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Commit 18dc9562 authored by Vaarre-Lamoureux, Kaysa S's avatar Vaarre-Lamoureux, Kaysa S
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create legend and map save functions

parent 3d4364bf
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1 merge request!86Findex global maps
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findex/_targets.R
+ 29
− 66
View file @ 18dc9562
......@@ -145,21 +145,23 @@ p3 <- list(
p3_threat_map_png,
{
final_plot <- threat_map(in_dat = p2_mean_weighted_threats,
threat_category = p2_threat_categories,
threat_pal = p3_color_pal,
hybas_habitat_types = p2_hybas_habitat_types_sf,
proj = p1_proj) +
threat_category = p2_threat_categories,
threat_pal = p3_color_pal,
hybas_habitat_types = p2_hybas_habitat_types_sf,
proj = p1_proj) +
theme(legend.position = "none")
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)
save_map(type = "threat", plot = final_plot,
threat_category = p2_threat_categories,
subcat_habitat = NA,
subcat_pollution = NA,
subcat_climate = NA
)
},
format = "file",
pattern = p2_threat_categories
),
tar_target(
tar_target( # will turn this into a function
p3_legend_png,
{
final_plot <- threat_map(in_dat = p2_mean_weighted_threats,
......@@ -168,21 +170,16 @@ p3 <- list(
proj = p1_proj,
hybas_habitat_types = p2_hybas_habitat_types_sf)
plot_legend <- get_plot_component(final_plot, "guide-box-right", return_all = T)
out_file <- paste0("out/", str_replace_all(p2_threat_categories, " ", "_"), "_legend_raw.png")
ggsave(out_file,
plot_legend, dpi = 300, bg = "transparent")
knitr::plot_crop(out_file)
out_file_final <- paste0("../src/assets/images/", str_replace_all(p2_threat_categories, " ", "_"), "_legend.png")
cowplot_legend(in_dat = p2_mean_weighted_threats, legend_png = out_file, threat_category = p2_threat_categories, out_file = out_file_final)
save_legend(type = "threat", plot = final_plot,
threat_category = p2_threat_categories,
subcat_habitat = NA,
subcat_pollution = NA,
subcat_climate = NA,
in_dat = p2_mean_weighted_threats)
},
pattern = p2_threat_categories
),
tar_target( # will turn this into a function
tar_target(
p3_sub_threat_map_png,
{
final_plot <- subThreat_map(in_dat = p2_mean_weighted_subThreats,
......@@ -195,20 +192,11 @@ p3 <- list(
hybas_habitat_types = p2_hybas_habitat_types_sf) +
theme(legend.position = "none")
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)
save_map(type = "threat", plot = final_plot,
threat_category = p2_threat_subcategories,
subcat_habitat = p2_habitat_subthreats,
subcat_pollution = p2_pollution_subthreats,
subcat_climate = p2_climate_subthreats)
},
format = "file",
pattern = p2_threat_subcategories
......@@ -225,37 +213,12 @@ p3 <- list(
proj = p1_proj,
hybas_habitat_types = p2_hybas_habitat_types_sf)
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)
save_legend(type = "subThreat", plot = final_plot,
threat_category = p2_threat_subcategories,
subcat_habitat = p2_habitat_subthreats,
subcat_pollution = p2_pollution_subthreats,
subcat_climate = p2_climate_subthreats,
in_dat = p2_mean_weighted_subThreats)
},
format = "file",
pattern = p2_threat_subcategories
......
