Corrected Spansih translations Jordi

r_app/90_CI_report_with_kpis_agronomic_support.Rmd

@@ -8,7 +8,7 @@ params:
   borders: FALSE
   ci_plot_type: "both"
   colorblind_friendly: TRUE
-  lang: "es"
+  lang: "en"
   facet_by_season: FALSE
   x_axis_unit: "days"
 output:
@@ -503,12 +503,13 @@ t <- function(key) {
   if (key %in% names(tr)) {
     txt <- glue(tr[key], .envir = parent.frame())
     txt <- gsub("\n", "  \n", txt)
-    
     return(enc2utf8(as.character(txt)))
-  } else if (key == "" | is.na(key)) {
+  } else if (is.na(key)) {
+    return(t("NA"))
+  } else if (key == "") {
     return("")
   } else {
-    return(paste0("[", key, "]"))
+    return(paste0(key))
   }
 }
 ```
@@ -538,7 +539,7 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
   
   # 1. Uniformity insights - group by interpretation
   if (!is.null(summary_tables$uniformity) && nrow(summary_tables$uniformity) > 0) {
-    cat(t("field_unif"), "\n\n")
+    cat("\n", t("field_unif"))
     uniformity_counts <- summary_tables$uniformity %>%
       dplyr::select(interpretation, count = field_count)
     
@@ -546,14 +547,14 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
       status <- uniformity_counts$interpretation[i]
       count <- uniformity_counts$count[i]
       if (!is.na(status) && !is.na(count) && count > 0) {
-        cat("-", t("unif_status"), "\n\n")
+        cat(" -", t("unif_status"))
       }
     }
   }
   
   # 2. Area change insights - group by interpretation
   if (!is.null(summary_tables$area_change) && nrow(summary_tables$area_change) > 0) {
-    cat(t("field_area"), "\n\n")
+    cat("\n\n", t("field_area"))
     area_counts <- summary_tables$area_change %>%
       dplyr::select(interpretation, count = field_count)
     
@@ -561,14 +562,14 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
       status <- area_counts$interpretation[i]
       count <- area_counts$count[i]
       if (!is.na(status) && !is.na(count) && count > 0) {
-        cat("-", t("area_status"), "\n\n")
+        cat(" -", t("area_status"))
       }
     }
   }
   
   # 3. Growth trend insights - group by trend_interpretation
   if (!is.null(summary_tables$growth_decline) && nrow(summary_tables$growth_decline) > 0) {
-    cat(t("growth_trend"), "\n\n")
+    cat("\n\n", t("growth_trend"))
     growth_counts <- summary_tables$growth_decline %>%
       dplyr::select(trend_interpretation, count = field_count)
     
@@ -576,14 +577,14 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
       trend <- growth_counts$trend_interpretation[i]
       count <- growth_counts$count[i]
       if (!is.na(trend) && !is.na(count) && count > 0) {
-        cat("-", t("trend_status"), "\n\n")
+        cat(" -", t("trend_status"))
       }
     }
   }
   
   # 4. Patchiness insights - group by patchiness_risk
   if (!is.null(summary_tables$patchiness) && nrow(summary_tables$patchiness) > 0) {
-    cat(t("patch_risk"), "\n\n")
+    cat("\n\n", t("patch_risk"))
     patchiness_counts <- summary_tables$patchiness %>%
       dplyr::select(patchiness_risk, count = field_count)
     
@@ -591,14 +592,14 @@ if (exists("summary_tables") && !is.null(summary_tables) && length(summary_table
       risk <- patchiness_counts$patchiness_risk[i]
       count <- patchiness_counts$count[i]
       if (!is.na(risk) && !is.na(count) && count > 0) {
-        cat("-", t("patch_status"), "\n\n")
+        cat(" -", t("patch_status"))
       }
     }
   }
   
   # 5. Total fields analyzed
   total_fields <- sum(summary_tables$uniformity$field_count, na.rm = TRUE)
