Fix pkgdown

NAMESPACE

@@ -31,8 +31,8 @@ export(crps_sample)
 export(dispersion)
 export(dss_sample)
 export(get_duplicate_forecasts)
-export(get_forecast_unit)
 export(get_forecast_type)
+export(get_forecast_unit)
 export(interval_coverage_deviation_quantile)
 export(interval_coverage_quantile)
 export(interval_coverage_sample)
@@ -61,6 +61,7 @@ export(plot_ranges)
 export(plot_score_table)
 export(plot_wis)
 export(quantile_score)
+export(quantile_to_interval)
 export(run_safely)
 export(sample_to_quantile)
 export(score)

R/check-input-helpers.R

@@ -5,7 +5,7 @@
 #' @inheritDotParams checkmate::check_numeric
 #' @importFrom checkmate check_atomic_vector check_numeric
 #' @inherit document_check_functions return
-#' @keywords internal
+#' @keywords internal_input_check
 check_numeric_vector <- function(x, ...) {
   # check functions must return TRUE on success
   # and a custom error message otherwise
@@ -36,7 +36,7 @@ check_numeric_vector <- function(x, ...) {
 #'
 #' @return None. Function errors if quantiles are invalid.
 #'
-#' @keywords internal
+#' @keywords internal_input_check
 check_quantiles <- function(quantiles, name = "quantiles", range = c(0, 1)) {
   if (any(quantiles < range[1]) || any(quantiles > range[2])) {
     stop(name, " must be between ", range[1], " and ", range[2])
@@ -57,7 +57,7 @@ check_quantiles <- function(quantiles, name = "quantiles", range = c(0, 1)) {
 #' @param expr an expression to be evaluated
 #' @importFrom checkmate assert assert_numeric check_matrix
 #' @inherit document_check_functions return
-#' @keywords internal
+#' @keywords internal_input_check
 check_try <- function(expr) {
   result <- try(expr, silent = TRUE)
   if (is.null(result)) {
@@ -79,7 +79,7 @@ check_try <- function(expr) {
 #' @return The function returns `NULL`, but throws an error if the variable is
 #' missing.
 #'
-#' @keywords internal
+#' @keywords internal_input_check
 assert_not_null <- function(...) {
   vars <- list(...)
   varnames <- names(vars)
@@ -112,7 +112,7 @@ assert_not_null <- function(...) {
 #' within another checking function.
 #' @inherit document_assert_functions return
 #'
-#' @keywords internal
+#' @keywords internal_input_check
 assert_equal_length <- function(...,
                                 one_allowed = TRUE,
                                 call_levels_up = 2) {
@@ -161,7 +161,7 @@ assert_equal_length <- function(...,
 #' @param attribute The name of the attribute to check
 #' @param expected The expected value of the attribute
 #' @inherit document_check_functions return
-#' @keywords internal
+#' @keywords internal_input_check
 check_attribute_conflict <- function(object, attribute, expected) {
   existing <- attr(object, attribute)
   if (is.vector(existing) && is.vector(expected)) {
@@ -188,8 +188,9 @@ check_attribute_conflict <- function(object, attribute, expected) {
 #' @description
 #' Check whether the data.table has a column called `model`.
 #' If not, a column called `model` is added with the value `Unspecified model`.
+#' @inheritParams score
 #' @return The data.table with a column called `model`
-#' @keywords internal
+#' @keywords internal_input_check
 assure_model_column <- function(data) {
   if (!("model" %in% colnames(data))) {
     message(
@@ -208,7 +209,7 @@ assure_model_column <- function(data) {
 #' returns TRUE and a string with an error message otherwise.
 #' @param forecast_unit Character vector denoting the unit of a single forecast.
 #' @inherit document_check_functions params return
-#' @keywords internal
+#' @keywords internal_input_check
 check_number_per_forecast <- function(data, forecast_unit) {
   # check whether there are the same number of quantiles, samples --------------
   data[, scoringutils_InternalNumCheck := length(predicted), by = forecast_unit]
@@ -235,7 +236,7 @@ check_number_per_forecast <- function(data, forecast_unit) {
 #' an error message, otherwise it returns TRUE.
 #' @inherit document_check_functions params return
 #'
-#' @keywords internal
+#' @keywords internal_input_check
 check_no_NA_present <- function(data, columns) {
   for (x in columns){
     if (anyNA(data[[x]])) {
@@ -253,20 +254,13 @@ check_no_NA_present <- function(data, columns) {
 }
 