findex/src/plot_utils.R
+ 136
− 77
View file @ 18dc9562
threat_map <- function(in_dat, threat_category, threat_pal, hybas_habitat_types, proj){
# hybas_habitat_types = p2_hybas_habitat_types_sf
filtered_df <- in_dat |>
left_join(hybas_habitat_types) |>
st_as_sf() |>
dplyr::filter(ThreatCategory == threat_category) |>
# remove visual bug with robinson projection
st_wrap_dateline()
proj_df <- st_transform(filtered_df, crs = st_crs(proj))
if(threat_category == "Habitat"){
pal <- threat_pal$Habitat_pal
} else if(threat_category == "Pollution"){
pal <- threat_pal$Pollution_pal
} else if(threat_category == "Exploitation"){
pal <- threat_pal$Exploitation_pal
} else if(threat_category == "Invasive species"){
pal <- threat_pal$Invasive_pal
} else if(threat_category == "Climate and weather"){
pal <- threat_pal$Climate_pal
}
threat_map <- ggplot()+
geom_sf(data = proj_df, aes(geometry = Shape, fill = MeanWeightedThreatMetric, color = MeanWeightedThreatMetric))+
scale_fill_gradientn(
colors = colorRampPalette(c(rev(unlist(pal))))(100),
limits = c(0, max(proj_df$MeanWeightedThreatMetric, na.rm = T)),
na.value = "gray80",
breaks = c(0 + max(proj_df$MeanWeightedThreatMetric, na.rm = T)/10,
#max(habitat_data$MeanWeightedThreatMetric)/2,
max(proj_df$MeanWeightedThreatMetric, na.rm = T) - max(proj_df$MeanWeightedThreatMetric, na.rm = T)/10),
labels = c("Lower", "Higher")
)+
scale_color_gradientn(
colors = colorRampPalette(c(rev(unlist(pal))))(100),
na.value= "gray80"
)+
guides(color = "none")+
guides(fill = guide_colorbar(title = "Mean Threat",
title.position = "top",
direction = "horizontal",
barwidth = 7,
barheight = 1))+
theme_void()+
theme(
#legend.position = c(0.1, 0.21),
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, subcat_habitat, subcat_pollution, subcat_climate, proj, hybas_habitat_types){
general_threat_map <- function(in_dat, threat_category, threat_pal, hybas_habitat_types, proj){
filtered_df <- in_dat |>
left_join(hybas_habitat_types) |>
st_as_sf() |>
......@@ -65,22 +8,10 @@ subThreat_map <- function(in_dat, threat_category, threat_pal, subcat_habitat, s
proj_df <- st_transform(filtered_df, crs = st_crs(proj))
if(threat_category %in% subcat_habitat){
pal <- threat_pal$Habitat_pal
} else if(threat_category %in% subcat_pollution){
pal <- threat_pal$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% subcat_climate){
pal <- threat_pal$Climate_pal
}
threat_map <- ggplot()+
geom_sf(data = proj_df, aes(geometry = Shape, fill = MeanWeightedThreatMetric, color = MeanWeightedThreatMetric))+
scale_fill_gradientn(
colors = colorRampPalette(c(rev(unlist(pal))))(100),
colors = colorRampPalette(c(rev(unlist(threat_pal))))(100),
limits = c(0, max(proj_df$MeanWeightedThreatMetric, na.rm = T)),
na.value = "gray80",
breaks = c(0 + max(proj_df$MeanWeightedThreatMetric, na.rm = T)/10,
......@@ -89,7 +20,7 @@ subThreat_map <- function(in_dat, threat_category, threat_pal, subcat_habitat, s
labels = c("Lower", "Higher")
)+
scale_color_gradientn(
colors = colorRampPalette(c(rev(unlist(pal))))(100),
colors = colorRampPalette(c(rev(unlist(threat_pal))))(100),
na.value= "gray80"
)+
guides(color = "none")+
......@@ -107,12 +38,53 @@ subThreat_map <- function(in_dat, threat_category, threat_pal, subcat_habitat, s
)
return(threat_map)
}
threat_map <- function(in_dat, threat_category, threat_pal, hybas_habitat_types, proj){
if(threat_category == "Habitat"){
pal <- threat_pal$Habitat_pal
} else if(threat_category == "Pollution"){
pal <- threat_pal$Pollution_pal
} else if(threat_category == "Exploitation"){
pal <- threat_pal$Exploitation_pal
} else if(threat_category == "Invasive species"){
pal <- threat_pal$Invasive_pal
} else if(threat_category == "Climate and weather"){
pal <- threat_pal$Climate_pal
}
final_plot <- general_threat_map(in_dat = in_dat,
threat_category = threat_category,
threat_pal = pal,
hybas_habitat_types = hybas_habitat_types,
proj = proj)
}
# 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
subThreat_map <- function(in_dat, threat_category, threat_pal, subcat_habitat, subcat_pollution, subcat_climate, proj, hybas_habitat_types){
# establish palette
if(threat_category %in% subcat_habitat){
pal <- threat_pal$Habitat_pal
} else if(threat_category %in% subcat_pollution){
pal <- threat_pal$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% subcat_climate){
