updated create_report.sh to have borders option

build_report.sh

@@ -15,6 +15,9 @@ for arg in "$@"; do
         --data_dir=*)
                    data_dir="${arg#*=}"
                    ;;
+        --borders=*)
+                   borders="${arg#*=}"
+                   ;;
                *)
             echo "Unknown option: $arg"
             exit 1
@@ -23,8 +26,8 @@ for arg in "$@"; do
 done
 
 # Check if required arguments are set
-if [ -z "$filename" ] || [ -z "$report_date" ]|| [ -z "$mail_day" ] || [ -z "$data_dir" ]; then
+if [ -z "$filename" ] || [ -z "$report_date" ]|| [ -z "$borders" ] || [ -z "$mail_day" ] || [ -z "$data_dir" ]; then
-    echo "Missing arguments. Use: build_reports.sh --filename=hello.txt --report_date=2020-01-01 --mail_day=Friday --data_dir=chemba"
+    echo "Missing arguments. Use: build_reports.sh --filename=hello.txt --report_date=2020-01-01 --mail_day=Friday --data_dir=chemba --borders=TRUE"
     exit 1
 fi
 
@@ -33,6 +36,7 @@ echo "Filename: $filename"
 echo "Report date: $report_date"
 echo "Mail day: $mail_day"
 echo "Data directory: $data_dir"
+echo "Borders: $borders"
 
 if [ "$(uname)" == "Darwin" ]; then
     # Commando's voor Mac
@@ -44,4 +48,4 @@ elif [ "$(uname)" == "Linux" ]; then
 else
     echo "Onbekend systeem"
 fi
-Rscript -e "rmarkdown::render('CI_report_dashboard_planet.Rmd', output_file='$filename', params=list(ref='$ref', report_date='$report_date', data_dir='$data_dir'))"
+Rscript -e "rmarkdown::render('CI_report_dashboard_planet.Rmd', output_file='$filename', params=list(ref='$ref', report_date='$report_date', data_dir='$data_dir', borders='$borders'))"

r_app/CI_report_dashboard_planet.Rmd

@@ -5,6 +5,7 @@ params:
   report_date: "2024-04-18"
   data_dir: "Sony"
   mail_day: "Wednesday"
+  borders: TRUE
 output:
  # html_document:
  #   toc: yes
@@ -22,6 +23,7 @@ editor_options:
 # output_file <- params$output_file
 report_date <- params$report_date
 mail_day <- params$mail_day
+borders <- params$borders
 # 
 # 
 # # Activeer de renv omgeving
@@ -260,30 +262,46 @@ subchunkify <- function(g, fig_height=7, fig_width=5) {
   cat(knitr::knit(text = knitr::knit_expand(text = sub_chunk), quiet = TRUE))
 }
 
-create_CI_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend = F, legend_is_portrait = F, week, age){
+create_CI_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend = F, legend_is_portrait = F, week, age, borders = FALSE){
-  tm_shape(pivot_raster, unit = "m")+
+  map <- tm_shape(pivot_raster, unit = "m") +
     tm_raster(breaks = c(0,0.5,1,2,3,4,5,6,7,Inf), palette = "RdYlGn",legend.is.portrait = legend_is_portrait ,midpoint = NA) +
     tm_layout(main.title = paste0("\nMax CI week ", week,"\n",  age, " weeks old"),
-            main.title.size = 0.7, legend.show = show_legend) # +
+              main.title.size = 0.7, legend.show = show_legend)
-  # tm_shape(pivot_shape) +
+
-  # tm_borders(lwd = 3) +  tm_text("sub_field", size = 1/2) +
+  if (borders) {
-  # tm_shape(pivot_spans) + tm_borders(lwd = 0.5, alpha=0.5)
+    map <- map +
+      tm_shape(pivot_shape) +
+      tm_borders(lwd = 3) +
+      tm_text("sub_field", size = 1/2) +
+      tm_shape(pivot_spans) +
+      tm_borders(lwd = 0.5, alpha = 0.5)
+  }
+
+  return(map)
 }
 
-create_CI_diff_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend = F, legend_is_portrait = F, week_1, week_2, age){
+create_CI_diff_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend = F, legend_is_portrait = F, week_1, week_2, age, borders = TRUE){
-  tm_shape(pivot_raster, unit = "m")+
+  map <- tm_shape(pivot_raster, unit = "m") +
-  tm_raster(breaks = c(-3,-2,-1,0,1,2, 3), palette = "RdYlGn",legend.is.portrait = legend_is_portrait ,midpoint = 0, title = "CI difference") +
+    tm_raster(breaks = c(-3,-2,-1,0,1,2,3), palette = "RdYlGn",legend.is.portrait = legend_is_portrait, midpoint = 0, title = "CI difference") +
-  tm_layout(main.title =  paste0("CI change week ", week_1, "- week ",week_2, "\n", age," weeks old"),
+    tm_layout(main.title = paste0("CI change week ", week_1, " - week ", week_2, "\n", age, " weeks old"),
-            main.title.size = 0.7, legend.show = show_legend) # +
+              main.title.size = 0.7, legend.show = show_legend)
- # tm_shape(pivot_shape) +
+
- # tm_borders(lwd = 3) +  tm_text("sub_field", size = 1/2) +
+  if (borders) {
- # tm_shape(pivot_spans) + tm_borders(lwd = 0.5, alpha=0.5)
+    map <- map +
+      tm_shape(pivot_shape) +
+      tm_borders(lwd = 3) +
+      tm_text("sub_field", size = 1/2) +
+      tm_shape(pivot_spans) +
+      tm_borders(lwd = 0.5, alpha = 0.5)
+  }
+
+  return(map)
 }
 
