Enhance report utility functions and add validation scripts
- Updated `create_CI_map` and `create_CI_diff_map` functions to enforce a 1:1 aspect ratio for consistent map sizing. - Modified `ci_plot` function to adjust widths of arranged maps for better layout. - Changed raster merging method in `aggregate_per_field_mosaics_to_farm_level` from `mosaic` to `merge` for improved handling of field data. - Introduced `test_kpi_validation.R` script to validate the structure of KPI RDS files, ensuring expected KPIs are present. - Added `test_overview_maps_aggregation.R` script to test the aggregation pipeline for overview maps, including loading field mosaics, creating a farm-level mosaic, and generating visualizations.
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@ -18,5 +18,7 @@ SmartCane processes 4-band satellite imagery (RGB + NIR) into actionable crop he
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---
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**Last Updated**: February 2026
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**Maintained By**: Resilience BV
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**Repository**: https://github.com/TimonWeitkamp/smartcane_experimental_area
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@ -152,10 +152,10 @@ crop_tiff_to_fields <- function(tif_path, tif_date, fields, output_base_dir) {
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#' @param field_tiles_dir Character. Target directory for per-field TIFFs
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#' (e.g., "field_tiles/").
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#' @param fields sf object. GeoDataFrame of field boundaries with 'field_name' column.
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#' @param field_tiles_ci_dir Character. Optional. Directory where migrated CI-calculated
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#' TIFFs are stored. If provided, skips dates
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#' already processed and moved to field_tiles_CI/.
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#' Default: NULL (process all dates).
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#' @param field_tiles_ci_dir Character. Optional. DEPRECATED - no longer used.
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#' Kept for backward compatibility but ignored.
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#' Script 10 now only checks its own output
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#' directory (field_tiles/).
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#' @param end_date Date. Optional. End date for processing window (YYYY-MM-DD).
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#' Default: NULL (process all available dates).
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#' @param offset Integer. Optional. Number of days to look back from end_date.
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@ -245,31 +245,10 @@ process_new_merged_tif <- function(merged_tif_dir, field_tiles_dir, fields, fiel
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for (tif_path in tiff_files) {
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tif_date <- gsub("\\.tif$", "", basename(tif_path))
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# CHECK 1: Skip if this date was already migrated to field_tiles_CI/
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# (This means Script 20 already processed it and extracted RDS)
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if (!is.null(field_tiles_ci_dir) && dir.exists(field_tiles_ci_dir)) {
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# Check if ANY field has this date in field_tiles_CI/
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date_migrated <- FALSE
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# Sample check: look for date in field_tiles_CI/*/DATE.tif
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sample_field_dirs <- list.dirs(field_tiles_ci_dir, full.names = TRUE, recursive = FALSE)
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for (field_dir in sample_field_dirs) {
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potential_file <- file.path(field_dir, paste0(tif_date, ".tif"))
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if (file.exists(potential_file)) {
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date_migrated <- TRUE
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break
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}
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}
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if (date_migrated) {
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safe_log(paste("Skipping:", tif_date, "(already migrated and processed by Script 20)"), "INFO")
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total_skipped <- total_skipped + 1
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next
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}
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}
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# CHECK 2: Skip if this date already exists in field_tiles/
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# (means this date has already been processed through Script 10)
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# SKIP CHECK: Only check Script 10's own output directory (field_tiles/)
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# Do NOT check field_tiles_CI/ — that's Script 20's responsibility.
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# Script 10 and Script 20 are independent; Script 10 should not depend on
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# Script 20's success/failure. If field_tiles/ is missing, reprocess it.
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if (dir.exists(field_tiles_dir)) {
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date_exists_in_field_tiles <- FALSE
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@ -150,7 +150,9 @@ main <- function() {
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ci_raster <- calc_ci_from_raster(raster_4band)
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# Create 5-band (R, G, B, NIR, CI)
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# Explicitly set band names after combining to ensure proper naming
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five_band <- c(raster_4band, ci_raster)
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names(five_band) <- c("Red", "Green", "Blue", "NIR", "CI")
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# Now process all fields from this single merged TIFF
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fields_processed_this_date <- 0
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@ -1013,6 +1013,10 @@ calc_ci_from_raster <- function(raster_obj) {
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# NDVI ranges -1 to 1 and is different from Chlorophyll Index
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ci <- nir / green - 1
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# CRITICAL: Explicitly name the CI band before returning
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# This ensures proper band naming when combined with other rasters
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names(ci) <- "CI"
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return(ci)
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}
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@ -543,7 +543,7 @@ create_field_detail_table <- function(field_df, all_kpis, field_boundaries_sf) {
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by = c("field_idx")
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) %>%
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left_join(
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all_kpis$tch_forecasted %>% select(field_idx, tch_forecasted),
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all_kpis$tch_forecasted %>% select(field_idx, tch_forecasted, mean_ci),
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by = c("field_idx")
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) %>%
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left_join(
