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[rand.dist.samp.pconst] plus some bug fixes in the tests of the other distributions

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git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@104224 91177308-0d34-0410-b5e6-96231b3b80d8
This commit is contained in:
Howard Hinnant
2010-05-20 15:11:46 +00:00
parent 551d8e4ddb
commit d6d1171f2c
56 changed files with 2593 additions and 393 deletions
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377
include/random
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@@ -371,7 +371,7 @@ typedef subtract_with_carry_engine<uint_fast64_t, 48, 5, 12> ranlux48_base;
typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24; typedef discard_block_engine<ranlux24_base, 223, 23> ranlux24;
typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48; typedef discard_block_engine<ranlux48_base, 389, 11> ranlux48;
typedef shuffle_order_engine<minstd_rand0, 256> knuth_b; typedef shuffle_order_engine<minstd_rand0, 256> knuth_b;
typedef minstd_rand0 default_random_engine; typedef minstd_rand default_random_engine;
// Generators // Generators
@@ -1477,7 +1477,79 @@ public:
}; };
template<class RealType = double> template<class RealType = double>
class piecewise_constant_distribution; class piecewise_constant_distribution
{
// types
typedef RealType result_type;
class param_type
{
public:
typedef piecewise_constant_distribution distribution_type;
param_type();
template<class InputIteratorB, class InputIteratorW>
param_type(InputIteratorB firstB, InputIteratorB lastB,
InputIteratorW firstW);
template<class UnaryOperation>
param_type(initializer_list<result_type> bl, UnaryOperation fw);
template<class UnaryOperation>
param_type(size_t nw, result_type xmin, result_type xmax,
UnaryOperation fw);
vector<result_type> intervals() const;
vector<double> densities() 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
piecewise_constant_distribution();
template<class InputIteratorB, class InputIteratorW>
piecewise_constant_distribution(InputIteratorB firstB,
InputIteratorB lastB,
InputIteratorW firstW);
template<class UnaryOperation>
piecewise_constant_distribution(initializer_list<result_type> bl,
UnaryOperation fw);
template<class UnaryOperation>
piecewise_constant_distribution(size_t nw, result_type xmin,
result_type xmax, UnaryOperation fw);
explicit piecewise_constant_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
vector<result_type> intervals() const;
vector<double> densities() const;
param_type param() const;
void param(const param_type& parm);
result_type min() const;
result_type max() const;
friend bool operator==(const piecewise_constant_distribution& x,
const piecewise_constant_distribution& y);
friend bool operator!=(const piecewise_constant_distribution& x,
const piecewise_constant_distribution& y);
template <class charT, class traits>
friend
basic_ostream<charT, traits>&
operator<<(basic_ostream<charT, traits>& os,
const piecewise_constant_distribution& x);
template <class charT, class traits>
friend
basic_istream<charT, traits>&
operator>>(basic_istream<charT, traits>& is,
piecewise_constant_distribution& x);
};
template<class RealType = double> template<class RealType = double>
class piecewise_linear_distribution; class piecewise_linear_distribution;
@@ -1825,9 +1897,9 @@ operator>>(basic_istream<_CharT, _Traits>& __is,
typedef linear_congruential_engine<uint_fast32_t, 16807, 0, 2147483647> typedef linear_congruential_engine<uint_fast32_t, 16807, 0, 2147483647>
minstd_rand0; minstd_rand0;
typedef minstd_rand0 default_random_engine;
typedef linear_congruential_engine<uint_fast32_t, 48271, 0, 2147483647> typedef linear_congruential_engine<uint_fast32_t, 48271, 0, 2147483647>
minstd_rand; minstd_rand;
typedef minstd_rand default_random_engine;
// mersenne_twister_engine // mersenne_twister_engine
template <class _UIntType, size_t __w, size_t __n, size_t __m, size_t __r, template <class _UIntType, size_t __w, size_t __n, size_t __m, size_t __r,
@@ -3655,7 +3727,8 @@ inline
bernoulli_distribution::result_type bernoulli_distribution::result_type
bernoulli_distribution::operator()(_URNG& __g, const param_type& __p) bernoulli_distribution::operator()(_URNG& __g, const param_type& __p)
{ {
return (__g() - __g.min()) < __p.p() * (__g.max() - __g.min() + 1.); uniform_real_distribution<double> __gen;
return __gen(__g) < __p.p();
} }
template <class _CharT, class _Traits> template <class _CharT, class _Traits>
@@ -5535,7 +5608,7 @@ operator>>(basic_istream<_CharT, _Traits>& __is,
__is.flags(ios_base::dec | ios_base::skipws); __is.flags(ios_base::dec | ios_base::skipws);
size_t __n; size_t __n;
__is >> __n; __is >> __n;
std::vector<double> __p(__n); vector<double> __p(__n);
for (size_t __i = 0; __i < __n; ++__i) for (size_t __i = 0; __i < __n; ++__i)
__is >> __p[__i]; __is >> __p[__i];
if (!__is.fail()) if (!__is.fail())
@@ -5543,6 +5616,300 @@ operator>>(basic_istream<_CharT, _Traits>& __is,
return __is; return __is;
} }
// piecewise_constant_distribution
template<class _RealType = double>
class piecewise_constant_distribution
{
public:
// types
typedef _RealType result_type;
class param_type
{
vector<double> __p_;
vector<result_type> __b_;
public:
typedef piecewise_constant_distribution distribution_type;
param_type();
template<class _InputIteratorB, class _InputIteratorW>
param_type(_InputIteratorB __fB, _InputIteratorB __lB,
_InputIteratorW __fW);
template<class _UnaryOperation>
param_type(initializer_list<result_type> __bl, _UnaryOperation __fw);
template<class _UnaryOperation>
param_type(size_t __nw, result_type __xmin, result_type __xmax,
_UnaryOperation __fw);
vector<result_type> intervals() const {return __b_;}
vector<double> densities() const;
friend bool operator==(const param_type& __x, const param_type& __y)
{return __x.__p_ == __y.__p_ && __x.__b_ == __y.__b_;}
friend bool operator!=(const param_type& __x, const param_type& __y)
{return !(__x == __y);}
private:
void __init();
friend class piecewise_constant_distribution;
template <class _CharT, class _Traits, class _RT>
friend
basic_ostream<_CharT, _Traits>&
operator<<(basic_ostream<_CharT, _Traits>& __os,
const piecewise_constant_distribution<_RT>& __x);
template <class _CharT, class _Traits, class _RT>
friend
