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muffle "X should be in range (0, 1)" warning #788

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merged 3 commits into from
Dec 18, 2023
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muffle "X should be in range (0, 1)" warning #788

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47f785b
muffle "X should be in range (0, 1)" warning
EmilHvitfeldt Dec 15, 2023
a6efda2
remove duplicate withCallingHandlers()
EmilHvitfeldt Dec 15, 2023
250d2ff
rev version
Dec 18, 2023
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
Package: tune
Title: Tidy Tuning Tools
Version: 1.1.2.9004
Version: 1.1.2.9005
Authors@R: c(
person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-2402-136X")),
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10 changes: 9 additions & 1 deletion R/tune_bayes.R
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Expand Up @@ -578,13 +578,21 @@ fit_gp <- function(dat, pset, metric, control, eval_time = NULL, ...) {
}

opts <- list(...)

withCallingHandlers({
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i chose to do one call to withCallingHandlers() around the whole if instead of two because it felt better.

no strong opinion either way

if (any(names(opts) == "trace") && opts$trace) {
gp_fit <- GPfit::GP_fit(X = x, Y = dat$mean, ...)
} else {
tmp_output <- utils::capture.output(
gp_fit <- GPfit::GP_fit(X = x, Y = dat$mean, ...)
)
}
}},
warning = function(w) {
if (w$message == "X should be in range (0, 1)") {
rlang::cnd_muffle(w)
}
}
)

gp_fit
}
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12 changes: 0 additions & 12 deletions tests/testthat/_snaps/bayes.md
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Expand Up @@ -451,8 +451,6 @@
Message
! The Gaussian process model is being fit using 1 features but only has 2
data points to do so. This may cause errors or a poor model fit.
! Gaussian process model: X should be in range (0, 1)
! Gaussian process model: X should be in range (0, 1)

# too few starting values

Expand Down Expand Up @@ -523,42 +521,32 @@
the Gaussian process model.
! The Gaussian process model is being fit using 1 features but only has 2
data points to do so. This may cause errors or a poor model fit.
! Gaussian process model: X should be in range (0, 1)
! For the rsq estimates, 1 missing value was found and removed before fitting
the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 2 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 3 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 4 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 5 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 6 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 7 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 8 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! For the rsq estimates, 9 missing values were found and removed before
fitting the Gaussian process model.
! Gaussian process model: X should be in range (0, 1)
! validation: internal: A correlation computation is required, but `estimate` is constant and ha...
! No improvement for 10 iterations; returning current results.

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