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@ -562,6 +562,7 @@ create_field_detail_table <- function(field_df, all_kpis, field_boundaries_sf) {
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`Decline Risk` = decline_severity,
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`Weed Risk` = weed_pressure_risk,
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`CI Change %` = mean_ci_pct_change,
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`Mean CI` = mean_ci,
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`CV Value` = cv_value
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) %>%
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# Add placeholder columns expected by reporting script (will be populated from other sources)
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@ -570,7 +571,7 @@ create_field_detail_table <- function(field_df, all_kpis, field_boundaries_sf) {
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`Gap Score` = NA_real_
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) %>%
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select(field_idx, Field, `Field Size (ha)`, `Growth Uniformity`, `Yield Forecast (t/ha)`,
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`Gap Score`, `Decline Risk`, `Weed Risk`, `CI Change %`, `CV Value`)
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`Gap Score`, `Decline Risk`, `Weed Risk`, `CI Change %`, `Mean CI`, `CV Value`)
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return(result)
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}
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@ -53,6 +53,7 @@ suppressPackageStartupMessages({
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# Visualization
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library(tmap) # For interactive maps (field boundary visualization)
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library(ggspatial) # For basemap tiles and spatial annotations (OSM basemap with ggplot2)
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# Reporting
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library(knitr) # For R Markdown document generation (code execution and output)
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@ -378,43 +379,101 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
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## Executive Summary - Key Performance Indicators
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```{r combined_kpi_table, echo=FALSE, results='asis'}
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# Safely display KPI tables
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# Display KPI tables - standardized format with Level, Count, Percent columns
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if (exists("summary_tables") && !is.null(summary_tables) && length(summary_tables) > 0) {
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# Try to combine KPI tables, with fallback if structure is unexpected
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tryCatch({
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# Build a list of valid dataframes from summary_tables
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valid_tables <- list()
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# KPI metadata for display
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kpi_display_order <- list(
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uniformity = list(display = "Field Uniformity", level_col = "Status", count_col = "Field Count"),
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area_change = list(display = "Area Change", level_col = "Status", count_col = "Field Count"),
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tch_forecast = list(display = "TCH Forecasted", level_col = NULL, count_col = "Fields"),
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growth_decline = list(display = "Growth Decline", level_col = "Trend", count_col = "Field Count"),
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weed_pressure = list(display = "Weed Presence", level_col = "Risk Level", count_col = "Field Count"),
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gap_filling = list(display = "Gap Filling", level_col = NULL, count_col = NULL)
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)
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for (kpi_name in names(summary_tables)) {
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kpi_df <- summary_tables[[kpi_name]]
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# Skip NULL, empty, or non-dataframe items
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if (!is.null(kpi_df) && is.data.frame(kpi_df) && nrow(kpi_df) > 0) {
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# Add KPI name as a column if not already present
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if (!"KPI" %in% names(kpi_df)) {
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display_name <- gsub("_", " ", tools::toTitleCase(gsub("_summary|_data", "", kpi_name)))
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kpi_df$KPI <- display_name
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standardize_kpi <- function(df, level_col, count_col) {
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if (is.null(level_col) || !(level_col %in% names(df)) || is.null(count_col) || !(count_col %in% names(df))) {
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return(NULL)
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}
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valid_tables[[kpi_name]] <- kpi_df
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total <- sum(df[[count_col]], na.rm = TRUE)
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total <- ifelse(total == 0, NA_real_, total)
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df %>%
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dplyr::transmute(
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Level = as.character(.data[[level_col]]),
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Count = as.integer(round(as.numeric(.data[[count_col]]))),
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Percent = dplyr::if_else(
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is.na(total),
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NA_real_,
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round(Count / total * 100, 1)
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)
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)
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}
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combined_df_list <- list()
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order_keys <- names(kpi_display_order)
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for (kpi_key in order_keys) {
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config <- kpi_display_order[[kpi_key]]
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if (!kpi_key %in% names(summary_tables)) next
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kpi_df <- summary_tables[[kpi_key]]
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if (is.null(kpi_df) || !is.data.frame(kpi_df) || nrow(kpi_df) == 0) next
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kpi_rows <- standardize_kpi(kpi_df, config$level_col, config$count_col)
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if (is.null(kpi_rows) && kpi_key %in% c("tch_forecast", "gap_filling")) {
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numeric_cols <- names(kpi_df)[vapply(kpi_df, is.numeric, logical(1))]
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if (length(numeric_cols) > 0) {
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kpi_rows <- tibble::tibble(
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Level = numeric_cols,
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Count = round(as.numeric(kpi_df[1, numeric_cols]), 2),
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Percent = NA_real_
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)
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}
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}
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# Combine all valid tables
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if (length(valid_tables) > 0) {
