[rand.dist.samp.plinear]. This means we've got a fully tested and functional <random>! 489 tests over 48 sections are passing. :-) The only thing still on my plate in this area is to back-port some of this technology to random_shuffle/shuffle in <algorithm>. That will involve shuffling header bits around (<random> depepends on <algorithm>), but it won't entail that much development (compared to what has been required for <random>).
git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@104575 91177308-0d34-0410-b5e6-96231b3b80d8
diff --git a/include/random b/include/random
index 1a680ff..adefa8b 100644
--- a/include/random
+++ b/include/random
@@ -1552,7 +1552,82 @@
};
template<class RealType = double>
- class piecewise_linear_distribution;
+class piecewise_linear_distribution
+{
+ // types
+ typedef RealType result_type;
+
+ class param_type
+ {
+ public:
+ typedef piecewise_linear_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_linear_distribution();
+ template<class InputIteratorB, class InputIteratorW>
+ piecewise_linear_distribution(InputIteratorB firstB,
+ InputIteratorB lastB,
+ InputIteratorW firstW);
+
+ template<class UnaryOperation>
+ piecewise_linear_distribution(initializer_list<result_type> bl,
+ UnaryOperation fw);
+
+ template<class UnaryOperation>
+ piecewise_linear_distribution(size_t nw, result_type xmin,
+ result_type xmax, UnaryOperation fw);
+
+ explicit piecewise_linear_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_linear_distribution& x,
+ const piecewise_linear_distribution& y);
+ friend bool operator!=(const piecewise_linear_distribution& x,
+ const piecewise_linear_distribution& y);
+
+ template <class charT, class traits>
+ friend
+ basic_ostream<charT, traits>&
+ operator<<(basic_ostream<charT, traits>& os,
+ const piecewise_linear_distribution& x);
+
+ template <class charT, class traits>
+ friend
+ basic_istream<charT, traits>&
+ operator>>(basic_istream<charT, traits>& is,
+ piecewise_linear_distribution& x);
+};
} // std
*/
@@ -5772,7 +5847,8 @@
template<class _RealType>
piecewise_constant_distribution<_RealType>::param_type::param_type()
: __b_(2),
- __densities_(1, 1.0)
+ __densities_(1, 1.0),
+ __areas_(1, 0.0)
{
__b_[1] = 1;
}
@@ -5789,6 +5865,7 @@
__b_[0] = 0;
__b_[1] = 1;
__densities_.assign(1, 1.0);
+ __areas_.assign(1, 0.0);
}
else
{
@@ -5811,6 +5888,7 @@
__b_[0] = 0;
__b_[1] = 1;
__densities_.assign(1, 1.0);
+ __areas_.assign(1, 0.0);
}
else
{
@@ -5910,6 +5988,301 @@
return __is;
}
+// piecewise_linear_distribution
+
+template<class _RealType = double>
+class piecewise_linear_distribution
+{
+public:
+ // types
+ typedef _RealType result_type;
+
+ class param_type
+ {
+ typedef typename common_type<double, result_type>::type __area_type;
+ vector<result_type> __b_;
+ vector<double> __densities_;
+ vector<__area_type> __areas_;
+ public:
+ typedef piecewise_linear_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 {return __densities_;}
+
+ friend bool operator==(const param_type& __x, const param_type& __y)
+ {return __x.__densities_ == __y.__densities_ && __x.__b_ == __y.__b_;}
+ friend bool operator!=(const param_type& __x, const param_type& __y)
+ {return !(__x == __y);}
