CRAN Package Check Results for Package FLightR

Last updated on 2016-12-28 23:47:12.

Check Details

Version: 0.4.5
Flags: --no-stop-on-test-error
Check: dependencies in R code
Result: NOTE
    Namespace in Imports field not imported from: ‘rgdal’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-macos-x86_64-clang

Version: 0.4.5
Check: dependencies in R code
Result: NOTE
    Namespace in Imports field not imported from: ‘rgdal’
     All declared Imports should be used.
Flavors: r-patched-solaris-sparc, r-patched-solaris-x86, r-release-osx-x86_64-mavericks, r-oldrel-windows-ix86+x86_64

Version: 0.4.5
Check: examples
Result: ERROR
    Running examples in ‘FLightR-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: map.FLightR.ggmap
    > ### Title: plots result over map
    > ### Aliases: map.FLightR.ggmap
    >
    > ### ** Examples
    >
    > 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'))
    Detected Intigeo_Mode_1 tag
    Data found to be logtransformed
    tag saved data every 300 seconds, and is assumed to measure data every 60 seconds, and write down max
    > 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)
    
     checking dawn 1
     checking dawn 2
     checking dawn 3
     checking dawn 4
     checking dawn 5
     checking dawn 6
     checking dusk 1
     checking dusk 2
     checking dusk 3
     checking dusk 4
     checking dusk 5
     checking dusk 6
     checking dusk 7
     checking dusk 8
    calibration method used: parametric.slope
    >
    > 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)
    likelihood correction turned off as no correction found in the calibration
    making cluster
    estimating dusks
    estimating dawns
    processing results
    > # 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)
    smart filter is OFF
    
    
    ##########################
     Time.Period 1 of 13
    generating new particlesESS is 1000
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 2 of 13
    generating new particlesESS is 720.9099 - resampling 1
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 3 of 13
    generating new particlesESS is 700.179 - resampling 2
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 4 of 13
    generating new particlesESS is 838.1146 - resampling 3
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 5 of 13
    generating new particlesESS is 885.706 - resampling 4
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 6 of 13
    generating new particlesESS is 856.2748 - resampling 5
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 7 of 13
    generating new particlesESS is 868.8898 - resampling 6
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 8 of 13
    generating new particlesESS is 840.0859 - resampling 7
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 9 of 13
    generating new particlesESS is 930.395 - resampling 8
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 10 of 13
    generating new particlesESS is 942.2885 - resampling 9
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 11 of 13
    generating new particlesESS is 902.2955 - resampling 10
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 12 of 13
    generating new particlesESS is 925.0391 - resampling 11
     unique P in point leaving stack 1
    creating stack
    
    
    ##########################
     Time.Period 13 of 13
    generating new particlesESS is 664.7534 - resampling 12
     unique P in point leaving stack 1
    creating stack
    adding last points form the stack to the resutls
    +----------------------------------+
    | estimated negative Log Likelihood is -2.322912
    +----------------------------------+
    estimating results object
    estimating quantiles for positions
    adding 95% credibility intervals to medians
     estimating distances
     estimating directions
     estimating mean directions and kappas
     estimating kappas
     estimating mean dists
     estimating probs of migration
     estimating median dists
     creating output DONE!
    DONE!
    >
    > map.FLightR.ggmap(Result, seasonal.donut.location=NULL, zoom=6, save=FALSE)
    Map from URL : http://maps.googleapis.com/maps/api/staticmap?center=53.1,5.25&zoom=6&size=640x640&scale=2&maptype=terrain&language=en-EN&sensor=false
    Error: GeomRasterAnn was built with an incompatible version of ggproto.
    Please reinstall the package that provides this extension.
    Execution halted
Flavor: r-release-osx-x86_64-mavericks

Version: 0.4.5
Check: tests
Result: ERROR
    Running the tests in ‘tests/testthat.R’ failed.
    Last 13 lines of output:
     estimating mean dists
     estimating probs of migration
     estimating median dists
     creating output DONE!
     DONE!
     bird likely dod not move, exiting without result
     testthat results ================================================================
     OK: 27 SKIPPED: 0 FAILED: 2
     1. Error: map_flightr_ggmap_works (@test_data_result_summary_and_plotting.R#36)
     2. Error: plot_util_distr_works (@test_data_result_summary_and_plotting.R#57)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-release-osx-x86_64-mavericks