#' Fetch Red List data (non-parallel)
#' @description Download Red List habitat and elevation data from the Red List API.
#' @author Matt Lewis, \email{matthewlewis896@@gmail.com}
#' @keywords internal
#'
#' @param x Vector of species names or IDs.
#' @param query Character string. 'name' if querying by species name; 'ID' if querying by IUCN Red List ID.
#' @param key Character string. IUCN Red List API key - available from https://apiv3.iucnredlist.org/api/v3/token
#' @param sleep_dur (optional) Numeric. Duration of sleep between API calls in seconds. Defaults to 2 seconds.
#' @param subset (optional). Numeric. Specify proportion of x to run for between 0 and 1. Defaults to 1.
#' @param verbose (optional) Numeric. If 0 gives no progress update, if 1 prints progress bar, if 2 prints 1 row per task completed. Default is 1.
#'
#' @return A dataframe in wide format (one column per habitat type and one row per species' season).
fetch_nopar <-
function(x,
key,
query,
subset,
sleep_dur,
verbose) {
temp_df <- wideform()
seasons <- redlistManipulatr::seasons
suitability <- redlistManipulatr::suitability
major_importance <- redlistManipulatr::major_importance
cols_to_check <-
hab_col_positions() %>%
unlist() %>%
sort()
if(verbose == 1){
pb = txtProgressBar(min = 0, max = length(subset), initial = 0, style = 3)
}
ret <- foreach::foreach (
i = subset,
.combine = rbind,
.packages = c("rredlist")#packages needing maintaining in this loop
) %do% {
#Let's see how many of 5 seasons we can fill - output df in the form we want
df <- temp_df
#what species we after
species <- as.character(x[i])
#trying with an error phase if needed
df <- tryCatch({
if (query == "name") {
habs <- rredlist::rl_habitats(name = species, key = key)
} else if (query == "ID") {
habs <-
rredlist::rl_habitats(id = as.numeric(as.character(species)), key = key)
}
if(length(habs$result)>0){
habs$result$season <- tolower(as.character(habs$result$season))
habs$result$season[habs$result$season %in% c("unknown", "seasonal occurrence unknown")] <- "seasonal occurrence uncertain"
habs$result$suitability <- tolower(as.character(habs$result$suitability))
habs$result$season[is.na(habs$result$season)] = 999
habs$result$suitability[is.na(habs$result$suitability)] = 999
#reformatting season
for(j in 1:length(habs$result$season)){
season_code <-
seasons$Code[tolower(seasons$Seasonality) == tolower(habs$result$season[j])]
if(any(is.na(season_code))){
next()
}else if(length(season_code) == 0L){
next()
}else{
habs$result$season[j] <- season_code
}
}
#reformatting suitability
for(j in 1:length(habs$result$suitability)){
suit_code <-
suitability$Code[tolower(suitability$Name) == tolower(habs$result$suitability[j])]
if(any(is.na(suit_code))){
next()
}else if(length(suit_code) == 0L){
next()
}else{
habs$result$suitability[j] <- suit_code
}
}
# Add codes for major importance
for (j in 1:nrow(habs$result)){
mi_code <-
major_importance$Code[tolower(major_importance$Major_Importance) == tolower(habs$result$majorimportance[j])][1] # [1] deals with NA
if(is.na(mi_code)){
habs$result$majorimportance[j] <- major_importance$Code[is.na(major_importance$Major_Importance)]
}else{
habs$result$majorimportance[j] <- mi_code
}
habs$result$suitability[j] <-
paste0(
habs$result$suitability[j],
habs$result$majorimportance[j]
)
}
habs$result <-
habs$result[order(habs$result$season), ]
#adding habitat suitability values to relevant columns
for (j in 1:length(unique(habs$result$season))) {
this.season <- as.numeric(as.character(unique(habs$result$season)[j]))
df[j, 2] = this.season
temp <-
habs$result[which(as.numeric(as.character(habs$result$season)) ==
this.season), ]
for (k in 1:nrow(temp)) {
hab_column <-
paste("iucn", paste(unlist(
strsplit(temp$code[k], split = "[.]")
), collapse = "_"), sep = "_")
df[j, hab_column] = temp$suitability[k]
}
}
}else{
df<-df[1,]
df[,2]=999
df[,cols_to_check] <-
66
}
#and now the rest
#brief sleep
Sys.sleep(sample(rnorm(100, sleep_dur, 0.1), 1))
if (query == "name") {
elevation <- rredlist::rl_search(name = species, key = key)
} else if (query == "ID") {
elevation <-
rredlist::rl_search(id = as.numeric(as.character(species)), key = key)
}
if(length(elevation$result)>0){
df$iucn_id = as.numeric(as.character(elevation$result$taxonid[1]))
df$kingdom = as.character(elevation$result$kingdom[1])
df$class = as.character(elevation$result$class[1])
df$binomial = as.character(elevation$result$scientific_name[1])
df$min_alt = as.numeric(as.character(elevation$result$elevation_lower[1]))
df$max_alt = as.numeric(as.character(elevation$result$elevation_upper[1]))
df$iucn_category=as.character(elevation$result$category[1])
}else{
if (query == "name") {
df$binomial = species
} else if (query == "ID") {
df$iucn_id = species
}
}
#if NA lets make it clear that's because of a lack of data
if (is.na(df$min_alt[1])) {
df$min_alt = -99999
}
if (is.na(df$max_alt[1])) {
df$max_alt = 99999
}
#to stop the redlist api getting annoyed
df <- df[which(!is.na(df$season)),, drop = F]
df <- df
},
error = function(err) {
df<-df[1,]
#but if this fails then just fill all the hab columns with 6s
df[,which(colnames(df) == "iucn_1_1"):length(df)] <-
66
if (query == "name") {
df$binomial = species
} else if (query == "ID") {
df$iucn_id = species
}
df$min_alt=-99999
df$max_alt=99999
df[,2]=999
df <- df
})
Sys.sleep(sample(rnorm(100, sleep_dur, 0.1), 1))
if(verbose == 1){
setTxtProgressBar(pb,i)
}else if(verbose ==2){
print(paste("task", i, "is complete"))
}
df
}
df <- do.call("cbind", ret)
return(df)
}
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