Subject: [Boost-commit] svn:boost r60279 - in trunk: boost/random boost/random/detail libs/random/extra libs/random/test
From: steven_at_[hidden]
Date: 2010-03-07 00:22:42
Author: steven_watanabe
Date: 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
New Revision: 60279
URL: http://svn.boost.org/trac/boost/changeset/60279
Log:
Make statistics_tests usable with the current library
Added:
trunk/libs/random/extra/
trunk/libs/random/extra/Jamfile.v2 (contents, props changed)
trunk/libs/random/extra/haertel.hpp
- copied, changed from r60246, /trunk/libs/random/test/statistic_tests.cpp
trunk/libs/random/extra/test_haertel.cpp
- copied, changed from r60246, /trunk/libs/random/test/statistic_tests.cpp
Text files modified:
trunk/boost/random/detail/disable_warnings.hpp | 1
trunk/boost/random/uniform_int.hpp | 11
trunk/boost/random/uniform_smallint.hpp | 2
trunk/libs/random/extra/haertel.hpp | 518 ------------------------------
trunk/libs/random/extra/test_haertel.cpp | 676 ++-------------------------------------
trunk/libs/random/test/Jamfile.v2 | 5
trunk/libs/random/test/statistic_tests.cpp | 292 ++++------------
trunk/libs/random/test/statistic_tests.hpp | 32 +
8 files changed, 152 insertions(+), 1385 deletions(-)
Modified: trunk/boost/random/detail/disable_warnings.hpp
==============================================================================
--- trunk/boost/random/detail/disable_warnings.hpp (original)
+++ trunk/boost/random/detail/disable_warnings.hpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -19,4 +19,5 @@
#pragma warning(push)
#pragma warning(disable:4512)
#pragma warning(disable:4127)
+#pragma warning(disable:4724)
#endif
Modified: trunk/boost/random/uniform_int.hpp
==============================================================================
--- trunk/boost/random/uniform_int.hpp (original)
+++ trunk/boost/random/uniform_int.hpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -115,6 +115,13 @@
private:
+#ifdef BOOST_MSVC
+#pragma warning(push)
+// disable division by zero warning, since we can't
+// actually divide by zero.
+#pragma warning(disable:4723)
+#endif
+
/// \cond hide_private_members
template<class Engine>
static result_type generate(Engine& eng, result_type min_value, result_type /*max_value*/, range_type range)
@@ -271,6 +278,10 @@
}
}
+#ifdef BOOST_MSVC
+#pragma warning(pop)
+#endif
+
void init()
{
_range = random::detail::subtract<result_type>()(_max, _min);
Modified: trunk/boost/random/uniform_smallint.hpp
==============================================================================
--- trunk/boost/random/uniform_smallint.hpp (original)
+++ trunk/boost/random/uniform_smallint.hpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -126,7 +126,7 @@
r_base /= 2;
}
- return ((eng() - (eng.min)()) / _factor) % _range + _min;
+ return static_cast<result_type>(((eng() - (eng.min)()) / _factor) % _range + _min);
}
#ifndef BOOST_RANDOM_NO_STREAM_OPERATORS
Added: trunk/libs/random/extra/Jamfile.v2
==============================================================================
--- (empty file)
+++ trunk/libs/random/extra/Jamfile.v2 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -0,0 +1,10 @@
+# Jamfile.v2
+#
+# Copyright (c) 2009
+# Steven Watanabe
+#
+# 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)
+
+run test_haertel.cpp ;
Copied: trunk/libs/random/extra/haertel.hpp (from r60246, /trunk/libs/random/test/statistic_tests.cpp)
==============================================================================
--- /trunk/libs/random/test/statistic_tests.cpp (original)
+++ trunk/libs/random/extra/haertel.hpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -1,4 +1,4 @@
-/* statistic_tests.cpp file
+/* haertel.hpp file
*
* Copyright Jens Maurer 2000, 2002
* Distributed under the Boost Software License, Version 1.0. (See
@@ -15,20 +15,12 @@
* only as a collection of ideas.
*/
-#include <iostream>
-#include <iomanip>
-#include <string>
-#include <functional>
-#include <math.h> // lgamma is not in namespace std
-#include <vector>
-#include <algorithm>
+#ifndef BOOST_RANDOM_HAERTEL_HPP
+#define BOOST_RANDOM_HAERTEL_HPP
#include <boost/cstdint.hpp>
-#include <boost/random.hpp>
-
-#include "statistic_tests.hpp"
-#include "integrate.hpp"
-
+#include <boost/random/linear_congruential.hpp>
+#include <boost/random/inversive_congruential.hpp>
namespace boost {
namespace random {
@@ -159,506 +151,6 @@
(1<<30)-35, 0> MRG_Acorn7;
typedef boost::random::lagged_fibonacci_int<boost::uint32_t, 607, 273,
0, 0> MRG_Fib2;
-
- template<class Gen, class T>
- inline void check_validation(Gen & gen, T value, const std::string & name)
- {
- for(int i = 0; i < 100000-1; ++i)
- gen();
- if(value != gen())
- std::cout << name << ": validation failed" << std::endl;
- }
-
- // we have validation after 100000 steps with Haertel's generators
- template<class Gen, class T>
- void validate(T value, const std::string & name)
- {
- Gen gen(1234567);
- check_validation(gen, value, name);
- }
-
- void validate_all()
- {
- validate<LCG_Af2>(183269031u, "LCG_Af2");
- validate<LCG_Die1>(522319944u, "LCG_Die1");
- validate<LCG_Fis>(-2065162233u, "LCG_Fis");
- validate<LCG_FM>(581815473u, "LCG_FM");
- validate<LCG_Hae>(28931709, "LCG_Hae");
- validate<LCG_VAX>(1508154087u, "LCG_VAX");
- validate<NLG_Inv2>(6666884, "NLG_Inv2");
- validate<NLG_Inv4>(1521640076, "NLG_Inv4");
- validate<NLG_Inv5>(641840839, "NLG_Inv5");
- static const int acorn7_init[]
- = { 1234567, 7654321, 246810, 108642, 13579, 97531, 555555 };
- MRG_Acorn7 acorn7(acorn7_init);
- check_validation(acorn7, 874294697, "MRG_Acorn7");
- validate<MRG_Fib2>(1234567u, "MRG_Fib2");
- }
} // namespace Haertel
-
-
-
-double normal_density(double x)
-{
- const double pi = 3.14159265358979323846;
- return 1/std::sqrt(2*pi) * std::exp(-x*x/2);
-}
-
-namespace std {
-#ifdef _CXXRTCF_H__
- using _CS_swamp::lgamma;
-#elif defined __SGI_STL_PORT
- using ::lgamma;
#endif
-}
-
-
-class chi_square_density : public std::unary_function<double, double>
-{
-public:
- chi_square_density(int freedom)
- : _exponent( static_cast<double>(freedom)/2-1 ),
- _factor(1/(std::pow(2, _exponent+1) * std::exp(lgamma(_exponent+1))))
- { }
-
- double operator()(double x)
- {
- return _factor*std::pow(x, _exponent)*std::exp(-x/2);
- }
-private:
- double _exponent, _factor;
-};
-
-// computes F(x) or F(y) - F(x)
-class chi_square_probability : public distribution_function<double>
-{
-public:
- chi_square_probability(int freedom) : dens(freedom) {}
- double operator()(double x) { return operator()(0, x); }
- double operator()(double x, double y)
- { return trapezoid(dens, x, y, 1000); }
-private:
- chi_square_density dens;
-};
-
-class uniform_distribution : public distribution_function<double>
-{
-public:
- uniform_distribution(double from, double to) : from(from), to(to)
