Update Diagnostic to include monthly hdcd plot for all years compare …

…to NOAA latest year

R/diagnostics.R

@@ -49,6 +49,20 @@ diagnostics <- function(hdcd = tibble::tibble(),
       dplyr::mutate(heatcool = dplyr::if_else(value < 0, "heat","cool"),
                     value = abs(value))
 
+    hdcd_comb_year_range <- paste(min(unique(hdcd_comb_diagnostics$year)),
+                                  max(unique(hdcd_comb_diagnostics$year)),
+                                  sep = '-')
+
+    filename_diagnostics <-
+      paste0(folder_diagnostics, "/", basename(gsub(".csv", "", filename)), "_",
+             hdcd_comb_year_range, name_append, '.csv')
+
+    # save plot data for segment diagnostic
+    data.table::fwrite(x = hdcd_comb_diagnostics,
+                       file = filename_diagnostics)
+
+    print(paste0("Diagnostic table saved as ", filename_diagnostics))
+
     segment_levels = c("Jan_day","Jan_night","Feb_day","Feb_night",
                        "Mar_day","Mar_night","Apr_day","Apr_night",
                        "May_day","May_night","Jun_day","Jun_night",
@@ -58,9 +72,11 @@ diagnostics <- function(hdcd = tibble::tibble(),
 
     # Individual Years
     for(year_i in (hdcd_comb_diagnostics$year) %>% unique()) {
-      ggplot2::ggplot(data = hdcd_comb_diagnostics %>%
-                        dplyr::filter(year == year_i) %>%
-                        dplyr::mutate(segment = factor(segment, levels = segment_levels))) +
+      data_plot <- hdcd_comb_diagnostics %>%
+        dplyr::filter(year == year_i) %>%
+        dplyr::mutate(segment = factor(segment, levels = segment_levels))
+
+      ggplot2::ggplot(data = data_plot) +
         ggplot2::aes(x = segment, y = value, group = heatcool) +
         ggplot2::geom_line(ggplot2::aes(color = heatcool)) +
         ggplot2::facet_wrap(subRegion ~ ., scales = "free_y") +
@@ -73,19 +89,22 @@ diagnostics <- function(hdcd = tibble::tibble(),
                                                            vjust = 0.5))
 
         filename_diagnostics_i <-
-          paste0(folder_diagnostics, "/", basename(gsub(".csv", "", filename)), "_", year_i,name_append,".png")
+          paste0(folder_diagnostics, "/", basename(gsub(".csv", "", filename)), "_", year_i,name_append, '.png')
 
-        ggplot2::ggsave(filename =  filename_diagnostics_i,
+        # save plot
+        ggplot2::ggsave(filename = filename_diagnostics_i,
                         width = 25,
-                        height = 15) # save plot
+                        height = 15)
 
         print(paste0("Diagnostic figure saved as ", filename_diagnostics_i))
     }
 
     # Combined years free scale
     if(T) {
-      ggplot2::ggplot(data = hdcd_comb_diagnostics %>%
-                        dplyr::mutate(segment = factor(segment, levels = segment_levels))) +
+      data_plot <- hdcd_comb_diagnostics %>%
+        dplyr::mutate(segment = factor(segment, levels = segment_levels))
+
+      ggplot2::ggplot(data = data_plot) +
         ggplot2::aes(x = segment, y = value,
                      group = interaction(year, heatcool),
                      color = interaction(heatcool)) +
@@ -102,19 +121,22 @@ diagnostics <- function(hdcd = tibble::tibble(),
                        legend.position = 'right')
 
       filename_diagnostics_i <-
-        paste0(folder_diagnostics, "/", basename(gsub(".csv", "", filename)), "_allYears_freeScale",name_append,".png")
+        paste0(folder_diagnostics, "/", basename(gsub(".csv", "", filename)), "_allYears_freeScale", name_append, '.png')
 
-      ggplot2::ggsave(filename =  filename_diagnostics_i,
+      # save plot
+      ggplot2::ggsave(filename = filename_diagnostics_i,
                       width = 25,
-                      height = 15) # save plot
+                      height = 15)
 
       print(paste0("Diagnostic figure saved as ", filename_diagnostics_i))
     }
 
     # Combined years fixed scale
     if(T) {
-      ggplot2::ggplot(data = hdcd_comb_diagnostics %>%
-                        dplyr::mutate(segment = factor(segment, levels = segment_levels))) +
+      data_plot <- hdcd_comb_diagnostics %>%
+        dplyr::mutate(segment = factor(segment, levels = segment_levels))
+
+      ggplot2::ggplot(data = data_plot) +
         ggplot2::aes(x = segment, y = value,
                      group = interaction(year, heatcool),
                      color = interaction(heatcool)) +
@@ -182,8 +204,18 @@ diagnostics <- function(hdcd = tibble::tibble(),
     current_years <- as.integer(unique(hdcd_monthly$year))
     noaa_years <- as.integer(unique(helios::noaa_hddcdd$year))
 
