plot_forecast_counts: Visualise the number of available forecasts

In epiforecasts/scoringutils: Utilities for Scoring and Assessing Predictions

Visualise the number of available forecasts

Description

Visualise Where Forecasts Are Available.

Usage

plot_forecast_counts(
  forecast_counts,
  x,
  y = "model",
  x_as_factor = TRUE,
  show_counts = TRUE
)

Arguments

forecast_counts	A data.table (or similar) with a column count holding forecast counts, as produced by get_forecast_counts().
x	Character vector of length one that denotes the name of the column to appear on the x-axis of the plot.
y	Character vector of length one that denotes the name of the column to appear on the y-axis of the plot. Default is "model".
x_as_factor	Logical (default is TRUE). Whether or not to convert the variable on the x-axis to a factor. This has an effect e.g. if dates are shown on the x-axis.
show_counts	Logical (default is TRUE) that indicates whether or not to show the actual count numbers on the plot.

Value

A ggplot object with a plot of forecast counts

Examples

library(ggplot2)
library(magrittr) # pipe operator
forecast_counts <- example_quantile %>%
  as_forecast_quantile %>%
  get_forecast_counts(by = c("model", "target_type", "target_end_date"))
plot_forecast_counts(
 forecast_counts, x = "target_end_date", show_counts = FALSE
) +
 facet_wrap("target_type")

epiforecasts/scoringutils documentation built on Dec. 11, 2024, 11:12 a.m.