In luismurao/ntbox: From Getting Biodiversity Data to Evaluating Species Distribution Models in a Friendly GUI Environment

This is NicheToolBox Ecological Niche Modeling module report here you can find a quick view of the thinks that you have done in the software. Remember that this is free software so it comes with no waranty, please report any bugs you find at [e-mail] or or via projects GitHub repository https://github.com/luismurao/ntbox.

library(knitr)
library(rgl)
knitr::opts_chunk$set(echo = TRUE)
knit_hooks$set(rgl = hook_rgl, webgl = hook_webgl)
plot_function <- system.file("shinyApp/helpers/ellipsoid_3D_plot.R",
                             package = "ntbox")

printEllip_all_all_train <- FALSE
printEllip_all_m_train <- FALSE
printEllip_m_m_train <- FALSE 
printEllip_m_all_train <- FALSE
emap_all_all_train <- FALSE
emap_all_m_train <- FALSE
emap_m_all_train <- FALSE
emap_m_m_train <- FALSE

if(input$selectBios_all_all_train && (!is.null(mve_obj_all()) || !is.null(mve_obj_m()))){
  printEllip_all_all_train <- TRUE
  if(!is.null(leaf_ellip_all_all_train())) emap_all_all_train <- TRUE

}
if(input$selectBios_all_m_train && (!is.null(mve_obj_all()) || !is.null(mve_obj_m()))){

  printEllip_all_m_train <- TRUE
  if(!is.null(leaf_ellip_all_m_train())) emap_all_m_train <- TRUE
}
if(input$selectBios_m_m_train && (!is.null(mve_obj_all()) || !is.null(mve_obj_m()))){
  printEllip_m_m_train <- TRUE
  if(!is.null(leaf_ellip_m_m_train())) emap_m_m_train <- TRUE

}
if(input$selectBios_m_all_train && (!is.null(mve_obj_all()) || !is.null(mve_obj_m()))){
  printEllip_m_all_train <- TRUE
  if(!is.null(leaf_ellip_m_all_train())) emap_m_all_train <- TRUE

}

all_opts <- c(printEllip_all_all_train,
              printEllip_all_m_train,
              printEllip_m_m_train,
              printEllip_m_all_train)


if(TRUE %in% all_opts){
  cat("## Ellipsoid modeling report")
  cat("\n")
}

cat("### Ellipsoid data for model trained in all raster area and projected in all raster area\n")

ellipsoid_metadata <- mve_obj_all()

cat("##### Ellipsoid centroid\n")

print(ellipsoid_metadata$centroid)

cat("##### Shape matrix\n")

print(ellipsoid_metadata$covariance)

cat("##### Ellipsoid volume")

ellipsoid_metadata$niche_volume

if(length(ellipsoid_metadata$centroid) == 3){
  rgl::plot3d(rgl::ellipse3d(ellipsoid_metadata$covariance,
                           centre = ellipsoid_metadata$centroid,
                           level = 0.99),
            alpha=0.4,col="blue")
  rglwidget()
}

cat("##### Ellipsoid projection in E")

plot_function <- system.file("shinyApp/helpers/ellipsoid_3D_plot.R",
                             package = "ntbox")
source(plot_function)
vars_used <- names(ellipsoid_metadata$centroid)
if(length(ellipsoid_metadata$centroid) == 3){
  ellipsoid_obj <- ellip_model_all_rast_all_train()
  suits <-ellipsoid_obj$suits[,"suitability"]
  data <- ellipsoid_obj$suits[,vars_used]
  covar <- ellipsoid_metadata$covariance
  centroid <- ellipsoid_metadata$centroid
  ellipsoid_plot_3d(suits = suits,
                    data = data,covar = covar,
                    centroid = centroid,
                    xlab1 = vars_used[1],
                    ylab1 = vars_used[2])
  rglwidget()
} else{
  multi.hist(occ_extract()$data[,vars_used],
                 dcol= c("blue","red"),dlty=c("dotted", "solid"))
}

