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[rand.dist.samp.plinear]. This means we've got a fully tested and functional <random>! 489 tests over 48 sections are passing. :-) The only thing still on my plate in this area is to back-port some of this technology to random_shuffle/shuffle in <algorithm>. That will involve shuffling header bits around (<random> depepends on <algorithm>), but it won't entail that much development (compared to what has been required for <random>).

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git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@104575 91177308-0d34-0410-b5e6-96231b3b80d8
This commit is contained in:
Howard Hinnant
2010-05-25 00:27:34 +00:00
parent fff534ee48
commit 5430540d57
25 changed files with 1880 additions and 2 deletions
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341
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval.pass.cpp Normal file
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//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class RealType = double>
// class piecewise_linear_distribution
// template<class _URNG> result_type operator()(_URNG& g);
#include <iostream>
#include <random>
#include <vector>
#include <iterator>
#include <numeric>
#include <cassert>
template <class T>
inline
T
sqr(T x)
{
return x*x;
}
double
f(double x, double a, double m, double b, double c)
{
return a + m*(sqr(x) - sqr(b))/2 + c*(x-b);
}
int main()
{
{
typedef std::piecewise_linear_distribution<> D;
typedef D::param_type P;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {0, 1, 1, 0};
const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
D d(b, b+Np+1, p);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g);
assert(d.min() <= v && v < d.max());
u.push_back(v);
}
std::sort(u.begin(), u.end());
int kp = -1;
double a;
double m;
double bk;
double c;
std::vector<double> areas(Np);
double S = 0;
for (int i = 0; i < areas.size(); ++i)
{
areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
S += areas[i];
}
for (int i = 0; i < areas.size(); ++i)
areas[i] /= S;
for (int i = 0; i < Np+1; ++i)
p[i] /= S;
for (int i = 0; i < N; ++i)
{
int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
if (k != kp)
{
a = 0;
for (int j = 0; j < k; ++j)
a += areas[j];
m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
bk = b[k];
c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
kp = k;
}
assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
}
}
{
typedef std::piecewise_linear_distribution<> D;
typedef D::param_type P;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {0, 0, 1, 0};
const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
D d(b, b+Np+1, p);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g);
assert(d.min() <= v && v < d.max());
u.push_back(v);
}
std::sort(u.begin(), u.end());
int kp = -1;
double a;
double m;
double bk;
double c;
std::vector<double> areas(Np);
double S = 0;
for (int i = 0; i < areas.size(); ++i)
{
areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
S += areas[i];
}
for (int i = 0; i < areas.size(); ++i)
areas[i] /= S;
for (int i = 0; i < Np+1; ++i)
p[i] /= S;
for (int i = 0; i < N; ++i)
{
int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
if (k != kp)
{
a = 0;
for (int j = 0; j < k; ++j)
a += areas[j];
m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
bk = b[k];
c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
kp = k;
}
assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
}
}
{
typedef std::piecewise_linear_distribution<> D;
typedef D::param_type P;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {1, 0, 0, 0};
const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
D d(b, b+Np+1, p);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g);
assert(d.min() <= v && v < d.max());
u.push_back(v);
}
std::sort(u.begin(), u.end());
int kp = -1;
double a;
double m;
double bk;
double c;
std::vector<double> areas(Np);
double S = 0;
for (int i = 0; i < areas.size(); ++i)
{
areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
S += areas[i];
}
for (int i = 0; i < areas.size(); ++i)
areas[i] /= S;
for (int i = 0; i < Np+1; ++i)
p[i] /= S;
for (int i = 0; i < N; ++i)
{
int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
if (k != kp)
{
a = 0;
for (int j = 0; j < k; ++j)
a += areas[j];
m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
bk = b[k];
c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
kp = k;
}
assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
}
}
{
typedef std::piecewise_linear_distribution<> D;
typedef D::param_type P;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16};
double p[] = {0, 1, 0};
const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
D d(b, b+Np+1, p);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g);
assert(d.min() <= v && v < d.max());
u.push_back(v);
}
std::sort(u.begin(), u.end());
int kp = -1;
double a;
double m;
double bk;
double c;
std::vector<double> areas(Np);
double S = 0;
for (int i = 0; i < areas.size(); ++i)
{
areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
S += areas[i];
}
for (int i = 0; i < areas.size(); ++i)
areas[i] /= S;
for (int i = 0; i < Np+1; ++i)
p[i] /= S;
for (int i = 0; i < N; ++i)
{
int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
if (k != kp)
{
a = 0;
for (int j = 0; j < k; ++j)
a += areas[j];
m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
bk = b[k];
c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
kp = k;
}
assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
}
}
{
typedef std::piecewise_linear_distribution<> D;
typedef D::param_type P;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14};
double p[] = {1, 1};
const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
D d(b, b+Np+1, p);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g);
assert(d.min() <= v && v < d.max());
u.push_back(v);
}
std::sort(u.begin(), u.end());
int kp = -1;
double a;
double m;
double bk;
double c;
std::vector<double> areas(Np);
double S = 0;
for (int i = 0; i < areas.size(); ++i)
{
areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
S += areas[i];
}
for (int i = 0; i < areas.size(); ++i)
areas[i] /= S;
for (int i = 0; i < Np+1; ++i)
p[i] /= S;
for (int i = 0; i < N; ++i)
{
int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
if (k != kp)
{
a = 0;
for (int j = 0; j < k; ++j)
a += areas[j];
m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
bk = b[k];
c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
kp = k;
}
assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
}
}
{
typedef std::piecewise_linear_distribution<> D;
typedef D::param_type P;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5, 0};
const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
D d(b, b+Np+1, p);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g);
assert(d.min() <= v && v < d.max());
u.push_back(v);
}
std::sort(u.begin(), u.end());
int kp = -1;
double a;
double m;
double bk;
double c;
std::vector<double> areas(Np);
double S = 0;
for (int i = 0; i < areas.size(); ++i)
{
areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
S += areas[i];
}
for (int i = 0; i < areas.size(); ++i)
areas[i] /= S;
for (int i = 0; i < Np+1; ++i)
p[i] /= S;
for (int i = 0; i < N; ++i)
{
int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
if (k != kp)
{
a = 0;
for (int j = 0; j < k; ++j)
a += areas[j];
m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
bk = b[k];
c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
kp = k;
}
assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
}
}
}