basic_istream<_CharT, _Traits>&
operator>>(basic_istream<_CharT, _Traits>& __is,
piecewise_constant_distribution<_RT>& __x);
};
private:
param_type __p_;
public:
// constructor and reset functions
piecewise_constant_distribution() {}
template<class _InputIteratorB, class _InputIteratorW>
piecewise_constant_distribution(_InputIteratorB __fB,
_InputIteratorB __lB,
_InputIteratorW __fW)
: __p_(__fB, __lB, __fW) {}
template<class _UnaryOperation>
piecewise_constant_distribution(initializer_list<result_type> __bl,
_UnaryOperation __fw)
: __p_(__bl, __fw) {}
template<class _UnaryOperation>
piecewise_constant_distribution(size_t __nw, result_type __xmin,
result_type __xmax, _UnaryOperation __fw)
: __p_(__nw, __xmin, __xmax, __fw) {}
explicit piecewise_constant_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
vector<result_type> intervals() const {return __p_.intervals();}
vector<double> densities() const {return __p_.densities();}
param_type param() const {return __p_;}
void param(const param_type& __p) {__p_ = __p;}
result_type min() const {return __p_.__b_.front();}
result_type max() const {return __p_.__b_.back();}
friend bool operator==(const piecewise_constant_distribution& __x,
const piecewise_constant_distribution& __y)
{return __x.__p_ == __y.__p_;}
friend bool operator!=(const piecewise_constant_distribution& __x,
const piecewise_constant_distribution& __y)
{return !(__x == __y);}
template <class _CharT, class _Traits, class _RT>
friend
basic_ostream<_CharT, _Traits>&
operator<<(basic_ostream<_CharT, _Traits>& __os,
const piecewise_constant_distribution<_RT>& __x);
template <class _CharT, class _Traits, class _RT>
friend
basic_istream<_CharT, _Traits>&
operator>>(basic_istream<_CharT, _Traits>& __is,
piecewise_constant_distribution<_RT>& __x);
};
template<class _RealType>
void
piecewise_constant_distribution<_RealType>::param_type::__init()
{
if (!__p_.empty())
{
if (__p_.size() > 1)
{
double __s = _STD::accumulate(__p_.begin(), __p_.end(), 0.0);
for (_STD::vector<double>::iterator __i = __p_.begin(), __e = __p_.end();
__i < __e; ++__i)
*__i /= __s;
vector<double> __t(__p_.size() - 1);
_STD::partial_sum(__p_.begin(), __p_.end() - 1, __t.begin());
swap(__p_, __t);
}
else
{
__p_.clear();
__p_.shrink_to_fit();
}
}
}
template<class _RealType>
piecewise_constant_distribution<_RealType>::param_type::param_type()
: __b_(2)
{
__b_[1] = 1;
}
template<class _RealType>
template<class _InputIteratorB, class _InputIteratorW>
piecewise_constant_distribution<_RealType>::param_type::param_type(
_InputIteratorB __fB, _InputIteratorB __lB, _InputIteratorW __fW)
: __b_(__fB, __lB)
{
if (__b_.size() < 2)
{
__b_.resize(2);
__b_[0] = 0;
__b_[1] = 1;
}
else
{
__p_.reserve(__b_.size() - 1);
for (size_t __i = 0; __i < __b_.size() - 1; ++__i, ++__fW)
__p_.push_back(*__fW);
__init();
}
}
template<class _RealType>
template<class _UnaryOperation>
piecewise_constant_distribution<_RealType>::param_type::param_type(
initializer_list<result_type> __bl, _UnaryOperation __fw)
: __b_(__bl.begin(), __bl.end())
{
if (__b_.size() < 2)
{
__b_.resize(2);
__b_[0] = 0;
__b_[1] = 1;
}
else
{
__p_.reserve(__b_.size() - 1);
for (size_t __i = 0; __i < __b_.size() - 1; ++__i)
__p_.push_back(__fw((__b_[__i+1] + __b_[__i])*.5));
__init();
}
}
template<class _RealType>
template<class _UnaryOperation>
piecewise_constant_distribution<_RealType>::param_type::param_type(
size_t __nw, result_type __xmin, result_type __xmax, _UnaryOperation __fw)
: __b_(__nw == 0 ? 2 : __nw + 1)
{
size_t __n = __b_.size() - 1;
result_type __d = (__xmax - __xmin) / __n;
__p_.reserve(__n);
for (size_t __i = 0; __i < __n; ++__i)
{
__b_[__i] = __xmin + __i * __d;
__p_.push_back(__fw(__b_[__i] + __d*.5));
}
__b_[__n] = __xmax;
__init();
}
template<class _RealType>
vector<double>
piecewise_constant_distribution<_RealType>::param_type::densities() const
{
const size_t __n = __b_.size() - 1;
vector<double> __d(__n);
if (__n == 1)
__d[0] = 1/(__b_[1] - __b_[0]);
else
{
__d[0] = __p_[0] / (__b_[1] - __b_[0]);
for (size_t __i = 1; __i < __n - 1; ++__i)
__d[__i] = (__p_[__i] - __p_[__i-1]) / (__b_[__i+1] - __b_[__i]);
__d[__n-1] = (1 - __p_[__n-2]) / (__b_[__n] - __b_[__n-1]);
}
return __d;
};
template<class _RealType>
template<class _URNG>
_RealType
piecewise_constant_distribution<_RealType>::operator()(_URNG& __g, const param_type& __p)
{
typedef uniform_real_distribution<result_type> _Gen;
if (__p.__b_.size() == 2)
return _Gen(__p.__b_[0], __p.__b_[1])(__g);
result_type __u = _Gen()(__g);
const vector<double>& __dd = __p.__p_;
size_t __k = static_cast<size_t>(_STD::upper_bound(__dd.begin(),
__dd.end(), static_cast<double>(__u)) - __dd.begin());
if (__k == 0)
return static_cast<result_type>(__u * (__p.__b_[1] - __p.__b_[0]) /
__dd[0] + __p.__b_[0]);
__u -= __dd[__k-1];
if (__k == __dd.size())
return static_cast<result_type>(__u * (__p.__b_[__k+1] - __p.__b_[__k]) /
(1 - __dd[__k-1]) + __p.__b_[__k]);
return static_cast<result_type>(__u * (__p.__b_[__k+1] - __p.__b_[__k]) /
(__dd[__k] - __dd[__k-1]) + __p.__b_[__k]);
}
template <class _CharT, class _Traits, class _RT>
basic_ostream<_CharT, _Traits>&
operator<<(basic_ostream<_CharT, _Traits>& __os,
const piecewise_constant_distribution<_RT>& __x)
{
__save_flags<_CharT, _Traits> _(__os);
__os.flags(ios_base::dec | ios_base::left);
_CharT __sp = __os.widen(' ');
__os.fill(__sp);
size_t __n = __x.__p_.__p_.size();
__os << __n;
for (size_t __i = 0; __i < __n; ++__i)
__os << __sp << __x.__p_.__p_[__i];
__n = __x.__p_.__b_.size();
__os << __sp << __n;
for (size_t __i = 0; __i < __n; ++__i)
__os << __sp << __x.__p_.__b_[__i];
return __os;
}
template <class _CharT, class _Traits, class _RT>
basic_istream<_CharT, _Traits>&
operator>>(basic_istream<_CharT, _Traits>& __is,
piecewise_constant_distribution<_RT>& __x)
{
typedef piecewise_constant_distribution<_RT> _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);
size_t __n;
__is >> __n;
vector<double> __p(__n);
for (size_t __i = 0; __i < __n; ++__i)
__is >> __p[__i];
__is >> __n;
vector<result_type> __b(__n);
for (size_t __i = 0; __i < __n; ++__i)
__is >> __b[__i];
if (!__is.fail())
{
swap(__x.__p_.__p_, __p);
swap(__x.__p_.__b_, __b);
}
return __is;
}
_LIBCPP_END_NAMESPACE_STD _LIBCPP_END_NAMESPACE_STD
#endif // _LIBCPP_RANDOM #endif // _LIBCPP_RANDOM

