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[rand.dist.bern.negbin]

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git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@103916 91177308-0d34-0410-b5e6-96231b3b80d8
This commit is contained in:
Howard Hinnant
2010-05-17 00:09:38 +00:00
parent df40dc6c1a
commit f2fe5d5a61
21 changed files with 1137 additions and 5 deletions
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173
include/random
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@@ -669,7 +669,62 @@ template<class IntType = int>
class geometric_distribution;
template<class IntType = int>
class negative_binomial_distribution;
class negative_binomial_distribution
{
public:
// types
typedef IntType result_type;
class param_type
{
public:
typedef negative_binomial_distribution distribution_type;
explicit param_type(result_type k = 1, double p = 0.5);
result_type k() const;
double p() const;
friend bool operator==(const param_type& x, const param_type& y);
friend bool operator!=(const param_type& x, const param_type& y);
};
// constructor and reset functions
explicit negative_binomial_distribution(result_type k = 1, double p = 0.5);
explicit negative_binomial_distribution(const param_type& parm);
void reset();
// generating functions
template<class URNG> result_type operator()(URNG& g);
template<class URNG> result_type operator()(URNG& g, const param_type& parm);
// property functions
result_type k() const;
double p() const;
param_type param() const;
void param(const param_type& parm);
result_type min() const;
result_type max() const;
friend bool operator==(const negative_binomial_distribution& x,
const negative_binomial_distribution& y);
friend bool operator!=(const negative_binomial_distribution& x,
const negative_binomial_distribution& y);
template <class charT, class traits>
friend
basic_ostream<charT, traits>&
operator<<(basic_ostream<charT, traits>& os,
const negative_binomial_distribution& x);
template <class charT, class traits>
friend
basic_istream<charT, traits>&
operator>>(basic_istream<charT, traits>& is,
negative_binomial_distribution& x);
};
template<class IntType = int>
class poisson_distribution
@@ -4098,6 +4153,122 @@ operator>>(basic_istream<_CharT, _Traits>& __is,
return __is;
}
// negative_binomial_distribution
template<class _IntType = int>
class negative_binomial_distribution
{
public:
// types
typedef _IntType result_type;
class param_type
{
result_type __k_;
double __p_;
public:
typedef negative_binomial_distribution distribution_type;
explicit param_type(result_type __k = 1, double __p = 0.5)
: __k_(__k), __p_(__p) {}
result_type k() const {return __k_;}
double p() const {return __p_;}
friend bool operator==(const param_type& __x, const param_type& __y)
{return __x.__k_ == __y.__k_ && __x.__p_ == __y.__p_;}
friend bool operator!=(const param_type& __x, const param_type& __y)
{return !(__x == __y);}
};
private:
param_type __p_;
public:
// constructor and reset functions
explicit negative_binomial_distribution(result_type __k = 1, double __p = 0.5)
: __p_(__k, __p) {}
explicit negative_binomial_distribution(const param_type& __p) : __p_(__p) {}
void reset() {}
// generating functions
template<class _URNG> result_type operator()(_URNG& __g)
{return (*this)(__g, __p_);}
template<class _URNG> result_type operator()(_URNG& __g, const param_type& __p);
// property functions
result_type k() const {return __p_.k();}
double p() const {return __p_.p();}
param_type param() const {return __p_;}
void param(const param_type& __p) {__p_ = __p;}
result_type min() const {return 0;}
result_type max() const {return numeric_limits<result_type>::max();}
friend bool operator==(const negative_binomial_distribution& __x,
const negative_binomial_distribution& __y)
{return __x.__p_ == __y.__p_;}
friend bool operator!=(const negative_binomial_distribution& __x,
const negative_binomial_distribution& __y)
{return !(__x == __y);}
};
template <class _IntType>
template<class _URNG>
_IntType
negative_binomial_distribution<_IntType>::operator()(_URNG& __urng, const param_type& __pr)
{
result_type __k = __pr.k();
double __p = __pr.p();
if (__k <= 21 * __p)
{
bernoulli_distribution __gen(__p);
result_type __f = 0;
result_type __s = 0;
while (__s < __k)
{
if (__gen(__urng))
++__s;
else
++__f;
}
return __f;
}
return poisson_distribution<result_type>(gamma_distribution<double>
(__k, (1-__p)/__p)(__urng))(__urng);
}
template <class _CharT, class _Traits, class _IntType>
basic_ostream<_CharT, _Traits>&
operator<<(basic_ostream<_CharT, _Traits>& __os,
const negative_binomial_distribution<_IntType>& __x)
{
__save_flags<_CharT, _Traits> _(__os);
__os.flags(ios_base::dec | ios_base::left);
_CharT __sp = __os.widen(' ');
__os.fill(__sp);
return __os << __x.k() << __sp << __x.p();
}
template <class _CharT, class _Traits, class _IntType>
basic_istream<_CharT, _Traits>&
operator>>(basic_istream<_CharT, _Traits>& __is,
negative_binomial_distribution<_IntType>& __x)
{
typedef negative_binomial_distribution<_IntType> _Eng;
typedef typename _Eng::result_type result_type;
typedef typename _Eng::param_type param_type;
__save_flags<_CharT, _Traits> _(__is);
__is.flags(ios_base::dec | ios_base::skipws);
result_type __k;
double __p;
__is >> __k >> __p;
if (!__is.fail())
__x.param(param_type(__k, __p));
return __is;
}
// chi_squared_distribution
template<class _RealType = double>

