Mercurial > repos > ecology > ecoregion_brt_analysis
comparison GeoNN.R @ 2:f8962f1c832a draft
planemo upload for repository https://github.com/galaxyecology/tools-ecology/tree/master/tools/Ecoregionalization_workflow commit 5d48df67919fbc9d77b98a8243d438c397f61a0e
author | ecology |
---|---|
date | Thu, 21 Mar 2024 14:04:25 +0000 |
parents | |
children |
comparison
equal
deleted
inserted
replaced
1:fc621f3f8226 | 2:f8962f1c832a |
---|---|
1 #Date : 09/02/2024 | |
2 #Author : Seguineau Pauline | |
3 | |
4 #Load libraries | |
5 library(tidyr) | |
6 library(dplyr) | |
7 library(sf) | |
8 | |
9 #load arguments | |
10 args = commandArgs(trailingOnly=TRUE) | |
11 if (length(args)==0) | |
12 { | |
13 stop("This tool needs at least one argument") | |
14 }else{ | |
15 enviro <- args[1] | |
16 envlong <- as.numeric(args[2]) | |
17 envlat <- as.numeric(args[3]) | |
18 occu <- args[4] | |
19 occulat <- as.numeric(args[5]) | |
20 occulong <- as.numeric(args[6]) | |
21 } | |
22 | |
23 env = read.table(enviro, header = TRUE, sep="\t") | |
24 occ = read.table(occu, header = TRUE, sep = "\t") | |
25 | |
26 cols_env = c(names(env[envlong]),names(env[envlat])) | |
27 cols_occ = c(names(occ[occulong]),names(occ[occulat])) | |
28 | |
29 ###calculate distances### | |
30 #transform tables into sf object | |
31 | |
32 env_sf <- st_as_sf(env, coords = cols_env, crs = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") | |
33 occ_sf <- st_as_sf(occ, coords = cols_occ, crs = "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") | |
34 | |
35 #Find the indices of env_sf entities closest to each point in occ_sf. | |
36 | |
37 nearest_indices <- st_nearest_feature(occ_sf, env_sf) | |
38 | |
39 nearest_points <- env[nearest_indices, ] | |
40 | |
41 # Calculate distances between env_sf and occ_sf points | |
42 distances <- st_distance(env_sf, occ_sf) | |
43 | |
44 #Extract the corresponding distances between occ and env | |
45 | |
46 nearest_distances <- numeric(length(nearest_indices)) | |
47 | |
48 for (i in 1:length(nearest_indices)) { | |
49 nearest_distances[i] <- st_distance(env_sf[nearest_indices[i],], occ_sf[i,]) | |
50 } | |
51 | |
52 #assemble occurrences and environmental parameters in the same file | |
53 | |
54 nearest_points <- nearest_points[, !names(nearest_points) %in% cols_env] #remove lat and long from env to clean data | |
55 new_occ = cbind(occ, nearest_points) | |
56 | |
57 #Save the file | |
58 | |
59 write.table(new_occ, file = "occurrence_env.tsv",sep ="\t",quote = F, row.names = F,col.names = T) | |
60 | |
61 #create an information file with the distances between the points of the two files | |
62 | |
63 distance_info <- data.frame( | |
64 occ_geometry = occ_sf$geometry, | |
65 env_geometry = env_sf$geometry[nearest_indices], | |
66 distance = nearest_distances | |
67 ) | |
68 | |
69 colnames(distance_info)[1] <- "occ_geometry" | |
70 colnames(distance_info)[2] <- "env_geometry" | |
71 colnames(distance_info)[3] <- "Distances (meters)" | |
72 #save the information file | |
73 | |
74 write.table(distance_info, file = "infos_file.tsv",sep ="\t",quote = F, row.names = F,col.names = T) | |
75 | |
76 | |
77 |