#!/usr/bin/r -t
#
# Copyright (C) 2012 - 2013  Christian Gunning
# Copyright (C) 2013  Romain Francois
#
# This file is part of RcppArmadillo.
#
# RcppArmadillo is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# RcppArmadillo is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with RcppArmadillo.  If not, see <http://www.gnu.org/licenses/>.

.setUp <- RcppArmadillo:::unit_test_setup( "sample.cpp" ) 

test.sample <- function() {
    ## set up S3 dispatching,
    ## simplifies lapply(tests, ...) below
    csample <- function(x, ...) UseMethod("csample")
    csample.numeric <- csample_numeric
    csample.integer <- csample_integer
    csample.complex <- csample_complex
    csample.character <- csample_character
    csample.logical <- csample_logical

    ## Seed needs to be reset to compare R to C++
    seed <- 441
    ## Input vectors to sample
    N <- 100
    ## Number of samples
    ## works for size == N?!
    size <- N%/%2

    ## all atomic vector classes except raw
    ## for each list element, check that sampling works
    ## with and without replacement, with and without prob
    tests <- list()
    tests <- within(tests, {
        int <- 1:N
        num <- (1:N)/10
        cpx <- (1:N)/10 + 1i
        char <-rep(letters, 4)[1:N]
        bool <- rep(c(T,F), times=N/2)
    })

    ## Un-normalized probs
    probs <- seq(from=0, to=1, length.out=N)
    #probs <- probs/sum(probs)

    ## Run the S3 generic function csample
    ## and associated R function on each data type
    ## ReplaceYN.ProbsYN
    lapply(tests, function(dat) {
        .class <- class(dat)
        set.seed(seed)
        ## R
        r.no.no <- sample(dat, size, replace=F)
        set.seed(seed)
        r.yes.no <- sample(dat, size, replace=T)
        set.seed(seed)
        r.no.yes <- sample(dat, size, replace=F, prob=probs)
        set.seed(seed)
        r.yes.yes <- sample(dat, size, replace=T, prob=probs)
        ## C
        set.seed(seed)
        c.no.no <- csample(dat, size, replace=F)
        set.seed(seed)
        c.yes.no <- csample(dat, size, replace=T)
        set.seed(seed)
        c.no.yes <- csample(dat, size, replace=F, prob=probs)
        set.seed(seed)
        c.yes.yes <- csample(dat, size, replace=T, prob=probs)
        ## comparisons
        checkEquals(r.no.no, c.no.no, msg=sprintf("sample.%s.no_replace.no_prob",.class))
        checkEquals(r.yes.no, c.yes.no, msg=sprintf("sample.%s.replace.no_prob",.class))
        ## the following don't pass
        checkEquals(r.no.yes, c.no.yes, msg=sprintf("sample.%s.no_replace.prob",.class))
        checkEquals(r.yes.yes, c.yes.yes, msg=sprintf("sample.%s.replace.prob",.class))
    })
    ## Walker Alias method test
    ## With replacement, >200 "nonzero" probabilities
    ## Not implemented, see below
    walker.N <- 1e3
    walker.sample <- (1:walker.N)/10
    walker.probs <- rep(0.1, walker.N)
    ## uncomment following 5 lines if/when walker alias method is implemented
    set.seed(seed)
    r.walker <- sample( walker.sample, walker.N, replace=T, prob=walker.probs)
    set.seed(seed)
    c.walker <- csample( walker.sample, walker.N, replace=T, prob=walker.probs)
    checkEquals(r.walker, c.walker, msg=sprintf("Walker Alias method test"))
    ## Walker Alias method is not implemented.
    ## For this problem (replace, >200 non-zero probs) R is much faster
    ## So throw an error and refuse to proceed
    #walker.error <- try( csample( walker.sample, walker.N, replace=T, prob=walker.probs), TRUE)
    #checkEquals(inherits(walker.error, "try-error"), TRUE, msg=sprintf("Walker Alias method test"))
}