pal <- threat_pal$Climate_pal
}
final_plot <- general_threat_map(in_dat = in_dat,
threat_category = threat_category,
threat_pal = pal,
hybas_habitat_types = hybas_habitat_types,
proj = proj)
}
cowplot_legend <- function(in_dat, legend_png, threat_category, out_file){
threat_df <- in_dat |>
......@@ -170,4 +142,91 @@ cowplot_legend <- function(in_dat, legend_png, threat_category, out_file){
size = 9)
#429x176
ggsave(out_file, final_legend, height = 176, width = 429, units = "px", dpi = 300, bg = "transparent")
}
\ No newline at end of file
}
# plot = final_plot, in_dat = p2_mean_weighted_threats
save_legend <- function(type, plot, threat_category, subcat_habitat, subcat_pollution, subcat_climate, in_dat){
if(type == "threat"){
plot_legend <- get_plot_component(plot, "guide-box-right", return_all = T)
out_file <- paste0("out/", str_replace_all(threat_category, " ", "_"), "_legend_raw.png")
ggsave(out_file,
plot_legend, dpi = 300, bg = "transparent")
knitr::plot_crop(out_file)
out_file_final <- paste0("../src/assets/images/", str_replace_all(threat_category, " ", "_"), "_legend.png")
cowplot_legend(in_dat = in_dat, legend_png = out_file, threat_category = threat_category, out_file = out_file_final)
return(out_file_final)
} else if(type == "subThreat"){
plot_legend <- get_plot_component(plot, "guide-box-right", return_all = T)
if(threat_category %in% subcat_habitat){
out_file <- paste0("out/H_", str_replace_all(threat_category, " ", "_"), "_legend_raw.png")
} else if(threat_category %in% subcat_pollution){
out_file <- paste0("out/P_", str_replace_all(threat_category, " ", "_"), "_legend_raw.png")
} else if(threat_category == "Overfishing"){
out_file <- paste0("out/E_", str_replace_all(threat_category, " ", "_"), "_legend_raw.png")
} else if(threat_category == "Invasive non-native species"){
out_file <- paste0("out/IS_", str_replace_all(threat_category, " ", "_"), "_legend_raw.png")
} else if(threat_category %in% subcat_climate){
out_file <- paste0("out/CW_", str_replace_all(threat_category, " ", "_"), "_legend_raw.png")
}
ggsave(out_file,
plot_legend, dpi = 300, bg = "transparent")
knitr::plot_crop(out_file)
if(threat_category %in% subcat_habitat){
out_file_final <- paste0("../src/assets/images/H_", str_replace_all(threat_category, " ", "_"), "_legend.png")
} else if(threat_category %in% subcat_pollution){
out_file_final <- paste0("../src/assets/images/P_", str_replace_all(threat_category, " ", "_"), "_legend.png")
} else if(threat_category == "Overfishing"){
out_file_final <- paste0("../src/assets/images/E_", str_replace_all(threat_category, " ", "_"), "_legend.png")
} else if(threat_category == "Invasive non-native species"){
out_file_final <- paste0("../src/assets/images/IS_", str_replace_all(threat_category, " ", "_"), "_legend.png")
} else if(threat_category %in% subcat_climate){
out_file_final <- paste0("../src/assets/images/CW_", str_replace_all(threat_category, " ", "_"), "_legend.png")
}
cowplot_legend(in_dat = in_dat, legend_png = out_file, threat_category = threat_category, out_file = out_file_final)
return(out_file_final)
}
}
save_map <- function(type, plot, threat_category, subcat_habitat, subcat_pollution, subcat_climate){
if(type == "threat"){
out_file <- paste0("../src/assets/images/", str_replace_all(threat_category, " ", "_"), "_map.png")
ggsave(out_file,
plot, height = 6, width = 10, dpi = 300)
} else if(type == "subThreat"){
if(threat_category %in% subcat_habitat){
out_file <- paste0("../src/assets/images/H_", str_replace_all(threat_category, " ", "_"), "_map.png")
} else if(threat_category %in% subcat_pollution){
out_file <- paste0("../src/assets/images/P_", str_replace_all(threat_category, " ", "_"), "_map.png")
} else if(threat_category == "Overfishing"){
out_file <- paste0("../src/assets/images/E_", str_replace_all(threat_category, " ", "_"), "_map.png")
} else if(threat_category == "Invasive non-native species"){
out_file <- paste0("../src/assets/images/IS_", str_replace_all(threat_category, " ", "_"), "_map.png")
} else if(threat_category %in% subcat_climate){
out_file <- paste0("../src/assets/images/CW_", str_replace_all(threat_category, " ", "_"), "_map.png")
}
ggsave(out_file,
plot, height = 6, width = 10, dpi = 300)
}
}
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