- { assert(from < to); }
- double operator()(double x)
- {
- if(x < from)
- return 0;
- else if(x > to)
- return 1;
- else
- return (x-from)/(to-from);
- }
- double operator()(double x, double delta)
- { return operator()(x+delta) - operator()(x); }
-private:
- double from, to;
-};
-
-class test_environment;
-
-class test_base
-{
-protected:
- explicit test_base(test_environment & env) : environment(env) { }
- void check(double val) const;
-private:
- test_environment & environment;
-};
-
-class equidistribution_test : test_base
-{
-public:
- equidistribution_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "equidistribution: " << std::flush;
- equidistribution_experiment equi(classes);
- uniform_smallint<RNG> uint_linear(rng, 0, classes-1);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi, uint_linear, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi, uint_linear, n1), 2*n2));
-
- std::cout << " 2D: " << std::flush;
- equidistribution_2d_experiment equi_2d(classes);
- unsigned int root = static_cast<unsigned int>(std::sqrt(double(classes)));
- assert(root * root == classes);
- uniform_smallint<RNG> uint_square(rng, 0, root-1);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi_2d, uint_square, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi_2d, uint_square, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class ks_equidistribution_test : test_base
-{
-public:
- ks_equidistribution_test(test_environment & env, unsigned int classes)
- : test_base(env),
- test_distrib_chi_square(kolmogorov_smirnov_probability(5000),
- classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "KS: " << std::flush;
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- kolmogorov_experiment ks(n1);
- uniform_distribution ud((rng.min)(), (rng.max)());
- check(run_experiment(test_distrib_chi_square,
- ks_experiment_generator(ks, gen_ref, ud), n2));
- check(run_experiment(test_distrib_chi_square,
- ks_experiment_generator(ks, gen_ref, ud), 2*n2));
- }
-private:
- distribution_experiment test_distrib_chi_square;
-};
-
-class runs_test : test_base
-{
-public:
- runs_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "runs: up: " << std::flush;
- runs_experiment<true> r_up(classes);
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_up, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_up, gen_ref, n1), 2*n2));
-
- std::cout << " down: " << std::flush;
- runs_experiment<false> r_down(classes);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_down, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_down, gen_ref, n1), 2*n2));
-
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class gap_test : test_base
-{
-public:
- gap_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "gaps: " << std::flush;
- gap_experiment gap(classes, 0.2, 0.8);
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(gap, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(gap, gen_ref, n1), 2*n2));
-
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class poker_test : test_base
-{
-public:
- poker_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "poker: " << std::flush;
- poker_experiment poker(8, classes);
- uniform_smallint<RNG> usmall(rng, 0, 7);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(poker, usmall, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(poker, usmall, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class coupon_collector_test : test_base
-{
-public:
- coupon_collector_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "coupon collector: " << std::flush;
- coupon_collector_experiment coupon(5, classes);
-
- uniform_smallint<RNG> usmall(rng, 0, 4);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(coupon, usmall, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(coupon, usmall, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class permutation_test : test_base
-{
-public:
- permutation_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(fac<int>(classes)-1),
- high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "permutation: " << std::flush;
- permutation_experiment perm(classes);
-
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class maximum_test : test_base
-{
-public:
- maximum_test(test_environment & env, unsigned int high_classes)
- : test_base(env),
- test_distrib_chi_square(kolmogorov_smirnov_probability(1000),
- high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "maximum-of-t: " << std::flush;
- maximum_experiment<RNG> mx(rng, n1, 5);
- check(run_experiment(test_distrib_chi_square, mx, n2));
- check(run_experiment(test_distrib_chi_square, mx, 2*n2));
- std::cout << std::endl;
- }
-private:
- distribution_experiment test_distrib_chi_square;
-};
-
-class birthday_test : test_base
-{
-public:
- birthday_test(test_environment & env)
- : test_base(env)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "birthday spacing: " << std::flush;
- uniform_int<RNG> uni(rng, 0, (1<<25)-1);
- birthday_spacing_experiment bsp(4, 512, (1<<25));
- std::cout << run_experiment(bsp, uni, n1);
-#if 0
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), 2*n2));
-#endif
- std::cout << std::endl;
- }
-
-
-};
-
-class test_environment
-{
-public:
- static const int classes = 20;
- explicit test_environment(double confid)
- : confidence(confid),
- confidence_chi_square_quantil(quantil(chi_square_density(classes-1), 0, confidence, 1e-4)),
- test_distrib_chi_square6(chi_square_probability(7-1), classes),
- ksequi_test(*this, classes),
- equi_test(*this, 100, classes),
- rns_test(*this, 7, classes),
- gp_test(*this, 7, classes),
- pk_test(*this, 5, classes),
- cpn_test(*this, 15, classes),
- perm_test(*this, 5, classes),
- max_test(*this, classes),
- bday_test(*this)
- {
- std::cout << "Confidence level: " << confid
- << "; 1-alpha = " << (1-confid)
- << "; chi_square(" << (classes-1)
- << ", " << confidence_chi_square_quantil
- << ") = "
- << chi_square_probability(classes-1)(0, confidence_chi_square_quantil)
- << std::endl;
- }
-
- bool check_confidence(double val, double chi_square_conf) const
- {
- std::cout << val;
- bool result = (val <= chi_square_conf);
- if(!result) {
- std::cout << "* [";
- double prob = (val > 10*chi_square_conf ? 1 :
- chi_square_probability(classes-1)(0, val));
- std::cout << (1-prob) << "]";
- }
- std::cout << " " << std::flush;
- return result;
- }
-
- bool check(double chi_square_value) const
- {
- return check_confidence(chi_square_value, confidence_chi_square_quantil);
- }
-
- template<class RNG>
- void run_test(const std::string & name)
- {
- using namespace boost;
-
- std::cout << "Running tests on " << name << std::endl;
-
- RNG rng(1234567);
- typedef boost::uniform_01<RNG> UGen;
-
-#if 1
- ksequi_test.run(rng, 5000, 250);
- equi_test.run(rng, 5000, 250);
- rns_test.run(rng, 100000, 250);
