diff options
Diffstat (limited to 'libcxx')
56 files changed, 2593 insertions, 393 deletions
diff --git a/libcxx/include/random b/libcxx/include/random index 0ee6633273d..c5f9b170ecf 100644 --- a/libcxx/include/random +++ b/libcxx/include/random @@ -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<ranlux48_base, 389, 11> ranlux48; typedef shuffle_order_engine<minstd_rand0, 256> knuth_b; -typedef minstd_rand0 default_random_engine; +typedef minstd_rand default_random_engine; // Generators @@ -1477,7 +1477,79 @@ public: }; 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> class piecewise_linear_distribution; @@ -1825,9 +1897,9 @@ operator>>(basic_istream<_CharT, _Traits>& __is, typedef linear_congruential_engine<uint_fast32_t, 16807, 0, 2147483647> minstd_rand0; -typedef minstd_rand0 default_random_engine; typedef linear_congruential_engine<uint_fast32_t, 48271, 0, 2147483647> minstd_rand; +typedef minstd_rand default_random_engine; // mersenne_twister_engine 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::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> @@ -5535,11 +5608,305 @@ operator>>(basic_istream<_CharT, _Traits>& __is, __is.flags(ios_base::dec | ios_base::skipws); size_t __n; __is >> __n; - std::vector<double> __p(__n); + vector<double> __p(__n); + for (size_t __i = 0; __i < __n; ++__i) + __is >> __p[__i]; + if (!__is.fail()) + swap(__x.__p_.__p_, __p); + 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; } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp index 6764efaa56f..d1927b2d751 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp @@ -59,10 +59,10 @@ int main() double x_var = d.p()*(1-d.p()); double x_skew = (1 - 2 * d.p())/std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } { typedef std::bernoulli_distribution D; @@ -95,9 +95,9 @@ int main() double x_var = d.p()*(1-d.p()); double x_skew = (1 - 2 * d.p())/std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp index bb4be855243..5754a8dc6d6 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp @@ -61,10 +61,10 @@ int main() double x_var = p.p()*(1-p.p()); double x_skew = (1 - 2 * p.p())/std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } { typedef std::bernoulli_distribution D; @@ -99,9 +99,9 @@ int main() double x_var = p.p()*(1-p.p()); double x_skew = (1 - 2 * p.p())/std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp index 71bbf198b5e..a919c9dedae 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp @@ -31,10 +31,10 @@ int main() { { typedef std::binomial_distribution<> D; - typedef std::minstd_rand G; + typedef std::mt19937_64 G; G g; D d(5, .75); - const int N = 100000; + const int N = 1000000; std::vector<D::result_type> u; for (int i = 0; i < N; ++i) { @@ -64,10 +64,10 @@ int main() double x_var = x_mean*(1-d.p()); double x_skew = (1-2*d.p()) / std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04); } { typedef std::binomial_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = x_mean*(1-d.p()); double x_skew = (1-2*d.p()) / std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::binomial_distribution<> D; @@ -144,10 +144,10 @@ int main() double x_var = x_mean*(1-d.p()); double x_skew = (1-2*d.p()) / std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.03); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.03); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.3); } { typedef std::binomial_distribution<> D; @@ -260,10 +260,10 @@ int main() double x_var = x_mean*(1-d.p()); double x_skew = (1-2*d.p()) / std::sqrt(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(var - x_var) / x_var < 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(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; @@ -300,10 +300,10 @@ int main() double x_var = x_mean*(1-d.p()); double x_skew = (1-2*d.p()) / std::sqrt(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(var - x_var) / x_var < 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(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; diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp index 2632ab5f3ae..264a4a2f11e 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp @@ -32,11 +32,11 @@ int main() { typedef std::binomial_distribution<> D; typedef D::param_type P; - typedef std::minstd_rand G; + typedef std::mt19937_64 G; G g; D d(16, .75); P p(5, .75); - const int N = 100000; + const int N = 1000000; std::vector<D::result_type> u; for (int i = 0; i < N; ++i) { @@ -66,10 +66,10 @@ int main() double x_var = x_mean*(1-p.p()); double x_skew = (1-2*p.p()) / std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04); } { typedef std::binomial_distribution<> D; @@ -108,10 +108,10 @@ int main() double x_var = x_mean*(1-p.p()); double x_skew = (1-2*p.p()) / std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::binomial_distribution<> D; @@ -120,7 +120,7 @@ int main() G g; D d(16, .75); P p(40, .25); - const int N = 100000; + const int N = 1000000; std::vector<D::result_type> u; for (int i = 0; i < N; ++i) { @@ -150,9 +150,9 @@ int main() double x_var = x_mean*(1-p.p()); double x_skew = (1-2*p.p()) / std::sqrt(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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.03); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.04); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.3); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp index 48a6c57aac8..452bb8224c3 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp @@ -64,10 +64,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::geometric_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::geometric_distribution<> D; @@ -144,10 +144,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } { typedef std::geometric_distribution<> D; @@ -184,10 +184,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } { typedef std::geometric_distribution<> D; @@ -224,10 +224,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } { typedef std::geometric_distribution<> D; @@ -264,9 +264,9 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp index bea0159faa7..184124df8ce 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp @@ -66,10 +66,10 @@ int main() double x_var = x_mean / p.p(); double x_skew = (2 - p.