16
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
View File

@@ -59,10 +59,10 @@ int main()
double x_var = d.p()*(1-d.p()); double x_var = d.p()*(1-d.p());
double x_skew = (1 - 2 * d.p())/std::sqrt(x_var); double x_skew = (1 - 2 * d.p())/std::sqrt(x_var);
double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/x_var; double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
{ {
typedef std::bernoulli_distribution D; typedef std::bernoulli_distribution D;
@@ -95,9 +95,9 @@ int main()
double x_var = d.p()*(1-d.p()); double x_var = d.p()*(1-d.p());
double x_skew = (1 - 2 * d.p())/std::sqrt(x_var); double x_skew = (1 - 2 * d.p())/std::sqrt(x_var);
double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/x_var; double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
} }

16
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
View File

@@ -61,10 +61,10 @@ int main()
double x_var = p.p()*(1-p.p()); double x_var = p.p()*(1-p.p());
double x_skew = (1 - 2 * p.p())/std::sqrt(x_var); double x_skew = (1 - 2 * p.p())/std::sqrt(x_var);
double x_kurtosis = (6 * sqr(p.p()) - 6 * p.p() + 1)/x_var; double x_kurtosis = (6 * sqr(p.p()) - 6 * p.p() + 1)/x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
{ {
typedef std::bernoulli_distribution D; typedef std::bernoulli_distribution D;
@@ -99,9 +99,9 @@ int main()
double x_var = p.p()*(1-p.p()); double x_var = p.p()*(1-p.p());
double x_skew = (1 - 2 * p.p())/std::sqrt(x_var); double x_skew = (1 - 2 * p.p())/std::sqrt(x_var);
double x_kurtosis = (6 * sqr(p.p()) - 6 * p.p() + 1)/x_var; double x_kurtosis = (6 * sqr(p.p()) - 6 * p.p() + 1)/x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
} }

40
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
View File

@@ -31,10 +31,10 @@ int main()
{ {
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
typedef std::minstd_rand G; typedef std::mt19937_64 G;
G g; G g;
D d(5, .75); D d(5, .75);
const int N = 100000; const int N = 1000000;
std::vector<D::result_type> u; std::vector<D::result_type> u;
for (int i = 0; i < N; ++i) for (int i = 0; i < N; ++i)
{ {
@@ -64,10 +64,10 @@ int main()
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@@ -144,10 +144,10 @@ int main()
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.03); assert(std::abs((skew - x_skew) / x_skew) < 0.03);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.3);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@@ -260,10 +260,10 @@ int main()
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs(kurtosis - x_kurtosis) < 0.01);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@@ -300,10 +300,10 @@ int main()
double x_var = x_mean*(1-d.p()); double x_var = x_mean*(1-d.p());
double x_skew = (1-2*d.p()) / std::sqrt(x_var); double x_skew = (1-2*d.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var; double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;

30
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
View File

@@ -32,11 +32,11 @@ int main()
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
typedef D::param_type P; typedef D::param_type P;
typedef std::minstd_rand G; typedef std::mt19937_64 G;
G g; G g;
D d(16, .75); D d(16, .75);
P p(5, .75); P p(5, .75);
const int N = 100000; const int N = 1000000;
std::vector<D::result_type> u; std::vector<D::result_type> u;
for (int i = 0; i < N; ++i) for (int i = 0; i < N; ++i)
{ {
@@ -66,10 +66,10 @@ int main()
double x_var = x_mean*(1-p.p()); double x_var = x_mean*(1-p.p());
double x_skew = (1-2*p.p()) / std::sqrt(x_var); double x_skew = (1-2*p.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*p.p()*(1-p.p())) / x_var; double x_kurtosis = (1-6*p.p()*(1-p.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@@ -108,10 +108,10 @@ int main()
double x_var = x_mean*(1-p.p()); double x_var = x_mean*(1-p.p());
double x_skew = (1-2*p.p()) / std::sqrt(x_var); double x_skew = (1-2*p.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*p.p()*(1-p.p())) / x_var; double x_kurtosis = (1-6*p.p()*(1-p.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::binomial_distribution<> D; typedef std::binomial_distribution<> D;
@@ -120,7 +120,7 @@ int main()
G g; G g;
D d(16, .75); D d(16, .75);
P p(40, .25); P p(40, .25);
const int N = 100000; const int N = 1000000;
std::vector<D::result_type> u; std::vector<D::result_type> u;
for (int i = 0; i < N; ++i) for (int i = 0; i < N; ++i)
{ {
@@ -150,9 +150,9 @@ int main()
double x_var = x_mean*(1-p.p()); double x_var = x_mean*(1-p.p());
double x_skew = (1-2*p.p()) / std::sqrt(x_var); double x_skew = (1-2*p.p()) / std::sqrt(x_var);
double x_kurtosis = (1-6*p.p()*(1-p.p())) / x_var; double x_kurtosis = (1-6*p.p()*(1-p.p())) / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.03); assert(std::abs((skew - x_skew) / x_skew) < 0.04);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.3);
} }
} }

48
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt((1 - d.p())); double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p()); double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt((1 - d.p())); double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p()); double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -144,10 +144,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt((1 - d.p())); double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p()); double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -184,10 +184,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt((1 - d.p())); double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p()); double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -224,10 +224,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt((1 - d.p())); double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p()); double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -264,9 +264,9 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt((1 - d.p())); double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p()); double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
View File

@@ -66,10 +66,10 @@ int main()
double x_var = x_mean / p.p(); double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt((1 - p.p())); double x_skew = (2 - p.p()) / std::sqrt((1 - p.p()));
double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p()); double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -108,10 +108,10 @@ int main()
double x_var = x_mean / p.p(); double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt((1 - p.p())); double x_skew = (2 - p.p()) / std::sqrt((1 - p.p()));
double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p()); double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::geometric_distribution<> D; typedef std::geometric_distribution<> D;
@@ -150,9 +150,9 @@ int main()
double x_var = x_mean / p.p(); double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt((1 - p.p())); double x_skew = (2 - p.p()) / std::sqrt((1 - p.p()));
double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p()); double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p());
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
} }