- gp_test.run(rng, 10000, 250);
- pk_test.run(rng, 5000, 250);
- cpn_test.run(rng, 500, 250);
- perm_test.run(rng, 1200, 250);
- max_test.run(rng, 1000, 250);
-#endif
- bday_test.run(rng, 1000, 150);
-
- std::cout << std::endl;
- }
-
-private:
- double confidence;
- double confidence_chi_square_quantil;
- distribution_experiment test_distrib_chi_square6;
- ks_equidistribution_test ksequi_test;
- equidistribution_test equi_test;
- runs_test rns_test;
- gap_test gp_test;
- poker_test pk_test;
- coupon_collector_test cpn_test;
- permutation_test perm_test;
- maximum_test max_test;
- birthday_test bday_test;
-};
-
-void test_base::check(double val) const
-{
- environment.check(val);
-}
-
-void print_ks_table()
-{
- std::cout.setf(std::ios::fixed);
- std::cout.precision(5);
- static const double all_p[] = { 0.01, 0.05, 0.25, 0.5, 0.75, 0.95, 0.99 };
- for(int n = 0; n <= 10000; (n < 55 ? ++n : n *= 10)) {
- std::cout << std::setw(4) << n << " ";
- for(unsigned int i = 0; i < sizeof(all_p)/sizeof(all_p[0]); ++i) {
- std::cout << std::setw(8)
- << (n == 0 ? all_p[i] :
- invert_monotone_inc(kolmogorov_smirnov_probability(n), all_p[i], 0, 10))
- << " ";
- }
- std::cout << std::endl;
- }
-}
-
-int main()
-{
- // Haertel::validate_all();
- test_environment env(0.99);
- env.run_test<boost::minstd_rand>("minstd_rand");
- env.run_test<boost::mt19937>("mt19937");
- env.run_test<Haertel::LCG_Af2>("LCG_Af2");
- env.run_test<Haertel::LCG_Die1>("LCG_Die1");
- env.run_test<Haertel::LCG_Fis>("LCG_Fis");
- env.run_test<Haertel::LCG_FM>("LCG_FM");
- env.run_test<Haertel::LCG_Hae>("LCG_Hae");
- env.run_test<Haertel::LCG_VAX>("LCG_VAX");
- env.run_test<Haertel::NLG_Inv1>("NLG_Inv1");
- env.run_test<Haertel::NLG_Inv2>("NLG_Inv2");
- env.run_test<Haertel::NLG_Inv4>("NLG_Inv4");
- env.run_test<Haertel::NLG_Inv5>("NLG_Inv5");
-}
Copied: trunk/libs/random/extra/test_haertel.cpp (from r60246, /trunk/libs/random/test/statistic_tests.cpp)
==============================================================================
--- /trunk/libs/random/test/statistic_tests.cpp (original)
+++ trunk/libs/random/extra/test_haertel.cpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -1,4 +1,4 @@
-/* statistic_tests.cpp file
+/* haertel.hpp file
*
* Copyright Jens Maurer 2000, 2002
* Distributed under the Boost Software License, Version 1.0. (See
@@ -10,655 +10,53 @@
* Revision history
*/
-/*
- * NOTE: This is not part of the official boost submission. It exists
- * only as a collection of ideas.
- */
-
-#include <iostream>
-#include <iomanip>
#include <string>
-#include <functional>
-#include <math.h> // lgamma is not in namespace std
-#include <vector>
-#include <algorithm>
-
-#include <boost/cstdint.hpp>
-#include <boost/random.hpp>
-
-#include "statistic_tests.hpp"
-#include "integrate.hpp"
-
-
-namespace boost {
-namespace random {
-
-// Wikramaratna 1989 ACORN
-template<class IntType, int k, IntType m, IntType val>
-class additive_congruential
-{
-public:
- typedef IntType result_type;
-#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
- static const bool has_fixed_range = true;
- static const result_type min_value = 0;
- static const result_type max_value = m-1;
-#else
- enum {
- has_fixed_range = true,
- min_value = 0,
- max_value = m-1
- };
-#endif
- template<class InputIterator>
- explicit additive_congruential(InputIterator start) { seed(start); }
- template<class InputIterator>
- void seed(InputIterator start)
- {
- for(int i = 0; i <= k; ++i, ++start)
- values[i] = *start;
- }
-
- result_type operator()()
- {
- for(int i = 1; i <= k; ++i) {
- IntType tmp = values[i-1] + values[i];
- if(tmp >= m)
- tmp -= m;
- values[i] = tmp;
- }
- return values[k];
- }
- result_type validation() const { return val; }
-private:
- IntType values[k+1];
-};
-
-
-template<class IntType, int r, int s, IntType m, IntType val>
-class lagged_fibonacci_int
-{
-public:
- typedef IntType result_type;
-#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
- static const bool has_fixed_range = true;
- static const result_type min_value = 0;
- static const result_type max_value = m-1;
-#else
- enum {
- has_fixed_range = true,
- min_value = 0,
- max_value = m-1
- };
-#endif
- explicit lagged_fibonacci_int(IntType start) { seed(start); }
- template<class Generator>
- explicit lagged_fibonacci_int(Generator & gen) { seed(gen); }
- void seed(IntType start)
- {
- linear_congruential<uint32_t, 299375077, 0, 0, 0> init;
- seed(init);
- }
- template<class Generator>
- void seed(Generator & gen)
- {
- assert(r > s);
- for(int i = 0; i < 607; ++i)
- values[i] = gen();
- current = 0;
- lag = r-s;
- }
-
- result_type operator()()
- {
- result_type tmp = values[current] + values[lag];
- if(tmp >= m)
- tmp -= m;
- values[current] = tmp;
- ++current;
- if(current >= r)
- current = 0;
- ++lag;
- if(lag >= r)
- lag = 0;
- return tmp;
- }
- result_type validation() const { return val; }
-private:
- result_type values[r];
- int current, lag;
-};
-
-} // namespace random
-} // namespace boost
-
-// distributions from Haertel's dissertation
-// (additional parameterizations of the basic templates)
-namespace Haertel {
- typedef boost::random::linear_congruential<boost::uint64_t, 45965, 453816691,
- (boost::uint64_t(1)<<31), 0> LCG_Af2;
- typedef boost::random::linear_congruential<boost::uint64_t, 211936855, 0,
- (boost::uint64_t(1)<<29)-3, 0> LCG_Die1;
- typedef boost::random::linear_congruential<boost::uint32_t, 2824527309u, 0,
- 0, 0> LCG_Fis;
- typedef boost::random::linear_congruential<boost::uint64_t, 950706376u, 0,
- (boost::uint64_t(1)<<31)-1, 0> LCG_FM;
- typedef boost::random::linear_congruential<boost::int32_t, 51081, 0,
- 2147483647, 0> LCG_Hae;
- typedef boost::random::linear_congruential<boost::uint32_t, 69069, 1,
- 0, 0> LCG_VAX;
- typedef boost::random::inversive_congruential<boost::int64_t, 240318, 197,
- 1000081, 0> NLG_Inv1;
- typedef boost::random::inversive_congruential<boost::int64_t, 15707262,
- 13262967, (1<<24)-17, 0> NLG_Inv2;
- typedef boost::random::inversive_congruential<boost::int32_t, 1, 1,
- 2147483647, 0> NLG_Inv4;
- typedef boost::random::inversive_congruential<boost::int32_t, 1, 2,
- 1<<30, 0> NLG_Inv5;
- typedef boost::random::additive_congruential<boost::int32_t, 6,
- (1<<30)-35, 0> MRG_Acorn7;
- typedef boost::random::lagged_fibonacci_int<boost::uint32_t, 607, 273,
- 0, 0> MRG_Fib2;
-
- template<class Gen, class T>
- inline void check_validation(Gen & gen, T value, const std::string & name)
- {
- for(int i = 0; i < 100000-1; ++i)
- gen();
- if(value != gen())
- std::cout << name << ": validation failed" << std::endl;
- }
-
- // we have validation after 100000 steps with Haertel's generators
- template<class Gen, class T>
- void validate(T value, const std::string & name)
- {
- Gen gen(1234567);
