util/R_sample_scripts/rocc_sample.R

In mmondelli/rdt2repr: rdt to reproduceme parser

remotes::install_github("saramortara/rocc")
library(rdt)
prov.init(save.debug = T, prov.dir = './prov_samples', annotate.inside.functions = T, overwrite = F)
library(Rocc)

species <- c("Asplenium truncorum")
data_splink <- rspeciesLink(species = species,
                            filename = "specieslink")

data_gbif <- rgbif2(species = species,
                    filename = "gbif")

species_name_raw <- unique(data_splink$scientificName)
species_name_check  <- check_string(species_name_raw)
species_name_check
species_ok <- species_name_check[species_name_check$speciesStatus %in% "possibly_ok", ]
suggest_taxa <- suggest_flora(species_ok$species)
search_taxa <- unique(suggest_taxa$species)
list_taxa <- lapply(search_taxa, check_flora)

list_taxa[[1]]$taxon
list_taxa[[1]]$synonyms

list_taxa[[2]]$taxon
list_taxa[[2]]$synonyms

library(modleR)
library(sp)

species <- names(example_occs)
occs <- example_occs[[1]]

test_folder <- "~/Dropbox/Reproducibility/rdt_new/modler_results"
sdmdata_1sp <- modleR::setup_sdmdata(species_name = species[1],
                                     occurrences = occs,
                                     predictors = example_vars,
                                     models_dir = test_folder,
                                     partition_type = "crossvalidation",
                                     cv_partitions = 5,
                                     cv_n = 1,
                                     buffer_type = "mean",
                                     png_sdmdata = F,
                                     n_back = 500,
                                     clean_dupl = FALSE,
                                     clean_uni = FALSE,
                                     clean_nas = FALSE,
                                     geo_filt = FALSE,
                                     geo_filt_dist = 10,
                                     select_variables = TRUE,
                                     sample_proportion = 0.5,
                                     cutoff = 0.7)