40
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
{ {
typedef std::negative_binomial_distribution<> D; typedef std::negative_binomial_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::negative_binomial_distribution<> D; typedef std::negative_binomial_distribution<> D;
@@ -144,10 +144,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::negative_binomial_distribution<> D; typedef std::negative_binomial_distribution<> D;
@@ -222,10 +222,10 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.04);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
} }
{ {
typedef std::negative_binomial_distribution<> D; typedef std::negative_binomial_distribution<> D;
@@ -262,9 +262,9 @@ int main()
double x_var = x_mean / d.p(); double x_var = x_mean / d.p();
double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
View File

@@ -66,10 +66,10 @@ int main()
double x_var = x_mean / p.p(); double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::negative_binomial_distribution<> D; typedef std::negative_binomial_distribution<> D;
@@ -108,10 +108,10 @@ int main()
double x_var = x_mean / p.p(); double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::negative_binomial_distribution<> D; typedef std::negative_binomial_distribution<> D;
@@ -150,9 +150,9 @@ int main()
double x_var = x_mean / p.p(); double x_var = x_mean / p.p();
double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - 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())); 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((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
double x_var = 2 * d.n(); double x_var = 2 * d.n();
double x_skew = std::sqrt(8 / d.n()); double x_skew = std::sqrt(8 / d.n());
double x_kurtosis = 12 / d.n(); double x_kurtosis = 12 / d.n();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::chi_squared_distribution<> D; typedef std::chi_squared_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = 2 * d.n(); double x_var = 2 * d.n();
double x_skew = std::sqrt(8 / d.n()); double x_skew = std::sqrt(8 / d.n());
double x_kurtosis = 12 / d.n(); double x_kurtosis = 12 / d.n();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::chi_squared_distribution<> D; typedef std::chi_squared_distribution<> D;
@@ -144,9 +144,9 @@ int main()
double x_var = 2 * d.n(); double x_var = 2 * d.n();
double x_skew = std::sqrt(8 / d.n()); double x_skew = std::sqrt(8 / d.n());
double x_kurtosis = 12 / d.n(); double x_kurtosis = 12 / d.n();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
View File

@@ -65,10 +65,10 @@ int main()
double x_var = 2 * p.n(); double x_var = 2 * p.n();
double x_skew = std::sqrt(8 / p.n()); double x_skew = std::sqrt(8 / p.n());
double x_kurtosis = 12 / p.n(); double x_kurtosis = 12 / p.n();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::chi_squared_distribution<> D; typedef std::chi_squared_distribution<> D;
@@ -106,10 +106,10 @@ int main()
double x_var = 2 * p.n(); double x_var = 2 * p.n();
double x_skew = std::sqrt(8 / p.n()); double x_skew = std::sqrt(8 / p.n());
double x_kurtosis = 12 / p.n(); double x_kurtosis = 12 / p.n();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::chi_squared_distribution<> D; typedef std::chi_squared_distribution<> D;
@@ -147,9 +147,9 @@ int main()
double x_var = 2 * p.n(); double x_var = 2 * p.n();
double x_skew = std::sqrt(8 / p.n()); double x_skew = std::sqrt(8 / p.n());
double x_kurtosis = 12 / p.n(); double x_kurtosis = 12 / p.n();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

40
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
View File

@@ -66,10 +66,10 @@ int main()
std::sqrt((std::exp(sqr(d.s())) - 1)); std::sqrt((std::exp(sqr(d.s())) - 1));
double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
3*std::exp(2*sqr(d.s())) - 6; 3*std::exp(2*sqr(d.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.05); assert(std::abs((skew - x_skew) / x_skew) < 0.05);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.25); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -108,10 +108,10 @@ int main()
std::sqrt((std::exp(sqr(d.s())) - 1)); std::sqrt((std::exp(sqr(d.s())) - 1));
double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
3*std::exp(2*sqr(d.s())) - 6; 3*std::exp(2*sqr(d.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -150,10 +150,10 @@ int main()
std::sqrt((std::exp(sqr(d.s())) - 1)); std::sqrt((std::exp(sqr(d.s())) - 1));
double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
3*std::exp(2*sqr(d.s())) - 6; 3*std::exp(2*sqr(d.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.02); assert(std::abs((skew - x_skew) / x_skew) < 0.02);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -192,10 +192,10 @@ int main()
std::sqrt((std::exp(sqr(d.s())) - 1)); std::sqrt((std::exp(sqr(d.s())) - 1));
double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
3*std::exp(2*sqr(d.s())) - 6; 3*std::exp(2*sqr(d.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.02); assert(std::abs((var - x_var) / x_var) < 0.02);
assert(std::abs(skew - x_skew) / x_skew < 0.08); assert(std::abs((skew - x_skew) / x_skew) < 0.08);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.4); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -234,9 +234,9 @@ int main()
std::sqrt((std::exp(sqr(d.s())) - 1)); std::sqrt((std::exp(sqr(d.s())) - 1));
double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
3*std::exp(2*sqr(d.s())) - 6; 3*std::exp(2*sqr(d.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.04); assert(std::abs((var - x_var) / x_var) < 0.04);
assert(std::abs(skew - x_skew) / x_skew < 0.2); assert(std::abs((skew - x_skew) / x_skew) < 0.2);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.7); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7);
} }
} }

40
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
View File

@@ -68,10 +68,10 @@ int main()
std::sqrt((std::exp(sqr(p.s())) - 1)); std::sqrt((std::exp(sqr(p.s())) - 1));
double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
3*std::exp(2*sqr(p.s())) - 6; 3*std::exp(2*sqr(p.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.05); assert(std::abs((skew - x_skew) / x_skew) < 0.05);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.25); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -111,10 +111,10 @@ int main()
std::sqrt((std::exp(sqr(p.s())) - 1)); std::sqrt((std::exp(sqr(p.s())) - 1));
double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
3*std::exp(2*sqr(p.s())) - 6; 3*std::exp(2*sqr(p.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -154,10 +154,10 @@ int main()
std::sqrt((std::exp(sqr(p.s())) - 1)); std::sqrt((std::exp(sqr(p.s())) - 1));
double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
3*std::exp(2*sqr(p.s())) - 6; 3*std::exp(2*sqr(p.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) / x_skew < 0.02); assert(std::abs((skew - x_skew) / x_skew) < 0.02);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -197,10 +197,10 @@ int main()
std::sqrt((std::exp(sqr(p.s())) - 1)); std::sqrt((std::exp(sqr(p.s())) - 1));
double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
3*std::exp(2*sqr(p.s())) - 6; 3*std::exp(2*sqr(p.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.02); assert(std::abs((var - x_var) / x_var) < 0.02);
assert(std::abs(skew - x_skew) / x_skew < 0.08); assert(std::abs((skew - x_skew) / x_skew) < 0.08);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.4); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4);
} }
{ {
typedef std::lognormal_distribution<> D; typedef std::lognormal_distribution<> D;
@@ -240,9 +240,9 @@ int main()
std::sqrt((std::exp(sqr(p.s())) - 1)); std::sqrt((std::exp(sqr(p.s())) - 1));
double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
3*std::exp(2*sqr(p.s())) - 6; 3*std::exp(2*sqr(p.s())) - 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.04); assert(std::abs((var - x_var) / x_var) < 0.04);
assert(std::abs(skew - x_skew) / x_skew < 0.2); assert(std::abs((skew - x_skew) / x_skew) < 0.2);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.7); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7);
} }
} }

