Plot a heat map of accepted samples by scenario

Plot a heat map of accepted samples by scenario

plot_per_accepted_tile(proportion_allowed = NULL)

Arguments

proportion_allowed	data.frame of allowed proportions as produced by proportion_allowed_by_condition by condition_and_report_on_cases.

Value

A ggplot2 heat-map of accepted percentages by scenario

Examples

## Code
plot_per_accepted_tile
#> function (proportion_allowed = NULL) 
#> {
#>     event_duration <- NULL
#>     event_size <- NULL
#>     serial_mean <- NULL
#>     upper_R0 <- NULL
#>     allowed_per <- NULL
#>     lower_R0 <- NULL
#>     joined_R0 <- NULL
#>     serial_type <- NULL
#>     proportion_allowed %>% dplyr::mutate(joined_R0 = paste0(lower_R0, 
#>         " - ", upper_R0), serial_type = serial_type %>% stringr::str_replace_all("initial SARS-like", 
#>         "pre-intervention SARS-like") %>% factor(levels = c("MERS-like", 
#>         "SARS-like", "pre-intervention SARS-like"))) %>% tidyr::complete(event_duration, 
#>         event_size, serial_type, joined_R0, fill = list(allowed_per = 0)) %>% 
#>         dplyr::mutate_at(.vars = c("event_duration", "event_size"), 
#>             factor) %>% ggplot2::ggplot(ggplot2::aes(x = event_duration, 
#>         y = event_size, fill = allowed_per)) + ggplot2::geom_tile(alpha = 0.95) + 
#>         ggplot2::scale_fill_continuous(label = scales::percent_format(accuracy = 1L), 
#>             type = "viridis", direction = 1) + ggplot2::facet_grid(serial_type ~ 
#>         joined_R0) + ggplot2::theme_minimal() + ggplot2::theme(legend.position = "bottom") + 
#>         ggplot2::guides(fill = ggplot2::guide_colorbar(title = "Percentage of samples accepted")) + 
#>         ggplot2::labs(x = "Transmission event duration", y = "Transmission event size")
#> }
#> <bytecode: 0x55a6b54dbc18>
#> <environment: namespace:WuhanSeedingVsTransmission>