- check_validation(gen, value, name);
- }
-
- void validate_all()
- {
- validate<LCG_Af2>(183269031u, "LCG_Af2");
- validate<LCG_Die1>(522319944u, "LCG_Die1");
- validate<LCG_Fis>(-2065162233u, "LCG_Fis");
- validate<LCG_FM>(581815473u, "LCG_FM");
- validate<LCG_Hae>(28931709, "LCG_Hae");
- validate<LCG_VAX>(1508154087u, "LCG_VAX");
- validate<NLG_Inv2>(6666884, "NLG_Inv2");
- validate<NLG_Inv4>(1521640076, "NLG_Inv4");
- validate<NLG_Inv5>(641840839, "NLG_Inv5");
- static const int acorn7_init[]
- = { 1234567, 7654321, 246810, 108642, 13579, 97531, 555555 };
- MRG_Acorn7 acorn7(acorn7_init);
- check_validation(acorn7, 874294697, "MRG_Acorn7");
- validate<MRG_Fib2>(1234567u, "MRG_Fib2");
- }
-} // namespace Haertel
-
-
-
-
-double normal_density(double x)
-{
- const double pi = 3.14159265358979323846;
- return 1/std::sqrt(2*pi) * std::exp(-x*x/2);
-}
-
-namespace std {
-#ifdef _CXXRTCF_H__
- using _CS_swamp::lgamma;
-#elif defined __SGI_STL_PORT
- using ::lgamma;
-#endif
-}
-
-
-class chi_square_density : public std::unary_function<double, double>
-{
-public:
- chi_square_density(int freedom)
- : _exponent( static_cast<double>(freedom)/2-1 ),
- _factor(1/(std::pow(2, _exponent+1) * std::exp(lgamma(_exponent+1))))
- { }
-
- double operator()(double x)
- {
- return _factor*std::pow(x, _exponent)*std::exp(-x/2);
- }
-private:
- double _exponent, _factor;
-};
-
-// computes F(x) or F(y) - F(x)
-class chi_square_probability : public distribution_function<double>
-{
-public:
- chi_square_probability(int freedom) : dens(freedom) {}
- double operator()(double x) { return operator()(0, x); }
- double operator()(double x, double y)
- { return trapezoid(dens, x, y, 1000); }
-private:
- chi_square_density dens;
-};
-
-class uniform_distribution : public distribution_function<double>
-{
-public:
- uniform_distribution(double from, double to) : from(from), to(to)
- { assert(from < to); }
- double operator()(double x)
- {
- if(x < from)
- return 0;
- else if(x > to)
- return 1;
- else
- return (x-from)/(to-from);
- }
- double operator()(double x, double delta)
- { return operator()(x+delta) - operator()(x); }
-private:
- double from, to;
-};
-
-class test_environment;
-
-class test_base
-{
-protected:
- explicit test_base(test_environment & env) : environment(env) { }
- void check(double val) const;
-private:
- test_environment & environment;
-};
-
-class equidistribution_test : test_base
-{
-public:
- equidistribution_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "equidistribution: " << std::flush;
- equidistribution_experiment equi(classes);
- uniform_smallint<RNG> uint_linear(rng, 0, classes-1);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi, uint_linear, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi, uint_linear, n1), 2*n2));
-
- std::cout << " 2D: " << std::flush;
- equidistribution_2d_experiment equi_2d(classes);
- unsigned int root = static_cast<unsigned int>(std::sqrt(double(classes)));
- assert(root * root == classes);
- uniform_smallint<RNG> uint_square(rng, 0, root-1);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi_2d, uint_square, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(equi_2d, uint_square, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class ks_equidistribution_test : test_base
-{
-public:
- ks_equidistribution_test(test_environment & env, unsigned int classes)
- : test_base(env),
- test_distrib_chi_square(kolmogorov_smirnov_probability(5000),
- classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "KS: " << std::flush;
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- kolmogorov_experiment ks(n1);
- uniform_distribution ud((rng.min)(), (rng.max)());
- check(run_experiment(test_distrib_chi_square,
- ks_experiment_generator(ks, gen_ref, ud), n2));
- check(run_experiment(test_distrib_chi_square,
- ks_experiment_generator(ks, gen_ref, ud), 2*n2));
- }
-private:
- distribution_experiment test_distrib_chi_square;
-};
-
-class runs_test : test_base
-{
-public:
- runs_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "runs: up: " << std::flush;
- runs_experiment<true> r_up(classes);
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_up, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_up, gen_ref, n1), 2*n2));
-
- std::cout << " down: " << std::flush;
- runs_experiment<false> r_down(classes);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_down, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(r_down, gen_ref, n1), 2*n2));
-
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class gap_test : test_base
-{
-public:
- gap_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "gaps: " << std::flush;
- gap_experiment gap(classes, 0.2, 0.8);
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(gap, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(gap, gen_ref, n1), 2*n2));
-
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class poker_test : test_base
-{
-public:
- poker_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "poker: " << std::flush;
- poker_experiment poker(8, classes);
- uniform_smallint<RNG> usmall(rng, 0, 7);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(poker, usmall, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(poker, usmall, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class coupon_collector_test : test_base
-{
-public:
- coupon_collector_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(classes-1), high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "coupon collector: " << std::flush;
- coupon_collector_experiment coupon(5, classes);
-
- uniform_smallint<RNG> usmall(rng, 0, 4);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(coupon, usmall, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(coupon, usmall, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class permutation_test : test_base
-{
-public:
- permutation_test(test_environment & env, unsigned int classes,
- unsigned int high_classes)
- : test_base(env), classes(classes),
- test_distrib_chi_square(chi_square_probability(fac<int>(classes)-1),
- high_classes)
- { }
-
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "permutation: " << std::flush;
- permutation_experiment perm(classes);
-
- // generator_reference_t<RNG> gen_ref(rng);
- RNG& gen_ref(rng);
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), 2*n2));
- std::cout << std::endl;
- }
-private:
- unsigned int classes;
- distribution_experiment test_distrib_chi_square;
-};
-
-class maximum_test : test_base
-{
-public:
- maximum_test(test_environment & env, unsigned int high_classes)
- : test_base(env),
- test_distrib_chi_square(kolmogorov_smirnov_probability(1000),
- high_classes)
- { }
+#include <iostream>
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "maximum-of-t: " << std::flush;
- maximum_experiment<RNG> mx(rng, n1, 5);