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::geometric_distribution<> D; @@ -108,10 +108,10 @@ int main() double x_var = x_mean / p.p(); double x_skew = (2 - p.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::geometric_distribution<> D; @@ -150,9 +150,9 @@ int main() double x_var = x_mean / p.p(); double x_skew = (2 - p.p()) / std::sqrt((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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp index 96b4c180261..6bf3d3788ef 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp @@ -64,10 +64,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p())); double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } { typedef std::negative_binomial_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p())); double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::negative_binomial_distribution<> D; @@ -144,10 +144,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p())); double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::negative_binomial_distribution<> D; @@ -222,10 +222,10 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p())); double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.04); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.04); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05); } { typedef std::negative_binomial_distribution<> D; @@ -262,9 +262,9 @@ int main() double x_var = x_mean / d.p(); double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p())); double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.02); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp index b8906721e61..eec909ec7b8 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp @@ -66,10 +66,10 @@ int main() double x_var = x_mean / p.p(); double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p())); double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::negative_binomial_distribution<> D; @@ -108,10 +108,10 @@ int main() double x_var = x_mean / p.p(); double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p())); double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::negative_binomial_distribution<> D; @@ -150,9 +150,9 @@ int main() double x_var = x_mean / p.p(); double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p())); double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.p())); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp index 5713643291c..6e9d11e87f3 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp @@ -64,10 +64,10 @@ int main() double x_var = 2 * d.n(); double x_skew = std::sqrt(8 / d.n()); double x_kurtosis = 12 / d.n(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::chi_squared_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = 2 * d.n(); double x_skew = std::sqrt(8 / d.n()); double x_kurtosis = 12 / d.n(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::chi_squared_distribution<> D; @@ -144,9 +144,9 @@ int main() double x_var = 2 * d.n(); double x_skew = std::sqrt(8 / d.n()); double x_kurtosis = 12 / d.n(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp index 561f94dafda..8c456e9b1d0 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp @@ -65,10 +65,10 @@ int main() double x_var = 2 * p.n(); double x_skew = std::sqrt(8 / p.n()); double x_kurtosis = 12 / p.n(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::chi_squared_distribution<> D; @@ -106,10 +106,10 @@ int main() double x_var = 2 * p.n(); double x_skew = std::sqrt(8 / p.n()); double x_kurtosis = 12 / p.n(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::chi_squared_distribution<> D; @@ -147,9 +147,9 @@ int main() double x_var = 2 * p.n(); double x_skew = std::sqrt(8 / p.n()); double x_kurtosis = 12 / p.n(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp index 4779eb6ca0a..6402fed534c 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp @@ -66,10 +66,10 @@ int main() std::sqrt((std::exp(sqr(d.s())) - 1)); double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + 3*std::exp(2*sqr(d.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.05); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.25); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.05); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25); } { typedef std::lognormal_distribution<> D; @@ -108,10 +108,10 @@ int main() std::sqrt((std::exp(sqr(d.s())) - 1)); double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + 3*std::exp(2*sqr(d.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::lognormal_distribution<> D; @@ -150,10 +150,10 @@ int main() std::sqrt((std::exp(sqr(d.s())) - 1)); double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + 3*std::exp(2*sqr(d.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.02); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.02); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05); } { typedef std::lognormal_distribution<> D; @@ -192,10 +192,10 @@ int main() std::sqrt((std::exp(sqr(d.s())) - 1)); double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + 3*std::exp(2*sqr(d.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.02); - assert(std::abs(skew - x_skew) / x_skew < 0.08); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.4); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.02); + assert(std::abs((skew - x_skew) / x_skew) < 0.08); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4); } { typedef std::lognormal_distribution<> D; @@ -234,9 +234,9 @@ int main() std::sqrt((std::exp(sqr(d.s())) - 1)); double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) + 3*std::exp(2*sqr(d.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.04); - assert(std::abs(skew - x_skew) / x_skew < 0.2); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.7); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.04); + assert(std::abs((skew - x_skew) / x_skew) < 0.2); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp index 27909b4f567..f223d89718f 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp @@ -68,10 +68,10 @@ int main() std::sqrt((std::exp(sqr(p.s())) - 1)); double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + 3*std::exp(2*sqr(p.