Dear everyone,
my R package stepR (https://cran.r-project.org/web/packages/stepR/) fails the
CRAN package checks on M1 Mac, but the error does not occur on the macOS
builder (https://mac.r-project.org/macbuilder/submit.html). So, I am unable to
reproduce the error and hence unable to fix it (starring at the code did not
help either).
The relevant part is
* checking tests ...
Running ��testthat.R�� [35s/35s]
[36s/36s] ERROR
Running the tests in ��tests/testthat.R�� failed.
> test_check("stepR")
[ FAIL 1 | WARN 0 | SKIP 23 | PASS 22741 ]
���� Failed tests
��������������������������������������������������������������������������������������������������������������������������������
�w�w Failure ('test-critVal.R:2463:3'): family 'hsmuce' works
�w�w�w�w�w�w�w�w�w�w�w�w�w�w�w�w�w�w�w�w
compare <= as.integer(ncol(compareStat) * testalpha + tolerance) is not TRUE
`actual`: FALSE
`expected`: TRUE
sqrt
Backtrace:
�g
1. �|�wstepR (local) testVector(...) at test-critVal.R:2463:2
2. �|�wtestthat::expect_true(...) at test-critVal.R:50:2
[ FAIL 1 | WARN 0 | SKIP 23 | PASS 22741 ]
Error: Test failures
Execution halted
Has anyone an idea how to tackle this problem?
The test code is long (a full version is available on CRAN). The following is
the code part that I think is relevant (once again I cannot reproduce the
error, so I am also unable to give a minimal reproducible example, I can only
guess one):
library(stepR)
library(testthat)
testn <- 1024L
teststat <- monteCarloSimulation(n = 1024L, r = 100L, family = "hsmuce") #
essentially a matrix with values generated by rnorm()
testalpha <- 0.0567
tolerance <- 1e-12
ret <- critVal(n = 1024L, penalty = "sqrt", output = "vector", family =
"hsmuce", alpha = testalpha, stat = teststat)
statVec <- as.numeric(teststat)
tol <- min(min(diff(sort(statVec[is.finite(statVec)]))) / 2, 1e-12) # different
to the CRAN version to be robust to two values very close to each other
rejected <- matrix(FALSE, ncol(teststat), nrow(teststat))
compare <- integer(ncol(teststat))
for (i in 1:nrow(teststat)) {
rejected[, i] <- teststat[i, ] > ret[i] + tol
}
for (i in 1:ncol(teststat)) {
compare[i] <- max(rejected[i, ])
}
compare <- sum(compare)
expect_true(compare <= as.integer(ncol(teststat) * testalpha + tolerance), info
= "sqrt")
# version with an additional tolerance (suggested when the test failed on CRAN,
but it does not help either)
# both sides are small intgers, so it should not be needed
expect_true(as.integer(compare + tolerance) <= as.integer(ncol(teststat) *
testalpha + tolerance) + 0.5, info = "sqrt")
I am not sure how to approach this problem, so any suggestions are very much
welcomed.
Many thanks and best wishes,
Florian Pein
(Lancaster university)
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