 ci_plot <- function(pivotName){
    # pivotName = "1.1"
    pivotShape <- AllPivots0 %>% terra::subset(field %in% pivotName)  %>% st_transform(crs(CI))
-   age <- harvesting_data %>% dplyr::filter(field %in% pivotName) %>% dplyr::select(age) %>% unique()
+   age <- harvesting_data %>% dplyr::filter(field %in% pivotName) %>% sort("year") %>% tail(., 1) %>% dplyr::select(age) %>% unique() %>% pull() %>% round()
 
    AllPivots2 <- AllPivots0 %>% dplyr::filter(field %in% pivotName)
 
@@ -300,13 +318,13 @@ ci_plot <- function(pivotName){
 
    joined_spans2 <- AllPivots0 %>% st_transform(crs(pivotShape))  %>%  dplyr::filter(field %in% pivotName) #%>% unique() %>% st_crop(., pivotShape)
 
-   CImap_m2 <- create_CI_map(singlePivot_m2, AllPivots2,  joined_spans2, show_legend= T, legend_is_portrait = T, week = week_minus_2, age = age  -2)
+   CImap_m2 <- create_CI_map(singlePivot_m2, AllPivots2,  joined_spans2, show_legend= T, legend_is_portrait = T, week = week_minus_2, age = age  -2, borders = borders)
-   CImap_m1 <- create_CI_map(singlePivot_m1, AllPivots2,  joined_spans2, show_legend= F, legend_is_portrait = F, week = week_minus_1, age = age  -1)
+   CImap_m1 <- create_CI_map(singlePivot_m1, AllPivots2,  joined_spans2, show_legend= F, legend_is_portrait = F, week = week_minus_1, age = age  -1, borders = borders)
-   CImap <- create_CI_map(singlePivot, AllPivots2,  joined_spans2, show_legend= F, legend_is_portrait = F, week = week, age = age )
+   CImap <- create_CI_map(singlePivot, AllPivots2,  joined_spans2, show_legend= F, legend_is_portrait = F, week = week, age = age, borders = borders)
 
 
-   CI_max_abs_last_week <- create_CI_diff_map(abs_CI_last_week,AllPivots2,  joined_spans2,  show_legend = T, legend_is_portrait = T, week_1 = week, week_2 = week_minus_1, age = age)
+   CI_max_abs_last_week <- create_CI_diff_map(abs_CI_last_week,AllPivots2,  joined_spans2,  show_legend = T, legend_is_portrait = T, week_1 = week, week_2 = week_minus_1, age = age, borders = borders)
-   CI_max_abs_three_week <- create_CI_diff_map(abs_CI_three_week, AllPivots2,  joined_spans2, show_legend = T, legend_is_portrait = T, week_1 = week, week_2 = week_minus_3, age = age)
+   CI_max_abs_three_week <- create_CI_diff_map(abs_CI_three_week, AllPivots2,  joined_spans2, show_legend = T, legend_is_portrait = T, week_1 = week, week_2 = week_minus_3, age = age, borders = borders)
 
    tst <- tmap_arrange(CImap_m2, CImap_m1, CImap,CI_max_abs_last_week, CI_max_abs_three_week, nrow = 1)
 
