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BOT: Fix #807: Clean up linter statements around cli conditions #1086

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1 change: 0 additions & 1 deletion .lintr
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Expand Up @@ -15,7 +15,6 @@ linters: linters_with_tags(
implicit_assignment_linter = NULL, # false positives with data.table :=
strings_as_factors_linter = NULL, # R 4.0+ defaults to stringsAsFactors = FALSE
one_call_pipe_linter = NULL, # stylistic preference
keyword_quote_linter = NULL, # stylistic preference
unnecessary_concatenation_linter = NULL, # intentional patterns
library_call_linter = NULL, # intentional patterns in scripts
pipe_consistency_linter = NULL # one_call_pipe_linter exclusion triggers false positives
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8 changes: 3 additions & 5 deletions R/class-forecast-binary.R
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Expand Up @@ -69,24 +69,22 @@
forecast, c("sample_id", "quantile_level")
)
if (!columns_correct) {
#nolint start: keyword_quote_linter
cli_abort(
c(
"!" = "Checking `forecast`: Input looks like a binary forecast, but an
`!` = "Checking `forecast`: Input looks like a binary forecast, but an
additional column called `sample_id` or `quantile` was found.",
"i" = "Please remove the column."
`i` = "Please remove the column."

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file=R/class-forecast-binary.R,line=76,col=9,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
)
)
}
input_check <- check_input_binary(forecast$observed, forecast$predicted)
if (!isTRUE(input_check)) {
cli_abort(
c(
"!" = "Checking `forecast`: Input looks like a binary forecast, but
`!` = "Checking `forecast`: Input looks like a binary forecast, but
found the following issue: {input_check}"
)
)
#nolint end
}
return(invisible(NULL))
}
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2 changes: 1 addition & 1 deletion R/class-forecast-nominal.R
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Expand Up @@ -100,7 +100,7 @@ assert_forecast.forecast_nominal <- function(
if (!all(complete$correct)) {
first_issue <- complete[(correct), ..forecast_unit][1]
first_issue <- lapply(first_issue, FUN = as.character)
#nolint start: keyword_quote_linter object_usage_linter duplicate_argument_linter
#nolint start: object_usage_linter duplicate_argument_linter
issue_location <- paste(names(first_issue), "==", first_issue)
cli_abort(
c(`!` = "Found incomplete forecasts",
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2 changes: 1 addition & 1 deletion R/class-forecast-ordinal.R
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Expand Up @@ -106,7 +106,7 @@ assert_forecast.forecast_ordinal <- function(
if (!all(complete$correct)) {
first_issue <- complete[(correct), ..forecast_unit][1]
first_issue <- lapply(first_issue, FUN = as.character)
#nolint start: keyword_quote_linter object_usage_linter duplicate_argument_linter
#nolint start: object_usage_linter duplicate_argument_linter
issue_location <- paste(names(first_issue), "==", first_issue)
cli_abort(
c(`!` = "Found incomplete forecasts",
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4 changes: 2 additions & 2 deletions R/class-forecast-point.R
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Expand Up @@ -53,12 +53,12 @@ assert_forecast.forecast_point <- function(
) {
forecast <- assert_forecast_generic(forecast, verbose)
assert_forecast_type(forecast, actual = "point", desired = forecast_type)
#nolint start: keyword_quote_linter object_usage_linter
#nolint start: object_usage_linter
input_check <- check_input_point(forecast$observed, forecast$predicted)
if (!isTRUE(input_check)) {
cli_abort(
c(
"!" = "Checking `forecast`: Input looks like a point forecast, but found
`!` = "Checking `forecast`: Input looks like a point forecast, but found
the following issue: {input_check}"
)
)
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30 changes: 12 additions & 18 deletions R/class-forecast.R
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Expand Up @@ -79,13 +79,11 @@
forecast, forecast_type = NULL, verbose = TRUE, ...
) {
cli_abort(
#nolint start: keyword_quote_linter
c(
"!" = "The input needs to be a valid forecast object.",
"i" = "Please convert to `forecast` object first by calling the
`!` = "The input needs to be a valid forecast object.",
`i` = "Please convert to `forecast` object first by calling the