2
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
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@@ -14,8 +14,6 @@
// template<class _URNG> result_type operator()(_URNG& g);
#include <iostream>
#include <random>
#include <numeric>
#include <vector>

34
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/assign.pass.cpp Normal file
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@@ -0,0 +1,34 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// negative_binomial_distribution& operator=(const negative_binomial_distribution&);
#include <random>
#include <cassert>
void
test1()
{
typedef std::negative_binomial_distribution<> D;
D d1(2, 0.75);
D d2;
assert(d1 != d2);
d2 = d1;
assert(d1 == d2);
}
int main()
{
test1();
}

32
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/copy.pass.cpp Normal file
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@@ -0,0 +1,32 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// negative_binomial_distribution(const negative_binomial_distribution&);
#include <random>
#include <cassert>
void
test1()
{
typedef std::negative_binomial_distribution<> D;
D d1(2, 0.75);
D d2 = d1;
assert(d1 == d2);
}
int main()
{
test1();
}

40
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/ctor_int_double.pass.cpp Normal file
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@@ -0,0 +1,40 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// explicit negative_binomial_distribution(IntType t = 1, double p = 0.5);
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
D d;
assert(d.k() == 1);
assert(d.p() == 0.5);
}
{
typedef std::negative_binomial_distribution<> D;
D d(3);
assert(d.k() == 3);
assert(d.p() == 0.5);
}
{
typedef std::negative_binomial_distribution<> D;
D d(3, 0.75);
assert(d.k() == 3);
assert(d.p() == 0.75);
}
}

30
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/ctor_param.pass.cpp Normal file
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@@ -0,0 +1,30 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// explicit negative_binomial_distribution(const param_type& parm);
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type P;
P p(5, 0.25);
D d(p);
assert(d.k() == 5);
assert(d.p() == 0.25);
}
}

43
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eq.pass.cpp Normal file
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@@ -0,0 +1,43 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// bool operator=(const negative_binomial_distribution& x,
// const negative_binomial_distribution& y);
// bool operator!(const negative_binomial_distribution& x,
// const negative_binomial_distribution& y);
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
D d1(3, .25);
D d2(3, .25);
assert(d1 == d2);
}
{
typedef std::negative_binomial_distribution<> D;
D d1(3, .28);
D d2(3, .25);
assert(d1 != d2);
}
{
typedef std::negative_binomial_distribution<> D;
D d1(3, .25);
D d2(4, .25);
assert(d1 != d2);
}
}

270
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp Normal file
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@@ -0,0 +1,270 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// template<class _URNG> result_type operator()(_URNG& g);
#include <random>
#include <numeric>
#include <vector>
#include <cassert>
template <class T>
inline
T
sqr(T x)
{
return x * x;
}
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef std::minstd_rand G;
G g;
D d(5, .25);
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);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = d.k() * (1 - d.p()) / d.p();
double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
}
{
typedef std::negative_binomial_distribution<> D;
typedef std::mt19937 G;
G g;
D d(30, .03125);
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);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = d.k() * (1 - d.p()) / d.p();
double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
}
{
typedef std::negative_binomial_distribution<> D;
typedef std::mt19937 G;
G g;
D d(40, .25);
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);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = d.k() * (1 - d.p()) / d.p();
double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03);
}
{
typedef std::negative_binomial_distribution<> D;
typedef std::mt19937 G;
G g;
D d(40, 1);
const int N = 1000;
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);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = d.k() * (1 - d.p()) / d.p();
double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
assert(mean == x_mean);
assert(var == x_var);
}
{
typedef std::negative_binomial_distribution<> D;
typedef std::mt19937 G;
G g;
D d(400, 0.5);
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);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = d.k() * (1 - d.p()) / d.p();
double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.04);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05);
}
{
typedef std::negative_binomial_distribution<> D;
typedef std::mt19937 G;
G g;
D d(1, 0.05);
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);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = d.k() * (1 - d.p()) / d.p();
double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02);
}
}