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.05); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.25); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.05); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25); } { typedef std::lognormal_distribution<> D; @@ -111,10 +111,10 @@ int main() std::sqrt((std::exp(sqr(p.s())) - 1)); double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + 3*std::exp(2*sqr(p.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::lognormal_distribution<> D; @@ -154,10 +154,10 @@ int main() std::sqrt((std::exp(sqr(p.s())) - 1)); double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + 3*std::exp(2*sqr(p.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.02); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.05); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.02); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05); } { typedef std::lognormal_distribution<> D; @@ -197,10 +197,10 @@ int main() std::sqrt((std::exp(sqr(p.s())) - 1)); double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + 3*std::exp(2*sqr(p.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.02); - assert(std::abs(skew - x_skew) / x_skew < 0.08); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.4); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.02); + assert(std::abs((skew - x_skew) / x_skew) < 0.08); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4); } { typedef std::lognormal_distribution<> D; @@ -240,9 +240,9 @@ int main() std::sqrt((std::exp(sqr(p.s())) - 1)); double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) + 3*std::exp(2*sqr(p.s())) - 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.04); - assert(std::abs(skew - x_skew) / x_skew < 0.2); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.7); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.04); + assert(std::abs((skew - x_skew) / x_skew) < 0.2); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp index abfb8aaa6b2..cc56780fdee 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp @@ -60,8 +60,8 @@ int main() double x_var = sqr(d.stddev()); double x_skew = 0; double x_kurtosis = 0; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 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(skew - x_skew) < 0.01); assert(std::abs(kurtosis - x_kurtosis) < 0.01); } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp index e55c75fe29c..8a3dabb24a5 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp @@ -61,8 +61,8 @@ int main() double x_var = sqr(p.stddev()); double x_skew = 0; double x_kurtosis = 0; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 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(skew - x_skew) < 0.01); assert(std::abs(kurtosis - x_kurtosis) < 0.01); } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp index 86ffd793384..a0bc1d807a4 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp @@ -61,9 +61,9 @@ int main() double x_skew = 0; double x_kurtosis = 6 / (d.n() - 4); 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(kurtosis - x_kurtosis) / x_kurtosis < 0.2); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.2); } { typedef std::student_t_distribution<> D; @@ -97,9 +97,9 @@ int main() double x_skew = 0; double x_kurtosis = 6 / (d.n() - 4); 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(kurtosis - x_kurtosis) / x_kurtosis < 0.04); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04); } { typedef std::student_t_distribution<> D; @@ -133,8 +133,8 @@ int main() double x_skew = 0; double x_kurtosis = 6 / (d.n() - 4); 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(kurtosis - x_kurtosis) / x_kurtosis < 0.02); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp index 18207701a3a..3c94bfc89c4 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp @@ -62,9 +62,9 @@ int main() double x_skew = 0; double x_kurtosis = 6 / (p.n() - 4); 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(kurtosis - x_kurtosis) / x_kurtosis < 0.2); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.2); } { typedef std::student_t_distribution<> D; @@ -99,9 +99,9 @@ int main() double x_skew = 0; double x_kurtosis = 6 / (p.n() - 4); 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(kurtosis - x_kurtosis) / x_kurtosis < 0.04); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04); } { typedef std::student_t_distribution<> D; @@ -136,8 +136,8 @@ int main() double x_skew = 0; double x_kurtosis = 6 / (p.n() - 4); 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(kurtosis - x_kurtosis) / x_kurtosis < 0.02); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp index b4e8928fba3..c94fc80f978 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp @@ -64,10 +64,10 @@ int main() double x_var = 1/sqr(d.lambda()); double x_skew = 2; double x_kurtosis = 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::exponential_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = 1/sqr(d.lambda()); double x_skew = 2; double x_kurtosis = 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::exponential_distribution<> D; @@ -144,9 +144,9 @@ int main() double x_var = 1/sqr(d.lambda()); double x_skew = 2; double x_kurtosis = 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp index e5805f1c52b..18e9ec1d38a 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp @@ -65,9 +65,9 @@ int main() double x_var = 1/sqr(p.lambda()); double x_skew = 2; double x_kurtosis = 6; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp index 071ea6bc60f..22de3e9a2e0 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp @@ -63,10 +63,10 @@ int main() double x_var = sqr(d.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::extreme_value_distribution<> D; @@ -102,10 +102,10 @@ int main() double x_var = sqr(d.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::extreme_value_distribution<> D; @@ -141,10 +141,10 @@ int main() double x_var = sqr(d.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::extreme_value_distribution<> D; @@ -180,9 +180,9 @@ int main() double x_var = sqr(d.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp index dd335a05900..62add972fcc 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp @@ -64,10 +64,10 @@ int main() double x_var = sqr(p.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::extreme_value_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = sqr(p.