prepare_dataset
is the workhorse function for creating portalcasting rodent datasets using existing functions.
Wraps around portalr::summarize_rodent_data
to produce a data.frame
associated with a set of data specifications. Inputs are ready for implementation via prepare_rodents
. prepare_rodents
creates specified datasets
using their associated function (typically prepare_dataset
) and arguments, according to the directory_settings
. prepare_abundance
creates a model-ready vector of abundances for fitting and casting, according to the model's requirements and time settings.
Usage
prepare_abundance(main = ".", dataset = NULL, species = NULL, model = NULL)
prepare_rodents(
main = ".",
datasets = prefab_datasets(),
new_datasets_controls = NULL
)
prepare_dataset(
name = "all",
main = ".",
filename = "rodents_all.csv",
clean = FALSE,
level = "Site",
type = "Rodents",
plots = "all",
unknowns = FALSE,
shape = "crosstab",
time = "newmoon",
output = "abundance",
fillweight = FALSE,
treatment = NULL,
na_drop = FALSE,
zero_drop = FALSE,
min_traps = 1,
min_plots = 24,
effort = TRUE,
species = prefab_species(main = main),
total = TRUE,
save = TRUE
)
read_datasets_controls(main = ".")
datasets_controls(main = ".", datasets = NULL)
write_datasets_controls(
main = ".",
new_datasets_controls = NULL,
datasets = prefab_datasets()
)
Arguments
- main
character
value of the name of the main component of the directory tree.- dataset, datasets
character
value(s) of name(s) of rodent dataset(s) to include.- species
character
-valued vector of species names to include.- model
character
value of the model name.- new_datasets_controls
Optional
list
of controls for new datasets. Seedatasets_controls
.- name
character
name to be given to the dataset.- filename
character
value of the file for saving the output.- clean
logical
indicator of if only the rodent data that passed QA/QC (clean = TRUE
) or if all data (clean = FALSE
) should be loaded.- level
character
indicating the type of summary:"Plot"
,"Treatment"
, or"Site"
. Pipes directly toportalr::summarize_rodent_data
.- type
character
value of the rodent data set type, according to pre-existing definitions. An alternative toggle tospecies
.
Either all species (type = "Rodents"
) or only granivoes (type = "Granivores"
).- plots
Specification of subset of plots. Can be a vector of
numeric
plots indicators or specific sets indicated bycharacter
values:"all"
plots or"Longterm"
plots (plots that have had the same treatment for the entire time series).- unknowns
logical
indicator to either remove all individuals not identified to species (unknowns = FALSE
) or sum them in an additional column (unknowns = TRUE
.- shape
character
value indicating a "crosstab" or "flat" output.- time
character
value specifying the format of the time index in the output. Options are"period"
(sequential Portal surveys),"newmoon"
(lunar cycle numbering), and"date"
(calendar date).
The defaulttime = "newmoon"
produces an equispaced observation timestep, a common format format for discrete-time modeling.- output
character
indicating the type of data:"abundance"
,"biomass"
, or"energy"
.- fillweight
logical
specifier of whether to fill in unknown weights with other records from that individual or species, where possible.- treatment
character
indicating the specific treatment(s) to trim to iflevel = "Treatment"
:"control"
,"exclosure"
,"removal"
, or"spectabs"
- na_drop
logical
indicator of ifNA
values (representing insufficient sampling) should be dropped.- zero_drop
logical
indicator of if0
values (representing sufficient sampling but no detection) should be dropped.- min_traps
integer
(or integernumeric
) of the minimum number of traps collected for a plot to be used.- min_plots
integer
(or integernumeric
) of the minimum number of plots surveyed for a survey to be used.- effort
logical
indicator of if the effort columns should be included in the output.- total
logical
value indicating if a total (sum across species should be added or not. Only available if more than one species is included.- save
logical
indicator controlling if the output should be saved out.
Value
prepare_dataset
: data.frame
for the specified dataset. prepare_rodents
: list
of data.frame
s for the specified datasets. prepare_abundance
: numeric
vector of abundance data corresponding to the time articulated in the metadata file. Missing values are interpolated if requested via the model controls. read_datasets_controls
, write_datasets_controls
, datasets_controls
: list
of datasets
' control list
s, invisible
-ly for write_datasets_controls
.
See also
Content preparation functions:
directory filling
,
prepare covariates
,
prepare metadata
,
prepare models
,
prepare newmoons
Examples
if (FALSE) { # \dontrun{
main1 <- file.path(tempdir(), "rodents")
create_dir(main = main1)
fill_resources(main = main1)
fill_forecasts(main = main1)
fill_fits(main = main1)
fill_models(main = main1)
prepare_newmoons(main = main1)
prepare_rodents(main = main1)
write_datasets_controls(main = main1)
read_datasets_controls(main = main1)
datasets_controls(main = main1)
unlink(main1, recursive = TRUE)
} # }