diff --git a/findex/_targets.R b/findex/_targets.R index 941e43a8eeaf3f746242f158dd0d1d443753ccf1..1bcbd29a720d5906cfd7962bcd952141dbda0a0c 100644 --- a/findex/_targets.R +++ b/findex/_targets.R @@ -34,6 +34,10 @@ p1 <- list( p1_hybas_legend_xlsx, "in/BasinATLAS_Data_v10.gdb/HydroATLAS_v10_Legends.xlsx", format = "file" + ), + tar_target( + p1_proj, + "ESRI:54030" ) ) @@ -89,23 +93,41 @@ p2 <- list( #sub_threat = subThreat_cat ) ), + + ## set up threat and sub-category threat lists for visualization dynamic branching + + tar_target( + p2_threat_categories, + p2_weights |> + pull(Threat_Category) |> + unique() + ), + tar_target( + p2_threat_subcategories, + p2_mean_weighted_subThreats |> + pull(ThreatCategory) |> + unique() + ), tar_target( p2_habitat_subthreats, - c("Dams", "Wetland drainage", "Deforestation and associated runoff", - "Riparian degradation", "Agricultural extraction", "Urban extraction", - "Industrial extraction") + p2_mean_weighted_subThreats |> + filter(MajorCat == "Habitat") |> + pull(ThreatCategory) |> + unique() ), tar_target( p2_pollution_subthreats, - c("Agricultural effluents", "Urban wastewater", - "Industrial effluents", "Aquaculture effluents", - "Pharmaceuticals", "Oil or gas exploration", - "Plastics", "Mining") + p2_mean_weighted_subThreats |> + filter(MajorCat == "Pollution") |> + pull(ThreatCategory) |> + unique() ), tar_target( p2_climate_subthreats, - c("Change in water temperature", "Drought", "Change in flooding", - "Change in wind patterns", "Change in ice cover") + p2_mean_weighted_subThreats |> + filter(MajorCat == "Climate and weather") |> + pull(ThreatCategory) |> + unique() ) ) @@ -118,105 +140,117 @@ p3 <- list( Invasive_pal = list(c("#4E6D6E", "#C9D8D9")), Climate_pal = list(c("#835192", "#DDCCE2")) #9D6AAC )), - #### major threat category maps #### - tar_map( - values = tibble::tibble(threat_cat = c("Habitat", "Exploitation", - "Invasive species", "Pollution", - "Climate and weather")), - tar_target( - # change all out file paths to the earth in flux directroy: src/assets/images - p3_threat_map, - threat_map(in_dat = p2_mean_weighted_threats, - threat_category = threat_cat, - threat_pal = p3_color_pal - ) - ), tar_target( p3_threat_map_png, { - final_plot <- p3_threat_map + + final_plot <- threat_map(in_dat = p2_mean_weighted_threats, + threat_category = p2_threat_categories, + threat_pal = p3_color_pal, + proj = p1_proj) + theme(legend.position = "none") - out_file <- paste0("../src/assets/images/", str_replace_all(threat_cat, " ", "_"), "_map.png") + out_file <- paste0("../src/assets/images/", str_replace_all(p2_threat_categories, " ", "_"), "_map.png") ggsave(out_file, final_plot, height = 6, width = 10, dpi = 300) }, - format = "file" + format = "file", + pattern = p2_threat_categories ), tar_target( p3_legend_png, { - plot_legend <- get_plot_component(p3_threat_map, "guide-box-right", return_all = T) + final_plot <- threat_map(in_dat = p2_mean_weighted_threats, + threat_category = p2_threat_categories, + threat_pal = p3_color_pal, + proj = p1_proj) - out_file <- paste0("../src/assets/images/", str_replace_all(threat_cat, " ", "_"), "_legend.png") + plot_legend <- get_plot_component(final_plot, "guide-box-right", return_all = T) + + out_file <- paste0("../src/assets/images/", str_replace_all(p2_threat_categories, " ", "_"), "_legend.png") ggsave(out_file, plot_legend, dpi = 300, bg = "transparent") knitr::plot_crop(out_file) - } - )), - #### subcategory threat maps #### - tar_map( - values = tibble::tibble(sub_threat_cat = c("Dams", "Wetland drainage", "Deforestation and associated runoff", - "Riparian degradation", "Agricultural effluents", "Agricultural extraction", - "Aquaculture effluents", "Industrial effluents", "Industrial extraction", - "Urban extraction", "Urban wastewater", "Overfishing", - "Invasive non-native species", "Change in water temperature", "Drought", - "Change in flooding", "Pharmaceuticals", "Plastics", - "Oil or gas