4
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
View File

@@ -60,8 +60,8 @@ int main()
double x_var = sqr(d.stddev()); double x_var = sqr(d.stddev());
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 0; double x_kurtosis = 0;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) < 0.01); assert(std::abs(kurtosis - x_kurtosis) < 0.01);
} }

4
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
View File

@@ -61,8 +61,8 @@ int main()
double x_var = sqr(p.stddev()); double x_var = sqr(p.stddev());
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 0; double x_kurtosis = 0;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) < 0.01); assert(std::abs(kurtosis - x_kurtosis) < 0.01);
} }

12
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
View File

@@ -61,9 +61,9 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 6 / (d.n() - 4); double x_kurtosis = 6 / (d.n() - 4);
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.2); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.2);
} }
{ {
typedef std::student_t_distribution<> D; typedef std::student_t_distribution<> D;
@@ -97,9 +97,9 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 6 / (d.n() - 4); double x_kurtosis = 6 / (d.n() - 4);
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.04); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
} }
{ {
typedef std::student_t_distribution<> D; typedef std::student_t_distribution<> D;
@@ -133,8 +133,8 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 6 / (d.n() - 4); double x_kurtosis = 6 / (d.n() - 4);
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
} }

12
test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
View File

@@ -62,9 +62,9 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 6 / (p.n() - 4); double x_kurtosis = 6 / (p.n() - 4);
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.2); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.2);
} }
{ {
typedef std::student_t_distribution<> D; typedef std::student_t_distribution<> D;
@@ -99,9 +99,9 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 6 / (p.n() - 4); double x_kurtosis = 6 / (p.n() - 4);
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.04); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
} }
{ {
typedef std::student_t_distribution<> D; typedef std::student_t_distribution<> D;
@@ -136,8 +136,8 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = 6 / (p.n() - 4); double x_kurtosis = 6 / (p.n() - 4);
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
double x_var = 1/sqr(d.lambda()); double x_var = 1/sqr(d.lambda());
double x_skew = 2; double x_skew = 2;
double x_kurtosis = 6; double x_kurtosis = 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::exponential_distribution<> D; typedef std::exponential_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = 1/sqr(d.lambda()); double x_var = 1/sqr(d.lambda());
double x_skew = 2; double x_skew = 2;
double x_kurtosis = 6; double x_kurtosis = 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::exponential_distribution<> D; typedef std::exponential_distribution<> D;
@@ -144,9 +144,9 @@ int main()
double x_var = 1/sqr(d.lambda()); double x_var = 1/sqr(d.lambda());
double x_skew = 2; double x_skew = 2;
double x_kurtosis = 6; double x_kurtosis = 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

8
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
View File

@@ -65,9 +65,9 @@ int main()
double x_var = 1/sqr(p.lambda()); double x_var = 1/sqr(p.lambda());
double x_skew = 2; double x_skew = 2;
double x_kurtosis = 6; double x_kurtosis = 6;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

32
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
View File

@@ -63,10 +63,10 @@ int main()
double x_var = sqr(d.b()) * 1.644934067; double x_var = sqr(d.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::extreme_value_distribution<> D; typedef std::extreme_value_distribution<> D;
@@ -102,10 +102,10 @@ int main()
double x_var = sqr(d.b()) * 1.644934067; double x_var = sqr(d.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::extreme_value_distribution<> D; typedef std::extreme_value_distribution<> D;
@@ -141,10 +141,10 @@ int main()
double x_var = sqr(d.b()) * 1.644934067; double x_var = sqr(d.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::extreme_value_distribution<> D; typedef std::extreme_value_distribution<> D;
@@ -180,9 +180,9 @@ int main()
double x_var = sqr(d.b()) * 1.644934067; double x_var = sqr(d.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

32
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
double x_var = sqr(p.b()) * 1.644934067; double x_var = sqr(p.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::extreme_value_distribution<> D; typedef std::extreme_value_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = sqr(p.b()) * 1.644934067; double x_var = sqr(p.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::extreme_value_distribution<> D; typedef std::extreme_value_distribution<> D;
@@ -144,10 +144,10 @@ int main()
double x_var = sqr(p.b()) * 1.644934067; double x_var = sqr(p.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::extreme_value_distribution<> D; typedef std::extreme_value_distribution<> D;
@@ -184,9 +184,9 @@ int main()
double x_var = sqr(p.b()) * 1.644934067; double x_var = sqr(p.b()) * 1.644934067;
double x_skew = 1.139547; double x_skew = 1.139547;
double x_kurtosis = 12./5; double x_kurtosis = 12./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
double x_var = d.alpha() * sqr(d.beta()); double x_var = d.alpha() * sqr(d.beta());
double x_skew = 2 / std::sqrt(d.alpha()); double x_skew = 2 / std::sqrt(d.alpha());
double x_kurtosis = 6 / d.alpha(); double x_kurtosis = 6 / d.alpha();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::gamma_distribution<> D; typedef std::gamma_distribution<> D;
@@ -104,10 +104,10 @@ int main()
double x_var = d.alpha() * sqr(d.beta()); double x_var = d.alpha() * sqr(d.beta());
double x_skew = 2 / std::sqrt(d.alpha()); double x_skew = 2 / std::sqrt(d.alpha());
double x_kurtosis = 6 / d.alpha(); double x_kurtosis = 6 / d.alpha();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::gamma_distribution<> D; typedef std::gamma_distribution<> D;
@@ -144,9 +144,9 @@ int main()
double x_var = d.alpha() * sqr(d.beta()); double x_var = d.alpha() * sqr(d.beta());
double x_skew = 2 / std::sqrt(d.alpha()); double x_skew = 2 / std::sqrt(d.alpha());
double x_kurtosis = 6 / d.alpha(); double x_kurtosis = 6 / d.alpha();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
View File

@@ -65,10 +65,10 @@ int main()
double x_var = p.alpha() * sqr(p.beta()); double x_var = p.alpha() * sqr(p.beta());
double x_skew = 2 / std::sqrt(p.alpha()); double x_skew = 2 / std::sqrt(p.alpha());
double x_kurtosis = 6 / p.alpha(); double x_kurtosis = 6 / p.alpha();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::gamma_distribution<> D; typedef std::gamma_distribution<> D;
@@ -106,10 +106,10 @@ int main()
double x_var = p.alpha() * sqr(p.beta()); double x_var = p.alpha() * sqr(p.beta());
double x_skew = 2 / std::sqrt(p.alpha()); double x_skew = 2 / std::sqrt(p.alpha());
double x_kurtosis = 6 / p.alpha(); double x_kurtosis = 6 / p.alpha();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::gamma_distribution<> D; typedef std::gamma_distribution<> D;
@@ -147,9 +147,9 @@ int main()
double x_var = p.alpha() * sqr(p.beta()); double x_var = p.alpha() * sqr(p.beta());
double x_skew = 2 / std::sqrt(p.alpha()); double x_skew = 2 / std::sqrt(p.alpha());
double x_kurtosis = 6 / p.alpha(); double x_kurtosis = 6 / p.alpha();
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
View File