- check(run_experiment(test_distrib_chi_square, mx, n2));
- check(run_experiment(test_distrib_chi_square, mx, 2*n2));
- std::cout << std::endl;
- }
-private:
- distribution_experiment test_distrib_chi_square;
-};
+#include <boost/format.hpp>
-class birthday_test : test_base
-{
-public:
- birthday_test(test_environment & env)
- : test_base(env)
- { }
+#include "haertel.hpp"
- template<class RNG>
- void run(RNG & rng, int n1, int n2)
- {
- using namespace boost;
- std::cout << "birthday spacing: " << std::flush;
- uniform_int<RNG> uni(rng, 0, (1<<25)-1);
- birthday_spacing_experiment bsp(4, 512, (1<<25));
- std::cout << run_experiment(bsp, uni, n1);
-#if 0
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), n2));
- check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), 2*n2));
-#endif
- std::cout << std::endl;
- }
-
-
-};
+#define BOOST_TEST_MAIN
+#include <boost/test/included/unit_test.hpp>
-class test_environment
+template<class Gen, class T>
+inline void check_validation(Gen & gen, T value, const std::string & name)
{
-public:
- static const int classes = 20;
- explicit test_environment(double confid)
- : confidence(confid),
- confidence_chi_square_quantil(quantil(chi_square_density(classes-1), 0, confidence, 1e-4)),
- test_distrib_chi_square6(chi_square_probability(7-1), classes),
- ksequi_test(*this, classes),
- equi_test(*this, 100, classes),
- rns_test(*this, 7, classes),
- gp_test(*this, 7, classes),
- pk_test(*this, 5, classes),
- cpn_test(*this, 15, classes),
- perm_test(*this, 5, classes),
- max_test(*this, classes),
- bday_test(*this)
- {
- std::cout << "Confidence level: " << confid
- << "; 1-alpha = " << (1-confid)
- << "; chi_square(" << (classes-1)
- << ", " << confidence_chi_square_quantil
- << ") = "
- << chi_square_probability(classes-1)(0, confidence_chi_square_quantil)
- << std::endl;
- }
-
- bool check_confidence(double val, double chi_square_conf) const
- {
- std::cout << val;
- bool result = (val <= chi_square_conf);
- if(!result) {
- std::cout << "* [";
- double prob = (val > 10*chi_square_conf ? 1 :
- chi_square_probability(classes-1)(0, val));
- std::cout << (1-prob) << "]";
- }
- std::cout << " " << std::flush;
- return result;
- }
-
- bool check(double chi_square_value) const
- {
- return check_confidence(chi_square_value, confidence_chi_square_quantil);
- }
-
- template<class RNG>
- void run_test(const std::string & name)
- {
- using namespace boost;
-
- std::cout << "Running tests on " << name << std::endl;
-
- RNG rng(1234567);
- typedef boost::uniform_01<RNG> UGen;
-
-#if 1
- ksequi_test.run(rng, 5000, 250);
- equi_test.run(rng, 5000, 250);
- rns_test.run(rng, 100000, 250);
- gp_test.run(rng, 10000, 250);
- pk_test.run(rng, 5000, 250);
- cpn_test.run(rng, 500, 250);
- perm_test.run(rng, 1200, 250);
- max_test.run(rng, 1000, 250);
-#endif
- bday_test.run(rng, 1000, 150);
-
- std::cout << std::endl;
- }
-
-private:
- double confidence;
- double confidence_chi_square_quantil;
- distribution_experiment test_distrib_chi_square6;
- ks_equidistribution_test ksequi_test;
- equidistribution_test equi_test;
- runs_test rns_test;
- gap_test gp_test;
- poker_test pk_test;
- coupon_collector_test cpn_test;
- permutation_test perm_test;
- maximum_test max_test;
- birthday_test bday_test;
-};
+ for(int i = 0; i < 100000-1; ++i)
+ gen();
-void test_base::check(double val) const
-{
- environment.check(val);
+ typename Gen::result_type actual = gen();
+ BOOST_CHECK_MESSAGE(value == actual,
+ boost::str(boost::format("%s: check value == gen() failed [%d != %d]") %
+ name % value % actual));
}
-void print_ks_table()
+// we have validation after 100000 steps with Haertel's generators
+template<class Gen, class T>
+void validate(T value, const std::string & name)
{
- std::cout.setf(std::ios::fixed);
- std::cout.precision(5);
- static const double all_p[] = { 0.01, 0.05, 0.25, 0.5, 0.75, 0.95, 0.99 };
- for(int n = 0; n <= 10000; (n < 55 ? ++n : n *= 10)) {
- std::cout << std::setw(4) << n << " ";
- for(unsigned int i = 0; i < sizeof(all_p)/sizeof(all_p[0]); ++i) {
- std::cout << std::setw(8)
- << (n == 0 ? all_p[i] :
- invert_monotone_inc(kolmogorov_smirnov_probability(n), all_p[i], 0, 10))
- << " ";
- }
- std::cout << std::endl;
- }
+ Gen gen(1234567);
+ check_validation(gen, value, name);
}
-int main()
+BOOST_AUTO_TEST_CASE(test_haertel)
{
- // Haertel::validate_all();
- test_environment env(0.99);
- env.run_test<boost::minstd_rand>("minstd_rand");
- env.run_test<boost::mt19937>("mt19937");
- env.run_test<Haertel::LCG_Af2>("LCG_Af2");
- env.run_test<Haertel::LCG_Die1>("LCG_Die1");
- env.run_test<Haertel::LCG_Fis>("LCG_Fis");
- env.run_test<Haertel::LCG_FM>("LCG_FM");
- env.run_test<Haertel::LCG_Hae>("LCG_Hae");
- env.run_test<Haertel::LCG_VAX>("LCG_VAX");
- env.run_test<Haertel::NLG_Inv1>("NLG_Inv1");
- env.run_test<Haertel::NLG_Inv2>("NLG_Inv2");
- env.run_test<Haertel::NLG_Inv4>("NLG_Inv4");
- env.run_test<Haertel::NLG_Inv5>("NLG_Inv5");
+ using namespace Haertel;
+ validate<LCG_Af2>(183269031u, "LCG_Af2");
+ validate<LCG_Die1>(522319944u, "LCG_Die1");
+ validate<LCG_Fis>(-2065162233u, "LCG_Fis");
+ validate<LCG_FM>(581815473u, "LCG_FM");
+ validate<LCG_Hae>(28931709, "LCG_Hae");
+ validate<LCG_VAX>(1508154087u, "LCG_VAX");
+ validate<NLG_Inv2>(6666884, "NLG_Inv2");
+ validate<NLG_Inv4>(1521640076, "NLG_Inv4");
+ validate<NLG_Inv5>(641840839, "NLG_Inv5");
+ static const int acorn7_init[]
+ = { 1234567, 7654321, 246810, 108642, 13579, 97531, 555555 };
+ MRG_Acorn7 acorn7(acorn7_init);
+ check_validation(acorn7, 874294697, "MRG_Acorn7");
+ // This currently fails. I don't want to touch it until
+ // I trace the source of this generator. --SJW
+ validate<MRG_Fib2>(1234567u, "MRG_Fib2");
}
Modified: trunk/libs/random/test/Jamfile.v2
==============================================================================
--- trunk/libs/random/test/Jamfile.v2 (original)
+++ trunk/libs/random/test/Jamfile.v2 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -1,4 +1,5 @@
# Copyright 2003 Jens Maurer
+# Copyright 2009-2010 Steven Watanabe
# Distributed under the Boost Software License, Version 1.0. (See accompany-
# ing file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
@@ -43,5 +44,5 @@
# run random_speed.cpp ;
# run statistic_tests.cpp ;
-
-
+exe statistic_tests : statistic_tests.cpp ;
+explicit statistics_tests ;
Modified: trunk/libs/random/test/statistic_tests.cpp
==============================================================================
--- trunk/libs/random/test/statistic_tests.cpp (original)
+++ trunk/libs/random/test/statistic_tests.cpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -10,216 +10,35 @@
* Revision history
*/
-/*
- * NOTE: This is not part of the official boost submission. It exists
- * only as a collection of ideas.