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file=R/class-forecast.R,line=84,col=7,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
appropriate {.fn as_forecast_<type>} function)."
)
#nolint end
)
}

Expand Down Expand Up @@ -117,7 +115,7 @@
if (problem) {
cli_abort(
c(
"!" = "Found columns `quantile_level` and `sample_id`.
`!` = "Found columns `quantile_level` and `sample_id`.
Only one of these is allowed"
)
)
Expand All @@ -136,23 +134,21 @@
# check whether there are any NA values
if (anyNA(data)) {
if (nrow(na.omit(data)) == 0) {
#nolint start: keyword_quote_linter
cli_abort(
c(
"!" = "After removing rows with NA values in the data, no forecasts
`!` = "After removing rows with NA values in the data, no forecasts
are left."
)
)
}
if (verbose) {
cli_inform(
c(
"i" = "Some rows containing NA values may be removed.
`i` = "Some rows containing NA values may be removed.

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file=R/class-forecast.R,line=147,col=11,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
This is fine if not unexpected."
)
)
}
#nolint end
}

return(data[])
Expand Down Expand Up @@ -292,15 +288,13 @@
)
if (inherits(validation, "try-error")) {
cli_warn(
#nolint start: keyword_quote_linter
c(
"!" = "Error in validating forecast object: {validation}.",
"i" = "Note this error is sometimes related to `data.table`s `print`.
`!` = "Error in validating forecast object: {validation}.",
`i` = "Note this error is sometimes related to `data.table`s `print`.

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file=R/class-forecast.R,line=293,col=11,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
Run {.help [{.fun assert_forecast}](scoringutils::assert_forecast)}
to confirm. To get rid of this warning entirely,
call `as.data.table()` on the forecast object."
)
#nolint end
)
}
}
Expand All @@ -323,7 +317,7 @@
if (inherits(validation, "try-error")) {
cli_warn(
c(
"!" = "Error in validating forecast object: {validation}"
`!` = "Error in validating forecast object: {validation}"
)
)
}
Expand All @@ -346,7 +340,7 @@
if (inherits(validation, "try-error")) {
cli_warn(
c(
"!" = "Error in validating forecast object: {validation}"
`!` = "Error in validating forecast object: {validation}"
)
)
}
Expand All @@ -369,7 +363,7 @@
if (inherits(validation, "try-error")) {
cli_warn(
c(
"!" = "Error in validating forecast object: {validation}"
`!` = "Error in validating forecast object: {validation}"
)
)
}
Expand Down Expand Up @@ -428,7 +422,7 @@
if (inherits(forecast_type, "try-error")) {
cli_inform(
c(
"!" = "Could not determine forecast type due to error in validation." #nolint
`!` = "Could not determine forecast type due to error in validation."
)
)
} else {
Expand All @@ -443,7 +437,7 @@
if (inherits(forecast_unit, "try-error")) {
cli_inform(
c(
"!" = "Could not determine forecast unit." #nolint
`!` = "Could not determine forecast unit."
)
)
} else {
Expand Down
12 changes: 5 additions & 7 deletions R/class-scores.R
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Expand Up @@ -114,25 +114,23 @@
assert_data_frame(x)
metrics <- attr(x, "metrics")
if (error && is.null(metrics)) {
#nolint start: keyword_quote_linter
cli_abort(
c(
"!" = "Input needs an attribute `metrics` with the names of the
`!` = "Input needs an attribute `metrics` with the names of the
scoring rules that were used for scoring.",
"i" = "See `?get_metrics` for further information."
`i` = "See `?get_metrics` for further information."