cat("##### Ellipsoid projection in G")

leaf_ellip_all_all_train()

cat("### Ellipsoid data for model trained in M area and projected in All raster area\n")

ellipsoid_metadata <- mve_obj_m()

cat("##### Ellipsoid centroid\n")

print(ellipsoid_metadata$centroid)

cat("##### Shape matrix\n")

print(ellipsoid_metadata$covariance)

cat("##### Ellipsoid volume")

ellipsoid_metadata$niche_volume

cat("##### Ellipsoid projection in E")

plot_function <- system.file("shinyApp/helpers/ellipsoid_3D_plot.R",
                             package = "ntbox")
source(plot_function)
vars_used <- names(ellipsoid_metadata$centroid)
if(length(ellipsoid_metadata$centroid) == 3){
  ellipsoid_obj <- ellip_model_all_rast_m_train()
  suits <-ellipsoid_obj$suits[,"suitability"]
  data <- ellipsoid_obj$suits[,vars_used]
  covar <- ellipsoid_metadata$covariance
  centroid <- ellipsoid_metadata$centroid
  ellipsoid_plot_3d(suits = suits,
                    data = data,covar = covar,
                    centroid = centroid,
                    xlab1 = vars_used[1],
                    ylab1 = vars_used[2])
  rglwidget()
} else{
  multi.hist(occ_extract()$data[,vars_used],
                 dcol= c("blue","red"),dlty=c("dotted", "solid"))
}

cat("##### Ellipsoid projection in G")

leaf_ellip_all_m_train()

cat("### Ellipsoid data for model trained in all area and projected in M raster area\n")

ellipsoid_metadata <- mve_obj_all()

cat("##### Ellipsoid centroid\n")

print(ellipsoid_metadata$centroid)

cat("##### Shape matrix\n")

print(ellipsoid_metadata$covariance)

cat("##### Ellipsoid volume")

ellipsoid_metadata$niche_volume

cat("##### Ellipsoid projection in E")

plot_function <- system.file("shinyApp/helpers/ellipsoid_3D_plot.R",
                             package = "ntbox")
source(plot_function)
vars_used <- names(ellipsoid_metadata$centroid)
if(length(ellipsoid_metadata$centroid) == 3){
  ellipsoid_obj <- ellip_model_m_rast_all_train()
  suits <-ellipsoid_obj$suits[,"suitability"]
  data <- ellipsoid_obj$suits[,vars_used]
  covar <- ellipsoid_metadata$covariance
  centroid <- ellipsoid_metadata$centroid
  ellipsoid_plot_3d(suits = suits,
                    data = data,covar = covar,
                    centroid = centroid,
                    xlab1 = vars_used[1],
                    ylab1 = vars_used[2])
  rglwidget()
} else{
  multi.hist(occ_extract()$data[,vars_used],
                 dcol= c("blue","red"),dlty=c("dotted", "solid"))
}

cat("##### Ellipsoid projection in G")

leaf_ellip_m_all_train()

cat("### Ellipsoid data for model trained in M area and projected in M raster area\n")

ellipsoid_metadata <- mve_obj_m()

cat("##### Ellipsoid centroid\n")

print(ellipsoid_metadata$centroid)

cat("##### Shape matrix\n")

print(ellipsoid_metadata$covariance)

cat("##### Ellipsoid volume")

ellipsoid_metadata$niche_volume

cat("##### Ellipsoid projection in E")

plot_function <- system.file("shinyApp/helpers/ellipsoid_3D_plot.R",
                             package = "ntbox")
source(plot_function)
vars_used <- names(ellipsoid_metadata$centroid)
if(length(ellipsoid_metadata$centroid) == 3){
  ellipsoid_obj <-ellip_model_m_rast_m_train()
  suits <-ellipsoid_obj$suits[,"suitability"]
  data <- ellipsoid_obj$suits[,vars_used]
  covar <- ellipsoid_metadata$covariance
  centroid <- ellipsoid_metadata$centroid
  ellipsoid_plot_3d(suits = suits,
                    data = data,covar = covar,
                    centroid = centroid,
                    xlab1 = vars_used[1],
                    ylab1 = vars_used[2])
  rglwidget()
} else{
  multi.hist(occ_extract()$data[,vars_used],
                 dcol= c("blue","red"),dlty=c("dotted", "solid"))
}