exploration", "Mining", "Change in wind patterns", - "Change in ice cover")), - tar_target( - p3_sub_threat_map, - subThreat_map(in_dat = p2_mean_weighted_subThreats, - threat_category = sub_threat_cat, - threat_pal = p3_color_pal) + }, + pattern = p2_threat_categories ), - tar_target( + tar_target( # will turn this into a function p3_sub_threat_map_png, { - final_plot <- p3_sub_threat_map + + final_plot <- subThreat_map(in_dat = p2_mean_weighted_subThreats, + threat_category = p2_threat_subcategories, + subcat_habitat = p2_habitat_subthreats, + subcat_pollution = p2_pollution_subthreats, + subcat_climate = p2_climate_subthreats, + threat_pal = p3_color_pal, + proj = p1_proj) + theme(legend.position = "none") - if(sub_threat_cat %in% p2_habitat_subthreats){ - out_file <- paste0("../src/assets/images/H_", str_replace_all(sub_threat_cat, " ", "_"), "_map.png") - } else if(sub_threat_cat %in% p2_pollution_subthreats){ - out_file <- paste0("../src/assets/images/P_", str_replace_all(sub_threat_cat, " ", "_"), "_map.png") - } else if(sub_threat_cat == "Overfishing"){ - out_file <- paste0("../src/assets/images/E_", str_replace_all(sub_threat_cat, " ", "_"), "_map.png") - } else if(sub_threat_cat == "Invasive non-native species"){ - out_file <- paste0("../src/assets/images/IS_", str_replace_all(sub_threat_cat, " ", "_"), "_map.png") - } else if(sub_threat_cat %in% p2_climate_subthreats){ - out_file <- paste0("../src/assets/images/CW_", str_replace_all(sub_threat_cat, " ", "_"), "_map.png") + if(p2_threat_subcategories %in% p2_habitat_subthreats){ + out_file <- paste0("../src/assets/images/H_", str_replace_all(p2_threat_subcategories, " ", "_"), "_map.png") + } else if(p2_threat_subcategories %in% p2_pollution_subthreats){ + out_file <- paste0("../src/assets/images/P_", str_replace_all(p2_threat_subcategories, " ", "_"), "_map.png") + } else if(p2_threat_subcategories == "Overfishing"){ + out_file <- paste0("../src/assets/images/E_", str_replace_all(p2_threat_subcategories, " ", "_"), "_map.png") + } else if(p2_threat_subcategories == "Invasive non-native species"){ + out_file <- paste0("../src/assets/images/IS_", str_replace_all(p2_threat_subcategories, " ", "_"), "_map.png") + } else if(p2_threat_subcategories %in% p2_climate_subthreats){ + out_file <- paste0("../src/assets/images/CW_", str_replace_all(p2_threat_subcategories, " ", "_"), "_map.png") } ggsave(out_file, final_plot, height = 6, width = 10, dpi = 300) }, - format = "file" + format = "file", + pattern = p2_threat_subcategories ), - tar_target( + tar_target( # will turn this into a function p3_sub_threat_legend_png, { - plot_legend <- get_plot_component(p3_sub_threat_map, "guide-box-right", return_all = T) + final_plot <- subThreat_map(in_dat = p2_mean_weighted_subThreats, + threat_category = p2_threat_subcategories, + subcat_habitat = p2_habitat_subthreats, + subcat_pollution = p2_pollution_subthreats, + subcat_climate = p2_climate_subthreats, + threat_pal = p3_color_pal, + proj = p1_proj) - if(sub_threat_cat %in% p2_habitat_subthreats){ - out_file <- paste0("../src/assets/images/H_", str_replace_all(sub_threat_cat, " ", "_"), "_legend.png") - } else if(sub_threat_cat %in% p2_pollution_subthreats){ - out_file <- paste0("../src/assets/images/P_", str_replace_all(sub_threat_cat, " ", "_"), "_legend.png") - } else if(sub_threat_cat == "Overfishing"){ - out_file <- paste0("../src/assets/images/E_", str_replace_all(sub_threat_cat, " ", "_"), "_legend.png") - } else if(sub_threat_cat == "Invasive non-native species"){ - out_file <- paste0("../src/assets/images/IS_", str_replace_all(sub_threat_cat, " ", "_"), "_legend.png") - } else if(sub_threat_cat %in% p2_climate_subthreats){ - out_file <- paste0("../src/assets/images/CW_", str_replace_all(sub_threat_cat, " ", "_"), "_legend.png") + plot_legend <- get_plot_component(final_plot, "guide-box-right", return_all = T) + + if(p2_threat_subcategories %in% p2_habitat_subthreats){ + out_file <- paste0("out/H_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend_raw.png") + } else if(p2_threat_subcategories %in% p2_pollution_subthreats){ + out_file <- paste0("out/P_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend_raw.png") + } else if(p2_threat_subcategories == "Overfishing"){ + out_file <- paste0("out/E_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend_raw.png") + } else if(p2_threat_subcategories == "Invasive non-native species"){ + out_file <- paste0("out/IS_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend_raw.png") + } else if(p2_threat_subcategories %in% p2_climate_subthreats){ + out_file <- paste0("out/CW_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend_raw.png") } ggsave(out_file, plot_legend, dpi = 300, bg = "transparent") knitr::plot_crop(out_file) - } - )) + + if(p2_threat_subcategories %in% p2_habitat_subthreats){ + out_file_final <- paste0("../src/assets/images/H_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend.png") + } else if(p2_threat_subcategories %in% p2_pollution_subthreats){ + out_file_final <- paste0("../src/assets/images/P_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend.png") + } else if(p2_threat_subcategories == "Overfishing"){ + out_file_final <- paste0("../src/assets/images/E_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend.png") + } else if(p2_threat_subcategories == "Invasive non-native species"){ + out_file_final <- paste0("../src/assets/images/IS_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend.png") + } else if(p2_threat_subcategories %in% p2_climate_subthreats){ + out_file_final <- paste0("../src/assets/images/CW_", str_replace_all(p2_threat_subcategories, " ", "_"), "_legend.png") + } + + cowplot_legend(in_dat = p2_mean_weighted_subThreats, legend_png = out_file, threat_category = p2_threat_subcategories, out_file = out_file_final) + }, + format = "file", + pattern = p2_threat_subcategories + ) ) diff --git a/findex/src/data_utils.R b/findex/src/data_utils.R index 14d0419f8fb9887a8981fd1ec9e587af5b0dd621..2c47c826b34c64238024c7a0e74ad73a07514798 100644 --- a/findex/src/data_utils.R +++ b/findex/src/data_utils.R @@ -74,6 +74,7 @@ compute_mean_weighted_subThreats <- function(threat_data, threat_weights, mutate(MeanWeightedThreatMetric = mean(weightedThreatMetric, na.rm = TRUE)) |> ungroup() |> select(HYBAS_ID, ThreatCategory, Threat, MeanWeightedThreatMetric, Shape) |> + rename(MajorCat = ThreatCategory, ThreatCategory = Threat) |> unique() |> arrange(desc(MeanWeightedThreatMetric)) } diff --git a/findex/src/plot_utils.R b/findex/src/plot_utils.R index 33d70a4c84c566ed5acd5fda0270f240e8f84540..b5ed06e0ae17f148a05afab6fa43d7071340b805 100644 --- a/findex/src/plot_utils.R +++ b/findex/src/plot_utils.R @@ -1,11 +1,11 @@ -threat_map <- function(in_dat, threat_category, threat_pal){ +threat_map <- function(in_dat, threat_category, threat_pal, proj){ filtered_df <- st_as_sf(in_dat) |> dplyr::filter(ThreatCategory == threat_category) |> # remove visual bug with robinson projection st_wrap_dateline() -proj_df <- st_transform(filtered_df, crs = st_crs("ESRI:54030")) +proj_df <- st_transform(filtered_df, crs = st_crs(proj)) if(threat_category == "Habitat"){ pal <- threat_pal$Habitat_pal @@ -43,37 +43,33 @@ threat_map <- ggplot()+ theme_void()+ theme( #legend.position = c(0.1, 0.21), - legend.ticks = element_blank() + legend.ticks = element_blank(), + legend.title = element_text(face = "bold"), + legend.text = element_text(size = 11) ) return(threat_map) } -subThreat_map <- function(in_dat, threat_category, threat_pal){ +subThreat_map <- function(in_dat, threat_category, threat_pal, subcat_habitat, subcat_pollution, subcat_climate, proj){ filtered_df <- st_as_sf(in_dat) |> - dplyr::filter(Threat == threat_category) |> + dplyr::filter(ThreatCategory == threat_category) |> # remove visual bug with robinson projection st_wrap_dateline() - proj_df <- st_transform(filtered_df, crs = st_crs("ESRI:54030")) + proj_df <- st_transform(filtered_df, crs = st_crs(proj)) - if(threat_category %in% c("Dams", "Wetland drainage", "Deforestation and associated runoff", - "Riparian degradation", "Agricultural extraction", "Urban extraction", - "Industrial extraction")){ + if(threat_category %in% subcat_habitat){ pal <- threat_pal$Habitat_pal - } else if(threat_category %in% c("Agricultural effluents", "Urban wastewater", - "Industrial effluents", "Aquaculture effluents", - "Pharmaceuticals", "Oil or gas exploration", - "Plastics", "Mining")){ + } else if(threat_category %in% subcat_pollution){ pal <- threat_pal$Pollution_pal } else if(threat_category == "Overfishing"){ pal <- threat_pal$Exploitation_pal } else if(threat_category == "Invasive non-native species"){ pal <- threat_pal$Invasive_pal - } else if(threat_category %in% c("Change in water temperature", "Drought", "Change in flooding", - "Change in wind patterns", "Change in ice cover")){ + } else if(threat_category %in% subcat_climate){ pal <- threat_pal$Climate_pal } @@ -101,9 +97,73 @@ subThreat_map <- function(in_dat, threat_category, threat_pal){ theme_void()+ theme( #legend.position = c(0.1, 0.21), - legend.ticks = element_blank() + legend.ticks = element_blank(), + legend.title = element_text(face = "bold"), + legend.text = element_text(size = 11) ) return(threat_map) +} +# in_dat = p2_mean_weighted_threats, legend_png = p3_legend_png, threat_category = threat_cat +## note about out_file - need to find a way to save the cowplot version of the legend without crowding the images folder +## maybe by saving the initial legend png in the findex out folder and then saving +## the cowplot version to the earth-in-flux parent directory "src/assets/images/" folder +cowplot_legend <- function(in_dat, legend_png, threat_category, out_file){ + + threat_df <- in_dat |> + filter(ThreatCategory == threat_category) + + min_val <- min(threat_df$MeanWeightedThreatMetric, na.rm = T) + max_val <- max(threat_df$MeanWeightedThreatMetric, na.rm = T) + + # Define colors + background_color = NA + font_color = "#ffffff" + + # The background canvas for your viz (DO NOT EDIT) + canvas <- grid::rectGrob( + x = 0, y = 0, + width = 9, height = 9, + gp = grid::gpar(fill = background_color, alpha = 1, col = background_color) + ) + + # margin for plotting (DO NOT EDIT) + margin = 0.04 + + # Load in USGS logo (also a black logo available) + legend <- magick::image_read(legend_png) + + final_legend <- ggdraw(ylim = c(0,1), # 0-1 scale makes it easy to place viz items on canvas + xlim = c(0,1)) + + # a background (DO NOT EDIT) + draw_grob(canvas, + x = 0, y = 1, + height = 9, width = 16, + hjust = 0, vjust = 1) + + draw_image(legend, + x = 0.08, + y = 0.08, + width = 0.77, + hjust = 0, vjust = 0, + halign = 0, valign = 0)+ + # min max values + draw_label(as.character(min_val), + x = 0.02, + y = 0.54, + hjust = 0, + vjust = 1, + lineheight = 0.75, + color = "gray50", + size = 9) + + draw_label(as.character(max_val), + x = 1, + y = 0.54, + hjust = 1, + vjust = 1, + lineheight = 0.75, + color = "gray50", + size = 9) + #429x176 + ggsave(out_file, final_legend, height = 176, width = 429, units = "px", dpi = 300, bg = "transparent") } \ No newline at end of file diff --git a/src/assets/images/CW_Change_in_flooding_legend.png b/src/assets/images/CW_Change_in_flooding_legend.png index c13515bf55399414ea82fdd186adf9c4e8770621..760b51b4f1b8422022f2ae03f6ea06af3a1dc58d 100644 Binary files a/src/assets/images/CW_Change_in_flooding_legend.png and b/src/assets/images/CW_Change_in_flooding_legend.png differ diff --git a/src/assets/images/CW_Change_in_ice_cover_legend.png b/src/assets/images/CW_Change_in_ice_cover_legend.png index 8d601db741a93322fa3002a13326508a4b4037c8..50869416f69ff773f223c69e11e0dc5fa597f8fd 100644 Binary files a/src/assets/images/CW_Change_in_ice_cover_legend.png and b/src/assets/images/CW_Change_in_ice_cover_legend.png differ diff --git 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