View source: R/data_preparation.R
| make.prerun.object | R Documentation |
This function is one step before run.particle.filter. It combines data, calibration, spatial extent and movement priors and estimates spatial likelihoods that used later in the particle filter.
make.prerun.object(
Proc.data,
Grid,
start,
end = start,
Calibration,
threads = -1,
Decision = 0.05,
Direction = 0,
Kappa = 0,
M.mean = 300,
M.sd = 500,
likelihood.correction = TRUE
)
Proc.data |
Processed data object created by |
Grid |
Spatial grid created by |
start |
release location (lat, lon). |
end |
end of the track location. Will use |
Calibration |
Calibration object created by |
threads |
number of parallel threads to use. default is -1, which means FLightR will use all available threads except 1. Value 1 will force sequential evaluation |
Decision |
prior for migration probability values from 0 to 1 are allowed |
Direction |
Direction prior for direction of migration (in degrees) with 0 pointing to the North |
Kappa |
concentration parameter for vonMises distribution, 0 means uniform or even distribution. Will set some prior for direction for all the track, so is not recommended to be changed |
M.mean |
Prior for mean distance travelled between consecutive twilights, km |
M.sd |
Prior for sd of distance travelled between consecutive twilights, the higher the value is the wider is the the distribution |
likelihood.correction |
Should likelihood correction estimated during |
Object to be uses in the run.particle.filter
Eldar Rakhimberdiev
File<-system.file("extdata", "Godwit_TAGS_format.csv", package = "FLightR")
# to run example fast we will cut the real data file by 2013 Aug 20
Proc.data<-get.tags.data(File, end.date=as.POSIXct('2013-07-02', tz='GMT'))
Calibration.periods<-data.frame(
calibration.start=NA,
calibration.stop=as.POSIXct("2013-08-20", tz='GMT'),
lon=5.43, lat=52.93)
#use c() also for the geographic coordinates, if you have more than one calibration location
# (e. g., lon=c(5.43, 6.00), lat=c(52.93,52.94))
print(Calibration.periods)
# NB Below likelihood.correction is set to FALSE for fast run!
# Leave it as default TRUE for real examples
Calibration<-make.calibration(Proc.data, Calibration.periods, likelihood.correction=FALSE)
Grid<-make.grid(left=0, bottom=50, right=10, top=56,
distance.from.land.allowed.to.use=c(-Inf, Inf),
distance.from.land.allowed.to.stay=c(-Inf, Inf))
all.in<-make.prerun.object(Proc.data, Grid, start=c(5.43, 52.93),
Calibration=Calibration, threads=2)
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