FLightR (version 0.4.5)

map.FLightR.ggmap: plots result over map

Description

plots track over map with probability cloud. Can plot only part of the track if dates are specified

Usage

map.FLightR.ggmap(Result, dates = NULL, plot.cloud = TRUE, map.options = NULL, plot.options = NULL, save.options = NULL, zoom = "auto", return.ggobj = FALSE, seasonal.colors = TRUE, seasonal.donut.location = "topleft", seasonal.donut.proportion = 0.5, save = TRUE)

Arguments

Result
FLightR result object obtained from run.particle.filter
dates
either NULL if all twilights should be included or data.frame with first colum - start of the period and second end of the period. Each line represents a new period
plot.cloud
Shlould probability cloud be plotted? If TRUE cloud is estimated by stat_density2d
map.options
options passed to get_map, note that zoom option is defined separately
plot.options
plotting options. Not defined yet!
save.options
ptions passed to ggsave. Filename should be defined here.
zoom
Zoom for map. If 'auto' FLightR will try to find optimal zoom level by downloading different size maps and checking whether all the points fit the map.
return.ggobj
Should ggobj be returned for subsequent checks and/or replotting
seasonal.colors
if true points of the track will have seasonal colors
seasonal.donut.location
if NULL - no color wheel placed, otherwise select one of 'bottomleft', 'bottomright', 'topleft'
seasonal.donut.proportion
how much of X axis should color wheel occupy. return either NULL or ggplot2 class object
save
should function save results with ggsave?

Examples

Run this code
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('2013-06-25', tz='GMT'))
Calibration.periods<-data.frame(
       calibration.start=as.POSIXct(c(NA, "2014-05-05")),
       calibration.stop=as.POSIXct(c("2013-08-20", NA)),
       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))

# 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)
# here we will run only 1e4 partilces for a very short track.
# One should use 1e6 particles for the full run
Result<-run.particle.filter(all.in, threads=1,
           nParticles=1e3, known.last=TRUE,
           precision.sd=25, check.outliers=FALSE)

map.FLightR.ggmap(Result, seasonal.donut.location=NULL, zoom=6, save=FALSE) 
# for this short track without variance seasonal donut does not work,
# but for normall track it will.

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