 
-
-
-# print stuff
-diagnose <- function(data) {
-
-}
-
 #' Check that there are no duplicate forecasts
 #'
 #' @description
 #' Runs [get_duplicate_forecasts()] and returns a message if an issue is encountered
 #' @inheritParams get_duplicate_forecasts
 #' @inherit document_check_functions return
-#' @keywords internal
+#' @keywords internal_input_check
 check_duplicates <- function(data, forecast_unit = NULL) {
   check_duplicates <- get_duplicate_forecasts(data, forecast_unit = forecast_unit)
 
@@ -290,7 +284,7 @@ check_duplicates <- function(data, forecast_unit = NULL) {
 #' and returns a message with the first issue encountered.
 #' @inherit document_check_functions params return
 #' @importFrom checkmate assert_character
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_columns_present <- function(data, columns) {
   if (is.null(columns)) {
     return(TRUE)
@@ -322,7 +316,7 @@ check_columns_present <- function(data, columns) {
 #' are present, the function returns TRUE.
 #' @inheritParams document_check_functions
 #' @return Returns TRUE if all columns are present and FALSE otherwise
-#' @keywords internal
+#' @keywords internal_input_check
 test_columns_present <- function(data, columns) {
   check <- check_columns_present(data, columns)
   return(is.logical(check))
@@ -334,7 +328,7 @@ test_columns_present <- function(data, columns) {
 #' more columns are present, the function returns FALSE.
 #' @inheritParams document_check_functions
 #' @return Returns TRUE if none of the columns are present and FALSE otherwise
-#' @keywords internal
+#' @keywords internal_input_check
 test_columns_not_present <- function(data, columns) {
   if (any(columns %in% colnames(data))) {
     return(FALSE)
@@ -349,7 +343,7 @@ test_columns_not_present <- function(data, columns) {
 #' "quantile" and "sample_id" is present.
 #' @inherit document_check_functions params return
 #' @importFrom checkmate check_data_frame
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_data_columns <- function(data) {
   is_data <- check_data_frame(data, min.rows = 1)
   if (!is.logical(is_data)) {
@@ -374,7 +368,7 @@ check_data_columns <- function(data) {
 #' @param object An object to be checked
 #' @param attribute name of an attribute to be checked
 #' @inherit document_check_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_has_attribute <- function(object, attribute) {
   if (is.null(attr(object, attribute))) {
     return(

R/check-inputs-scoring-functions.R

@@ -10,7 +10,7 @@
 #' vector of size N.
 #' @importFrom checkmate assert assert_numeric check_matrix
 #' @inherit document_assert_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 assert_input_sample <- function(observed, predicted) {
   assert_numeric(observed, min.len = 1)
   n_obs <- length(observed)
@@ -30,7 +30,7 @@ assert_input_sample <- function(observed, predicted) {
 #' @title Check that inputs are correct for sample-based forecast
 #' @inherit assert_input_sample params description
 #' @inherit document_check_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_input_sample <- function(observed, predicted) {
   result <- check_try(assert_input_sample(observed, predicted))
   return(result)
@@ -54,7 +54,7 @@ check_input_sample <- function(observed, predicted) {
 #' FALSE. Whether the quantile levels are required to be unique or not.
 #' @importFrom checkmate assert assert_numeric check_matrix check_vector
 #' @inherit document_assert_functions return
-#' @keywords internal
+#' @keywords internal_input_check
 assert_input_quantile <- function(observed, predicted, quantile,
                                   unique_quantiles = TRUE) {
   assert_numeric(observed, min.len = 1)
@@ -85,7 +85,7 @@ assert_input_quantile <- function(observed, predicted, quantile,
 #' @title Check that inputs are correct for quantile-based forecast
 #' @inherit assert_input_quantile params description
 #' @inherit check_input_sample return description
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_input_quantile <- function(observed, predicted, quantile) {
   result <- check_try(assert_input_quantile(observed, predicted, quantile))
   return(result)
@@ -106,7 +106,7 @@ check_input_quantile <- function(observed, predicted, quantile) {
 #' (25%, 75%) prediction interval.
 #' @importFrom rlang warn
 #' @inherit document_assert_functions return
-#' @keywords internal
+#' @keywords internal_input_check
 assert_input_interval <- function(observed, lower, upper, range) {
 