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# Use careful bind_rows that handles mismatched columns
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combined_df <- dplyr::bind_rows(valid_tables, .id = NULL)
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if (!is.null(kpi_rows)) {
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kpi_rows$KPI <- config$display
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combined_df_list[[length(combined_df_list) + 1]] <- kpi_rows
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}
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}
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# Display as flextable
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ft <- flextable(combined_df) %>% autofit()
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ft
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combined_df <- dplyr::bind_rows(combined_df_list)
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if (nrow(combined_df) > 0) {
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combined_df <- combined_df %>%
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dplyr::group_by(KPI) %>%
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dplyr::mutate(
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KPI_display = if_else(dplyr::row_number() == 1, KPI, "")
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) %>%
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dplyr::ungroup() %>%
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dplyr::select(KPI = KPI_display, Level, Count, Percent)
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ft <- flextable(combined_df) %>%
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merge_v(j = "KPI") %>%
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autofit()
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kpi_group_sizes <- combined_df %>%
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dplyr::group_by(KPI) %>%
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dplyr::tally() %>%
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dplyr::pull(n)
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cum_rows <- cumsum(kpi_group_sizes)
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for (i in seq_along(cum_rows)) {
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if (i < length(cum_rows)) {
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ft <- ft %>%
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hline(i = cum_rows[i], border = officer::fp_border(width = 2))
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}
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}
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print(ft)
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} else {
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cat("No valid KPI summary tables found.\n")
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cat("No valid KPI summary tables found for display.\n")
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}
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}, error = function(e) {
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safe_log(paste("Error combining KPI tables:", e$message), "WARNING")
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cat("KPI summary tables could not be combined for display. Individual KPI sections will be shown below.\n")
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safe_log(paste("Error displaying KPI tables:", e$message), "WARNING")
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cat("KPI summary tables could not be displayed. Individual KPI sections will be shown below.\n")
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})
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} else {
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@ -620,6 +679,372 @@ if (!exists("field_details_table") || is.null(field_details_table)) {
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}
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```
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## Farm-Level Overview Maps
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```{r aggregate_farm_level_rasters, message=FALSE, warning=FALSE, include=FALSE}
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# Aggregate per-field weekly mosaics into single farm-level rasters for visualization
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# This creates on-the-fly mosaics for current week and historical weeks without saving intermediate files
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tryCatch({
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safe_log("Starting farm-level raster aggregation for overview maps")
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# Helper function to safely aggregate mosaics for a specific week
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aggregate_mosaics_safe <- function(week_num, year_num, label) {
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tryCatch({
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safe_log(paste("Aggregating mosaics for", label, "(week", week_num, ",", year_num, ")"))
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# Call the utility function from report_utils.R
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# This function reads all per-field mosaics and merges them into a single raster
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farm_mosaic <- aggregate_per_field_mosaics_to_farm_level(
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weekly_mosaic_dir = weekly_CI_mosaic,
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target_week = week_num,
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target_year = year_num
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)
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if (!is.null(farm_mosaic)) {
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safe_log(paste("✓ Successfully aggregated farm mosaic for", label, ""))
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return(farm_mosaic)
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} else {
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safe_log(paste("Warning: Farm mosaic is NULL for", label), "WARNING")
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return(NULL)
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}
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}, error = function(e) {
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safe_log(paste("Error aggregating mosaics for", label, ":", e$message), "WARNING")
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return(NULL)
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})
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}
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# Aggregate mosaics for three weeks: current, week-1, week-3
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farm_mosaic_current <- aggregate_mosaics_safe(current_week, current_iso_year, "current week")
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farm_mosaic_minus_1 <- aggregate_mosaics_safe(week_minus_1, week_minus_1_year, "week-1")
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farm_mosaic_minus_3 <- aggregate_mosaics_safe(week_minus_3, week_minus_3_year, "week-3")
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# Extract CI band (5th band, or named "CI") from each aggregated mosaic
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farm_ci_current <- NULL
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farm_ci_minus_1 <- NULL
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farm_ci_minus_3 <- NULL
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if (!is.null(farm_mosaic_current)) {
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if ("CI" %in% names(farm_mosaic_current)) {
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farm_ci_current <- farm_mosaic_current[["CI"]]
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} else if (terra::nlyr(farm_mosaic_current) >= 5) {
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farm_ci_current <- farm_mosaic_current[[5]] # CI is typically band 5 (R,G,B,NIR,CI)
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}
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if (!is.null(farm_ci_current)) {