+
+ private:
+ void __init();
+
+ friend class piecewise_linear_distribution;
+
+ template <class _CharT, class _Traits, class _RT>
+ friend
+ basic_ostream<_CharT, _Traits>&
+ operator<<(basic_ostream<_CharT, _Traits>& __os,
+ const piecewise_linear_distribution<_RT>& __x);
+
+ template <class _CharT, class _Traits, class _RT>
+ friend
+ basic_istream<_CharT, _Traits>&
+ operator>>(basic_istream<_CharT, _Traits>& __is,
+ piecewise_linear_distribution<_RT>& __x);
+ };
+
+private:
+ param_type __p_;
+
+public:
+ // constructor and reset functions
+ piecewise_linear_distribution() {}
+ template<class _InputIteratorB, class _InputIteratorW>
+ piecewise_linear_distribution(_InputIteratorB __fB,
+ _InputIteratorB __lB,
+ _InputIteratorW __fW)
+ : __p_(__fB, __lB, __fW) {}
+
+ template<class _UnaryOperation>
+ piecewise_linear_distribution(initializer_list<result_type> __bl,
+ _UnaryOperation __fw)
+ : __p_(__bl, __fw) {}
+
+ template<class _UnaryOperation>
+ piecewise_linear_distribution(size_t __nw, result_type __xmin,
+ result_type __xmax, _UnaryOperation __fw)
+ : __p_(__nw, __xmin, __xmax, __fw) {}
+
+ explicit piecewise_linear_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_linear_distribution& __x,
+ const piecewise_linear_distribution& __y)
+ {return __x.__p_ == __y.__p_;}
+ friend bool operator!=(const piecewise_linear_distribution& __x,
+ const piecewise_linear_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_linear_distribution<_RT>& __x);
+
+ template <class _CharT, class _Traits, class _RT>
+ friend
+ basic_istream<_CharT, _Traits>&
+ operator>>(basic_istream<_CharT, _Traits>& __is,
+ piecewise_linear_distribution<_RT>& __x);
+};
+
+template<class _RealType>
+void
+piecewise_linear_distribution<_RealType>::param_type::__init()
+{
+ __areas_.assign(__densities_.size() - 1, __area_type());
+ __area_type _S = 0;
+ for (size_t __i = 0; __i < __areas_.size(); ++__i)
+ {
+ __areas_[__i] = (__densities_[__i+1] + __densities_[__i]) *
+ (__b_[__i+1] - __b_[__i]) * .5;
+ _S += __areas_[__i];
+ }
+ for (size_t __i = __areas_.size(); __i > 1;)
+ {
+ --__i;
+ __areas_[__i] = __areas_[__i-1] / _S;
+ }
+ __areas_[0] = 0;
+ for (size_t __i = 1; __i < __areas_.size(); ++__i)
+ __areas_[__i] += __areas_[__i-1];
+ for (size_t __i = 0; __i < __densities_.size(); ++__i)
+ __densities_[__i] /= _S;
+}
+
+template<class _RealType>
+piecewise_linear_distribution<_RealType>::param_type::param_type()
+ : __b_(2),
+ __densities_(2, 1.0),
+ __areas_(1, 0.0)
+{
+ __b_[1] = 1;
+}
+
+template<class _RealType>
+template<class _InputIteratorB, class _InputIteratorW>
+piecewise_linear_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;
+ __densities_.assign(2, 1.0);
+ __areas_.assign(1, 0.0);
+ }
+ else
+ {
+ __densities_.reserve(__b_.size());
+ for (size_t __i = 0; __i < __b_.size(); ++__i, ++__fW)
+ __densities_.push_back(*__fW);
+ __init();
+ }
+}
+
+template<class _RealType>
+template<class _UnaryOperation>
+piecewise_linear_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;
+ __densities_.assign(2, 1.0);
+ __areas_.assign(1, 0.0);
+ }
+ else
+ {
+ __densities_.reserve(__b_.size());
+ for (size_t __i = 0; __i < __b_.size(); ++__i)