   assert(check_numeric_vector(observed, min.len = 1))
@@ -145,7 +145,7 @@ assert_input_interval <- function(observed, lower, upper, range) {
 #' @title Check that inputs are correct for interval-based forecast
 #' @inherit assert_input_interval params description
 #' @inherit check_input_sample return description
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_input_interval <- function(observed, lower, upper, range) {
   result <- check_try(assert_input_quantile(observed, lower, upper, range))
   return(result)
@@ -167,7 +167,7 @@ check_input_interval <- function(observed, lower, upper, range) {
 #' available factor level.
 #' @importFrom checkmate assert assert_factor
 #' @inherit document_assert_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 assert_input_binary <- function(observed, predicted) {
   assert_factor(observed, n.levels = 2, min.len = 1)
   assert_numeric(predicted, lower = 0, upper = 1)
@@ -179,7 +179,7 @@ assert_input_binary <- function(observed, predicted) {
 #' @title Check that inputs are correct for binary forecast
 #' @inherit assert_input_binary params description
 #' @inherit document_check_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_input_binary <- function(observed, predicted) {
   result <- check_try(assert_input_binary(observed, predicted))
   return(result)
@@ -194,7 +194,7 @@ check_input_binary <- function(observed, predicted) {
 #' @param predicted Input to be checked. Should be a numeric vector with the
 #' predicted values of size n
 #' @inherit document_assert_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 assert_input_point <- function(observed, predicted) {
   assert(check_numeric(observed))
   assert(check_numeric(predicted))
@@ -205,7 +205,7 @@ assert_input_point <- function(observed, predicted) {
 #' @title Check that inputs are correct for point forecast
 #' @inherit assert_input_point params description
 #' @inherit document_check_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_input_point <- function(observed, predicted) {
   result <- check_try(assert_input_point(observed, predicted))
   return(result)
@@ -224,7 +224,7 @@ check_input_point <- function(observed, predicted) {
 #' @inherit assert_input_binary
 #' @inherit document_assert_functions return
 #' @importFrom checkmate assert_vector check_matrix check_vector assert
-#' @keywords check-inputs
+#' @keywords internal_input_check
 assert_dims_ok_point <- function(observed, predicted) {
   assert_vector(observed, min.len = 1)
   n_obs <- length(observed)
@@ -250,7 +250,7 @@ assert_dims_ok_point <- function(observed, predicted) {
 #' @title Check Inputs Have Matching Dimensions
 #' @inherit assert_dims_ok_point params description
 #' @inherit document_check_functions return
-#' @keywords check-inputs
+#' @keywords internal_input_check
 check_dims_ok_point <- function(observed, predicted) {
   result <- check_try(assert_dims_ok_point(observed, predicted))
   return(result)

R/documentation-templates.R

@@ -4,22 +4,26 @@
 #' @return Returns TRUE if the check was successful and a string with an
 #' error message otherwise
 #' @name document_check_functions
+#' @keywords internal
 NULL
 
 #' Documentation template for check functions
 #' @returns Returns NULL invisibly if the assertion was successful and throws an
 #' error otherwise.
 #' @name document_assert_functions
+#' @keywords internal
 NULL
 