-  cat(t("tot_fields_analyzed"))
+  cat("\n\n", t("tot_fields_analyzed"))
  
 } else {
   cat(t("kpi_na"))
@@ -1455,14 +1456,14 @@ tryCatch({
         if (nrow(field_kpi) > 0) {
           # Format KPIs as compact single line (no interpretations, just values)
           kpi_parts <- c(
-            sprintf("**CV:** %.2f", field_kpi$CV),
+            sprintf("**%s:** %.2f", t("cv_value"), field_kpi$CV),
-            sprintf("**Mean CI:** %.2f", field_kpi$Mean_CI)
+            sprintf("**%s:** %.2f", t("mean_ci"), field_kpi$Mean_CI)
           )
           
           # Add Weekly_CI_Change if available (note: capital C and I)
           if (!is.null(field_kpi$Weekly_CI_Change) && !is.na(field_kpi$Weekly_CI_Change)) {
             change_sign <- ifelse(field_kpi$Weekly_CI_Change >= 0, "+", "")
-            kpi_parts <- c(kpi_parts, sprintf("**Δ CI:** %s%.2f", change_sign, field_kpi$Weekly_CI_Change))
+            kpi_parts <- c(kpi_parts, sprintf("**Δ%s:** %s%.2f", t("CI"), change_sign, field_kpi$Weekly_CI_Change))
           }
           
           # Compact trend display with symbols
@@ -1474,17 +1475,17 @@ tryCatch({
             grepl("Strong decline|Severe", field_kpi$Trend_Interpretation, ignore.case = TRUE) ~ "↓↓",
             TRUE ~ field_kpi$Trend_Interpretation
           )
-          kpi_parts <- c(kpi_parts, sprintf("**Trend:** %s", trend_compact))
+          kpi_parts <- c(kpi_parts, sprintf("**%s:** %s", t("Trend"), trend_compact))
           
           if (!is.na(field_kpi$TCH_Forecasted) && field_kpi$TCH_Forecasted > 0) {
-            kpi_parts <- c(kpi_parts, sprintf("**Yield:** %.1f t/ha", field_kpi$TCH_Forecasted))
+            kpi_parts <- c(kpi_parts, sprintf("**%s:** %.1f t/ha", t("Yield"), field_kpi$TCH_Forecasted))
           }
           
           kpi_parts <- c(
             kpi_parts,
-            sprintf("**Gap:** %.0f", field_kpi$Gap_Score),
+            sprintf("**%s:** %.0f%%", t("Gaps"), field_kpi$Gap_Score),
-            sprintf("**Patchiness:** %s", field_kpi$Patchiness_Risk),
+            sprintf("**%s:** %s", t("Patchiness"), t(field_kpi$Patchiness_Risk)),
-            sprintf("**Decline:** %s", field_kpi$Decline_Severity)
+            sprintf("**%s:** %s", t("Decline"), t(field_kpi$Decline_Severity))
           )
           
           cat(paste(kpi_parts, collapse = " | "), "\n\n")  # Double newline for markdown paragraph break
@@ -1667,7 +1668,7 @@ img_path <- ifelse(file.exists(target_img), target_img, "CI_graph_example.png")
 ```
 
 <div align="center">
-![`r t("ci_caption")`](`r img_path`)
+![`r t("ci_caption")`](`r img_path`){width=4in}
 </div>
 
 `r t("sec_iii_1")`
@@ -1725,18 +1726,6 @@ img_path <- ifelse(file.exists(target_img), target_img, "CI_graph_example.png")
             - `r t("kpi_v_high")`
         - `r t("kpi_v_why")` 
      
-   - `r t("unif_v_patch")`
-     - `r t("unif")`
-     - `r t("patch")`
-     
-     
-      `r t("practical_example")`
-     
-     - `r t("field_a")`
-     - `r t("field_b")`
-     
-     `r t("scouting")`
-     
     - `r t("kpi_vi")`
         - `r t("kpi_vi_calc")`
             - `r t("kpi_vi_identify")`
@@ -1754,6 +1743,18 @@ img_path <- ifelse(file.exists(target_img), target_img, "CI_graph_example.png")
 
 `r t("hist_benchmark")`
 
+`r t("unif_v_patch")`
+
+- `r t("unif")`
+- `r t("patch")`
+
+`r t("practical_example")`
+
+- `r t("field_a")`
+- `r t("field_b")`
+
+`r t("scouting")`
+
 \newpage
 `r t("metadata")`