@@ -63,10 +63,10 @@ int main()
double x_var = d.mean(); double x_var = d.mean();
double x_skew = 1 / std::sqrt(x_var); double x_skew = 1 / std::sqrt(x_var);
double x_kurtosis = 1 / x_var; double x_kurtosis = 1 / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::poisson_distribution<> D; typedef std::poisson_distribution<> D;
@@ -102,10 +102,10 @@ int main()
double x_var = d.mean(); double x_var = d.mean();
double x_skew = 1 / std::sqrt(x_var); double x_skew = 1 / std::sqrt(x_var);
double x_kurtosis = 1 / x_var; double x_kurtosis = 1 / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.04); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
} }
{ {
typedef std::poisson_distribution<> D; typedef std::poisson_distribution<> D;
@@ -141,9 +141,9 @@ int main()
double x_var = d.mean(); double x_var = d.mean();
double x_skew = 1 / std::sqrt(x_var); double x_skew = 1 / std::sqrt(x_var);
double x_kurtosis = 1 / x_var; double x_kurtosis = 1 / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
View File

@@ -65,10 +65,10 @@ int main()
double x_var = p.mean(); double x_var = p.mean();
double x_skew = 1 / std::sqrt(x_var); double x_skew = 1 / std::sqrt(x_var);
double x_kurtosis = 1 / x_var; double x_kurtosis = 1 / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::poisson_distribution<> D; typedef std::poisson_distribution<> D;
@@ -106,10 +106,10 @@ int main()
double x_var = p.mean(); double x_var = p.mean();
double x_skew = 1 / std::sqrt(x_var); double x_skew = 1 / std::sqrt(x_var);
double x_kurtosis = 1 / x_var; double x_kurtosis = 1 / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.04); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
} }
{ {
typedef std::poisson_distribution<> D; typedef std::poisson_distribution<> D;
@@ -147,9 +147,9 @@ int main()
double x_var = p.mean(); double x_var = p.mean();
double x_skew = 1 / std::sqrt(x_var); double x_skew = 1 / std::sqrt(x_var);
double x_kurtosis = 1 / x_var; double x_kurtosis = 1 / x_var;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
View File

@@ -68,10 +68,10 @@ int main()
double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) - double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) -
4*x_skew*x_var*sqrt(x_var)*x_mean - 4*x_skew*x_var*sqrt(x_var)*x_mean -
6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3; 6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::weibull_distribution<> D; typedef std::weibull_distribution<> D;
@@ -112,10 +112,10 @@ int main()
double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) - double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) -
4*x_skew*x_var*sqrt(x_var)*x_mean - 4*x_skew*x_var*sqrt(x_var)*x_mean -
6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3; 6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::weibull_distribution<> D; typedef std::weibull_distribution<> D;
@@ -156,9 +156,9 @@ int main()
double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) - double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) -
4*x_skew*x_var*sqrt(x_var)*x_mean - 4*x_skew*x_var*sqrt(x_var)*x_mean -
6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3; 6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
} }

24
test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
View File

@@ -69,10 +69,10 @@ int main()
double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) - double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) -
4*x_skew*x_var*sqrt(x_var)*x_mean - 4*x_skew*x_var*sqrt(x_var)*x_mean -
6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3; 6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::weibull_distribution<> D; typedef std::weibull_distribution<> D;
@@ -114,10 +114,10 @@ int main()
double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) - double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) -
4*x_skew*x_var*sqrt(x_var)*x_mean - 4*x_skew*x_var*sqrt(x_var)*x_mean -
6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3; 6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
{ {
typedef std::weibull_distribution<> D; typedef std::weibull_distribution<> D;
@@ -159,9 +159,9 @@ int main()
double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) - double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) -
4*x_skew*x_var*sqrt(x_var)*x_mean - 4*x_skew*x_var*sqrt(x_var)*x_mean -
6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3; 6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 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((skew - x_skew) / x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
} }
} }

36
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp Normal file
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@@ -0,0 +1,36 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// piecewise_constant_distribution& operator=(const piecewise_constant_distribution&);
#include <random>
#include <cassert>
void
test1()
{
typedef std::piecewise_constant_distribution<> D;
double p[] = {2, 4, 1, 8};
double b[] = {2, 4, 5, 8, 9};
D d1(b, b+5, p);
D d2;
assert(d1 != d2);
d2 = d1;
assert(d1 == d2);
}
int main()
{
test1();
}

34
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.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 RealType = double>
// class piecewise_constant_distribution
// piecewise_constant_distribution(const piecewise_constant_distribution&);
#include <random>
#include <cassert>
void
test1()
{
typedef std::piecewise_constant_distribution<> D;
double p[] = {2, 4, 1, 8};
double b[] = {2, 4, 5, 8, 9};
D d1(b, b+5, p);
D d2 = d1;
assert(d1 == d2);
}
int main()
{
test1();
}

33
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp Normal file
View File

@@ -0,0 +1,33 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// piecewise_constant_distribution(initializer_list<double> wl);
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
D d;
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
}

64
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp Normal file
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@@ -0,0 +1,64 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// template<class UnaryOperation>
// piecewise_constant_distribution(size_t nw, result_type xmin,
// result_type xmax, UnaryOperation fw);
#include <random>
#include <cassert>
double fw(double x)
{
return 2*x;
}
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
D d(0, 0, 1, fw);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
D d(1, 10, 12, fw);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 10);
assert(iv[1] == 12);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 0.5);
}
{
typedef std::piecewise_constant_distribution<> D;
D d(2, 6, 14, fw);
std::vector<double> iv = d.intervals();
assert(iv.size() == 3);
assert(iv[0] == 6);
assert(iv[1] == 10);
assert(iv[2] == 14);
std::vector<double> dn = d.densities();
assert(dn.size() == 2);
assert(dn[0] == 0.1);
assert(dn[1] == 0.15);
}
}