 #' Documentation template for test functions
 #' @returns Returns TRUE if the check was successful and FALSE otherwise
 #' @name document_test_functions
+#' @keywords internal
 NULL
 
 #' Documentation template for scoring input data
 #' @param data A data frame (or similar) of forecasts following the
 #' specifications detailed in [score()].
 #' @param scores A data.table of scores as produced by [score()].
 #' @name document_score_data
+#' @keywords internal
 NULL

R/get_-functions.R

@@ -18,7 +18,7 @@
 #' @return Character vector of length one with either "binary", "quantile",
 #' "sample" or "point".
 #' @export
-#' @keywords check-forceasts
+#' @keywords check-forecasts
 get_forecast_type <- function(data) {
   assert_data_frame(data)
   assert(check_columns_present(data, c("observed", "predicted")))
@@ -50,7 +50,7 @@ get_forecast_type <- function(data) {
 #' @inheritParams document_check_functions
 #' @importFrom checkmate test_factor test_numeric
 #' @return Returns TRUE if basic requirements are satisfied and FALSE otherwise
-#' @keywords internal
+#' @keywords internal_input_check
 test_forecast_type_is_binary <- function(data) {
   observed_correct <- test_factor(x = data$observed)
   predicted_correct <- test_numeric(x = data$predicted)
@@ -61,7 +61,7 @@ test_forecast_type_is_binary <- function(data) {
 #' @description Checks type of the necessary columns.
 #' @inheritParams document_check_functions
 #' @return Returns TRUE if basic requirements are satisfied and FALSE otherwise
-#' @keywords internal
+#' @keywords internal_input_check
 test_forecast_type_is_sample <- function(data) {
   observed_correct <- test_numeric(x = data$observed)
   predicted_correct <- test_numeric(x = data$predicted)
@@ -73,7 +73,7 @@ test_forecast_type_is_sample <- function(data) {
 #' @description Checks type of the necessary columns.
 #' @inheritParams document_check_functions
 #' @return Returns TRUE if basic requirements are satisfied and FALSE otherwise
-#' @keywords internal
+#' @keywords internal_input_check
 test_forecast_type_is_point <- function(data) {
   observed_correct <- test_numeric(x = data$observed)
   predicted_correct <- test_numeric(x = data$predicted)
@@ -85,7 +85,7 @@ test_forecast_type_is_point <- function(data) {
 #' @description Checks type of the necessary columns.
 #' @inheritParams document_check_functions
 #' @return Returns TRUE if basic requirements are satisfied and FALSE otherwise
-#' @keywords internal
+#' @keywords internal_input_check
 test_forecast_type_is_quantile <- function(data) {
   observed_correct <- test_numeric(x = data$observed)
   predicted_correct <- test_numeric(x = data$predicted)
@@ -100,13 +100,10 @@ test_forecast_type_is_quantile <- function(data) {
 #' of observed or predicted values). The function checks whether the input is
 #' a factor, or else whether it is integer (or can be coerced to integer) or
 #' whether it's continuous.
-#'
 #' @param x Input used to get the type.
-#'
 #' @return Character vector of length one with either "classification",
 #' "integer", or "continuous"
-#'
-#' @keywords internal
+#' @keywords internal_input_check
 get_type <- function(x) {
   if (is.factor(x)) {
     return("classification")
@@ -129,15 +126,11 @@ get_type <- function(x) {
 
 
 #' @title Get metrics that were used for scoring
-#'
 #' @description Internal helper function to get the metrics that were used
 #' to score forecasts.
-#' @param score A data.table with an attribute `metric_names`
-#'
+#' @param scores A data.table with an attribute `metric_names`
 #' @return Character vector with the metrics that were used for scoring.
-#'
-#' @keywords internal
-
+#' @keywords internal_input_check
 get_metrics <- function(scores) {
   metric_names <- attr(scores, "metric_names")
   if (is.null(metric_names)) {