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Only redo data process and plotting for exclusions when user pushes button #98

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merged 3 commits into from
Feb 21, 2024
Merged

Only redo data process and plotting for exclusions when user pushes button #98

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a332bd3
suppress across warning about deprecated ...
nmdefries Feb 21, 2024
a141e5c
add button to filter aheads/geos on command by removing auto-dependen…
nmdefries Feb 21, 2024
7a7e4db
button name
nmdefries Feb 21, 2024
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24 changes: 17 additions & 7 deletions app.R
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ load_forecast_data <- memoise::memoise(load_forecast_data_raw, cache = cache)
prepare_forecaster_table <- function(selected_forecasters) {
forecasters <- tar_read(forecaster_params_grid) %>%
select(-id) %>%
mutate(across(where(is.list), map, `%||%`, c(0, 7, 14))) %>%
mutate(across(where(is.list), function(x) { map(x, `%||%`, c(0, 7, 14)) })) %>%
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note: this prevents across from warning that passing args via ... is deprecated.

mutate(lags = paste(lags, sep = ",")) %>%
group_by(parent_id) %>%
mutate(ahead = toString(unique(ahead))) %>%
Expand Down Expand Up @@ -164,7 +164,8 @@ shinyApp(
"Exclude aheads:",
choices = 1:28,
multiple = TRUE
)
),
actionButton("submit_exclusions", "Apply exclusions")
),
mainPanel(
verticalLayout(
Expand All @@ -181,7 +182,15 @@ shinyApp(
)
},
server = function(input, output, session) {
filtered_scorecards_reactive <- reactive({
EXCLUDED_GEO_VALUES <- reactive({
input$submit_exclusions # Take a dependency on
isolate(input$excluded_geo_values) # Prevent from taking a dependency on
})
EXCLUDED_AHEADS <- reactive({
input$submit_exclusions # Take a dependency on
isolate(input$excluded_aheads) # Prevent from taking a dependency on
})
FILTERED_SCORECARDS_REACTIVE <- reactive({
agg_forecasters <- unique(c(input$selected_forecasters, input$baseline))
if (length(agg_forecasters) == 0 ||
all(agg_forecasters == "" | is.null(agg_forecasters) | is.na(agg_forecasters))
Expand All @@ -194,14 +203,15 @@ shinyApp(
filter(
.data$forecast_date %>>% between(.env$input$selected_forecast_date_range[[1L]], .env$input$selected_forecast_date_range[[2L]]),
.data$target_end_date %>>% between(.env$input$selected_target_end_date_range[[1L]], .env$input$selected_target_end_date_range[[2L]]),
!.data$geo_value %in% c(.env$input$excluded_geo_values, "us"),
!.data$ahead %in% .env$input$excluded_aheads
!.data$geo_value %in% c(EXCLUDED_GEO_VALUES(), "us"),
!.data$ahead %in% EXCLUDED_AHEADS()
)
}) %>%
bind_rows()
})

output$main_plot <- renderPlotly({
input_df <- filtered_scorecards_reactive()
input_df <- FILTERED_SCORECARDS_REACTIVE()
if (nrow(input_df) == 0) {
return()
}
Expand Down Expand Up @@ -266,7 +276,7 @@ shinyApp(
# points smaller.
scale_factor_fcast <- length(input$selected_forecasters) * 2
scale_factor_facet <- length(input$facet_vars) * 5
scale_factor_geo <- ("geo_value" %in% input$facet_vars) * (60 - length(input$excluded_geo_values))
scale_factor_geo <- ("geo_value" %in% input$facet_vars) * (60 - length(EXCLUDED_GEO_VALUES()))
scale_factor_geo_x <- ("geo_value" %in% input$x_var) * 10
scale_factor_facet_fcast <- ifelse("forecaster" %in% input$facet_vars, length(input$selected_forecasters), 0) * 5
scale_factor <- scale_factor_geo + scale_factor_geo_x + scale_factor_fcast + scale_factor_facet + scale_factor_facet_fcast
Expand Down
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