- */
-
#include <iostream>
#include <iomanip>
#include <string>
#include <functional>
-#include <math.h> // lgamma is not in namespace std
#include <vector>
+#include <set>
#include <algorithm>
#include <boost/cstdint.hpp>
#include <boost/random.hpp>
+#include <boost/math/special_functions/gamma.hpp>
+
#include "statistic_tests.hpp"
#include "integrate.hpp"
-namespace boost {
-namespace random {
-
-// Wikramaratna 1989 ACORN
-template<class IntType, int k, IntType m, IntType val>
-class additive_congruential
-{
-public:
- typedef IntType result_type;
-#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
- static const bool has_fixed_range = true;
- static const result_type min_value = 0;
- static const result_type max_value = m-1;
-#else
- enum {
- has_fixed_range = true,
- min_value = 0,
- max_value = m-1
- };
-#endif
- template<class InputIterator>
- explicit additive_congruential(InputIterator start) { seed(start); }
- template<class InputIterator>
- void seed(InputIterator start)
- {
- for(int i = 0; i <= k; ++i, ++start)
- values[i] = *start;
- }
-
- result_type operator()()
- {
- for(int i = 1; i <= k; ++i) {
- IntType tmp = values[i-1] + values[i];
- if(tmp >= m)
- tmp -= m;
- values[i] = tmp;
- }
- return values[k];
- }
- result_type validation() const { return val; }
-private:
- IntType values[k+1];
-};
-
-
-template<class IntType, int r, int s, IntType m, IntType val>
-class lagged_fibonacci_int
-{
-public:
- typedef IntType result_type;
-#ifndef BOOST_NO_INCLASS_MEMBER_INITIALIZATION
- static const bool has_fixed_range = true;
- static const result_type min_value = 0;
- static const result_type max_value = m-1;
-#else
- enum {
- has_fixed_range = true,
- min_value = 0,
- max_value = m-1
- };
-#endif
- explicit lagged_fibonacci_int(IntType start) { seed(start); }
- template<class Generator>
- explicit lagged_fibonacci_int(Generator & gen) { seed(gen); }
- void seed(IntType start)
- {
- linear_congruential<uint32_t, 299375077, 0, 0, 0> init;
- seed(init);
- }
- template<class Generator>
- void seed(Generator & gen)
- {
- assert(r > s);
- for(int i = 0; i < 607; ++i)
- values[i] = gen();
- current = 0;
- lag = r-s;
- }
-
- result_type operator()()
- {
- result_type tmp = values[current] + values[lag];
- if(tmp >= m)
- tmp -= m;
- values[current] = tmp;
- ++current;
- if(current >= r)
- current = 0;
- ++lag;
- if(lag >= r)
- lag = 0;
- return tmp;
- }
- result_type validation() const { return val; }
-private:
- result_type values[r];
- int current, lag;
-};
-
-} // namespace random
-} // namespace boost
-
-// distributions from Haertel's dissertation
-// (additional parameterizations of the basic templates)
-namespace Haertel {
- typedef boost::random::linear_congruential<boost::uint64_t, 45965, 453816691,
- (boost::uint64_t(1)<<31), 0> LCG_Af2;
- typedef boost::random::linear_congruential<boost::uint64_t, 211936855, 0,
- (boost::uint64_t(1)<<29)-3, 0> LCG_Die1;
- typedef boost::random::linear_congruential<boost::uint32_t, 2824527309u, 0,
- 0, 0> LCG_Fis;
- typedef boost::random::linear_congruential<boost::uint64_t, 950706376u, 0,
- (boost::uint64_t(1)<<31)-1, 0> LCG_FM;
- typedef boost::random::linear_congruential<boost::int32_t, 51081, 0,
- 2147483647, 0> LCG_Hae;
- typedef boost::random::linear_congruential<boost::uint32_t, 69069, 1,
- 0, 0> LCG_VAX;
- typedef boost::random::inversive_congruential<boost::int64_t, 240318, 197,
- 1000081, 0> NLG_Inv1;
- typedef boost::random::inversive_congruential<boost::int64_t, 15707262,
- 13262967, (1<<24)-17, 0> NLG_Inv2;
- typedef boost::random::inversive_congruential<boost::int32_t, 1, 1,
- 2147483647, 0> NLG_Inv4;
- typedef boost::random::inversive_congruential<boost::int32_t, 1, 2,
- 1<<30, 0> NLG_Inv5;
- typedef boost::random::additive_congruential<boost::int32_t, 6,
- (1<<30)-35, 0> MRG_Acorn7;
- typedef boost::random::lagged_fibonacci_int<boost::uint32_t, 607, 273,
- 0, 0> MRG_Fib2;
-
- template<class Gen, class T>
- inline void check_validation(Gen & gen, T value, const std::string & name)
- {
- for(int i = 0; i < 100000-1; ++i)
- gen();
- if(value != gen())
- std::cout << name << ": validation failed" << std::endl;
- }
-
- // we have validation after 100000 steps with Haertel's generators
- template<class Gen, class T>
- void validate(T value, const std::string & name)
- {
- Gen gen(1234567);
- check_validation(gen, value, name);
- }
-
- void validate_all()
- {
- validate<LCG_Af2>(183269031u, "LCG_Af2");
- validate<LCG_Die1>(522319944u, "LCG_Die1");
- validate<LCG_Fis>(-2065162233u, "LCG_Fis");
- validate<LCG_FM>(581815473u, "LCG_FM");
- validate<LCG_Hae>(28931709, "LCG_Hae");
- validate<LCG_VAX>(1508154087u, "LCG_VAX");
- validate<NLG_Inv2>(6666884, "NLG_Inv2");
- validate<NLG_Inv4>(1521640076, "NLG_Inv4");
- validate<NLG_Inv5>(641840839, "NLG_Inv5");
- static const int acorn7_init[]
- = { 1234567, 7654321, 246810, 108642, 13579, 97531, 555555 };
- MRG_Acorn7 acorn7(acorn7_init);
- check_validation(acorn7, 874294697, "MRG_Acorn7");
- validate<MRG_Fib2>(1234567u, "MRG_Fib2");
- }
-} // namespace Haertel
-
-
-
-
double normal_density(double x)
{
const double pi = 3.14159265358979323846;
return 1/std::sqrt(2*pi) * std::exp(-x*x/2);
}
-namespace std {
-#ifdef _CXXRTCF_H__
- using _CS_swamp::lgamma;
-#elif defined __SGI_STL_PORT
