load.groundfish.environment = function( libs=NULL, p=NULL, assessment.year=NULL ) {
if (is.null(p)) p = list()
rlibs = RLibrary( "Hmisc", "date", "lubridate", "vegan", "fields", "sp",
"rgdal", "raster" , "INLA", "numDeriv", "lubridate", "geosphere", "parallel" )
blibs = bioLibrary( "bio.spacetime", "bio.utilities", "bio.taxonomy",
"netmensuration", "bio.temperature", "bio.bathymetry",
"bio.groundfish", "bio.polygons", "bio.coastline" )
if (!is.null(libs)) libs = RLibrary(libs)
if (exists("libs", p)) libs = c(libs, p$libs)
p$libs = unique( c( libs, rlibs, blibs) )
if (is.null (assessment.year ) ) {
p$assessment.year = lubridate::year( Sys.Date() )
} else {
p$assessment.year = assessment.year
}
p$odbc.data.yrs=1970:p$assessment.year
p$netmensuration.years = c(1990:1992, 2004:p$assessment.year) # 2009 is the first year with set logs from scanmar available .. if more are found, alter this date
p$taxa.of.interest = variable.list.expand("catch.summary")
p$season = "summer"
p = spatial_parameters( p, "SSE" ) # data are from this domain .. so far
p$taxa = "maxresolved"
p$nw = 10 # from temperature.r, number of intervals in a year
p$clusters = rep("localhost", detectCores() )
p$R.gs = file.path( project.datadirectory("bio.groundfish"), "R" )
# define location of local data files
p$scanmar.dir = file.path( project.datadirectory("bio.groundfish"), "data", "nets", "Scanmar" )
p$marport.dir = file.path( project.datadirectory("bio.groundfish"), "data", "nets", "Marport" )
p$netmens.dir = file.path( project.datadirectory("bio.groundfish"), "data", "nets", "netmensuration" )
setwd( p$R.gs )
# export to calling namespace .. should not be needed but just in case
assign("R.gs", p$R.gs, envir=parent.frame() )
return( p )
}
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