# This is a wrapper script to combine the results from each dataset-level pipeline into a single data frame.
library(drake)
library(dplyr)
library(ggplot2)
library(scadsanalysis)
all_di <- list()
#datasets <- c("bbs", "gentry", "fia_short", "mcdb", "misc_abund_short", "fia_small")
datasets <- c( "gentry-jk", "mcdb-jk", "bbs-jk","misc-jk", "fia_small-jk", "fia_short-jk" )
for(i in 1:length(datasets)) {
this_dataset = datasets[i]
if(this_dataset == "misc_abund_short") {
cache_loc = "misc_jk"
} else if(this_dataset == "fia_short") {
cache_loc = "fia"
} else {
cache_loc = this_dataset
}
## Set up the cache and config
db <- DBI::dbConnect(RSQLite::SQLite(), here::here("analysis", "drake", paste0("drake-cache-", cache_loc, ".sqlite")))
cache <- storr::storr_dbi("datatable", "keystable", db)
all_di[[i]] <- readd(all_di_obs, cache = cache)
all_di[[i]] <- filter(all_di[[i]], source == "observed")
DBI::dbDisconnect(db)
rm(cache)
rm(db)
}
all_di <- bind_rows(all_di)
write.csv(all_di, here::here("analysis", "reports", "submission2", "all_di_jk.csv"), row.names = F)
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