- using ::lgamma;
-#endif
-}
-
-
class chi_square_density : public std::unary_function<double, double>
{
public:
chi_square_density(int freedom)
: _exponent( static_cast<double>(freedom)/2-1 ),
- _factor(1/(std::pow(2, _exponent+1) * std::exp(lgamma(_exponent+1))))
+ _factor(1/(std::pow(2, _exponent+1) * std::exp(boost::math::lgamma(_exponent+1))))
{ }
double operator()(double x)
@@ -288,7 +107,7 @@
using namespace boost;
std::cout << "equidistribution: " << std::flush;
equidistribution_experiment equi(classes);
- uniform_smallint<RNG> uint_linear(rng, 0, classes-1);
+ variate_generator<RNG&, uniform_smallint<> > uint_linear(rng, uniform_smallint<>(0, classes-1));
check(run_experiment(test_distrib_chi_square,
experiment_generator(equi, uint_linear, n1), n2));
check(run_experiment(test_distrib_chi_square,
@@ -298,7 +117,7 @@
equidistribution_2d_experiment equi_2d(classes);
unsigned int root = static_cast<unsigned int>(std::sqrt(double(classes)));
assert(root * root == classes);
- uniform_smallint<RNG> uint_square(rng, 0, root-1);
+ variate_generator<RNG&, uniform_smallint<> > uint_square(rng, uniform_smallint<>(0, root-1));
check(run_experiment(test_distrib_chi_square,
experiment_generator(equi_2d, uint_square, n1), n2));
check(run_experiment(test_distrib_chi_square,
@@ -327,11 +146,12 @@
// generator_reference_t<RNG> gen_ref(rng);
RNG& gen_ref(rng);
kolmogorov_experiment ks(n1);
- uniform_distribution ud((rng.min)(), (rng.max)());
+ uniform_distribution ud(static_cast<double>((rng.min)()), static_cast<double>((rng.max)()));
check(run_experiment(test_distrib_chi_square,
ks_experiment_generator(ks, gen_ref, ud), n2));
check(run_experiment(test_distrib_chi_square,
ks_experiment_generator(ks, gen_ref, ud), 2*n2));
+ std::cout << std::endl;
}
private:
distribution_experiment test_distrib_chi_square;
@@ -417,7 +237,7 @@
using namespace boost;
std::cout << "poker: " << std::flush;
poker_experiment poker(8, classes);
- uniform_smallint<RNG> usmall(rng, 0, 7);
+ variate_generator<RNG&, uniform_smallint<> > usmall(rng, uniform_smallint<>(0, 7));
check(run_experiment(test_distrib_chi_square,
experiment_generator(poker, usmall, n1), n2));
check(run_experiment(test_distrib_chi_square,
@@ -445,7 +265,7 @@
std::cout << "coupon collector: " << std::flush;
coupon_collector_experiment coupon(5, classes);
- uniform_smallint<RNG> usmall(rng, 0, 4);
+ variate_generator<RNG&, uniform_smallint<> > usmall(rng, uniform_smallint<>(0, 4));
check(run_experiment(test_distrib_chi_square,
experiment_generator(coupon, usmall, n1), n2));
check(run_experiment(test_distrib_chi_square,
@@ -513,8 +333,9 @@
class birthday_test : test_base
{
public:
- birthday_test(test_environment & env)
- : test_base(env)
+ birthday_test(test_environment & env, unsigned int high_classes)
+ : test_base(env),
+ test_distrib_chi_square(chi_square_probability(4-1), high_classes)
{ }
template<class RNG>
@@ -522,21 +343,22 @@
{
using namespace boost;
std::cout << "birthday spacing: " << std::flush;
- uniform_int<RNG> uni(rng, 0, (1<<25)-1);
+ boost::variate_generator<RNG&, boost::uniform_int<> > uni(rng, boost::uniform_int<>(0, (1<<25)-1));
birthday_spacing_experiment bsp(4, 512, (1<<25));
- std::cout << run_experiment(bsp, uni, n1);
-#if 0
check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), n2));
+ experiment_generator(bsp, uni, n1), n2));
check(run_experiment(test_distrib_chi_square,
- experiment_generator(perm, gen_ref, n1), 2*n2));
-#endif
+ experiment_generator(bsp, uni, n1), 2*n2));
std::cout << std::endl;
}
-
-
+private:
+ distribution_experiment test_distrib_chi_square;
};
+#ifdef BOOST_MSVC
+#pragma warning(disable:4355)
+#endif
+
class test_environment
{
public:
@@ -553,7 +375,7 @@
cpn_test(*this, 15, classes),
perm_test(*this, 5, classes),
max_test(*this, classes),
- bday_test(*this)
+ bday_test(*this, classes)
{
std::cout << "Confidence level: " << confid
<< "; 1-alpha = " << (1-confid)
@@ -645,20 +467,60 @@
}
}
-int main()
+class program_args
{
- // Haertel::validate_all();
+public:
+ program_args(int argc, char** argv)
+ {
+ if(argc > 0) {
+ names.insert(argv + 1, argv + argc);
+ }
+ }
+ bool check(std::string test_name) const
+ {
+ return(names.empty() || names.find(test_name) != names.end());
+ }
+private:
+ std::set<std::string> names;
+};
+
+int main(int argc, char* argv[])
+{
+ program_args args(argc, argv);
test_environment env(0.99);
- env.run_test<boost::minstd_rand>("minstd_rand");
- env.run_test<boost::mt19937>("mt19937");
- env.run_test<Haertel::LCG_Af2>("LCG_Af2");
- env.run_test<Haertel::LCG_Die1>("LCG_Die1");
- env.run_test<Haertel::LCG_Fis>("LCG_Fis");
- env.run_test<Haertel::LCG_FM>("LCG_FM");
- env.run_test<Haertel::LCG_Hae>("LCG_Hae");
- env.run_test<Haertel::LCG_VAX>("LCG_VAX");
- env.run_test<Haertel::NLG_Inv1>("NLG_Inv1");
- env.run_test<Haertel::NLG_Inv2>("NLG_Inv2");
- env.run_test<Haertel::NLG_Inv4>("NLG_Inv4");
- env.run_test<Haertel::NLG_Inv5>("NLG_Inv5");
+
+#define TEST(name) \
+ if(args.check(#name)) \
+ env.run_test<boost::name>(#name)
+
+ TEST(minstd_rand0);
+ TEST(minstd_rand);
+ TEST(rand48);
+ TEST(ecuyer1988);
+ TEST(kreutzer1986);
+ TEST(taus88);
+ TEST(hellekalek1995);
+ TEST(mt11213b);
+ TEST(mt19937);
+ TEST(lagged_fibonacci607);
+ TEST(lagged_fibonacci1279);
+ TEST(lagged_fibonacci2281);