@@ -319,57 +337,60 @@ ci_plot <- function(pivotName){
  }
 
 cum_ci_plot <- function(pivotName){
-  # pivotName <- "4042903"
+
-  # Generate a sequence of dates for the last 12 months
+  # pivotName = "1.1"
+  data_ci <- CI_quadrant %>% filter(field == pivotName)
+
+  if (nrow(data_ci) == 0) {
+    return(cum_ci_plot2(pivotName))  # Return an empty data frame if no data is found
+  }
+
+  data_ci2 <- data_ci  %>% mutate(CI_rate = cumulative_CI/DOY,
+                                  week = week(Date))%>% group_by(field) %>%
+    mutate(mean_rolling10 = rollapplyr(CI_rate  , width = 10, FUN = mean, partial = TRUE))
+
+  date_preperation_perfect_pivot <- data_ci2 %>% group_by(season)  %>% summarise(min_date = min(Date),
+                                                                                max_date = max(Date),
+                                                                                days = max_date - min_date)
+
+
+  unique_seasons <- unique(date_preperation_perfect_pivot$season)
+
+  g <- ggplot(data= data_ci2 %>% filter(season %in% unique_seasons)) +
+          facet_wrap(~season, scales = "free_x") +
+          geom_line( aes(Date, mean_rolling10, col = sub_field, group = sub_field)) +
+          labs(title = paste("14 day rolling MEAN CI rate - Pivot ", pivotName))+
+          theme_minimal() +
+          theme(axis.text.x = element_text(angle = 60, hjust = 1),
+                legend.justification=c(1,0), legend.position = c(1, 0),
+                legend.title = element_text(size = 8),
+                legend.text = element_text(size = 8)) +
+          guides(color = guide_legend(nrow = 2, byrow = TRUE))
+
+    subchunkify(g, 3.2, 10)
+
+}
+
+cum_ci_plot2 <- function(pivotName){
   end_date <- Sys.Date()
   start_date <- end_date %m-% months(11) # 11 months ago from end_date
   date_seq <- seq.Date(from = start_date, to = end_date, by = "month")
   midpoint_date <- start_date + (end_date - start_date) / 2
-  # Create the empty plot
   g <- ggplot() +
     scale_x_date(limits = c(start_date, end_date), date_breaks = "1 month", date_labels = "%m-%Y") +
     scale_y_continuous(limits = c(0, 4)) +
-    labs(title = paste("14 day rolling MEAN CI rate - field ", pivotName),
+    labs(title = paste("14 day rolling MEAN CI rate - Field ", pivotName),
          x = "Date", y = "CI Rate") +
     theme(axis.text.x = element_text(angle = 60, hjust = 1),
           legend.justification = c(1, 0), legend.position = c(1, 0),
           legend.title = element_text(size = 8),
           legend.text = element_text(size = 8)) +
     annotate("text", x = midpoint_date, y = 2, label = "No data available", size = 6, hjust = 0.5)
+
   subchunkify(g, 3.2, 10)
 }
 
 
-cum_ci_plot2 <- function(pivotName){
-
-  # pivotName = "1.1"
-  data_ci <- CI_quadrant %>% filter(field == pivotName)
-  data_ci2 <- data_ci  %>% mutate(CI_rate = cumulative_CI/DOY,
-                                  week = week(Date))%>% group_by(field) %>%
-    mutate(mean_rolling10 = rollapplyr(CI_rate  , width = 10, FUN = mean, partial = TRUE)) #%>%
-
-  date_preperation_perfect_pivot <- data_ci2 %>% group_by(season)  %>% summarise(min_date = min(Date),
-                                                                                max_date = max(Date),
-                                                                                days = max_date - min_date)
-
-  unique_seasons <- unique(date_preperation_perfect_pivot$season)
-
-
-  g <- ggplot(data= data_ci2)  +
-          geom_line( aes(Date, mean_rolling10, col = sub_field)) +
-          # geom_line(data= perfect_pivot, aes(Date , mean_rolling10, col = "Model CI (p5.1 Data 2022, \n date x axis is fictive)"), lty="11",size=1) +
-          labs(title = paste("14 day rolling MEAN CI rate - Pivot ", pivotName))+
-          # scale_y_continuous(limits=c(0.5,3), breaks = seq(0.5, 3, 0.5))+
-          scale_x_date(date_breaks = "1 month", date_labels =  "%m-%Y") +
-          theme(axis.text.x = element_text(angle = 60, hjust = 1),
-                          legend.justification=c(1,0), legend.position = c(1, 0),
-                          legend.title = element_text(size = 8),
-                          legend.text = element_text(size = 8)) +
-          guides(color = guide_legend(nrow = 2, byrow = TRUE))
-  subchunkify(g, 3.2, 10)
-
-}
-
 ```
 
 ```{r eval=FALSE, fig.height=7.2, fig.width=10, message=FALSE, warning=FALSE, include=FALSE}
@@ -425,15 +446,13 @@ tm_shape(CI, unit = "m")+
 # pivots <- AllPivots_merged %>% filter(pivot != c("1.1", "1.17"))
 # pivots_estate <- AllPivots_merged %>% filter(pivot %in% c("1.1", "1.2", "1.7")) %>% filter(pivot != "1.17")
 
+AllPivots_merged <- AllPivots0 %>% dplyr::group_by(field) %>% summarise()
 
-walk(AllPivots0$field, ~ {
+walk(AllPivots_merged$field, ~ {
- # cat("# Hello!!!")
   cat("\n")  # Add an empty line for better spacing
   ci_plot(.x)
   cat("\n")
- # cum_ci_plot(.x)
+  cum_ci_plot(.x)
-#  cat("\n")
-   cum_ci_plot2(.x)
 })
 ```