cat("##### Ellipsoid projection in G")

leaf_ellip_m_m_train()

printBio_all_all_train <- FALSE
printBio_all_m_train <- FALSE
printBio_m_m_train <- FALSE 
printBio_m_all_train <- FALSE
bmap_all_all_train <- FALSE
bmap_all_m_train <- FALSE
bmap_m_all_train <- FALSE
bmap_m_m_train <- FALSE

if(input$run_bioclim_all_all_train && is.list(bioclim_model_all_all_train())){
  printBio_all_all_train <- TRUE
  if(!is.null(leaf_bio_all_all_train())) bmap_all_all_train <- TRUE
}

if(input$run_bioclim_all_m_train && is.list(bioclim_model_all_m_train())){
  printBio_all_m_train <- TRUE
  if(!is.null(leaf_bio_all_m_train())) bmap_all_m_train <- TRUE
}
if(input$run_bioclim_m_m_train && is.list(bioclim_model_m_m_train())){
  printBio_m_m_train <- TRUE
  if(!is.null(leaf_bio_m_m_train())) bmap_m_m_train <- TRUE
}
if(input$run_bioclim_m_all_train && is.list(bioclim_model_m_all_train())){
  printBio_m_all_train <- TRUE
  if(!is.null(leaf_bio_m_all_train())) bmap_m_all_train <- TRUE
}

bio_all_opts <- c(printBio_all_all_train,
                  printBio_all_m_train,
                  printBio_m_m_train,
                  printBio_m_all_train)

if(TRUE %in% bio_all_opts){
  cat("## Bioclim modeling report")
  cat("\n")
}

cat("### Bioclim data for model trained in all raster area and projected in all raster area\n")

bioclim_metadata <- bioclim_model_all_all_train()

cat("##### Bioclim ranges\n")

cat("Min values:\n")
print(bioclim_metadata$train@min)
cat("Max values:\n")
print(bioclim_metadata$train@max)

cat("##### Bioclim response curves\n")

dismo::response(bioclim_metadata$train)

cat("##### Bioclim projection in G")

leaf_bio_all_all_train()

cat("### Bioclim data for model trained in all raster area and projected in M area\n")

bioclim_metadata <- bioclim_model_m_all_train()

cat("##### Bioclim ranges\n")

cat("Min values:\n")
print(bioclim_metadata$train@min)
cat("Max values:\n")
print(bioclim_metadata$train@max)

cat("##### Bioclim response curves\n")

dismo::response(bioclim_metadata$train)

cat("##### Bioclim projection in G")

leaf_bio_m_all_train()

cat("### Bioclim data for model trained in M area and projected in all raster area\n")

bioclim_metadata <- bioclim_model_all_m_train()

cat("##### Bioclim ranges\n")

cat("Min values:\n")
print(bioclim_metadata$train@min)
cat("Max values:\n")
print(bioclim_metadata$train@max)

cat("##### Bioclim response curves\n")

dismo::response(bioclim_metadata$train)

cat("##### Bioclim projection in G")

leaf_bio_all_m_train()

cat("### Bioclim data for model trained in M area and projected in M area\n")

bioclim_metadata <- bioclim_model_m_m_train()

cat("##### Bioclim ranges\n")

cat("Min values:\n")
print(bioclim_metadata$train@min)
cat("Max values:\n")
print(bioclim_metadata$train@max)

cat("##### Bioclim response curves\n")

dismo::response(bioclim_metadata$train)

cat("##### Bioclim projection in G")

leaf_bio_m_m_train()

luismurao/ntbox documentation built on May 9, 2024, 8:24 p.m.