## Profile/manual-broadcast demo (mpiexec + .Rprofile + mpi.bcast.*).
## Run with two ranks (master + one worker), e.g.
##   mpiexec -env R_PROFILE_USER ../.Rprofile -env R_PROFILE "" \\
##           -n 2 R CMD BATCH --no-save <script>.R
## Do not use R CMD BATCH --vanilla for profile mode.
##
## Initialize master and slaves.

mpi.bcast.cmd(np.mpi.initialize(),
              caller.execute=TRUE)

## Turn off progress i/o as this clutters the output file (if you want
## to see search progress you can comment out this command)

mpi.bcast.cmd(options(np.messages=FALSE),
              caller.execute=TRUE)

## Generate some data and broadcast it to all slaves (it will be known
## to the master node)

mpi.bcast.cmd(set.seed(42),
              caller.execute=TRUE)

mpi.bcast.cmd(library(MASS),
              caller.execute=TRUE)

set.seed(42)

n <- as.integer(Sys.getenv("NP_DEMO_N", "5000"))
n.eval <- 25
rho <- 0.95
mu <- c(0,0)
Sigma <- matrix(c(1,rho,rho,1),2,2)
mydat <- mvrnorm(n=n, mu, Sigma)
mydat <- data.frame(x=mydat[,1],y=mydat[,2])

q.minm <- 0.0
q.max <- 1.0
grid.seq <- seq(q.minm,q.max,length=n.eval)
grid.dat <- data.frame(x = grid.seq, y = grid.seq)

mpi.bcast.Robj2slave(mydat)
mpi.bcast.Robj2slave(grid.dat)

## Estimate the copula

t.0 <- system.time(mpi.bcast.cmd(bw <- npudistbw(~x+y,data=mydat),
                                 caller.execute=TRUE))
t.1 <- system.time(mpi.bcast.cmd(copula <- npcopula(bws=bw, data=mydat, u=grid.dat),
                                 caller.execute=TRUE))

t <- t.0+t.1

summary(bw)

cat("Elapsed time =", t[3], "\n")

## Clean up properly then quit()

mpi.bcast.cmd(mpi.quit(),
              caller.execute=TRUE)