+    filename_monthly_diagnostics <-
+      paste0(folder_diagnostics,
+             "/monthly_ncdf_", min(current_years), '-', max(current_years),
+             "_noaa_", min(noaa_years), '-', max(noaa_years), name_append,".csv")
+
+    # save plot data for monthly diagnostic
+    data.table::fwrite(x = hdcd_comb_monthly_diagnostics,
+                       file = filename_monthly_diagnostics)
+    print(paste0("Diagnostic table saved as ", filename_monthly_diagnostics))
+
     # Individual Years
-    for(year_i in current_years) {
+    for(year_i in intersect(current_years, noaa_years)) {
 
       noaa_year_i <- noaa_years[which(abs(noaa_years - year_i) == min(abs(noaa_years - year_i)))]
 
@@ -231,6 +263,51 @@ diagnostics <- function(hdcd = tibble::tibble(),
       print(paste0("Diagnostic figure saved as ", filename_monthly_diagnostics_i))
     }
 
+    # All Years Together
+    noaa_year_latest <- noaa_years[length(noaa_years)]
+
+    noaa_latest <- hdcd_comb_monthly_diagnostics %>%
+      dplyr::filter((year == noaa_year_latest & scenario == "noaa") &
+                      (!subRegion %in% c('AK', 'HI'))) %>%
+      dplyr::rename(noaa = value) %>%
+      dplyr::select(subRegion, month, HDDCDD, noaa)
+
+    hdcd_comb_monthly_diagnostics_all <- hdcd_comb_monthly_diagnostics %>%
+      dplyr::filter(scenario == "ncdf" &
+                      (!subRegion %in% c('AK', 'HI'))) %>%
+      dplyr::left_join(noaa_latest, by = c('subRegion', 'month', 'HDDCDD')) %>%
+      dplyr::mutate(noaa = dplyr::if_else(is.na(noaa), 0, noaa)) %>%
+      dplyr::select(subRegion, scenario, year, month, HDDCDD, value, noaa)
+
+    n_color <- length(unique(hdcd_comb_monthly_diagnostics_all$year))
+    pal_hd <- colorRampPalette(RColorBrewer::brewer.pal(9, 'YlOrRd'))
+    pal_cd <-  colorRampPalette(RColorBrewer::brewer.pal(9, 'YlGnBu'))
+    pal <- c(rev(pal_hd(n_color)), rev(pal_cd(n_color)))
+
+    filename_monthly_diagnostics_all <-
+      paste0(folder_diagnostics, "/monthly_ncdf_AllYears", "_noaa_",noaa_year_latest, name_append,".png")
+
+    ggplot2::ggplot(data = hdcd_comb_monthly_diagnostics_all) +
+      ggplot2::geom_line(ggplot2::aes(x = month, y = value,
+                                      group = interaction(scenario, year, HDDCDD),
+                                      color = interaction(year, HDDCDD))) +
+      ggplot2::geom_line(ggplot2::aes(x = month, y = noaa, group = HDDCDD),
+                         color = 'black', size = 1.2, linetype = 'dashed') +
+      ggplot2::facet_wrap(subRegion ~ ., scales = "free_y") +
+      ggplot2::ggtitle(paste0("NCDF (all years) VS", " NOAA (", noaa_year_latest, ')')) +
+      ggplot2::ylab('Monthly Degree-Hours') +
+      ggplot2::scale_color_manual(values = pal,
+                                  guide = ggplot2::guide_legend(title = 'NCDF (All Years)')) +
+      ggplot2::scale_x_discrete(drop = FALSE) +
+      ggplot2::theme_bw() +
+      ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90,
+                                                         vjust = 0.5))
+
+    ggplot2::ggsave(filename = filename_monthly_diagnostics_all,
+                    width = 25,
+                    height = 15)
+    print(paste0("Diagnostic figure saved as ", filename_monthly_diagnostics_all))
+
     }
 
     #...............