1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
|
/* test_piecewise_linear.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_linear_distribution.hpp>
#include <boost/random/uniform_int.hpp>
#include <boost/random/mersenne_twister.hpp>
#include <boost/random/variate_generator.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_linear
{
public:
piecewise_linear(const std::vector<double>& intervals, const std::vector<double>& weights)
: intervals(intervals),
weights(weights),
cumulative(1, 0.0)
{
for(std::size_t i = 0; i < weights.size() - 1; ++i) {
cumulative.push_back((weights[i] + weights[i + 1]) / 2);
}
boost::partial_sum(cumulative, cumulative.begin());
double sum = cumulative.back();
for(std::vector<double>::iterator iter = cumulative.begin(), end = cumulative.end();
iter != end; ++iter)
{
*iter /= sum;
}
for(std::vector<double>::iterator iter = this->weights.begin(), end = this->weights.end();
iter != end; ++iter)
{
*iter /= sum;
}
assert(this->weights.size() == this->intervals.size());
assert(this->weights.size() == this->cumulative.size());
}
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 start = cumulative[index - 1];
double lower_weight = weights[index - 1];
double upper_weight = weights[index];
double lower = intervals[index - 1];
double upper = intervals[index];
double mid_weight = (lower_weight * (upper - x) + upper_weight * (x - lower)) / (upper - lower);
double segment_area = (x - lower) * (mid_weight + lower_weight) / 2;
return start + segment_area;
}
}
private:
std::vector<double> intervals;
std::vector<double> weights;
std::vector<double> cumulative;
};
double cdf(const piecewise_linear& dist, double x)
{
return dist.cdf(x);
}
bool do_test(int n, int max) {
std::cout << "running piecewise_linear(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_linear expected(intervals, weights);
boost::random::piecewise_linear_distribution<> dist(intervals, weights);
boost::mt19937 gen;
kolmogorov_experiment test(max);
boost::variate_generator<boost::mt19937&, boost::random::piecewise_linear_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(2, 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_linear -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;
}
}
|