+ __densities_.push_back(__fw(__b_[__i]));
+ __init();
+ }
+}
+
+template<class _RealType>
+template<class _UnaryOperation>
+piecewise_linear_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;
+ __densities_.reserve(__b_.size());
+ for (size_t __i = 0; __i < __n; ++__i)
+ {
+ __b_[__i] = __xmin + __i * __d;
+ __densities_.push_back(__fw(__b_[__i]));
+ }
+ __b_[__n] = __xmax;
+ __densities_.push_back(__fw(__b_[__n]));
+ __init();
+}
+
+template<class _RealType>
+template<class _URNG>
+_RealType
+piecewise_linear_distribution<_RealType>::operator()(_URNG& __g, const param_type& __p)
+{
+ typedef uniform_real_distribution<result_type> _Gen;
+ result_type __u = _Gen()(__g);
+ ptrdiff_t __k = _STD::upper_bound(__p.__areas_.begin(), __p.__areas_.end(),
+ static_cast<double>(__u)) - __p.__areas_.begin() - 1;
+ __u -= __p.__areas_[__k];
+ const double __dk = __p.__densities_[__k];
+ const double __dk1 = __p.__densities_[__k+1];
+ const double __deltad = __dk1 - __dk;
+ const result_type __bk = __p.__b_[__k];
+ if (__deltad == 0)
+ return static_cast<result_type>(__u / __dk + __bk);
+ const result_type __bk1 = __p.__b_[__k+1];
+ const result_type __deltab = __bk1 - __bk;
+ return static_cast<result_type>((__bk * __dk1 - __bk1 * __dk +
+ _STD::sqrt(__deltab * (__deltab * __dk * __dk + 2 * __deltad * __u))) /
+ __deltad);
+}
+
+template <class _CharT, class _Traits, class _RT>
+basic_ostream<_CharT, _Traits>&
+operator<<(basic_ostream<_CharT, _Traits>& __os,
+ const piecewise_linear_distribution<_RT>& __x)
+{
+ __save_flags<_CharT, _Traits> _(__os);
+ __os.flags(ios_base::dec | ios_base::left | ios_base::fixed |
+ ios_base::scientific);
+ _CharT __sp = __os.widen(' ');
+ __os.fill(__sp);
+ size_t __n = __x.__p_.__b_.size();
+ __os << __n;
+ for (size_t __i = 0; __i < __n; ++__i)
+ __os << __sp << __x.__p_.__b_[__i];
+ __n = __x.__p_.__densities_.size();
+ __os << __sp << __n;
+ for (size_t __i = 0; __i < __n; ++__i)
+ __os << __sp << __x.__p_.__densities_[__i];
+ __n = __x.__p_.__areas_.size();
+ __os << __sp << __n;
+ for (size_t __i = 0; __i < __n; ++__i)
+ __os << __sp << __x.__p_.__areas_[__i];
+ return __os;
+}
+
+template <class _CharT, class _Traits, class _RT>
+basic_istream<_CharT, _Traits>&
+operator>>(basic_istream<_CharT, _Traits>& __is,
+ piecewise_linear_distribution<_RT>& __x)
+{
+ typedef piecewise_linear_distribution<_RT> _Eng;
+ typedef typename _Eng::result_type result_type;
+ typedef typename _Eng::param_type param_type;
+ typedef typename param_type::__area_type __area_type;
+ __save_flags<_CharT, _Traits> _(__is);
+ __is.flags(ios_base::dec | ios_base::skipws);
+ size_t __n;
+ __is >> __n;
+ vector<result_type> __b(__n);
+ for (size_t __i = 0; __i < __n; ++__i)
+ __is >> __b[__i];
+ __is >> __n;
+ vector<double> __densities(__n);
+ for (size_t __i = 0; __i < __n; ++__i)
+ __is >> __densities[__i];
+ __is >> __n;
+ vector<__area_type> __areas(__n);
+ for (size_t __i = 0; __i < __n; ++__i)
+ __is >> __areas[__i];
+ if (!__is.fail())
+ {
+ swap(__x.__p_.__b_, __b);
+ swap(__x.__p_.__densities_, __densities);
+ swap(__x.__p_.__areas_, __areas);
+ }
+ return __is;
+}
+
_LIBCPP_END_NAMESPACE_STD
#endif // _LIBCPP_RANDOM