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::extreme_value_distribution<> D; @@ -144,10 +144,10 @@ int main() double x_var = sqr(p.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::extreme_value_distribution<> D; @@ -184,9 +184,9 @@ int main() double x_var = sqr(p.b()) * 1.644934067; double x_skew = 1.139547; double x_kurtosis = 12./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) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 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((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp index 0d803f36f8c..d1b4960f13d 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp @@ -64,10 +64,10 @@ int main() double x_var = d.alpha() * sqr(d.beta()); double x_skew = 2 / std::sqrt(d.alpha()); double x_kurtosis = 6 / d.alpha(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::gamma_distribution<> D; @@ -104,10 +104,10 @@ int main() double x_var = d.alpha() * sqr(d.beta()); double x_skew = 2 / std::sqrt(d.alpha()); double x_kurtosis = 6 / d.alpha(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::gamma_distribution<> D; @@ -144,9 +144,9 @@ int main() double x_var = d.alpha() * sqr(d.beta()); double x_skew = 2 / std::sqrt(d.alpha()); double x_kurtosis = 6 / d.alpha(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp index cdb3fc5865a..244303851ac 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp @@ -65,10 +65,10 @@ int main() double x_var = p.alpha() * sqr(p.beta()); double x_skew = 2 / std::sqrt(p.alpha()); double x_kurtosis = 6 / p.alpha(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::gamma_distribution<> D; @@ -106,10 +106,10 @@ int main() double x_var = p.alpha() * sqr(p.beta()); double x_skew = 2 / std::sqrt(p.alpha()); double x_kurtosis = 6 / p.alpha(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::gamma_distribution<> D; @@ -147,9 +147,9 @@ int main() double x_var = p.alpha() * sqr(p.beta()); double x_skew = 2 / std::sqrt(p.alpha()); double x_kurtosis = 6 / p.alpha(); - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp index 2bc5c2375a1..1df0444f358 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp @@ -63,10 +63,10 @@ int main() double x_var = d.mean(); double x_skew = 1 / std::sqrt(x_var); double x_kurtosis = 1 / x_var; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::poisson_distribution<> D; @@ -102,10 +102,10 @@ int main() double x_var = d.mean(); double x_skew = 1 / std::sqrt(x_var); double x_kurtosis = 1 / x_var; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.04); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04); } { typedef std::poisson_distribution<> D; @@ -141,9 +141,9 @@ int main() double x_var = d.mean(); double x_skew = 1 / std::sqrt(x_var); double x_kurtosis = 1 / x_var; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp index ba227297c3f..97ed29b14a9 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp @@ -65,10 +65,10 @@ int main() double x_var = p.mean(); double x_skew = 1 / std::sqrt(x_var); double x_kurtosis = 1 / x_var; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::poisson_distribution<> D; @@ -106,10 +106,10 @@ int main() double x_var = p.mean(); double x_skew = 1 / std::sqrt(x_var); double x_kurtosis = 1 / x_var; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.04); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04); } { typedef std::poisson_distribution<> D; @@ -147,9 +147,9 @@ int main() double x_var = p.mean(); double x_skew = 1 / std::sqrt(x_var); double x_kurtosis = 1 / x_var; - assert(std::abs(mean - x_mean) / x_mean < 0.01); - assert(std::abs(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp index 1381a43e740..b36706c5067 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp @@ -68,10 +68,10 @@ int main() double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) - 4*x_skew*x_var*sqrt(x_var)*x_mean - 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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::weibull_distribution<> D; @@ -112,10 +112,10 @@ int main() double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) - 4*x_skew*x_var*sqrt(x_var)*x_mean - 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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::weibull_distribution<> D; @@ -156,9 +156,9 @@ int main() double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) - 4*x_skew*x_var*sqrt(x_var)*x_mean - 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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp index 3c1076c4cda..3100f70cada 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp @@ -69,10 +69,10 @@ int main() double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) - 4*x_skew*x_var*sqrt(x_var)*x_mean - 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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::weibull_distribution<> D; @@ -114,10 +114,10 @@ int main() double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) - 4*x_skew*x_var*sqrt(x_var)*x_mean - 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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } { typedef std::weibull_distribution<> D; @@ -159,9 +159,9 @@ int main() double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) - 4*x_skew*x_var*sqrt(x_var)*x_mean - 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(var - x_var) / x_var < 0.01); - assert(std::abs(skew - x_skew) / x_skew < 0.01); - assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.03); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp new file mode 100644 index 00000000000..c0eea1d53f9 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp @@ -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(); +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.pass.cpp new file mode 100644 index 00000000000..8ba60d29b1a --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.pass.cpp @@ -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(); +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp new file mode 100644 index 00000000000..1706d0b2156 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp new file mode 100644 index 00000000000..74db04fdd56 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp new file mode 100644 index 