mirror of
https://github.com/dylanbenzi/hurricane_normalization_app.git
synced 2026-07-30 05:08:57 +00:00
add normalization graph filter functionality
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+56
-37
@@ -41,6 +41,7 @@ library(caret)
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library(scales)
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library(billboarder)
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library(shinyWidgets)
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library(paletteer)
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# local testing env setup
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os <- Sys.info()["sysname"]
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@@ -401,59 +402,77 @@ Col {data-width=500}
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### Normalization Cost Index {data-height=700}
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```{r}
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storm_yearly_normalization <- reactive({
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req(storm_selection$is_selected)
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result <- get_all_normalized_cost_index(storm_selection)
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return(result)
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})
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output$cost_index_chart <- renderDygraph({
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req(storm_selection$is_selected, input$storm_overview_cost_index_lf_select, input$storm_overview_cost_index_mmh_mmp)
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req(storm_yearly_normalization,
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input$storm_overview_cost_index_lf_select,
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input$storm_overview_cost_index_mmh_mmp,
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input$storm_overview_cost_index_scale)
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selected_lfs <- input$storm_overview_cost_index_lf_select
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loss_type <- input$storm_overview_cost_index_mmh_mmp
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display_columns <- c("normalization_year")
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normalizations <- get_normalized_cost_index(storm_selection) %>%
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normalized_data <- storm_yearly_normalization() %>%
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rename(
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hindex = mmh_index,
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pindex = mmp_index,
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"MMH Index" = mmh_index,
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"MMH Loss" = mmh_loss,
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"MMP Index" = mmp_index,
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"MMP Loss" = mmp_loss
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)
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selected_lf <- input$storm_overview_cost_index_lf_select
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selected_normalization <- input$storm_overview_cost_index_mmh_mmp
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selected_scale <- input$storm_overview_cost_index_scale
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method_map <- c("MMH", "MMP")
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selected_methods <- method_map[method_map %in% selected_normalization]
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if (selected_scale == "Index") {
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value_columns <- paste0(selected_methods, " Index")
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} else if (selected_scale == "Loss") {
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value_columns <- paste0(selected_methods, " Loss")
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}
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normalization_index <- normalized_data %>%
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filter(
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full_lf_id %in% selected_lf
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) %>%
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mutate(
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normalization_year = as.Date(paste0(normalization_year, "-01-01"))
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) %>%
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select(
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normalization_year,
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full_lf_id,
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all_of(value_columns)
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) %>%
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pivot_wider(
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names_from = full_lf_id,
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values_from = c(hindex, pindex, mmh, mmp),
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names_glue = "{full_lf_id}_{.value}"
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) %>%
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arrange(normalization_year)
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values_from = all_of(value_columns),
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names_glue = "{full_lf_id} {.value}"
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)
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# TODO: add filtering
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})
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output$cost_index_chart_old <- renderDygraph({
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req(storm_selection$is_selected, input$storm_overview_cost_index_lf)
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cost_index <- get_normalized_cost_index(storm_selection, input$storm_overview_cost_index_lf) %>%
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mutate(normalization_year = as.Date(paste0(normalization_year, "-01-01")))
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cost_index_ts <- cost_index %>%
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normalization_index_ts <- normalization_index %>%
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select(-normalization_year) %>%
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xts(order.by = cost_index$normalization_year)
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xts(order.by = normalization_index$normalization_year)
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dygraph(cost_index_ts, main = "Cost Index") %>%
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dySeries("mmh", label = "MMH24") %>%
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dySeries("mmp", label = "MMP24") %>%
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dyRangeSelector(height = 30)
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dygraph(normalization_index_ts) %>%
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dyOptions(
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colors = paletteer_d("ggthemes::Classic_Purple_Gray_12", ncol(normalization_index - 1)),
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fillGraph = T,
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fillAlpha = .2,
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) %>%
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dyAxis("x", drawGrid = F) %>%
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dyRangeSelector()
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})
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df <- data.frame(lf_type = c("LF", "LF", "LF", "DIL", "DIL", "DIL", "DIL", "ID", "ID", "ID", "ID"), lf_id = c("1", "2", "3", "1", "2", "3", "4", "1", "2", "3", "4"))
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df_tree <- create_tree(df, levels = names(df))
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fluidRow(
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style = "height: 100%",
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column(3,
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#selectInput("storm_overview_cost_index_lf", "Landfall", choices = NULL),
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#treeInput("storm_overview_cost_index_lf_tree", "Landfalls", choices = df_tree, returnValue = "text")
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virtualSelectInput("storm_overview_cost_index_lf_select", "Landfalls",
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#choices = list(
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# "LF" = c("LF1", "LF2", "LF3"),
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@@ -464,7 +483,7 @@ fluidRow(
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showValueAsTags = T,
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multiple = T,
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autoSelectFirstOption = T),
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radioGroupButtons("storm_overview_cost_index_value", label = "Value", choices = c("Index", "Loss"), status = "outline-primary rounded-0", justified = T),
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radioGroupButtons("storm_overview_cost_index_scale", label = "Value", choices = c("Index", "Loss"), status = "outline-primary rounded-0", justified = T),
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checkboxGroupButtons("storm_overview_cost_index_mmh_mmp", label = "MMH/MMP", choices = c("MMH", "MMP"), selected = c("MMH", "MMP"), status = "outline-primary rounded-0", justified = T)
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),
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column(9,
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@@ -168,7 +168,7 @@ get_all_normalized_cost_index <- function(storm) {
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full_lf_id = paste0(lf_type, lf_id)
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) %>%
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select(
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normalization_year, mmh_index, mmp_index, mmh, mmp, full_lf_id
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normalization_year, mmh_index, mmp_index, mmh_loss = mmh, mmp_loss = mmp, full_lf_id
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)
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result <- query %>% collect()
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