From e42f04195ec7341fb334bb42678e146ae808c303 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andrea=20Sa=CC=81nchez=20Tapia?= Date: Tue, 13 Aug 2019 13:38:06 -0700 Subject: [PATCH] eucl tests --- .../Euclidean_distance.Rmd | 144 ++++++++---------- euclidean_distance_tests/env/cropped_proj.tif | Bin 0 -> 574686 bytes 2 files changed, 66 insertions(+), 78 deletions(-) create mode 100644 euclidean_distance_tests/env/cropped_proj.tif diff --git a/euclidean_distance_tests/Euclidean_distance.Rmd b/euclidean_distance_tests/Euclidean_distance.Rmd index 37e44b3..bb68ad8 100644 --- a/euclidean_distance_tests/Euclidean_distance.Rmd +++ b/euclidean_distance_tests/Euclidean_distance.Rmd @@ -12,20 +12,19 @@ output: knitr::opts_chunk$set(echo = TRUE, message = F, warning = F) ``` - ```{r} library(rJava) library(raster) #library(ModelR) -devtools::load_all("../../ModelR") +devtools::load_all("../../../modelr_pkg/") library(dplyr) ``` # Dataset ```{r} -especies <- unique(coordenadas$sp) -coord1sp <- dplyr::filter(coordenadas, sp == especies[1]) +especies <- names(coordenadas)[1] +coord1sp <- coordenadas[[1]] head(coord1sp) dim(coord1sp) ceiling(0.7 * nrow(coord1sp)) @@ -37,87 +36,76 @@ test_set <- coord1sp[setdiff(1:nrow(coord1sp),set),] # Fitting and projection datasets -We want to fit everything in a small area around the occurrence points (generated through a "median distance buffer") and project it to other sample rasterStacks - -A simple model with no buffer and no projection: - -```{r enm1, message = F, eval = F} -fit_data <- stack("./env/cropped_proj.tif") -no_proj <- do_enm(species_name = especies[1], - occurrences = coord1sp[, -1], - predictors = fit_data, - models_dir = "./fit", - centroid = T, - mindist = T, - clean_dupl = T, - clean_nas = T) - -no_proj.c <- raster("./fit/Eugenia florida DC./present/partitions/centroid_cont_Eugenia florida DC._1_1.tif") -#no_proj.m <- raster("./fit/Eugenia florida DC./present/partitions/mindist_cont_Eugenia florida DC._1_1.tif") -par(mfrow = c(1,2)) -plot(no_proj.c, main = "centroid") -maps::map(, , add = T) -plot(no_proj.m, main = "mindist") -maps::map(, , add = T) + +```{r enm1, message = F, eval = T} +fit_data <- raster::stack("./env/cropped_proj.tif") ``` -## New implementation +```{r remedy001} +centroide1 <- modleR::euclidean(x = example_vars, + occs = train_set[,c(2,3)], + algo = "centroid") +centroide2 <- modleR::euclidean(x = fit_data, + occs = train_set[,c(2,3)], + algo = "centroid") +plot(centroide1) +plot(centroide2) +points(train_set[,c(2,3)]) -```{r remedy001} -fit_data <- stack("/Users/Sanchez/Documents/1 ModelR/package docs/2 projection/env/cropped_proj.tif") -source("/Users/Sanchez/Documents/1 ModelR/ModelR/R/euclidean.R") - -no_proj <- do_any2(species_name = especies[1], - occurrences = coord1sp[, -1], - predictors = fit_data, - models_dir = "./eucl_test", - algo = "centroid", - #centroid = T, - clean_dupl = T, - clean_nas = T) -no_proj.test <- raster("./eucl_test/Eugenia florida DC./present/partitions/centroid_cont_Eugenia florida DC._1_1.tif") -plot(no_proj.test) -#identical(no_proj.test, no_proj.c) -par(mfrow = c(1,2)) -plot(no_proj.test) -#plot(no_proj.c) -no_proj.test -#no_proj.c ``` -##mindist -```{r remedy002} - -no_proj <- do_any2(species_name = especies[1], - occurrences = coord1sp[, -1], - predictors = fit_data, - models_dir = "./eucl_test", - algo = "mindist", - clean_dupl = T, - clean_na = T) -no_proj.test2 <- raster("./eucl_test/Eugenia florida DC./present/partitions/mindist_cont_Eugenia florida DC._1_1.tif") -plot(no_proj.test2) -par(mfrow = c(1,2)) -plot(no_proj.test2) -no_proj.test2 +```{r mindist} + +mindist1 <- modleR::euclidean(x = example_vars, + occs = train_set[,c(2,3)], + algo = "mindist") +mindist2 <- modleR::euclidean(x = fit_data, + occs = train_set[,c(2,3)], + algo = "mindist") + +plot(mindist1) +points(train_set[,c(2,3)]) +plot(mindist2) +points(train_set[,c(2,3)]) ``` -## Model projection -We project to a series of projections in the specified folder: "./env/proj" - -```{r proj, message = T, eval = F} -yes_proj <- do_any2(species_name = especies[1], - occurrences = coord1sp[, -1], - predictors = fit_data, - models_dir = "./projtest", - algo = "centroid", - #algo = "mindist", - clean_dupl = T, - clean_nas = T, - project_model = T, - proj_data_folder = "./env/proj", - write_png = T, - ) +```{r} +a <- rescale_layer(mindist1) +plot(a) +a>0.8 +plot(sort(values(a))) + +plot(a > 0.95, main = "dist > 0.95", col = c("white", "green")) +plot(a > 0.99, main = "dist > 0.99", legend = F, add = T, col = c(NA, "red")) +maps::map(,,,add = T) + +``` + + +```{r} +setup <- setup_sdmdata( + species_name = especies[1], + occurrences = coord1sp[, -1], + predictors = fit_data, + models_dir = "./eucl") +``` + +```{r} +centroid_no_proj <- do_any(species_name = especies[1], + predictors = fit_data, + write_png = T, + algo = "centroid", + models_dir = "./eucl") +mindist_no_proj <- do_any(species_name = especies[1], + predictors = 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