00000000000..abbf559665d --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp @@ -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 +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp new file mode 100644 index 00000000000..985e147792c --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.pass.cpp new file mode 100644 index 00000000000..7249932ce0f --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp new file mode 100644 index 00000000000..605a3eb3460 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp new file mode 100644 index 00000000000..483526ba097 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp @@ -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); + } + } + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp new file mode 100644 index 00000000000..b842bed501a --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp @@ -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); + } + } + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.pass.cpp new file mode 100644 index 00000000000..0f60a40b52f --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.pass.cpp new file mode 100644 index 00000000000..64f0b808229 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.pass.cpp new file mode 100644 index 00000000000..c1846efac42 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.pass.cpp new file mode 100644 index 00000000000..7d18ce11e5d --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_assign.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_assign.pass.cpp new file mode 100644 index 00000000000..55a0f65c6ce --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_assign.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp new file mode 100644 index 00000000000..e6f9f8d9789 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.pass.cpp new file mode 100644 index 00000000000..63f338d2bb7 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp new file mode 100644 index 00000000000..b8fcfd583d4 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp new file mode 100644 index 00000000000..8d278364348 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp @@ -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 +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp new file mode 100644 index 00000000000..ee2e12908f7 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.pass.cpp new file mode 100644 index 00000000000..85e7232266d --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_types.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_types.pass.cpp new file mode 100644 index 00000000000..91db248af21 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_types.pass.cpp @@ -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), ""); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.pass.cpp new file mode 100644 index 00000000000..6a5fd0cfa08 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.pass.cpp @@ -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); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/types.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/types.pass.cpp new file mode 100644 index 00000000000..f3e21f27d51 --- /dev/null +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/types.pass.cpp @@ -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), ""); + } +} diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp index 3443e16f26f..17840983318 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp @@ -65,10 +65,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -106,10 +106,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -147,10 +147,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -188,10 +188,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -229,10 +229,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -270,10 +270,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -311,10 +311,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -352,10 +352,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -393,10 +393,10 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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; @@ -445,9 +445,9 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp index 6bbd4fabb68..f84a6d42c94 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp @@ -67,9 +67,9 @@ int main() double x_skew = 0; double x_kurtosis = -6. * (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(var - x_var) / x_var < 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(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); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp index b6de39535d2..a733fc915f7 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp @@ -64,10 +64,10 @@ int main() D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); 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; @@ -264,10 +264,10 @@ int main() D::result_type x_var = sqr(d.b() - d.a()) / 12; D::result_type x_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { typedef std::uniform_real_distribution<> D; @@ -425,9 +425,9 @@ int main() D::result_type x_skew = 0; D::result_type x_kurtosis = -6./5; 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(kurtosis - x_kurtosis) / x_kurtosis < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } { 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_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp index 79e2924ef62..0f726ed7a0f 100644 --- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp +++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp @@ -66,9 +66,9 @@ int main() D::result_type x_var = sqr(p.b() - p.a()) / 12; D::result_type x_skew = 0; D::result_type 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((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); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); } } diff --git a/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp b/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp index d936f89f602..91b0902c86d 100644 --- a/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp +++ b/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp @@ -20,5 +20,5 @@ int main() { std::default_random_engine e; e.discard(9999); - assert(e() == 1043618065u); + assert(e() == 399268537u); } |
