From ee34257ab51fbb709696b1a622c74d8f776de1c6 Mon Sep 17 00:00:00 2001
From: Sebastian Funk <sebastian.funk@lshtm.ac.uk>
Date: Mon, 21 Oct 2024 14:36:51 +0100
Subject: [PATCH] add plotting examples for pit histogram

---
 R/get-pit-histogram.R    | 12 ++++++++++++
 man/get_pit_histogram.Rd | 12 ++++++++++++
 2 files changed, 24 insertions(+)

diff --git a/R/get-pit-histogram.R b/R/get-pit-histogram.R
index c528268f..7aeab245 100644
--- a/R/get-pit-histogram.R
+++ b/R/get-pit-histogram.R
@@ -4,6 +4,8 @@
 #' Generate a Probability Integral Transformation (PIT) histogram for
 #' validated forecast objects.
 #'
+#' See the examples for how to plot the result of this function.
+#'
 #' @inherit score params
 #' @param num_bins The number of bins in the PIT histogram. For sample-based
 #'   forecasts, the default is 10 bins. For quantile-based forecasts, the
@@ -24,12 +26,22 @@
 #' @inheritParams pit_histogram_sample
 #' @return A data.table with density values for each bin in the PIT histogram.
 #' @examples
+#' library("ggplot2")
+#'
 #' example <- as_forecast_sample(example_sample_continuous)
 #' result <- get_pit_histogram(example, by = "model")
+#' ggplot(result,  aes(x = mid, y = density)) +
+#'   geom_col() +
+#'   facet_wrap(. ~ model) +
+#'   labs(x = "Quantile", "Density")
 #'
 #' # example with quantile data
 #' example <- as_forecast_quantile(example_quantile)
 #' result <- get_pit_histogram(example, by = "model")
+#' ggplot(result,  aes(x = mid, y = density)) +
+#'   geom_col() +
+#'   facet_wrap(. ~ model) +
+#'   labs(x = "Quantile", "Density")
 #' @export
 #' @keywords scoring
 #' @references
diff --git a/man/get_pit_histogram.Rd b/man/get_pit_histogram.Rd
index 8dbe89c5..074aa494 100644
--- a/man/get_pit_histogram.Rd
+++ b/man/get_pit_histogram.Rd
@@ -68,14 +68,26 @@ A data.table with density values for each bin in the PIT histogram.
 \description{
 Generate a Probability Integral Transformation (PIT) histogram for
 validated forecast objects.
+
+See the examples for how to plot the result of this function.
 }
 \examples{
+library("ggplot2")
+
 example <- as_forecast_sample(example_sample_continuous)
 result <- get_pit_histogram(example, by = "model")
+ggplot(result,  aes(x = mid, y = density)) +
+  geom_col() +
+  facet_wrap(. ~ model) +
+  labs(x = "Quantile", "Density")
 
 # example with quantile data
 example <- as_forecast_quantile(example_quantile)
 result <- get_pit_histogram(example, by = "model")
+ggplot(result,  aes(x = mid, y = density)) +
+  geom_col() +
+  facet_wrap(. ~ model) +
+  labs(x = "Quantile", "Density")
 }
 \references{
 Sebastian Funk, Anton Camacho, Adam J. Kucharski, Rachel Lowe,