Sleepingwell

#include <iostream>
#include <vector>
#include <utility>
#include <algorithm>
#include <boost/ref.hpp>
#include <boost/type_traits/remove_reference.hpp>
#include <boost/iterator/iterator_facade.hpp>
#include <boost/range/iterator_range.hpp>

using namespace std;

Sleepingwell

#include <boost/iterator/iterator_categories.hpp>
#include <boost/iterator/transform_iterator.hpp>
#include <boost/range/adaptor/transformed.hpp>
#include <boost/range/any_range.hpp>
#include <boost/range/numeric.hpp>
#include <boost/timer/timer.hpp>
#include <iostream>
#include <fstream>
#include <vector>
#include <numeric>

Sleepingwell

setwd("c:/dir/containing/compiled/binary")
dyn.load("deep_thought")
.External('the_meaning_of_life', environment())
.External('the_meaning_of_multiple_lives', 42, environment())
dyn.unload("deep_thought")

Sleepingwell

library(data.table)

nl <- 100
stp <- 50000
ss <- stp

ss <- seq(stp, length.out=20, by=stp)
times <- sapply(ss, function(ss) {
    mydata <- data.frame(
        to_location_id = as.factor(sample(nl, ss, T)),

Sleepingwell

#include <vector>
#include <utility>
#include <iterator>
#include <R.h>
#include <Rdefines.h>

template<typename Iter>
SEXP makePolygon(Iter b, Iter e) {
    SEXP
        coords;

Sleepingwell

/*
 * A 'functor descriptor' that can be used to generate a runtime polymorphic functor
 * for a set of input/ouput types. To be used to create python extensions in C++ for
 * wrapping with boost::python, such that the functors can be configured in Python
 * then applied to a number (greater than 1) of non-polymorphic input/output types
 * in C++ (the types used in practice will not be those in first_types and second
 * types, which are just for convenience).
 */

#include <new> // placement new

Sleepingwell

pre <- scan()
51.11
64.44
73.33
77.78
66.67
84.44
68.89
57.78
64.44

Sleepingwell

# A wrapper around Rcartogram::cartogram for shape files.
#
# @param polys:     Either a SpatialPolygonsDataFrame or the path to a shape file.
# @param variable:  Either a string giving the name of the variable to used in polys@data, or a vector
#                   of the same length as polys@polygons.
# @param nx:        The number of columns in the raster used to represent the region.
# @param ny:        The number of rows in the raster used to represent the region.
# @param buffer.by: The proportion width of the buffer to add to the region (see ?Rcartogram::addBoundary).
#
# @return           The new boundaries as A SpatialPolygonsDataFrame with the attribute 'cartogram.scaling.var'.

Sleepingwell

test.func <- function(n.samples) {
    nms <- c("Wichmann-Hill", "Marsaglia-Multicarry", "Super-Duper", "Mersenne-Twister", "Knuth-TAOCP-2002", "Knuth-TAOCP", "L'Ecuyer-CMRG")
    tmp <- lapply(nms, function(unif.rng.name) {
        RNGkind(unif.rng.name)
        nms <- c("Kinderman-Ramage", "Ahrens-Dieter", "Box-Muller", "Inversion")
        tmp <- sapply(nms, function(norm.rng.name) {
            RNGkind(, norm.rng.name)
            system.time(rnorm(n.samples))
        })[1:3,]
        # included here because I'm not sure if rziggurat uses the unif rng internally.

Sleepingwell

/*
Copyright (C) 2006  Anthony M. Pasqualoni 

This program 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.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of