78
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp Normal file
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@@ -0,0 +1,78 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// piecewise_constant_distribution(initializer_list<result_type> bl,
// UnaryOperation fw);
#include <iostream>
#include <random>
#include <cassert>
double f(double x)
{
return x*2;
}
int main()
{
#ifdef _LIBCPP_MOVE
{
typedef std::piecewise_constant_distribution<> D;
D d({}, f);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
D d({12}, f);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
D d({12, 14}, f);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 12);
assert(iv[1] == 14);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 0.5);
}
{
typedef std::piecewise_constant_distribution<> D;
D d({5.5, 7.5, 11.5}, f);
std::vector<double> iv = d.intervals();
assert(iv.size() == 3);
assert(iv[0] == 5.5);
assert(iv[1] == 7.5);
assert(iv[2] == 11.5);
std::vector<double> dn = d.densities();
assert(dn.size() == 2);
assert(dn[0] == 0.203125);
assert(dn[1] == 0.1484375);
}
#endif
}

96
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp Normal file
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@@ -0,0 +1,96 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// template<class InputIterator>
// piecewise_constant_distribution(InputIteratorB firstB,
// InputIteratorB lastB,
// InputIteratorW firstW);
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10};
double p[] = {12};
D d(b, b, p);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10};
double p[] = {12};
D d(b, b+1, p);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 15};
double p[] = {12};
D d(b, b+2, p);
std::vector<double> iv = d.intervals();
assert(iv.size() == 2);
assert(iv[0] == 10);
assert(iv[1] == 15);
std::vector<double> dn = d.densities();
assert(dn.size() == 1);
assert(dn[0] == 1/5.);
}
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 15, 16};
double p[] = {.25, .75};
D d(b, b+3, p);
std::vector<double> iv = d.intervals();
assert(iv.size() == 3);
assert(iv[0] == 10);
assert(iv[1] == 15);
assert(iv[2] == 16);
std::vector<double> dn = d.densities();
assert(dn.size() == 2);
assert(dn[0] == .25/5.);
assert(dn[1] == .75);
}
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
D d(b, b+4, p);
std::vector<double> iv = d.intervals();
assert(iv.size() == 4);
assert(iv[0] == 10);
assert(iv[1] == 14);
assert(iv[2] == 16);
assert(iv[3] == 17);
std::vector<double> dn = d.densities();
assert(dn.size() == 3);
assert(dn[0] == .0625);
assert(dn[1] == .3125);
assert(dn[2] == .125);
}
}

41
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.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 RealType = double>
// class piecewise_constant_distribution
// explicit piecewise_constant_distribution(const param_type& parm);
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
P pa(b, b+4, p);
D d(pa);
std::vector<double> iv = d.intervals();
assert(iv.size() == 4);
assert(iv[0] == 10);
assert(iv[1] == 14);
assert(iv[2] == 16);
assert(iv[3] == 17);
std::vector<double> dn = d.densities();
assert(dn.size() == 3);
assert(dn[0] == .0625);
assert(dn[1] == .3125);
assert(dn[2] == .125);
}
}

47
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp Normal file
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@@ -0,0 +1,47 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// bool operator=(const piecewise_constant_distribution& x,
// const piecewise_constant_distribution& y);
// bool operator!(const piecewise_constant_distribution& x,
// const piecewise_constant_distribution& y);
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
D d1;
D d2;
assert(d1 == d2);
}
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
D d1(b, b+4, p);
D d2(b, b+4, p);
assert(d1 == d2);
}
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
D d1(b, b+4, p);
D d2;
assert(d1 != d2);
}
}

693
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp Normal file
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@@ -0,0 +1,693 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// template<class _URNG> result_type operator()(_URNG& g);
#include <random>
#include <vector>
#include <iterator>
#include <numeric>
#include <cassert>
template <class T>
inline
T
sqr(T x)
{
return x*x;
}
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {0, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {25, 0, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 0};
const size_t Np = sizeof(p) / sizeof(p[0]);
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {25, 0, 0};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {0, 25, 0};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16, 17};
double p[] = {0, 0, 1};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16};
double p[] = {75, 25};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16};
double p[] = {0, 25};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14, 16};
double p[] = {1, 0};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
{
typedef std::piecewise_constant_distribution<> D;
typedef std::mt19937_64 G;
G g;
double b[] = {10, 14};
double p[] = {1};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
const int N = 100000;
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::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
}

95
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp Normal file
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@@ -0,0 +1,95 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
#include <random>
#include <vector>
#include <iterator>
#include <numeric>
#include <cassert>
template <class T>
inline
T
sqr(T x)
{
return x*x;
}
int main()
{
{
typedef std::piecewise_constant_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};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d;
P pa(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, pa);
assert(10 <= v && v < 17);
u.push_back(v);
}
std::vector<double> prob(std::begin(p), std::end(p));
double s = std::accumulate(prob.begin(), prob.end(), 0.0);
for (int i = 0; i < prob.size(); ++i)
prob[i] /= s;
std::sort(u.begin(), u.end());
for (int i = 0; i < Np; ++i)
{
typedef std::vector<D::result_type>::iterator I;
I lb = std::lower_bound(u.begin(), u.end(), b[i]);
I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
const size_t Ni = ub - lb;
if (prob[i] == 0)
assert(Ni == 0);
else
{
assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
double mean = std::accumulate(lb, ub, 0.0) / Ni;
double var = 0;
double skew = 0;
double kurtosis = 0;
for (I j = lb; j != ub; ++j)
{
double d = (*j - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= Ni;
double dev = std::sqrt(var);
skew /= Ni * dev * var;
kurtosis /= Ni * var * var;
kurtosis -= 3;
double x_mean = (b[i+1] + b[i]) / 2;
double x_var = sqr(b[i+1] - b[i]) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
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) < 0.01);
assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
}
}
}
}

32
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.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 RealType = double>
// class piecewise_constant_distribution
// param_type param() const;
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
P pa(b, b+Np+1, p);
D d(pa);
assert(d.param() == pa);
}
}

44
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.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 RealType = double>
// class piecewise_constant_distribution
// template <class charT, class traits>
// basic_ostream<charT, traits>&
// operator<<(basic_ostream<charT, traits>& os,
// const piecewise_constant_distribution& x);
//
// template <class charT, class traits>
// basic_istream<charT, traits>&
// operator>>(basic_istream<charT, traits>& is,
// piecewise_constant_distribution& x);
#include <random>
#include <sstream>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d1(b, b+Np+1, p);
std::ostringstream os;
os << d1;
std::istringstream is(os.str());
D d2;
is >> d2;
assert(d1 == d2);
}
}

30
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.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 RealType = double>
// class piecewise_constant_distribution
// result_type max() const;
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
assert(d.max() == 17);
}
}

30
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.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 RealType = double>
// class piecewise_constant_distribution
// result_type min() const;
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
D d(b, b+Np+1, p);
assert(d.min() == 10);
}
}

34
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_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 RealType = double>
// class piecewise_constant_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
P p0(b, b+Np+1, p);
P p1;
p1 = p0;
assert(p1 == p0);
}
}

33
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp Normal file
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@@ -0,0 +1,33 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
const size_t Np = sizeof(p) / sizeof(p[0]);
P p0(b, b+Np+1, p);
P p1 = p0;
assert(p1 == p0);
}
}

