library(purrr)
library(tidyr)
library(dismo)
sample_kfold_events <- function(drivers, k = 10, sample_iter = 5, weighting_varname = "pubs_fit") {
## ----select-events-------------------------------------------------------
selected_events <- eid_metadata %>%
filter(wildlife_zoonoses == 1,
event_year >= 1970) %>%
select(name = eid_name,
year = event_year)
## ----create-sampling-weights---------------------------------------------
drivers <- drivers %>% mutate_(weighting_var = weighting_varname)
set.seed(20161017)
presence_weights <- event_coverage %>%
filter(event_name %in% selected_events$name) %>%
left_join(select(drivers, gridid, weighting_var)) %>%
group_by(event_name) %>%
# only_if()(mutate)(weight = 1) %>%
mutate(weight = coverage * weighting_var / sum(coverage * weighting_var, na.rm = TRUE),
# We do this part to provide any weights where the publication value is NA.
total_weight = sum(weight, na.rm = TRUE),
weight = ifelse(total_weight == 0, coverage, weight)) %>%
ungroup() %>%
replace_na(replace = list(weight = 0, weighting_var = 0))
# We now deal with this by replacing pasture and crop NAs with 0s. There are a
# few locations where our presence weights don't overlap the drivers data frame.
# Because of this, we will omit those. quickmap(semi_join(presence_weights,
# decadal), weight)
# presence_weights <- semi_join(presence_weights, decadal)
# This removes all grid cells belonging to HED_166
absence_weights <- drivers %>%
select(gridid, weighting_var) %>%
replace_na(replace = list(weighting_var = 0))
# There are two polygons which did not produce a presence weight.
selected_events <- selected_events %>%
filter(name %in% presence_weights$event_name)
## ----sample-gridids-and-create-folds------------------------------
event_folds <- foreach(i = 1:sample_iter) %do% {
data.frame(selected_events, fold = kfold(selected_events$name, k = k))
}
# This is the sampling function from the bootstrap workflow -- identical.
sample_gridids <- function(to_sample) {
# print(to_sample$name)
presence <- presence_weights %>%
filter(event_name == to_sample$name) %>%
sample_n(size = 1, weight = weight) %>%
select(gridid) %>%
data.frame(presence = 1)
absence <- absence_weights %>%
sample_n(size = 1, weight = weighting_var) %>%
select(gridid) %>%
data.frame(presence = 0)
sampled <- rbind(presence, absence)
# sampled$name <- to_sample$name
# sampled$year <- to_sample$year
return(sampled)
}
# We will create two data frames this time.
kfold_gridids <- foreach(i = event_folds) %dopar% {
by_row(i, sample_gridids, .collate = "row") %>%
select(-.row)
}
return(kfold_gridids)
# save(training_gridids, file = file.path(current_cache_dir, paste0(model_name, "_training_gridids.RData")))
# save(testing_gridids, file = file.path(current_cache_dir, paste0(model_name, "_testing_gridids.RData")))
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.