add table coloring and cost charts

app/storm_report.qmd

@@ -1,9 +1,15 @@
 ---
-title: "`r params$storm_name` `r params$storm_year` STORM REPORT"
+title: "`r params$hurdat_id` `r params$storm_name` `r params$storm_year` STORM REPORT"
 subtitle: "Generated on: `r Sys.Date()`"
 format:
   pdf:
     theme: cosmo
+    geometry:
+      - top=0.75in
+      - bottom=0.75in
+      - left=0.75in
+      - right=0.75in
+      - footskip=0.3in
 execute:
   warning: false
   message: false
@@ -11,15 +17,18 @@ params:
     storm_basin: AL
     storm_year: 1900
     storm_name: GALVESTON
+    hurdat_id: AL011900
 ---
 
-```{r setup}
+```{r setup, echo=FALSE}
-#| echo: false
-
 library(ggplot2)
 library(sf)
 library(rnaturalearth)
 library(dplyr)
+library(scales)
+library(knitr)
+library(kableExtra)
+library(patchwork)
 
 source(file = "queries.R")
 
@@ -30,16 +39,56 @@ storm <- list(
 )
 
 unique_lfs <- get_unique_lf_ids(storm)
+hurdat_id <- get_hurdat_id(storm)
 
-storm_track <- get_hurdat_track(storm)
+plot_theme <- theme(
+  plot.title = element_text(hjust = 0.5, size = 10),
+  axis.title = element_text(size = 10),
+  axis.text = element_text(size = 8),
+  legend.title = element_text(face = "bold"),
+  legend.text = element_text(face = "bold")
+)
 ```
 
-```{r track_map}
+```{r storm_overview, echo=FALSE}
-#| echo: false
+# storm stats
+# mmh, mmp, landfalls, hurdat summary (max cat, min press, max wind, hurricane points, total points)
+# fatality data?
+
+hurdat_summary <- get_best_track_summary(storm)
+
+losses <- get_latest_aggregate_loss(storm)
+
+storm_track <- get_hurdat_track(storm)
+
+```
+
+# Storm Overview
+
+- **HURDAT2 ID** `r hurdat_id$hurdatid`
+- **HURDAT2 Revision Date** `r hurdat_id$hurdat_rev`
+
+## Normalized Cost
+
+- **MMH24** `r dollar(losses$mmh)`
+- **MMP24** `r dollar(losses$mmp)`
+
+## HURDAT2 Summary
+
+- **Date Range** `r min(storm_track$formatted_datetime)` to `r max(storm_track$formatted_datetime)`
+- **Total Observations** `r hurdat_summary$total_observations`
+- **Hurricane Observations** `r hurdat_summary$hurricane_observations`
+- **Landfall Observations** `r hurdat_summary$hurdat_landfalls`
+- **Maximum Saffir-Simpson Category** `r hurdat_summary$max_category`
+- **Minimum Pressure** `r hurdat_summary$min_pressure` mb
+- **Maximum Windspeed** `r hurdat_summary$max_windspeed` kts
+
+## Storm Track
+
+```{r track_map, echo=FALSE}
 #| fig-width: 10
 #| fig-height: 8
-
+#| out-width: "100%"
-  # Add color and category classification
   storm_track <- storm_track %>%
     mutate(
       hurricane_category = case_when(
@@ -80,7 +129,6 @@ storm_track <- get_hurdat_track(storm)
     ) %>%
     arrange(datetime)
 
-  # Create ordered factor for legend
   storm_track$status_label <- factor(
     storm_track$status_label,
     levels = c(
@@ -130,7 +178,8 @@ storm_track <- get_hurdat_track(storm)
       legend.position = "right",
       legend.key.size = unit(0.4, "cm"),
       legend.text = element_text(size = 8)
-    )
+    ) +
+    plot_theme
 
   if (nrow(storm_track) >= 2) {
     for (i in 1:(nrow(storm_track) - 1)) {
@@ -208,3 +257,114 @@ storm_track <- get_hurdat_track(storm)
 
   print(p)
 ```
+
+## Track Observations
+
+```{r track_table, echo=FALSE}
+landfall_rows <- which(storm_track$record_identifier == "L")
+
+storm_track %>%
+  select(
+    formatted_datetime,
+    storm_status,
+    record_identifier,
+    lon,
+    lat,
+    rmw,
+    pressure,
+    windspeed
+  ) %>%
+  kable(
+    col.names = c(
+      "Date",
+      "Status",
+      "Record ID",
+      "Lon",
+      "Lat",
+      "RMW",
+      "Pressure",
+      "Windspeed"
+    ),
+    align = c("l", "c", "c", "r", "r", "r", "r", "r"),
+    booktabs = TRUE
+  ) %>%
+  kable_styling(
+    #latex_options = c("striped"),
+    font_size = 9,
+    position = "center"
+  ) %>%
+  column_spec(
+    2,
+    color = "white",
+    background = paste0(storm_track$line_color, "A0"),
+    bold = T
+  ) %>%
+  row_spec(
+    landfall_rows,
+    color = "white",
+    background = paste0(storm_track$line_color[landfall_rows], "A0")
+  ) %>% 
+  column_spec(
+    6,
+    color = "white",
+    background = spec_color(storm_track$rmw, end = 0.7),
+    bold = T
+  ) %>% 
+  column_spec(
+    7,
+    color = "white",
+    background = spec_color(storm_track$pressure, end = 0.7),
+    bold = T
+  ) %>% 
+  column_spec(
+    8,
+    color = "white",
+    background = spec_color(storm_track$windspeed, end = 0.7),
+    bold = T
+  )
+
+```
+
+## Cost Normalization
+
+```{r normalization, echo=FALSE}
+#| out-width: "100%"
+
+costs <- get_all_normalized_cost_index(storm)
+
+# for each lf, create charts of mmh/mmp
+
+unique_lf_ids <- unique_lfs$full_lf_id
+
+for(lf in unique_lf_ids) {
+  filtered_costs <- costs %>% 
+    filter(
+      full_lf_id == lf
+    )
+  
+  mmh_plot <- ggplot(filtered_costs, aes(x = normalization_year, y = mmh_loss)) +
+    geom_area(fill = "blue", alpha = 0.7) +
+    scale_y_continuous(labels = scales::label_dollar(scale_cut = cut_short_scale())) +
+    labs(
+      title = paste(lf, "MMH Loss"),
+      x = "Year",
+      y = "Aggregate Loss (USD)"
+    ) +
+    theme_minimal() +
+    plot_theme
+
+  mmp_plot <- ggplot(filtered_costs, aes(x = normalization_year, y = mmp_loss)) +
+    geom_area(fill = "red", alpha = 0.7) +
+    scale_y_continuous(labels = scales::label_dollar(scale_cut = cut_short_scale())) +
+    labs(
+      title = paste(lf, "MMP Loss"),
+      x = "Year",
+      y = "Aggregate Loss (USD)"
+    ) +
+    theme_minimal() +
+    plot_theme
+
+  print(mmh_plot)
+  print(mmp_plot)
+}
+```