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file=R/class-scores.R,line=121,col=9,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
)
)
#nolint end
}

if (!all(metrics %in% names(x))) {
#nolint start: keyword_quote_linter object_usage_linter
#nolint start: object_usage_linter
missing <- setdiff(metrics, names(x))
cli_warn(
c(
"!" = "The following scores have been previously computed, but are no
`!` = "The following scores have been previously computed, but are no
longer column names of the data: {.val {missing}}",
"i" = "See {.code ?get_metrics} for further information."
`i` = "See {.code ?get_metrics} for further information."
)
)
#nolint end
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4 changes: 1 addition & 3 deletions R/get-correlations.R
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Expand Up @@ -87,14 +87,12 @@
# check correlations is actually a matrix of correlations
col_present <- check_columns_present(correlations, "metric")
if (any(lower_triangle > 1, na.rm = TRUE) || !isTRUE(col_present)) {
#nolint start: keyword_quote_linter
cli_abort(
c(
"Found correlations > 1 or missing `metric` column.",
"i" = "Did you forget to call {.fn scoringutils::get_correlations}?"
`i` = "Did you forget to call {.fn scoringutils::get_correlations}?"

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file=R/get-correlations.R,line=93,col=9,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
)
)
#nolint end
}

rownames(lower_triangle) <- colnames(lower_triangle)
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6 changes: 3 additions & 3 deletions R/get-forecast-type.R
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Expand Up @@ -29,12 +29,12 @@ assert_forecast_type <- function(data,
desired = NULL) {
assert_character(desired, null.ok = TRUE)
if (!is.null(desired) && desired != actual) {
#nolint start: object_usage_linter keyword_quote_linter
#nolint start: object_usage_linter
cli_abort(
c(
"!" = "Forecast type determined by scoringutils based on input:
`!` = "Forecast type determined by scoringutils based on input:
{.val {actual}}.",
"i" = "Desired forecast type: {.val {desired}}."
`i` = "Desired forecast type: {.val {desired}}."
)
)
#nolint end
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2 changes: 1 addition & 1 deletion R/get-pit-histogram.R
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Expand Up @@ -58,6 +58,6 @@ get_pit_histogram <- function(forecast, num_bins, breaks, by,
#' @export
get_pit_histogram.default <- function(forecast, num_bins, breaks, by, ...) {
cli_abort(c(
"!" = "The input needs to be a valid forecast object represented as quantiles or samples." # nolint
`!` = "The input needs to be a valid forecast object represented as quantiles or samples."
))
}
2 changes: 0 additions & 2 deletions R/helper-quantile-interval-range.R
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Expand Up @@ -82,12 +82,10 @@
if (length(unique(forecast$boundary)) < 2) {
cli_abort(
c(
#nolint start: keyword_quote_linter
`!` = "No valid forecast intervals found.",
`i` = "A forecast interval comprises two

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file=R/helper-quantile-interval-range.R,line=86,col=9,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
quantiles with quantile levels symmetric around the median
(e.g. 0.25 and 0.75)"
#nolint end
)
)
}
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8 changes: 3 additions & 5 deletions R/metrics-interval-range.R
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Expand Up @@ -32,25 +32,23 @@
if (any(diff < 0)) {
cli_abort(
c(
"!" = "All values in `upper` need to be greater than or equal to
`!` = "All values in `upper` need to be greater than or equal to
the corresponding values in `lower`"
)
)
}
if (any(interval_range > 0 & interval_range < 1, na.rm = TRUE)) {
#nolint start: keyword_quote_linter
cli_warn(
c(
"!" = "Found interval ranges between 0 and 1. Are you sure that's
`!` = "Found interval ranges between 0 and 1. Are you sure that's
right? An interval range of 0.5 e.g. implies a (49.75%, 50.25%)
prediction interval.",
"i" = "If you want to score a (25%, 75%) prediction interval, set
`i` = "If you want to score a (25%, 75%) prediction interval, set

