useDynLib(bayesPop, .registration = TRUE)

# import
import(
    bayesTFR, bayesLife, MortCast, parallel, abind, wpp2019, wpp2012, fields, googleVis, rworldmap
)

importFrom("graphics", "par", "plot", "grid", "lines", "mtext", "axis", "segments")
importFrom("grDevices", "dev.off", "rainbow", "adjustcolor")
importFrom("stats", "reshape", "lm", "coefficients", "smooth.spline", "splinefun", "approx", "median", "quantile", 
           "sd", "aggregate")
importFrom("utils", "write.table", "read.table", "menu", "read.csv", "read.delim", "data")
importFrom("reshape2", "melt")
importFrom("plyr", "aaply")
import(data.table, except=c(melt))

#exportPattern("^[[:alpha:]]+")
useDynLib(bayesPop)

# export functions
export(
pop.predict,
pop.predict.subnat,
pop.trajectories.plot,
pop.trajectories.plotAll,
pop.trajectories.table,
pop.byage.plot,
pop.byage.plotAll,
pop.byage.table,
pop.pyramid,
pop.pyramidAll,
pop.trajectories.pyramid,
pop.trajectories.pyramidAll,
get.pop.prediction,
has.pop.prediction,
pop.aggregate,
pop.aggregate.subnat,
get.pop.aggregation,
get.bPop.pyramid,
pop.map,
get.pop.map.parameters,
pop.map.gvis,
pop.ggmap,
write.pop.projection.summary,
write.pop.trajectories,
pop.cleanup.cache,
LifeTableMx,
LifeTableMxCol,
get.pop,
get.pop.ex,
get.pop.exba,
pop.trajectories,
get.trajectory.indices,
extract.trajectories.eq,
extract.trajectories.ge,
extract.trajectories.le,
cohorts,
pop.cohorts.plot,
mac.expression,
mac.expression1,
mac.expression5,
age.specific.migration,
project.pasfr,
project.pasfr.traj,
migration.totals2age,
rcastro.schedule
)

# register S3 methods
S3method(summary, bayesPop.prediction)
S3method(print, summary.bayesPop.prediction)
S3method(get.countries.table, bayesPop.prediction)
S3method(pop.pyramid, bayesPop.prediction)
S3method(pop.pyramid, bayesPop.pyramid)
S3method(plot, bayesPop.pyramid)
S3method(pop.trajectories.pyramid, bayesPop.prediction)
S3method(pop.trajectories.pyramid, bayesPop.pyramid)
S3method(get.bPop.pyramid, bayesPop.prediction)
S3method(get.bPop.pyramid, data.frame)
S3method(get.bPop.pyramid, matrix)
S3method(get.bPop.pyramid, list)
S3method(get.data.for.worldmap, bayesPop.prediction)
S3method(.map.main.default, bayesPop.prediction)
S3method(bdem.map.gvis, bayesPop.prediction)
S3method(as.environment, bayesPop.prediction)