Nothing
library(kamila)
context('KAMILA clustering')
test_that('KAMILA runs as expected, small data set', {
suppressWarnings(RNGversion("3.5.0"))
set.seed(1)
res1 <- kamila(
conVar = data.frame(rnorm(15)),
catFactor = data.frame(factor(sample(1:4,size=15,rep=T))),
numClust = 2,
numInit = 10,
maxIter = 25,
conInitMethod = 'runif',
catBw = 0.025,
verbose = FALSE,
calcNumClust = 'none',
numPredStrCvRun = 20,
predStrThresh = 0.8
)
expect_identical(res1$finalMemb, c(2,1,2,1,1,2,1,1,1,2,1,1,2,2,1))
})
test_that('KAMILA warns if pred-strength is used with a single numClust',{
expect_warning(
kamila(
conVar = data.frame(rnorm(10),rnorm(10))
,catFactor = data.frame(factor(sample(1:4,size=10,rep=T)),
factor(sample(1:4,size=10,rep=T)))
,numClust = 2
,numInit = 2
,maxIter = 2
,conInitMethod = 'runif'
,catBw = 0.025
,verbose = FALSE
,calcNumClust = 'ps'
,numPredStrCvRun = 2
,predStrThresh = 0.8
),
'Input parameter numClust is a scalar; the prediction strength'
)
})
test_that('KAMILA throws error if numClust is length > 1 with calcNumClust=="none"',{
expect_error(
kamila(
conVar = data.frame(rnorm(10),rnorm(10))
,catFactor = data.frame(factor(sample(1:4,size=10,rep=T)),
factor(sample(1:4,size=10,rep=T)))
,numClust = 2:5
,numInit = 2
,maxIter = 2
,conInitMethod = 'runif'
,catBw = 0.025
,verbose = FALSE
,calcNumClust = 'none'
,numPredStrCvRun = 2
,predStrThresh = 0.8
),
'Input parameter numClust must be length 1 if calcNumClust == "none"'
)
})
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