158
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp Normal file
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@@ -0,0 +1,158 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
#include <random>
#include <numeric>
#include <vector>
#include <cassert>
template <class T>
inline
T
sqr(T x)
{
return x * x;
}
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type P;
typedef std::minstd_rand G;
G g;
D d(16, .75);
P p(5, .75);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g, p);
assert(d.min() <= v && v <= d.max());
u.push_back(v);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = p.k() * (1 - p.p()) / p.p();
double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
}
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type P;
typedef std::mt19937 G;
G g;
D d(16, .75);
P p(30, .03125);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g, p);
assert(d.min() <= v && v <= d.max());
u.push_back(v);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = p.k() * (1 - p.p()) / p.p();
double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
}
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type P;
typedef std::mt19937 G;
G g;
D d(16, .75);
P p(40, .25);
const int N = 1000000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
{
D::result_type v = d(g, p);
assert(d.min() <= v && v <= d.max());
u.push_back(v);
}
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = p.k() * (1 - p.p()) / p.p();
double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p()));
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03);
}
}

29
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/get_param.pass.cpp Normal file
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@@ -0,0 +1,29 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// param_type param() const;
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type P;
P p(5, .125);
D d(p);
assert(d.param() == p);
}
}

41
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/io.pass.cpp Normal file
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@@ -0,0 +1,41 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// template <class charT, class traits>
// basic_ostream<charT, traits>&
// operator<<(basic_ostream<charT, traits>& os,
// const negative_binomial_distribution& x);
//
// template <class charT, class traits>
// basic_istream<charT, traits>&
// operator>>(basic_istream<charT, traits>& is,
// negative_binomial_distribution& x);
#include <random>
#include <sstream>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
D d1(7, .25);
std::ostringstream os;
os << d1;
std::istringstream is(os.str());
D d2;
is >> d2;
assert(d1 == d2);
}
}

27
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/max.pass.cpp Normal file
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@@ -0,0 +1,27 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// result_type max() const;
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
D d(4, .25);
assert(d.max() == std::numeric_limits<int>::max());
}
}

27
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/min.pass.cpp Normal file
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@@ -0,0 +1,27 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// result_type min() const;
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
D d(4, .5);
assert(d.min() == 0);
}
}

32
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_assign.pass.cpp Normal file
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@@ -0,0 +1,32 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p0(6, .7);
param_type p;
p = p0;
assert(p.k() == 6);
assert(p.p() == .7);
}
}

31
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_copy.pass.cpp Normal file
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@@ -0,0 +1,31 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p0(10, .125);
param_type p = p0;
assert(p.k() == 10);
assert(p.p() == .125);
}
}

44
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_ctor.pass.cpp Normal file
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@@ -0,0 +1,44 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p;
assert(p.k() == 1);
assert(p.p() == 0.5);
}
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p(10);
assert(p.k() == 10);
assert(p.p() == 0.5);
}
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p(10, 0.25);
assert(p.k() == 10);
assert(p.p() == 0.25);
}
}

37
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_eq.pass.cpp Normal file
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@@ -0,0 +1,37 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p1(3, 0.75);
param_type p2(3, 0.75);
assert(p1 == p2);
}
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
param_type p1(3, 0.75);
param_type p2(3, 0.5);
assert(p1 != p2);
}
}

28
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/param_types.pass.cpp Normal file
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@@ -0,0 +1,28 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// {
// class param_type;
#include <random>
#include <type_traits>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type param_type;
typedef param_type::distribution_type distribution_type;
static_assert((std::is_same<D, distribution_type>::value), "");
}
}

30
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/set_param.pass.cpp Normal file
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@@ -0,0 +1,30 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// void param(const param_type& parm);
#include <random>
#include <cassert>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::param_type P;
P p(10, 0.25);
D d(8, 0.75);
d.param(p);
assert(d.param() == p);
}
}

32
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/types.pass.cpp Normal file
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@@ -0,0 +1,32 @@
//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class IntType = int>
// class negative_binomial_distribution
// {
// typedef bool result_type;
#include <random>
#include <type_traits>
int main()
{
{
typedef std::negative_binomial_distribution<> D;
typedef D::result_type result_type;
static_assert((std::is_same<result_type, int>::value), "");
}
{
typedef std::negative_binomial_distribution<long> D;
typedef D::result_type result_type;
static_assert((std::is_same<result_type, long>::value), "");
}
}

2
test/numerics/rand/rand.util/rand.util.canonical/generate_canonical.pass.cpp
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@@ -15,8 +15,6 @@
#include <random>
#include <cassert>
#include <iostream>
int main()
{
{