+ TEST(lagged_fibonacci3217);
+ TEST(lagged_fibonacci4423);
+ TEST(lagged_fibonacci9689);
+ TEST(lagged_fibonacci19937);
+ TEST(lagged_fibonacci23209);
+ TEST(lagged_fibonacci44497);
+ TEST(ranlux3);
+ TEST(ranlux4);
+
+#if !defined(BOOST_NO_INT64_T) && !defined(BOOST_NO_INTEGRAL_INT64_T)
+ TEST(ranlux64_3);
+ TEST(ranlux64_4);
+#endif
+
+ TEST(ranlux3_01);
+ TEST(ranlux4_01);
+ TEST(ranlux64_3_01);
+ TEST(ranlux64_4_01);
}
Modified: trunk/libs/random/test/statistic_tests.hpp
==============================================================================
--- trunk/libs/random/test/statistic_tests.hpp (original)
+++ trunk/libs/random/test/statistic_tests.hpp 2010-03-07 00:22:40 EST (Sun, 07 Mar 2010)
@@ -84,7 +84,7 @@
: experiment_base(classes) { }
template<class NumberGenerator, class Counter>
- void run(NumberGenerator f, Counter & count, int n) const
+ void run(NumberGenerator & f, Counter & count, int n) const
{
assert((f.min)() == 0 &&
static_cast<unsigned int>((f.max)()) == classes()-1);
@@ -102,7 +102,7 @@
: equidistribution_experiment(classes) { }
template<class NumberGenerator, class Counter>
- void run(NumberGenerator f, Counter & count, int n) const
+ void run(NumberGenerator & f, Counter & count, int n) const
{
unsigned int range = (f.max)()+1;
assert((f.min)() == 0 && range*range == classes());
@@ -137,7 +137,7 @@
}
template<class NumberGenerator, class Counter>
- void run(NumberGenerator f, Counter & count, int n) const
+ void run(NumberGenerator & f, Counter & count, int n) const
{
for(int i = 0; i < n; ++i) {
limits_type::const_iterator it =
@@ -158,7 +158,7 @@
explicit runs_experiment(unsigned int classes) : experiment_base(classes) { }
template<class UniformRandomNumberGenerator, class Counter>
- void run(UniformRandomNumberGenerator f, Counter & count, int n) const
+ void run(UniformRandomNumberGenerator & f, Counter & count, int n) const
{
typedef typename UniformRandomNumberGenerator::result_type result_type;
result_type init = (up ? (f.min)() : (f.max)());
@@ -194,7 +194,7 @@
: experiment_base(classes), alpha(alpha), beta(beta) { }
template<class UniformRandomNumberGenerator, class Counter>
- void run(UniformRandomNumberGenerator f, Counter & count, int n) const
+ void run(UniformRandomNumberGenerator & f, Counter & count, int n) const
{
typedef typename UniformRandomNumberGenerator::result_type result_type;
double range = (f.max)() - (f.min)() + 1.0;
@@ -235,7 +235,7 @@
}
template<class UniformRandomNumberGenerator, class Counter>
- void run(UniformRandomNumberGenerator f, Counter & count, int n) const
+ void run(UniformRandomNumberGenerator & f, Counter & count, int n) const
{
typedef typename UniformRandomNumberGenerator::result_type result_type;
assert(std::numeric_limits<result_type>::is_integer);
@@ -282,7 +282,7 @@
}
template<class UniformRandomNumberGenerator, class Counter>
- void run(UniformRandomNumberGenerator f, Counter & count, int n) const
+ void run(UniformRandomNumberGenerator & f, Counter & count, int n) const
{
typedef typename UniformRandomNumberGenerator::result_type result_type;
assert(std::numeric_limits<result_type>::is_integer);
@@ -330,12 +330,14 @@
}
template<class UniformRandomNumberGenerator, class Counter>
- void run(UniformRandomNumberGenerator f, Counter & count, int n) const
+ void run(UniformRandomNumberGenerator & f, Counter & count, int n) const
{
typedef typename UniformRandomNumberGenerator::result_type result_type;
std::vector<result_type> v(t);
for(int i = 0; i < n; ++i) {
- std::generate_n(v.begin(), t, f);
+ for(int j = 0; j < t; ++j) {
+ v[j] = f();
+ }
int x = 0;
for(int r = t-1; r > 0; r--) {
typename std::vector<result_type>::iterator it =
@@ -360,7 +362,7 @@
}
template<class UniformRandomNumberGenerator, class Counter>
- void run(UniformRandomNumberGenerator f, Counter & count, int n_total) const
+ void run(UniformRandomNumberGenerator & f, Counter & count, int n_total) const
{
typedef typename UniformRandomNumberGenerator::result_type result_type;
assert(std::numeric_limits<result_type>::is_integer);
@@ -452,14 +454,14 @@
public:
kolmogorov_experiment(int n) : n(n), ksp(n) { }
template<class NumberGenerator, class Distribution>
- double run(NumberGenerator gen, Distribution distrib) const
+ double run(NumberGenerator & gen, Distribution distrib) const
{
const int m = n;
typedef std::vector<double> saved_temp;
saved_temp a(m,1.0), b(m,0);
std::vector<int> c(m,0);
for(int i = 0; i < n; ++i) {
- double val = gen();
+ double val = static_cast<double>(gen());
double y = distrib(val);
int k = static_cast<int>(std::floor(m*y));
if(k >= m)
@@ -509,7 +511,7 @@
private:
struct generator {
- generator(base_type & f, int t) : f(f), t(t) { }
+ generator(base_type & f, int t) : f(f, boost::uniform_01<>()), t(t) { }
double operator()()
{
double mx = f();
@@ -518,7 +520,7 @@
return mx;
}
private:
- boost::uniform_01<base_type> f;
+ boost::variate_generator<base_type&, boost::uniform_01<> > f;
int t;
};
base_type & f;
@@ -579,7 +581,7 @@
// chi_square test
template<class Experiment, class Generator>
-double run_experiment(const Experiment & experiment, Generator gen, int n)
+double run_experiment(const Experiment & experiment, Generator & gen, int n)
{
generic_counter<std::vector<int> > v(experiment.classes());
experiment.run(gen, v, n);