34
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.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 RealType = double>
// class piecewise_constant_distribution
// param_type();
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa;
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
}

67
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp Normal file
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@@ -0,0 +1,67 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// template<class UnaryOperation>
// param_type(size_t nw, double xmin, double xmax,
// UnaryOperation fw);
#include <random>
#include <cassert>
double fw(double x)
{
return 2*x;
}
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa(0, 0, 1, fw);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa(1, 10, 12, fw);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 10);
assert(iv[1] == 12);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 0.5);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa(2, 6, 14, fw);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 3);
assert(iv[0] == 6);
assert(iv[1] == 10);
assert(iv[2] == 14);
std::vector<double> dn = pa.densities();
assert(dn.size() == 2);
assert(dn[0] == 0.1);
assert(dn[1] == 0.15);
}
}

79
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp Normal file
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@@ -0,0 +1,79 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// param_type(initializer_list<result_type> bl, UnaryOperation fw);
#include <random>
#include <cassert>
double f(double x)
{
return x*2;
}
int main()
{
#ifdef _LIBCPP_MOVE
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa({}, f);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa({12}, f);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa({12, 14}, f);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 12);
assert(iv[1] == 14);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 0.5);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
P pa({5.5, 7.5, 11.5}, f);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 3);
assert(iv[0] == 5.5);
assert(iv[1] == 7.5);
assert(iv[2] == 11.5);
std::vector<double> dn = pa.densities();
assert(dn.size() == 2);
assert(dn[0] == 0.203125);
assert(dn[1] == 0.1484375);
}
#endif
}

100
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp Normal file
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@@ -0,0 +1,100 @@
//===----------------------------------------------------------------------===//
//
// 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_constant_distribution
// template<class InputIterator>
// param_type(InputIteratorB firstB, InputIteratorB lastB,
// InputIteratorW firstW);
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10};
double p[] = {12};
P pa(b, b, p);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10};
double p[] = {12};
P pa(b, b+1, p);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 0);
assert(iv[1] == 1);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 15};
double p[] = {12};
P pa(b, b+2, p);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 2);
assert(iv[0] == 10);
assert(iv[1] == 15);
std::vector<double> dn = pa.densities();
assert(dn.size() == 1);
assert(dn[0] == 1/5.);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 15, 16};
double p[] = {.25, .75};
P pa(b, b+3, p);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 3);
assert(iv[0] == 10);
assert(iv[1] == 15);
assert(iv[2] == 16);
std::vector<double> dn = pa.densities();
assert(dn.size() == 2);
assert(dn[0] == .25/5.);
assert(dn[1] == .75);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
P pa(b, b+4, p);
std::vector<double> iv = pa.intervals();
assert(iv.size() == 4);
assert(iv[0] == 10);
assert(iv[1] == 14);
assert(iv[2] == 16);
assert(iv[3] == 17);
std::vector<double> dn = pa.densities();
assert(dn.size() == 3);
assert(dn[0] == .0625);
assert(dn[1] == .3125);
assert(dn[2] == .125);
}
}

41
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.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 RealType = double>
// class piecewise_constant_distribution
// {
// class param_type;
#include <random>
#include <limits>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
P p1(b, b+4, p);
P p2(b, b+4, p);
assert(p1 == p2);
}
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
P p1(b, b+3, p);
P p2(b, b+4, p);
assert(p1 != p2);
}
}

28
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/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 RealType = double>
// class piecewise_constant_distribution
// {
// class param_type;
#include <random>
#include <type_traits>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type param_type;
typedef param_type::distribution_type distribution_type;
static_assert((std::is_same<D, distribution_type>::value), "");
}
}

32
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.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 RealType = double>
// class piecewise_constant_distribution
// void param(const param_type& parm);
#include <random>
#include <cassert>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::param_type P;
double b[] = {10, 14, 16, 17};
double p[] = {25, 62.5, 12.5};
P pa(b, b+4, p);
D d;
d.param(pa);
assert(d.param() == pa);
}
}

32
test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/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 RealType = double>
// class piecewise_constant_distribution
// {
// typedef bool result_type;
#include <random>
#include <type_traits>
int main()
{
{
typedef std::piecewise_constant_distribution<> D;
typedef D::result_type result_type;
static_assert((std::is_same<result_type, double>::value), "");
}
{
typedef std::piecewise_constant_distribution<float> D;
typedef D::result_type result_type;
static_assert((std::is_same<result_type, float>::value), "");
}
}

60
test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
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@@ -65,10 +65,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -106,10 +106,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -147,10 +147,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -188,10 +188,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -229,10 +229,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -270,10 +270,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -311,10 +311,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -352,10 +352,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -393,10 +393,10 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_int_distribution<> D; typedef std::uniform_int_distribution<> D;
@@ -445,9 +445,9 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
(5. * (sqr((double)d.b() - d.a() + 1) - 1)); (5. * (sqr((double)d.b() - d.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

6
test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
View File

@@ -67,9 +67,9 @@ int main()
double x_skew = 0; double x_skew = 0;
double x_kurtosis = -6. * (sqr((double)p.b() - p.a() + 1) + 1) / double x_kurtosis = -6. * (sqr((double)p.b() - p.a() + 1) + 1) /
(5. * (sqr((double)p.b() - p.a() + 1) - 1)); (5. * (sqr((double)p.b() - p.a() + 1) - 1));
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

64
test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
View File

@@ -64,10 +64,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -104,10 +104,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -144,10 +144,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -184,10 +184,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -224,10 +224,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.02); assert(std::abs(skew - x_skew) < 0.02);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -264,10 +264,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -304,10 +304,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -344,10 +344,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -384,10 +384,10 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -425,9 +425,9 @@ int main()
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) < 0.01); assert(std::abs(mean - x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
{ {
typedef std::uniform_real_distribution<> D; typedef std::uniform_real_distribution<> D;
@@ -464,9 +464,9 @@ int main()
D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_var = sqr(d.b() - d.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

6
test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
View File

@@ -66,9 +66,9 @@ int main()
D::result_type x_var = sqr(p.b() - p.a()) / 12; D::result_type x_var = sqr(p.b() - p.a()) / 12;
D::result_type x_skew = 0; D::result_type x_skew = 0;
D::result_type x_kurtosis = -6./5; D::result_type x_kurtosis = -6./5;
assert(std::abs(mean - x_mean) / x_mean < 0.01); assert(std::abs((mean - x_mean) / x_mean) < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01); assert(std::abs((var - x_var) / x_var) < 0.01);
assert(std::abs(skew - x_skew) < 0.01); assert(std::abs(skew - x_skew) < 0.01);
assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
} }
} }

2
test/numerics/rand/rand.predef/default_random_engine.pass.cpp
View File

@@ -20,5 +20,5 @@ int main()
{ {
std::default_random_engine e; std::default_random_engine e;
e.discard(9999); e.discard(9999);
assert(e() == 1043618065u); assert(e() == 399268537u);
} }