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/* test_piecewise_constant.cpp
*
* Copyright Steven Watanabe 2011
* Distributed under the Boost Software License, Version 1.0. (See
* accompanying file LICENSE_1_0.txt or copy at
* http://www.boost.org/LICENSE_1_0.txt)
*
* $Id$
*
*/
#include <boost/random/piecewise_constant_distribution.hpp>
#include <boost/random/uniform_int.hpp>
#include <boost/random/mersenne_twister.hpp>
#include <boost/lexical_cast.hpp>
#include <boost/exception/diagnostic_information.hpp>
#include <boost/range/algorithm/lower_bound.hpp>
#include <boost/range/numeric.hpp>
#include <vector>
#include <iostream>
#include <iomanip>
#include "statistic_tests.hpp"
class piecewise_constant
{
public:
piecewise_constant(const std::vector<double>& intervals, const std::vector<double>& weights)
: intervals(intervals),
cumulative(1, 0.0)
{
boost::partial_sum(weights, std::back_inserter(cumulative));
for(std::vector<double>::iterator iter = cumulative.begin(), end = cumulative.end();
iter != end; ++iter)
{
*iter /= cumulative.back();
}
}
double cdf(double x) const
{
std::size_t index = boost::lower_bound(intervals, x) - intervals.begin();
if(index == 0) return 0;
else if(index == intervals.size()) return 1;
else {
double lower_weight = cumulative[index - 1];
double upper_weight = cumulative[index];
double lower = intervals[index - 1];
double upper = intervals[index];
return lower_weight + (x - lower) / (upper - lower) * (upper_weight - lower_weight);
}
}
private:
std::vector<double> intervals;
std::vector<double> cumulative;
};
double cdf(const piecewise_constant& dist, double x)
{
return dist.cdf(x);
}
bool do_test(int n, int max) {
std::cout << "running piecewise_constant(p0, p1, ..., p" << n-1 << ")" << " " << max << " times: " << std::flush;
std::vector<double> weights;
{
boost::mt19937 egen;
for(int i = 0; i < n; ++i) {
weights.push_back(egen());
}
}
std::vector<double> intervals;
for(int i = 0; i <= n; ++i) {
intervals.push_back(i);
}
piecewise_constant expected(intervals, weights);
boost::random::piecewise_constant_distribution<> dist(intervals, weights);
boost::mt19937 gen;
kolmogorov_experiment test(max);
boost::variate_generator<boost::mt19937&, boost::random::piecewise_constant_distribution<> > vgen(gen, dist);
double prob = test.probability(test.run(vgen, expected));
bool result = prob < 0.99;
const char* err = result? "" : "*";
std::cout << std::setprecision(17) << prob << err << std::endl;
std::cout << std::setprecision(6);
return result;
}
bool do_tests(int repeat, int max_n, int trials) {
boost::mt19937 gen;
boost::uniform_int<> idist(1, max_n);
int errors = 0;
for(int i = 0; i < repeat; ++i) {
if(!do_test(idist(gen), trials)) {
++errors;
}
}
if(errors != 0) {
std::cout << "*** " << errors << " errors detected ***" << std::endl;
}
return errors == 0;
}
int usage() {
std::cerr << "Usage: test_piecewise_constant -r <repeat> -n <max n> -t <trials>" << std::endl;
return 2;
}
template<class T>
bool handle_option(int& argc, char**& argv, char opt, T& value) {
if(argv[0][1] == opt && argc > 1) {
--argc;
++argv;
value = boost::lexical_cast<T>(argv[0]);
return true;
} else {
return false;
}
}
int main(int argc, char** argv) {
int repeat = 10;
int max_n = 10;
int trials = 1000000;
if(argc > 0) {
--argc;
++argv;
}
while(argc > 0) {
if(argv[0][0] != '-') return usage();
else if(!handle_option(argc, argv, 'r', repeat)
&& !handle_option(argc, argv, 'n', max_n)
&& !handle_option(argc, argv, 't', trials)) {
return usage();
}
--argc;
++argv;
}
try {
if(do_tests(repeat, max_n, trials)) {
return 0;
} else {
return EXIT_FAILURE;
}
} catch(...) {
std::cerr << boost::current_exception_diagnostic_information() << std::endl;
return EXIT_FAILURE;
}
}
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