version avant dernière révision

R/correlation.R

@@ -0,0 +1,55 @@
+#' Title
+#' 
+#' Description
+#'
+#' @param
+#'
+#' @return
+
+env_occ_corr <- function(species) {
+
+  # Species occurrences
+  sp_occ <- terra::vect(sprintf("data/data-biotic/%s.gpkg", species))
+
+  # Import all environmental variables
+  env_files <- list.files("data/data-abiotic/")
+  env <- lapply(env_files, function(x) {
+    terra::rast(sprintf("data/data-abiotic/%s", x))
+  })
+  env <- terra::rast(env)
+
+  # Extract values of nv for every points
+  vals_extract <- terra::extract(env, 
+                                 sp_occ,
+                                 ID = FALSE)
+
+  # Bind values extracted with presence/absence data
+  dat <- cbind(sp_occ[,"presence"], vals_extract)
+  dat <- dat[,-c(16)] # Temporary
+
+  # Calculate correlation between presence and every environmental variable
+  correlations <- sapply(names(dat[,2:ncol(dat)]), function(x) {
+    tmp <- as.data.frame(dat[,c("presence",x)])
+    tmp <- tmp[complete.cases(tmp),]
+    cor(tmp[,1],
+        tmp[,2],
+        method = "pearson")
+  })
+
+  return(sort(correlations))
+}
+
+dat <- as.data.frame(dat)
+dat <- dat[complete.cases(dat),]
+coco <- prcomp(dat[,-1], scale = TRUE)
+g <- ggbiplot(coco,
+              obs.scale = 1,
+              var.scale = 1,
+              groups = dat[,"presence"],
+              ellipse = TRUE,
+              circle = TRUE,
+              ellipse.prob = 0.68)
+
+env <- rownames(coco$rotation[coco$rotation[,1]*coco$rotation[,2] < 0,])
+vif(dat[,env])
+env <- env[-which(env == "")];vif(dat[,env])

R/fig_abiotic.R

@@ -12,44 +12,20 @@
   # Get global parameters
   global_param()
 
-  env <- c("arag",
-           "bathy",
-           "slope",
-           "sat",
-           "bottom_chlorophyll_mean",
-           "bottom_current_velocity_max",
-           "bottom_dissolved_oxygen_mean",
-           "bottom_dissolved_oxygen_range",
-           "bottom_iron_mean",
-           "bottom_nitrate_mean",
-           "bottom_phosphate_mean",
-           "bottom_phytoplankton_mean",
-           "bottom_salinity_mean",
-           "bottom_salinity_range",
-           "bottom_silicate_mean",
-           "bottom_temperature_mean",
-           "bottom_temperature_range",
-           "mean_salinity",
-           "mean_temperature",
-           "sat")
-
+  env <- list.files("data/data-abiotic/", pattern = ".tif$") |>
+           gsub(pattern = ".tif",
+                replacement = "",
+                x = _)
 
   #---------- Plot every abiotic data ----------#
 
   lapply(env, function(x) {
 
-    # Species name with first capital letter and space instead of underscore
-    if(x %in% c("mean_salinity", "mean_temperature")) {
-      dat <- terra::rast(sapply(2011:2020, function(i) {
-        terra::rast(paste0("data/data-abiotic/",x,"_", i, ".tif"))
-      })) |>
-        terra::app(x = _, fun = mean, na.rm = TRUE)
-    } else {
-      dat <- terra::rast(paste0("data/data-abiotic/",x,".tif"))
-    }
+    # Load data
+    dat <- terra::rast(sprintf("data/data-abiotic/%s.tif", x))
 
     # Define filename of the figures
-    filename <- paste0("figures/env_", x, ".png")
+    filename <- sprintf("figures/env_%s.png", x)
 
     # Save figure in .png
     png(filename, 
@@ -68,8 +44,15 @@
 
     # Plot data
     terra::plot(dat,
-                add = TRUE)
-
+                add = TRUE,
+                col = "#6699CC")
+    legend("bottomright",
+           "Zones de concentration significative\nde plumes de mer",
+           col = "#6699CC",
+           bty = "n",
+           pch = 16,
+           cex = 0.8,
+           pt.cex = 1.3)
     plot(sf::st_geometry(aoi),
          add = TRUE)
     # Cities

R/get_basemap.R

@@ -98,8 +98,6 @@ get_basemap <- function() {
     c("Blanc-Sablon", 51.426883, -57.132590+.04, 0, -1.4, 0.14),
     c("Gaspé", 48.831567, -64.487300+.04, 0, -0.8, -0.08),
     c("Caraquet", 47.777730, -64.953491+.04, 0, -1, -0.25),
-    c("La Pocatière", 47.368856, -70.023220+.04, 0, 0.1, -0.1),
-    c("Tadoussac", 48.154946+.04, -69.725426+.02,.0, -1.2, -0.08),
     c("Rimouski", 48.444147-.03, -68.545120+.05, 0, 0.1, -0.1),
     c("Matane", 48.847708-.04, -67.527839+.03, 0, 0.1, -0.1),
     c("Channel-Port-Aux-Basques", 47.579661, -59.149330, 0, 0.1, 0.12)