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Issue #500: Reduce messages in bias_quantile() #501

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merged 2 commits into from
Nov 28, 2023
Merged

Issue #500: Reduce messages in bias_quantile() #501

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64435a3
Update bias_quantile to only produce a message once
nikosbosse Nov 24, 2023
5f182da
move error message from `bias_quantile_single_vector()` to `bias_quan…
nikosbosse Nov 24, 2023
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12 changes: 7 additions & 5 deletions R/metrics-quantile.R
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Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,7 @@
reformatted[, eval(cols) := do.call(
interval_score,
list(observed = observed,
lower = lower,

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file=R/metrics-quantile.R,line=123,col=9,[indentation_linter] Indentation should be 6 spaces but is 9 spaces.
upper = upper,
interval_range = range,
weigh = weigh,
Expand All @@ -128,7 +128,7 @@
)
)]

if (!count_median_twice) {

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file=R/metrics-quantile.R,line=131,col=7,[if_not_else_linter] In a simple if/else statement, prefer `if (A) x else y` to the less-readable `if (!A) y else x`.
reformatted[, weight := ifelse(range == 0, 0.5, 1)]
} else {
reformatted[, weight := 1]
Expand All @@ -137,7 +137,7 @@
# summarise results by forecast_id
reformatted <- reformatted[
, lapply(.SD, weighted.mean, na.rm = na.rm, w = weight),
by = c("forecast_id"),

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file=R/metrics-quantile.R,line=140,col=10,[unnecessary_concatenation_linter] Unneeded concatenation of a constant. Remove the "c" call.
.SDcols = colnames(reformatted) %like% paste(cols, collapse = "|")
]

Expand Down Expand Up @@ -224,14 +224,14 @@
necessary_quantiles <- c((100 - range) / 2, 100 - (100 - range) / 2) / 100
if (!all(necessary_quantiles %in% quantile)) {
warning(
"To compute the coverage for a range of ", range, "%, the quantiles ",

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file=R/metrics-quantile.R,line=227,col=6,[indentation_linter] Hanging indent should be 12 spaces but is 6 spaces.
necessary_quantiles, " are required. Returning `NA`.")
return(NA)
}
r <- range
reformatted <- quantile_to_interval(observed, predicted, quantile)
reformatted <- reformatted[range %in% r]
reformatted[, coverage := ifelse(

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file=R/metrics-quantile.R,line=234,col=29,[redundant_ifelse_linter] Just use the logical condition (or its negation) directly instead of calling ifelse(x, TRUE, FALSE)
observed >= lower & observed <= upper, TRUE, FALSE
)]
return(reformatted$coverage)
Expand Down Expand Up @@ -291,7 +291,7 @@
#' )
#' quantile <- c(0.1, 0.25, 0.5, 0.75, 0.9)
#' interval_coverage_deviation_quantile(observed, predicted, quantile)
interval_coverage_deviation_quantile <- function(observed, predicted, quantile) {

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file=R/metrics-quantile.R,line=294,col=1,[object_length_linter] Variable and function names should not be longer than 30 characters.
assert_input_quantile(observed, predicted, quantile)

# transform available quantiles into central interval ranges
Expand All @@ -299,25 +299,25 @@

# check if all necessary quantiles are available
necessary_quantiles <- unique(c(
(100 - available_ranges) / 2,

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file=R/metrics-quantile.R,line=302,col=4,[indentation_linter] Hanging indent should be 34 spaces but is 4 spaces.
100 - (100 - available_ranges) / 2) / 100
)
if (!all(necessary_quantiles %in% quantile)) {
missing <- necessary_quantiles[!necessary_quantiles %in% quantile]
warning(
"To compute coverage deviation, all quantiles must form central ",

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file=R/metrics-quantile.R,line=308,col=6,[indentation_linter] Hanging indent should be 12 spaces but is 6 spaces.
"symmetric prediction intervals. Missing quantiles: ",
toString(missing), ". Returning `NA`.")
return(NA)
}

reformatted <- quantile_to_interval(observed, predicted, quantile)[range != 0]
reformatted[, coverage := ifelse(

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file=R/metrics-quantile.R,line=315,col=29,[redundant_ifelse_linter] Just use the logical condition (or its negation) directly instead of calling ifelse(x, TRUE, FALSE)
observed >= lower & observed <= upper, TRUE, FALSE
)]
reformatted[, coverage_deviation := coverage - range / 100]
out <- reformatted[, .(coverage_deviation = mean(coverage_deviation)),
by = c("forecast_id")]

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file=R/metrics-quantile.R,line=320,col=27,[unnecessary_concatenation_linter] Unneeded concatenation of a constant. Remove the "c" call.
return(out$coverage_deviation)
}

Expand Down Expand Up @@ -390,8 +390,14 @@
if (is.null(dim(predicted))) {
dim(predicted) <- c(n, N)
}
if (!(0.5 %in% quantile)) {
message(
"Median not available, computing bias as mean of the two innermost ",
"quantiles in order to compute bias."
)
}
bias <- sapply(1:n, function(i) {
bias_quantile_single_vector(observed[i], predicted[i,], quantile, na.rm)
bias_quantile_single_vector(observed[i], predicted[i, ], quantile, na.rm)
})
return(bias)
}
Expand Down Expand Up @@ -437,10 +443,6 @@
median_prediction <- predicted[quantile == 0.5]
} else {
# if median is not available, compute as mean of two innermost quantile
message(
"Median not available, computing as mean of two innermost quantile",
" in order to compute bias."
)
median_prediction <-
0.5 * predicted[quantile == max(quantile[quantile < 0.5])] +
0.5 * predicted[quantile == min(quantile[quantile > 0.5])]
Expand Down
7 changes: 7 additions & 0 deletions tests/testthat/test-metrics-quantile.R
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Original file line number Diff line number Diff line change
Expand Up @@ -791,3 +791,10 @@ test_that("bias_quantile(): quantiles must be unique", {
quantiles <- c(0.3, 0.5, 0.8, 0.9)
expect_silent(bias_quantile(observed = 3, predicted, quantiles))
})

test_that("bias_quantile only produces one message", {
expect_message(
bias_quantile(observed, predicted[, -3], quantile[-3]),
"Median not available, computing bias as mean of the two innermost quantiles in order to compute bias."
)
})
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