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safe_log("✓ Extracted CI band from current week mosaic")
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}
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}
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if (!is.null(farm_mosaic_minus_1)) {
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if ("CI" %in% names(farm_mosaic_minus_1)) {
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farm_ci_minus_1 <- farm_mosaic_minus_1[["CI"]]
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} else if (terra::nlyr(farm_mosaic_minus_1) >= 5) {
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farm_ci_minus_1 <- farm_mosaic_minus_1[[5]]
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}
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if (!is.null(farm_ci_minus_1)) {
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safe_log("✓ Extracted CI band from week-1 mosaic")
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}
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}
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if (!is.null(farm_mosaic_minus_3)) {
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if ("CI" %in% names(farm_mosaic_minus_3)) {
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farm_ci_minus_3 <- farm_mosaic_minus_3[["CI"]]
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} else if (terra::nlyr(farm_mosaic_minus_3) >= 5) {
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farm_ci_minus_3 <- farm_mosaic_minus_3[[5]]
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}
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if (!is.null(farm_ci_minus_3)) {
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safe_log("✓ Extracted CI band from week-3 mosaic")
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}
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}
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# Calculate difference rasters
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farm_ci_diff_week <- NULL
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if (!is.null(farm_ci_current) && !is.null(farm_ci_minus_1)) {
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farm_ci_diff_week <- farm_ci_current - farm_ci_minus_1
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safe_log("✓ Calculated week-over-week difference raster")
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} else {
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safe_log("Warning: Cannot calculate week-over-week difference - missing data", "WARNING")
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}
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# Reproject rasters and boundaries for ggplot basemap (OSM uses EPSG:4326)
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farm_ci_current_ll <- farm_ci_current
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farm_ci_diff_week_ll <- farm_ci_diff_week
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AllPivots0_ll <- AllPivots0
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target_crs <- "EPSG:4326"
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downsample_raster <- function(r, max_cells = 2000000) {
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if (is.null(r)) {
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return(NULL)
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}
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n_cells <- terra::ncell(r)
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if (!is.na(n_cells) && n_cells > max_cells) {
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fact <- ceiling(sqrt(n_cells / max_cells))
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safe_log(paste("Downsampling raster by factor", fact), "INFO")
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return(terra::aggregate(r, fact = fact, fun = mean, na.rm = TRUE))
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}
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r
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}
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if (!is.null(farm_ci_current) && !terra::is.lonlat(farm_ci_current)) {
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farm_ci_current_ll <- terra::project(farm_ci_current, target_crs, method = "bilinear")
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}
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if (!is.null(farm_ci_diff_week) && !terra::is.lonlat(farm_ci_diff_week)) {
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farm_ci_diff_week_ll <- terra::project(farm_ci_diff_week, target_crs, method = "bilinear")
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}
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if (!is.null(AllPivots0)) {
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AllPivots0_ll <- sf::st_transform(AllPivots0, 4326)
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}
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farm_ci_current_ll <- downsample_raster(farm_ci_current_ll)
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farm_ci_diff_week_ll <- downsample_raster(farm_ci_diff_week_ll)
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# Ensure boundaries align with raster extent to avoid plotting issues
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sf::sf_use_s2(FALSE)
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if (!is.null(AllPivots0_ll) && !is.null(farm_ci_current_ll)) {
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AllPivots0_ll <- sf::st_make_valid(AllPivots0_ll)
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crop_bbox_current <- sf::st_as_sfc(sf::st_bbox(terra::ext(farm_ci_current_ll), crs = 4326))
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AllPivots0_ll <- sf::st_intersection(AllPivots0_ll, crop_bbox_current)
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AllPivots0_ll <- sf::st_collection_extract(AllPivots0_ll, "POLYGON")
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}
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# Prepare boundary and label data frames for ggplot (avoid geom_sf coord resets)
|
||||
bounds_df <- NULL
|
||||
labels_df <- NULL
|
||||
if (!is.null(AllPivots0_ll)) {
|
||||
bounds_coords <- sf::st_coordinates(AllPivots0_ll)
|
||||
bounds_df <- as.data.frame(bounds_coords)
|
||||
bounds_df$group <- interaction(bounds_df$L1, bounds_df$L2, drop = TRUE)
|
||||
label_pts <- sf::st_point_on_surface(AllPivots0_ll)
|
||||
labels_df <- cbind(as.data.frame(sf::st_coordinates(label_pts)), sub_field = label_pts$sub_field)
|
||||
}
|
||||
|
||||
# Log completion
|
||||
safe_log("Farm-level raster aggregation complete")
|
||||
|
||||
}, error = function(e) {
|
||||
safe_log(paste("Error in farm-level raster aggregation:", e$message), "ERROR")
|
||||
})
|
||||
```
|
||||
|
||||
### Chlorophyll Index (CI) Overview Map - Current Week
|
||||
|
||||
```{r render_farm_ci_map, echo=FALSE, fig.height=5.5, fig.width=6.5, dpi=150, dev='png', message=FALSE, warning=FALSE}
|
||||
# Create farm-level chlorophyll index map with OpenStreetMap basemap
|
||||
tryCatch({
|
||||
if (!is.null(farm_ci_current_ll)) {
|
||||
safe_log("Rendering farm-level CI overview map")
|
||||
|
||||
# Convert raster to data.frame for ggplot
|
||||
ci_df <- as.data.frame(farm_ci_current_ll, xy = TRUE, na.rm = FALSE)
|
||||
colnames(ci_df) <- c("x", "y", "ci_value")
|
||||
|
||||
# Choose color palette based on colorblind_friendly parameter
|
||||
if (colorblind_friendly) {
|
||||
fill_scale <- ggplot2::scale_fill_viridis_c(
|
||||
name = "Chlorophyll Index (CI)",
|
||||
limits = c(1, 8),
|
||||
direction = -1, # Reversed: green=high, yellow/red=low
|
||||
na.value = "transparent",
|
||||
oob = scales::squish
|
||||
)
|
||||
} else {
|
||||
# Use Red-Yellow-Green diverging palette (reversed for intuitive interpretation)
|
||||
fill_scale <- ggplot2::scale_fill_distiller(
|
||||
palette = "RdYlGn",
|
||||
name = "Chlorophyll Index (CI)",
|
||||
limits = c(1, 8),
|
||||
direction = 1, # Standard direction for RdYlGn
|
||||
na.value = "transparent"
|
||||
)
|
||||
}
|
||||
|
||||
# Build the map
|
||||
ci_ext <- terra::ext(farm_ci_current_ll)
|
||||
ci_bbox <- sf::st_bbox(c(xmin = ci_ext$xmin, xmax = ci_ext$xmax, ymin = ci_ext$ymin, ymax = ci_ext$ymax), crs = 4326)
|
||||
|
||||
