmanTest", "obsid","groupid","num_val", "datasetid = 2")
d1 <- as.matrix(data1)
d2 <- as.matrix(data2)
test_that("Friedman Test : DBLytix Example",{
res <- friedman.test(data = fltMD)
R_res1 <- friedman.test(d1)
R_res2 <- friedman.test(d2)
expect_equal(res[[1]]$statistic, R_res1$statistic)
expect_equal(res[[1]]$p.value, R_res1$p.value)
expect_equal(res[[2]]$statistic, R_res2$statistic)
expect_equal(res[[2]]$p.value, R_res2$p.value)
})
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