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file=R/metrics-interval-range.R,line=46,col=9,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
`interval_range = 50`."
),
.frequency = "once",
.frequency_id = "small_interval_range"
)
#nolint end
}
return(invisible(NULL))
}
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2 changes: 1 addition & 1 deletion R/metrics-nominal.R
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Expand Up @@ -75,7 +75,7 @@ assert_input_categorical <- function(
# Allow for numeric errors
invalid_rows <- abs(summed_predictions - 1) > 1e-4
if (any(invalid_rows)) {
#nolint start: keyword_quote_linter object_usage_linter
#nolint start: object_usage_linter
row_indices <- which(invalid_rows)
cli_abort(
c(
Expand Down
6 changes: 3 additions & 3 deletions R/metrics-point.R
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Expand Up @@ -49,12 +49,12 @@ assert_dims_ok_point <- function(observed, predicted) {
n_pred <- length(as.vector(predicted))
# check that both are either of length 1 or of equal length
if ((n_obs != 1) && (n_pred != 1) && (n_obs != n_pred)) {
#nolint start: keyword_quote_linter object_usage_linter
#nolint start: object_usage_linter
cli_abort(
c(
"!" = "`observed` and `predicted` must either be of length 1 or
`!` = "`observed` and `predicted` must either be of length 1 or
of equal length.",
"i" = "Found {n_obs} and {n_pred}."
`i` = "Found {n_obs} and {n_pred}."
)
)
#nolint end
Expand Down
20 changes: 7 additions & 13 deletions R/metrics-quantile.R
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Expand Up @@ -191,11 +191,11 @@
complete_intervals <-
duplicated(interval_ranges) | duplicated(interval_ranges, fromLast = TRUE)
if (!all(complete_intervals) && !isTRUE(na.rm)) {
#nolint start: keyword_quote_linter object_usage_linter
#nolint start: object_usage_linter
incomplete <- quantile_level[quantile_level != 0.5][!complete_intervals]
cli_abort(
c(
"!" = "Not all quantile levels specified form symmetric prediction
`!` = "Not all quantile levels specified form symmetric prediction
intervals.
The following quantile levels miss a corresponding lower/upper bound:
{.val {incomplete}}.
Expand Down Expand Up @@ -347,10 +347,10 @@
100 - (100 - interval_range) / 2
) / 100
if (!all(necessary_quantiles %in% quantile_level)) {
#nolint start: keyword_quote_linter object_usage_linter
#nolint start: object_usage_linter
cli_abort(
c(
"!" = "To compute the interval coverage for an interval range of
`!` = "To compute the interval coverage for an interval range of
{.val {interval_range}%}, the {.val {necessary_quantiles}} quantiles
are required"
)
Expand Down Expand Up @@ -442,14 +442,12 @@
dim(predicted) <- c(n, N)
}
if (!(0.5 %in% quantile_level)) {
#nolint start: keyword_quote_linter
cli_inform(
c(
"i" = "Median not available, interpolating median from the two
`i` = "Median not available, interpolating median from the two

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file=R/metrics-quantile.R,line=447,col=9,[keyword_quote_linter] Only quote named arguments to functions if necessary, i.e., if the name is not a valid R symbol (see ?make.names).
innermost quantiles in order to compute bias."
)
)
#nolint end
}
bias <- sapply(1:n, function(i) {
bias_quantile_single_vector(
Expand Down Expand Up @@ -493,14 +491,12 @@
order <- order(quantile_level)
predicted <- predicted[order]
if (!all(diff(predicted) >= 0)) {
#nolint start: keyword_quote_linter
cli_abort(
c(
"!" = "Predictions must not be decreasing with increasing
`!` = "Predictions must not be decreasing with increasing
quantile level."
)
)
#nolint end
}

median_prediction <- interpolate_median(predicted, quantile_level)
Expand Down Expand Up @@ -581,14 +577,12 @@
ae_median_quantile <- function(observed, predicted, quantile_level) {
assert_input_quantile(observed, predicted, quantile_level)
if (!any(quantile_level == 0.5)) {
#nolint start: keyword_quote_linter
cli_abort(
c(
"!" = "In order to compute the absolute error of the median,
`!` = "In order to compute the absolute error of the median,
{.val 0.5} must be among the quantiles given"
)
)
#nolint end
}
if (is.null(dim(predicted))) {
predicted <- matrix(predicted, nrow = 1)
Expand Down
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