map <- ggplot2::ggplot() +
|
||||
ggspatial::annotation_map_tile(
|
||||
type = "osm",
|
||||
zoom = 14,
|
||||
alpha = 0.4
|
||||
) +
|
||||
# Add raster layer with CI values
|
||||
ggplot2::geom_raster(
|
||||
data = ci_df,
|
||||
ggplot2::aes(x = x, y = y, fill = ci_value)
|
||||
) +
|
||||
fill_scale +
|
||||
ggplot2::coord_sf(
|
||||
crs = 4326,
|
||||
xlim = c(ci_ext$xmin, ci_ext$xmax),
|
||||
ylim = c(ci_ext$ymin, ci_ext$ymax),
|
||||
expand = FALSE
|
||||
)
|
||||
|
||||
if (!is.null(bounds_df)) {
|
||||
map <- map + ggplot2::geom_path(
|
||||
data = bounds_df,
|
||||
ggplot2::aes(x = X, y = Y, group = group),
|
||||
color = "black",
|
||||
linewidth = 0.4
|
||||
)
|
||||
}
|
||||
|
||||
if (!is.null(labels_df)) {
|
||||
map <- map + ggplot2::geom_text(
|
||||
data = labels_df,
|
||||
ggplot2::aes(x = X, y = Y, label = sub_field),
|
||||
size = 3,
|
||||
color = "black"
|
||||
)
|
||||
}
|
||||
|
||||
map <- map +
|
||||
# Add scale bar and theme
|
||||
ggspatial::annotation_scale(
|
||||
location = "br",
|
||||
width_hint = 0.25
|
||||
) +
|
||||
ggplot2::theme_void() +
|
||||
ggplot2::theme(
|
||||
legend.position = "bottom",
|
||||
legend.direction = "horizontal",
|
||||
legend.title = ggplot2::element_text(size = 10),
|
||||
legend.text = ggplot2::element_text(size = 9),
|
||||
plot.title = ggplot2::element_text(hjust = 0.5, size = 12, face = "bold"),
|
||||
panel.background = ggplot2::element_rect(fill = "white", color = NA)
|
||||
) +
|
||||
ggplot2::labs(
|
||||
title = paste("Current Week CI Overview - Week", current_week, "of", current_iso_year)
|
||||
)
|
||||
|
||||
# Print the map
|
||||
print(map)
|
||||
safe_log("✓ Farm-level CI map rendered successfully")
|
||||
|
||||
} else {
|
||||
safe_log("Farm-level CI raster not available - skipping overview map", "WARNING")
|
||||
plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
|
||||
text(1, 1, "Farm-level CI overview map not available", cex = 1.5, col = "gray")
|
||||
}
|
||||
}, error = function(e) {
|
||||
safe_log(paste("Error rendering farm CI overview map:", e$message), "ERROR")
|
||||
plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
|
||||
text(1, 1, "Error creating CI overview map", cex = 1.5, col = "red")
|
||||
})
|
||||
```
|
||||
|
||||
### Weekly Chlorophyll Index Difference Map
|
||||
|
||||
```{r render_farm_ci_diff_map, echo=FALSE, fig.height=5.5, fig.width=6.5, dpi=150, dev='png', message=FALSE, warning=FALSE}
|
||||
# Create farm-level CI difference map (week-over-week change)
|
||||
tryCatch({
|
||||
if (!is.null(farm_ci_diff_week_ll)) {
|
||||
safe_log("Rendering farm-level CI difference map (week-over-week)")
|
||||
|
||||
# Convert difference raster to data.frame for ggplot
|
||||
diff_df <- as.data.frame(farm_ci_diff_week_ll, xy = TRUE, na.rm = FALSE)
|
||||
colnames(diff_df) <- c("x", "y", "ci_diff")
|
||||
|
||||
# Determine color palette based on colorblind_friendly parameter
|
||||
if (colorblind_friendly) {
|
||||
# Use plasma for colorblind-friendly diverging visualization
|
||||
fill_scale <- ggplot2::scale_fill_viridis_c(
|
||||
name = "CI Change (Week-over-Week)",
|
||||
option = "plasma",
|
||||
limits = c(-3, 3),
|
||||
na.value = "transparent",
|
||||
oob = scales::squish
|
||||
)
|
||||
} else {
|
||||
# Use Red-Blue diverging palette (red=decline, blue=increase)
|
||||
fill_scale <- ggplot2::scale_fill_distiller(
|
||||
palette = "RdBu",
|
||||
name = "CI Change (Week-over-Week)",
|
||||
limits = c(-3, 3),
|
||||
direction = 1,
|
||||
na.value = "transparent"
|
||||
)
|
||||
}
|
||||
|
||||
# Build the map
|
||||
diff_ext <- terra::ext(farm_ci_diff_week_ll)
|
||||
diff_bbox <- sf::st_bbox(c(xmin = diff_ext$xmin, xmax = diff_ext$xmax, ymin = diff_ext$ymin, ymax = diff_ext$ymax), crs = 4326)
|
||||
|
||||
map <- ggplot2::ggplot() +
|
||||
ggspatial::annotation_map_tile(
|
||||
type = "osm",
|
||||
zoom = 12,
|
||||
alpha = 0.4
|
||||
) +
|
||||
# Add raster layer with difference values
|
||||
ggplot2::geom_raster(
|
||||
data = diff_df,
|
||||
ggplot2::aes(x = x, y = y, fill = ci_diff)
|
||||
) +
|
||||
fill_scale +
|
||||
ggplot2::coord_sf(
|
||||
crs = 4326,
|
||||
xlim = c(diff_ext$xmin, diff_ext$xmax),
|
||||
ylim = c(diff_ext$ymin, diff_ext$ymax),
|
||||
expand = FALSE
|
||||
)
|
||||
|
||||
if (!is.null(bounds_df)) {
|
||||
map <- map + ggplot2::geom_path(
|
||||
data = bounds_df,
|
||||
ggplot2::aes(x = X, y = Y, group = group),
|
||||
color = "black",
|
||||
linewidth = 0.4
|
||||
)
|
||||
}
|
||||
|
||||
if (!is.null(labels_df)) {
|
||||
map <- map + ggplot2::geom_text(
|
||||
data = labels_df,
|
||||
ggplot2::aes(x = X, y = Y, label = sub_field),
|
||||
size = 3,
|
||||
color = "black"
|
||||
)
|
||||
}
|
||||
|
||||
map <- map +
|
||||
# Add scale bar and theme
|
||||
ggspatial::annotation_scale(
|
||||
location = "br",
|
||||
width_hint = 0.25
|
||||
) +
|
||||
ggplot2::theme_void() +
|
||||
ggplot2::theme(
|
||||
legend.position = "bottom",
|
||||
legend.direction = "horizontal",
|
||||
legend.title = ggplot2::element_text(size = 10),
|
||||
legend.text = ggplot2::element_text(size = 9),
|
||||
plot.title = ggplot2::element_text(hjust = 0.5, size = 12, face = "bold"),
|
||||
panel.background = ggplot2::element_rect(fill = "white", color = NA)
|
||||
) +
|
||||
ggplot2::labs(
|
||||
title = paste("Weekly CI Change - Week", current_week, "vs Week", week_minus_1)
|
||||
)
|
||||
|
||||
# Print the map
|
||||
print(map)
|
||||
safe_log("✓ Farm-level CI difference map rendered successfully")
|
||||
|
||||
} else {
|
||||
safe_log("Farm-level difference raster not available - skipping difference map", "WARNING")
|
||||
plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
|
||||
text(1, 1, "Week-over-week difference map not available", cex = 1.5, col = "gray")
|
||||
}
|
||||
}, error = function(e) {
|
||||
safe_log(paste("Error rendering farm CI difference map:", e$message), "ERROR")
|
||||
plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
|
||||
text(1, 1, "Error creating CI difference map", cex = 1.5, col = "red")
|
||||
})
|
||||
```
|
||||
|
||||
\newpage
|
||||
|
||||
# Section 2: Field-by-Field Analysis
|
||||
|
||||
## Overview of Field-Level Insights
|
||||
|
|
@ -635,7 +1060,7 @@ This section provides detailed, field-specific analyses including chlorophyll in
|
|||
|
||||
\newpage
|
||||
|
||||
```{r generate_field_visualizations, eval=TRUE, fig.height=3.8, fig.width=10, dpi=300, dev='png', message=TRUE, echo=FALSE, warning=TRUE, include=TRUE, results='asis'}
|
||||
```{r generate_field_visualizations, eval=TRUE, fig.height=3.8, fig.width=6.5, dpi=150, dev='png', message=TRUE, echo=FALSE, warning=TRUE, include=TRUE, results='asis'}
|
||||
# Generate detailed visualizations for each field using purrr::walk
|
||||
tryCatch({
|
||||
# Prepare merged field list and week/year info
|
||||
|
|
@ -799,7 +1224,7 @@ tryCatch({
|
|||
})
|
||||
```
|
||||
|
||||
```{r generate_subarea_visualizations, echo=FALSE, fig.height=3.8, fig.width=10, message=FALSE, warning=FALSE, results='asis', eval=FALSE}
|
||||
```{r generate_subarea_visualizations, echo=FALSE, fig.height=3.8, fig.width=6.5, dpi=150, message=FALSE, warning=FALSE, results='asis', eval=FALSE}
|
||||
# Alternative visualization grouped by sub-area (disabled by default)
|
||||
tryCatch({
|
||||
# Group pivots by sub-area
|
||||
|
|
@ -907,12 +1332,12 @@ if (!exists("field_details_table") || is.null(field_details_table)) {
|
|||
|
||||
# Display the cleaned field table with flextable
|
||||
# Set column widths to fit page (approximately 6.5 inches for 1-inch margins)
|
||||
col_widths <- c(1.2, 0.9, 1.0, 1.0, 0.8, 0.9, 0.8, 0.7, 0.6) # inches for each column
|
||||
# Scale widths proportionally: original total = 8.0 inches, scale to 6.2 inches
|
||||
col_widths <- c(0.97, 0.73, 0.80, 0.80, 0.65, 0.73, 0.65, 0.56, 0.48) # inches for each column
|
||||
|
||||
ft <- flextable(field_details_clean) %>%
|
||||
set_caption("Detailed Field Performance Summary") %>%
|
||||
width(width = col_widths) %>%
|
||||
autofit(add_w = 0, add_h = 0)
|
||||
width(width = col_widths)
|
||||
|
||||
ft
|
||||
```
|
||||
|
|
|
|||
|
|
@ -438,8 +438,8 @@
|
|||
# rmarkdown::render(
|
||||
rmarkdown::render(
|
||||
"r_app/90_CI_report_with_kpis_agronomic_support.Rmd",
|
||||
params = list(data_dir = "aura", report_date = as.Date("2026-01-01")),
|
||||
output_file = "SmartCane_Report_agronomic_support_aura_2026-01-01.docx",
|
||||
params = list(data_dir = "aura", report_date = as.Date("2022-12-08")),
|
||||
output_file = "SmartCane_Report_agronomic_support_aura_2022-12-08.docx",
|
||||
output_dir = "laravel_app/storage/app/aura/reports"
|
||||
)
|
||||
#
|
||||
|
|
|
|||
|
|
@ -78,7 +78,11 @@ create_CI_map <- function(pivot_raster, pivot_shape, pivot_spans, show_legend =
|
|||
# Add layout configuration to prevent legend rescaling
|
||||
map <- map + tm_layout(legend.position = c("left", "bottom"),
|
||||
legend.outside = FALSE,
|
||||
inner.margins = 0.05)
|
||||
inner.margins = 0.05,
|
||||
asp = 1) # Force 1:1 aspect ratio for consistent sizing
|
||||
|
||||
# Add bounds/view settings for fixed aspect ratio
|
||||
map <- map + tm_view(asp = 1)
|
||||
|
||||
# Add borders if requested
|
||||
if (borders) {
|
||||
|
|
@ -146,7 +150,11 @@ create_CI_diff_map <- function(pivot_raster, pivot_shape, pivot_spans, show_lege
|
|||
# Add layout configuration to prevent legend rescaling
|
||||
map <- map + tm_layout(legend.position = c("right", "bottom"),
|
||||
legend.outside = FALSE,
|
||||
inner.margins = 0.05)
|
||||
inner.margins = 0.05,
|
||||
asp = 1) # Force 1:1 aspect ratio for consistent sizing
|
||||
|
||||
# Add bounds/view settings for fixed aspect ratio
|
||||
map <- map + tm_view(asp = 1)
|
||||
|
||||
# Add borders if requested
|
||||
if (borders) {
|
||||
|
|
@ -260,17 +268,19 @@ ci_plot <- function(pivotName,
|
|||
week = week, age = age, borders = borders, colorblind = colorblind_friendly)
|
||||
|
||||
# Create historical maps only if data is available
|
||||
maps_to_arrange <- list(CImap)
|
||||
widths_to_use <- c(1)
|
||||
# Build list with all available maps - order matches original: [m2, m1, current, diff_1w, diff_3w]
|
||||
# Widths match original hardcoded: c(0.23, 0.18, 0.18, 0.18, 0.23)
|
||||
maps_to_arrange <- list()
|
||||
widths_to_use <- c()
|
||||
field_heading_note <- ""
|
||||
|
||||
# Try to create 2-week ago map
|
||||
# Try to create 2-week ago map (legend on left)
|
||||
if (!is.null(singlePivot_m2)) {
|
||||
CImap_m2 <- create_CI_map(singlePivot_m2, AllPivots2, joined_spans2,
|
||||
show_legend = TRUE, legend_is_portrait = TRUE,
|
||||
week = week_minus_2, age = age - 2, borders = borders, colorblind = colorblind_friendly)
|
||||
maps_to_arrange <- c(list(CImap_m2), maps_to_arrange)
|
||||
widths_to_use <- c(0.4, widths_to_use)
|
||||
maps_to_arrange <- c(maps_to_arrange, list(CImap_m2))
|
||||
widths_to_use <- c(widths_to_use, 0.24)
|
||||
}
|
||||
|
||||
# Try to create 1-week ago map
|
||||
|
|
@ -279,25 +289,29 @@ ci_plot <- function(pivotName,
|
|||
show_legend = FALSE, legend_is_portrait = FALSE,
|
||||
week = week_minus_1, age = age - 1, borders = borders, colorblind = colorblind_friendly)
|
||||
maps_to_arrange <- c(maps_to_arrange, list(CImap_m1))
|
||||
widths_to_use <- c(widths_to_use, 0.3)
|
||||
widths_to_use <- c(widths_to_use, 0.17)
|
||||
}
|
||||
|
||||
# Always add current week map (center position)
|
||||
maps_to_arrange <- c(maps_to_arrange, list(CImap))
|
||||
widths_to_use <- c(widths_to_use, 0.17)
|
||||
|
||||
# Try to create 1-week difference map
|
||||
if (!is.null(abs_CI_last_week)) {
|
||||
CI_max_abs_last_week <- create_CI_diff_map(abs_CI_last_week, AllPivots2, joined_spans2,
|
||||
show_legend = FALSE, legend_is_portrait = FALSE,
|
||||
week_1 = week, week_2 = week_minus_1, age = age, borders = borders, colorblind = colorblind_friendly)
|
||||
maps_to_arrange <- c(maps_to_arrange, list(CI_max_abs_last_week))
|
||||
widths_to_use <- c(widths_to_use, 0.3)
|
||||
widths_to_use <- c(widths_to_use, 0.17)
|
||||
}
|
||||
|
||||
# Try to create 3-week difference map
|
||||
# Try to create 3-week difference map (legend on right)
|
||||
if (!is.null(abs_CI_three_week)) {
|
||||
CI_max_abs_three_week <- create_CI_diff_map(abs_CI_three_week, AllPivots2, joined_spans2,
|
||||
show_legend = TRUE, legend_is_portrait = TRUE,
|
||||
week_1 = week, week_2 = week_minus_3, age = age, borders = borders, colorblind = colorblind_friendly)
|
||||
maps_to_arrange <- c(maps_to_arrange, list(CI_max_abs_three_week))
|
||||
widths_to_use <- c(widths_to_use, 0.4)
|
||||
widths_to_use <- c(widths_to_use, 0.24)
|
||||
}
|
||||
|
||||
# Normalize widths to sum to 1
|
||||
|
|
@ -925,19 +939,19 @@ aggregate_per_field_mosaics_to_farm_level <- function(
|
|||
|
||||
safe_log(paste("Successfully loaded mosaics for", length(raster_list), "fields"), "INFO")
|
||||
|
||||
# Create a SpatRasterCollection and mosaic using correct terra syntax
|
||||
# Create a SpatRasterCollection and merge using correct terra syntax
|
||||
tryCatch({
|
||||
rsrc <- terra::sprc(raster_list)
|
||||
safe_log(paste("Created SpatRasterCollection with", length(raster_list), "rasters"), "DEBUG")
|
||||
|
||||
# Mosaic the rasters - this merges them into a single continuous raster
|
||||
farm_mosaic <- terra::mosaic(rsrc)
|
||||
# Merge the rasters into a single continuous raster (no overlap expected between fields)
|
||||
farm_mosaic <- terra::merge(rsrc)
|
||||
|
||||
safe_log(paste("Aggregated", length(raster_list), "per-field mosaics into farm-level mosaic"), "INFO")
|
||||
|
||||
# Verify mosaic was created successfully
|
||||
if (is.null(farm_mosaic)) {
|
||||
stop("mosaic() returned NULL")
|
||||
stop("merge() returned NULL")
|
||||
}
|
||||
|
||||
return(farm_mosaic)
|
||||
|
|
|
|||
155
r_app/test_kpi_validation.R
Normal file
155
r_app/test_kpi_validation.R
Normal file
|
|
@ -0,0 +1,155 @@
|
|||
#!/usr/bin/env Rscript
|
||||
# Diagnostic script to validate KPI RDS file structure
|
||||
# Usage: Rscript test_kpi_validation.R [project] [date]
|
||||
|
||||
# Set up arguments
|
||||
args <- commandArgs(trailingOnly = TRUE)
|
||||
|
||||
if (length(args) < 2) {
|
||||
cat("Usage: Rscript test_kpi_validation.R [project] [date]\n")
|
||||
cat("Example: Rscript test_kpi_validation.R aura 2022-11-14\n")
|
||||
quit(status = 1)
|
||||
}
|
||||
|
||||
project_dir <- args[1]
|
||||
report_date <- as.Date(args[2])
|
||||
|
||||
cat("\n=== KPI RDS Validation ===\n")
|
||||
cat("Project:", project_dir, "\n")
|
||||
cat("Date:", report_date, "\n")
|
||||
|
||||
# Load utilities
|
||||
source("r_app/parameters_project.R")
|
||||
source("r_app/00_common_utils.R")
|
||||
|
||||
# Set up paths
|
||||
paths <- setup_project_directories(project_dir)
|
||||
kpi_data_dir <- paths$kpi_reports_dir
|
||||
|
||||
# Calculate week
|
||||
current_week <- as.numeric(format(as.Date(report_date), "%V"))
|
||||
current_year <- as.numeric(format(as.Date(report_date), "%G"))
|
||||
|
||||
kpi_rds_filename <- paste0(project_dir, "_kpi_summary_tables_week",
|
||||
sprintf("%02d_%d", current_week, current_year), ".rds")
|
||||
kpi_rds_path <- file.path(kpi_data_dir, kpi_rds_filename)
|
||||
|
||||
cat("\nKPI directory:", kpi_data_dir, "\n")
|
||||
cat("KPI filename:", kpi_rds_filename, "\n")
|
||||
cat("Full path:", kpi_rds_path, "\n\n")
|
||||
|
||||
# Check if directory exists
|
||||
if (!dir.exists(kpi_data_dir)) {
|
||||
cat("ERROR: KPI directory does not exist!\n")
|
||||
quit(status = 1)
|
||||
}
|
||||
|
||||
# List available files
|
||||
cat("Files in KPI directory:\n")
|
||||
files <- list.files(kpi_data_dir, pattern = "\\.rds$")
|
||||
if (length(files) == 0) {
|
||||
cat(" (none)\n")
|
||||
} else {
|
||||
for (f in files) {
|
||||
cat(" -", f, "\n")
|
||||
}
|
||||
}
|
||||
|
||||
# Check if our specific file exists
|
||||
if (!file.exists(kpi_rds_path)) {
|
||||
cat("\nWARNING: Expected KPI file not found!\n")
|
||||
cat("Expected:", kpi_rds_filename, "\n")
|
||||
quit(status = 1)
|
||||
}
|
||||
|
||||
cat("\n✓ KPI file found. Loading...\n\n")
|
||||
|
||||
# Load the RDS
|
||||
loaded_data <- readRDS(kpi_rds_path)
|
||||
|
||||
# Inspect structure
|
||||
cat("=== RDS Structure ===\n")
|
||||
cat("Class:", class(loaded_data), "\n")
|
||||
cat("Length:", length(loaded_data), "\n")
|
||||
cat("Names:", paste(names(loaded_data), collapse = ", "), "\n\n")
|
||||
|
||||
# Check if new or legacy structure
|
||||
if (is.list(loaded_data) && "summary_tables" %in% names(loaded_data)) {
|
||||
cat("✓ New structure detected (has $summary_tables)\n\n")
|
||||
summary_tables <- loaded_data$summary_tables
|
||||
|
||||
if ("field_details" %in% names(loaded_data)) {
|
||||
cat("✓ Also has $field_details\n\n")
|
||||
}
|
||||
} else {
|
||||
cat("✓ Legacy structure (direct list of KPI tables)\n\n")
|
||||
summary_tables <- loaded_data
|
||||
}
|
||||
|
||||
# Now inspect the summary_tables
|
||||
cat("=== Available KPI Tables ===\n")
|
||||
cat("Keys:", paste(names(summary_tables), collapse = ", "), "\n\n")
|
||||
|
||||
# Expected KPIs
|
||||
expected_kpis <- c(
|
||||
"uniformity",
|
||||
"area_change",
|
||||
"tch_forecasted",
|
||||
"growth_decline",
|
||||
"weed_pressure",
|
||||
"gap_filling"
|
||||
)
|
||||
|
||||
cat("=== Expected vs Actual ===\n")
|
||||
for (kpi in expected_kpis) {
|
||||
# Try both formats
|
||||
found <- FALSE
|
||||
actual_key <- NA
|
||||
|
||||
if (kpi %in% names(summary_tables)) {
|
||||
found <- TRUE
|
||||
actual_key <- kpi
|
||||
} else if (paste0(kpi, "_summary") %in% names(summary_tables)) {
|
||||
found <- TRUE
|
||||
actual_key <- paste0(kpi, "_summary")
|
||||
}
|
||||
|
||||
status <- if (found) "✓ FOUND" else "✗ MISSING"
|
||||
cat(sprintf("%-20s %s", kpi, status))
|
||||
if (found) {
|
||||
cat(" (key: ", actual_key, ")")
|
||||
}
|
||||
cat("\n")
|
||||
}
|
||||
|
||||
cat("\n=== Detailed KPI Contents ===\n")
|
||||
for (kpi_key in names(summary_tables)) {
|
||||
kpi_df <- summary_tables[[kpi_key]]
|
||||
|
||||
cat("\n", kpi_key, ":\n", sep="")
|
||||
cat(" Class:", class(kpi_df), "\n")
|
||||
cat(" Dimensions:", nrow(kpi_df), "rows ×", ncol(kpi_df), "cols\n")
|
||||
cat(" Columns:", paste(names(kpi_df), collapse = ", "), "\n")
|
||||
|
||||
if (nrow(kpi_df) > 0) {
|
||||
cat(" First few rows:\n")
|
||||
print(head(kpi_df, 3))
|
||||
} else {
|
||||
cat(" (empty dataframe)\n")
|
||||
}
|
||||
}
|
||||
|
||||
cat("\n=== Validation Summary ===\n")
|
||||
missing_count <- sum(!expected_kpis %in% c(names(summary_tables), paste0(expected_kpis, "_summary")))
|
||||
if (missing_count == 0) {
|
||||
cat("✓ All expected KPIs are present!\n")
|
||||
} else {
|
||||
cat("✗ Missing", missing_count, "KPI(s):\n")
|
||||
for (kpi in expected_kpis) {
|
||||
if (!kpi %in% names(summary_tables) && !paste0(kpi, "_summary") %in% names(summary_tables)) {
|
||||
cat(" -", kpi, "\n")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cat("\n")
|
||||
371
r_app/test_overview_maps_aggregation.R
Normal file
371
r_app/test_overview_maps_aggregation.R
Normal file
|
|
@ -0,0 +1,371 @@
|
|||
#!/usr/bin/env Rscript
|
||||
|
||||
# ==============================================================================
|
||||
# TEST SCRIPT: Farm-Level Mosaic Aggregation for Overview Maps
|
||||
# ==============================================================================
|
||||
# Purpose: Test each step of the aggregation pipeline independently
|
||||
# ==============================================================================
|
||||
|
||||
# Parse arguments
|
||||
args <- commandArgs(trailingOnly = TRUE)
|
||||
project_dir <- if (length(args) > 0) args[1] else "aura"
|
||||
report_date_str <- if (length(args) > 1) args[2] else "2022-12-08"
|
||||
|
||||
cat("\n========== Testing Overview Maps Aggregation ==========\n")
|
||||
cat(paste("Project:", project_dir, "\n"))
|
||||
cat(paste("Report Date:", report_date_str, "\n\n"))
|
||||
cat(paste("Project:", project_dir, "\n"))
|
||||
cat(paste("Report Date:", report_date_str, "\n"))
|
||||
cat(paste(strrep("═", 80), "\n\n"))
|
||||
|
||||
# Load libraries
|
||||
suppressPackageStartupMessages({
|
||||
library(here)
|
||||
library(sf)
|
||||
library(terra)
|
||||
library(tidyverse)
|
||||
library(lubridate)
|
||||
library(ggspatial)
|
||||
})
|
||||
|
||||
# Load project config
|
||||
tryCatch({
|
||||
source(here::here("r_app", "parameters_project.R"))
|
||||
source(here::here("r_app", "00_common_utils.R"))
|
||||
}, error = function(e) {
|
||||
stop("Error loading project utilities: ", e$message)
|
||||
})
|
||||
|
||||
# Set up paths
|
||||
paths <- setup_project_directories(project_dir)
|
||||
weekly_CI_mosaic <- paths$weekly_mosaic_dir
|
||||
|
||||
# Calculate week/year from report_date
|
||||
report_date_obj <- as.Date(report_date_str)
|
||||
current_week <- lubridate::isoweek(report_date_obj)
|
||||
current_iso_year <- lubridate::isoyear(report_date_obj)
|
||||
|
||||
cat(paste(strrep("=", 80), "\n"))
|
||||
cat(paste("STEP 1: Check Directory Structure\n"))
|
||||
cat(paste(strrep("=", 80), "\n"))
|
||||
|
||||
cat(paste("\nweekly_CI_mosaic path:", weekly_CI_mosaic, "\n"))
|
||||
cat(paste("Directory exists:", dir.exists(weekly_CI_mosaic), "\n"))
|
||||
|
||||
if (!dir.exists(weekly_CI_mosaic)) {
|
||||
cat("ERROR: weekly_mosaic directory not found!\n")
|
||||
quit(status = 1)
|
||||
}
|
||||
|
||||
# List contents
|
||||
all_items <- list.files(weekly_CI_mosaic, full.names = FALSE)
|
||||
cat(paste("\nTotal items in weekly_mosaic/:", length(all_items), "\n"))
|
||||
cat("First 10 items:\n")
|
||||
for (i in 1:min(10, length(all_items))) {
|
||||
cat(paste(" ", all_items[i], "\n"))
|
||||
}
|
||||
|
||||
# Find field directories
|
||||
field_dirs <- all_items[
|
||||
!grepl("\\.tif$", all_items, ignore.case = TRUE) &
|
||||
dir.exists(file.path(weekly_CI_mosaic, all_items))
|
||||
]
|
||||
|
||||
cat(paste("\nField directories found:", length(field_dirs), "\n"))
|
||||
if (length(field_dirs) > 0) {
|
||||
cat("First 10 field directories:\n")
|
||||
for (i in 1:min(10, length(field_dirs))) {
|
||||
cat(paste(" ", field_dirs[i], "\n"))
|
||||
}
|
||||
}
|
||||
|
||||
cat(paste(strrep("=", 80), "\n"))
|
||||
cat(paste("STEP 2: Check Weekly Mosaic Files for Target Week\n"))
|
||||
cat(paste(strrep("=", 80), "\n"))
|
||||
|
||||
cat(paste("\nTarget week:", sprintf("%02d", current_week), "\n"))
|
||||
cat(paste("Target year:", current_iso_year, "\n\n"))
|
||||
|
||||
# Check which fields have mosaic files for this week
|
||||
found_files <- 0
|
||||
missing_files <- 0
|
||||
|
||||
for (field_dir in field_dirs[1:min(10, length(field_dirs))]) {
|
||||
expected_file <- paste0("week_", sprintf("%02d", current_week), "_", current_iso_year, ".tif")
|
||||
full_path <- file.path(weekly_CI_mosaic, field_dir, expected_file)
|
||||
|
||||
if (file.exists(full_path)) {
|
||||
cat(paste(" ✓ FOUND:", field_dir, "/", expected_file, "\n"))
|
||||
found_files <- found_files + 1
|
||||
} else {
|
||||
cat(paste(" ✗ MISSING:", field_dir, "/", expected_file, "\n"))
|
||||
missing_files <- missing_files + 1
|
||||
|
||||
# List what actually exists in this field's directory
|
||||
field_path <- file.path(weekly_CI_mosaic, field_dir)
|
||||
field_contents <- list.files(field_path, full.names = FALSE)
|
||||
if (length(field_contents) > 0) {
|
||||
cat(paste(" Available:", paste(field_contents[1:min(3, length(field_contents))], collapse = ", "), "\n"))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
cat(paste("\nFound: ", found_files, " files | Missing: ", missing_files, "\n"))
|
||||
|
||||
if (found_files == 0) {
|
||||
cat("\nERROR: No weekly mosaic files found for this week/year combination!\n")
|
||||
cat("Check if Script 40 (mosaic_creation) has been run for this week.\n")
|
||||
quit(status = 1)
|
||||
}
|
||||
|
||||
cat("\n================================================================================\n")
|
||||
cat("STEP 3: Load Individual Field Mosaics\n")
|
||||
cat("================================================================================\n")
|
||||
|
||||
# Load all available mosaics
|
||||
raster_list <- list()
|
||||
loaded_count <- 0
|
||||
|
||||
for (field_dir in field_dirs) {
|
||||
full_path <- file.path(weekly_CI_mosaic, field_dir,
|
||||
paste0("week_", sprintf("%02d", current_week), "_", current_iso_year, ".tif"))
|
||||
|
||||
if (file.exists(full_path)) {
|
||||
tryCatch({
|
||||
r <- terra::rast(full_path)
|
||||
raster_list[[field_dir]] <- r
|
||||
loaded_count <- loaded_count + 1
|
||||
|
||||
if (loaded_count <= 5) {
|
||||
cat(paste(" ✓", field_dir, "- Raster loaded\n"))
|
||||
cat(paste(" Dimensions:", dim(r)[1], "×", dim(r)[2], "\n"))
|
||||
cat(paste(" Bands:", terra::nlyr(r), "\n"))
|
||||
cat(paste(" Band names:", paste(names(r), collapse = ", "), "\n"))
|
||||
cat(paste(" CRS:", terra::crs(r), "\n\n"))
|
||||
}
|
||||
}, error = function(e) {
|
||||
cat(paste(" ✗", field_dir, "- ERROR loading:", e$message, "\n"))
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
cat(paste("\nSuccessfully loaded:", loaded_count, "field mosaics\n"))
|
||||
|
||||
if (loaded_count == 0) {
|
||||
cat("\nERROR: Could not load any field mosaics!\n")
|
||||
quit(status = 1)
|
||||
}
|
||||
|
||||
cat("\n================================================================================\n")
|
||||
cat("STEP 4: Test Mosaic Aggregation\n")
|
||||
cat("================================================================================\n")
|
||||
|
||||
cat(paste("\nAttempting to mosaic", length(raster_list), "rasters...\n"))
|
||||
|
||||
tryCatch({
|
||||
# Create SpatRasterCollection
|
||||
cat(" Creating SpatRasterCollection...\n")
|
||||
rsrc <- terra::sprc(raster_list)
|
||||
cat(paste(" ✓ SpatRasterCollection created with", length(raster_list), "rasters\n\n"))
|
||||
|
||||
# Mosaic
|
||||
cat(" Mosaicing rasters...\n")
|
||||
farm_mosaic <- terra::merge(rsrc)
|
||||
cat(" ✓ Mosaic successful!\n\n")
|
||||
|
||||
cat(paste("Farm mosaic dimensions:", dim(farm_mosaic)[1], "×", dim(farm_mosaic)[2], "\n"))
|
||||
cat(paste("Bands:", terra::nlyr(farm_mosaic), "\n"))
|
||||
cat(paste("Band names:", paste(names(farm_mosaic), collapse = ", "), "\n"))
|
||||
cat(paste("CRS:", terra::crs(farm_mosaic), "\n"))
|
||||
|
||||
}, error = function(e) {
|
||||
cat(paste("✗ ERROR during mosaicing:", e$message, "\n"))
|
||||
quit(status = 1)
|
||||
})
|
||||
|
||||
cat("\n================================================================================\n")
|
||||
cat("STEP 5: Extract CI Band\n")
|
||||
cat("================================================================================\n")
|
||||
|
||||
tryCatch({
|
||||
if ("CI" %in% names(farm_mosaic)) {
|
||||
cat(" CI band found by name\n")
|
||||
farm_ci <- farm_mosaic[["CI"]]
|
||||
} else if (terra::nlyr(farm_mosaic) >= 5) {
|
||||
cat(" CI band not named, using band 5\n")
|
||||
farm_ci <- farm_mosaic[[5]]
|
||||
} else {
|
||||
stop("Could not find CI band (expected band 5 or named 'CI')")
|
||||
}
|
||||
|
||||
cat(paste(" ✓ CI band extracted\n"))
|
||||
cat(paste(" Dimensions:", dim(farm_ci)[1], "×", dim(farm_ci)[2], "\n"))
|
||||
cat(paste(" Data range:", round(terra::minmax(farm_ci)[1], 2), "to", round(terra::minmax(farm_ci)[2], 2), "\n"))
|
||||
cat(paste(" NA values:", sum(is.na(terra::values(farm_ci))), "\n\n"))
|
||||
|
||||
}, error = function(e) {
|
||||
cat(paste("✗ ERROR extracting CI band:", e$message, "\n"))
|
||||
quit(status = 1)
|
||||
})
|
||||
|
||||
cat(paste(strrep("=", 80), "\n"))
|
||||
cat(paste("STEP 6: Load Field Boundaries for Visualization\n"))
|
||||
cat(paste(strrep("=", 80), "\n"))
|
||||
|
||||
tryCatch({
|
||||
boundaries_result <- load_field_boundaries(paths$data_dir)
|
||||
|
||||
if (is.list(boundaries_result) && "field_boundaries_sf" %in% names(boundaries_result)) {
|
||||
field_boundaries_sf <- boundaries_result$field_boundaries_sf
|
||||
} else {
|
||||
field_boundaries_sf <- boundaries_result
|
||||
}
|
||||
|
||||
if (nrow(field_boundaries_sf) == 0) {
|
||||
stop("No field boundaries loaded")
|
||||
}
|
||||
|
||||
AllPivots0 <- field_boundaries_sf %>%
|
||||
dplyr::filter(!is.na(field), !is.na(sub_field))
|
||||
|
||||
cat(paste(" ✓ Field boundaries loaded\n"))
|
||||
cat(paste(" Fields:", nrow(AllPivots0), "\n"))
|
||||
cat(paste(" CRS:", sf::st_crs(AllPivots0)$epsg, "\n\n"))
|
||||
|
||||
}, error = function(e) {
|
||||
cat(paste("✗ ERROR loading field boundaries:", e$message, "\n"))
|
||||
AllPivots0 <- NULL
|
||||
})
|
||||
|
||||
cat("\n================================================================================\n")
|
||||
cat("STEP 7: Test ggplot Visualization\n")
|
||||
cat("================================================================================\n")
|
||||
|
||||
tryCatch({
|
||||
cat(" Reprojecting raster and boundaries to EPSG:4326 for OSM basemap...\n")
|
||||
target_crs <- "EPSG:4326"
|
||||
farm_ci_ll <- farm_ci
|
||||
AllPivots0_ll <- AllPivots0
|
||||
|
||||
if (!terra::is.lonlat(farm_ci)) {
|
||||
farm_ci_ll <- terra::project(farm_ci, target_crs, method = "bilinear")
|
||||
}
|
||||
if (!is.null(AllPivots0)) {
|
||||
AllPivots0_ll <- sf::st_transform(AllPivots0, 4326)
|
||||
}
|
||||
|
||||
# Ensure boundaries align with raster extent to avoid plotting issues
|
||||
sf::sf_use_s2(FALSE)
|
||||
if (!is.null(AllPivots0_ll)) {
|
||||
AllPivots0_ll <- sf::st_make_valid(AllPivots0_ll)
|
||||
crop_bbox_current <- sf::st_as_sfc(sf::st_bbox(terra::ext(farm_ci_ll), crs = 4326))
|
||||
AllPivots0_ll <- sf::st_intersection(AllPivots0_ll, crop_bbox_current)
|
||||
AllPivots0_ll <- sf::st_collection_extract(AllPivots0_ll, "POLYGON")
|
||||
}
|
||||
|
||||
bounds_df <- NULL
|
||||
labels_df <- NULL
|
||||
if (!is.null(AllPivots0_ll)) {
|
||||
bounds_coords <- sf::st_coordinates(AllPivots0_ll)
|
||||
bounds_df <- as.data.frame(bounds_coords)
|
||||
bounds_df$group <- interaction(bounds_df$L1, bounds_df$L2, drop = TRUE)
|
||||
label_pts <- sf::st_point_on_surface(AllPivots0_ll)
|
||||
labels_df <- cbind(as.data.frame(sf::st_coordinates(label_pts)), sub_field = label_pts$sub_field)
|
||||
}
|
||||
|
||||
cat(" Converting raster to data.frame...\n")
|
||||
ci_df <- as.data.frame(farm_ci_ll, xy = TRUE, na.rm = FALSE)
|
||||
colnames(ci_df) <- c("x", "y", "ci_value")
|
||||
|
||||
cat(paste(" Data.frame dimensions:", nrow(ci_df), "rows ×", ncol(ci_df), "columns\n"))
|
||||
cat(paste(" Non-NA pixels:", sum(!is.na(ci_df$ci_value)), "\n\n"))
|
||||
|
||||
cat(" Building ggplot map with OSM basemap...\n")
|
||||
|
||||
ci_ext <- terra::ext(farm_ci_ll)
|
||||
map <- ggplot2::ggplot() +
|
||||
ggspatial::annotation_map_tile(
|
||||
type = "osm",
|
||||
zoom = 14,
|
||||
alpha = 0.4
|
||||
) +
|
||||
ggplot2::geom_raster(
|
||||
data = ci_df,
|
||||
ggplot2::aes(x = x, y = y, fill = ci_value)
|
||||
) +
|
||||
ggplot2::scale_fill_viridis_c(
|
||||
name = "Chlorophyll Index (CI)",
|
||||
limits = c(1, 8),
|
||||
direction = -1,
|
||||
na.value = "transparent",
|
||||
oob = scales::squish
|
||||
) +
|
||||
ggplot2::coord_sf(
|
||||
crs = 4326,
|
||||
xlim = c(ci_ext$xmin, ci_ext$xmax),
|
||||
ylim = c(ci_ext$ymin, ci_ext$ymax),
|
||||
expand = FALSE
|
||||
)
|
||||
|
||||
if (!is.null(bounds_df)) {
|
||||
map4 <- map + ggplot2::geom_path(
|
||||
data = bounds_df,
|
||||
ggplot2::aes(x = X, y = Y, group = group),
|
||||
color = "black",
|
||||
linewidth = 0.4
|
||||
)
|
||||
}
|
||||
|
||||
if (!is.null(labels_df)) {
|
||||
map5 <- map4 + ggplot2::geom_text(
|
||||
data = labels_df,
|
||||
ggplot2::aes(x = X, y = Y, label = sub_field),
|
||||
size = 3,
|
||||
color = "black"
|
||||
)
|
||||
}
|
||||
|
||||
map6 <- map5 +
|
||||
ggspatial::annotation_scale(
|
||||
location = "br",
|
||||
width_hint = 0.25
|
||||
) +
|
||||
ggplot2::theme_void() +
|
||||
ggplot2::theme(
|
||||
legend.position = "bottom",
|
||||
legend.direction = "horizontal",
|
||||
plot.title = ggplot2::element_text(hjust = 0.5, size = 12, face = "bold")
|
||||
) +
|
||||
ggplot2::labs(
|
||||
title = paste("Test: Farm-Level CI Overview - Week", sprintf("%02d", current_week), "of", current_iso_year)
|
||||
)
|
||||
|
||||
cat(" ✓ Map object created successfully!\n\n")
|
||||
|
||||
# Try to save the map
|
||||
output_path <- paste0("test_overview_map_", project_dir, "_w", sprintf("%02d", current_week), "_", current_iso_year, ".png")
|
||||
cat(paste(" Saving test map to:", output_path, "\n"))
|
||||
|
||||
tryCatch({
|
||||
ggplot2::ggsave(output_path, map, width = 12, height = 10, dpi = 150)
|
||||
cat(paste(" ✓ Map saved successfully!\n"))
|
||||
}, error = function(e) {
|
||||
cat(paste(" ✗ Could not save map:", e$message, "\n"))
|
||||
})
|
||||
|
||||
}, error = function(e) {
|
||||
cat(paste("✗ ERROR in ggplot visualization:", e$message, "\n"))
|
||||
cat(paste(" Full error:", deparse(e), "\n"))
|
||||
quit(status = 1)
|
||||
})
|
||||
|
||||
cat("\n================================================================================\n")
|
||||
cat("SUCCESS: All steps completed!\n")
|
||||
cat("================================================================================\n")
|
||||
cat("Summary:\n")
|
||||
cat(paste(" - Loaded", loaded_count, "field mosaics\n"))
|
||||
cat(paste(" - Created farm-level mosaic\n"))
|
||||
cat(paste(" - Extracted CI band\n"))
|
||||
cat(paste(" - Created ggplot visualization with OSM basemap\n"))
|
||||
cat("\nThe aggregation pipeline is working correctly.\n")
|
||||
cat("If the report still shows no maps, check the report date/week combination.\n")
|
||||
Loading…
Reference in a new issue