[rand.dist.samp.discrete]

git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@104103 91177308-0d34-0410-b5e6-96231b3b80d8
diff --git a/include/random b/include/random
index 6a3dcce..0ee6633 100644
--- a/include/random
+++ b/include/random
@@ -1410,7 +1410,71 @@
 };
 
 template<class IntType = int>
-    class discrete_distribution;
+class discrete_distribution
+{
+public:
+    // types
+    typedef IntType result_type;
+
+    class param_type
+    {
+    public:
+        typedef discrete_distribution distribution_type;
+
+        param_type();
+        template<class InputIterator>
+            param_type(InputIterator firstW, InputIterator lastW);
+        param_type(initializer_list<double> wl);
+        template<class UnaryOperation>
+            param_type(size_t nw, double xmin, double xmax, UnaryOperation fw);
+
+        vector<double> probabilities() 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
+    discrete_distribution();
+    template<class InputIterator>
+        discrete_distribution(InputIterator firstW, InputIterator lastW);
+    discrete_distribution(initializer_list<double> wl);
+    template<class UnaryOperation>
+        discrete_distribution(size_t nw, double xmin, double xmax,
+                              UnaryOperation fw);
+    explicit discrete_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<double> probabilities() const;
+
+    param_type param() const;
+    void param(const param_type& parm);
+
+    result_type min() const;
+    result_type max() const;
+
+    friend bool operator==(const discrete_distribution& x,
+                           const discrete_distribution& y);
+    friend bool operator!=(const discrete_distribution& x,
+                           const discrete_distribution& y);
+
+    template <class charT, class traits>
+    friend
+    basic_ostream<charT, traits>&
+    operator<<(basic_ostream<charT, traits>& os,
+               const discrete_distribution& x);
+    
+    template <class charT, class traits>
+    friend
+    basic_istream<charT, traits>&
+    operator>>(basic_istream<charT, traits>& is,
+               discrete_distribution& x);
+};
 
 template<class RealType = double>
     class piecewise_constant_distribution;
@@ -1428,6 +1492,7 @@
 #include <cstdint>
 #include <limits>
 #include <algorithm>
+#include <numeric>
 #include <vector>
 #include <string>
 #include <istream>
@@ -4075,7 +4140,7 @@
     result_type s() const {return __p_.s();}
 
     param_type param() const {return __p_;}
-    void param(const param_type& __p) {return __p_ = __p;}
+    void param(const param_type& __p) {__p_ = __p;}
 
     result_type min() const {return 0;}
     result_type max() const {return numeric_limits<result_type>::infinity();}
@@ -5176,6 +5241,8 @@
     return __is;
 }
 
+// student_t_distribution
+
 template<class _RealType = double>
 class student_t_distribution
 {
@@ -5220,7 +5287,7 @@
     result_type n() const {return __p_.n();}
 
     param_type param() const {return __p_;}
-    void param(const param_type& __p) {return __p_ = __p;}
+    void param(const param_type& __p) {__p_ = __p;}
 
     result_type min() const {return -numeric_limits<result_type>::infinity();}
     result_type max() const {return numeric_limits<result_type>::infinity();}
@@ -5270,6 +5337,212 @@
     return __is;
 }
 
+// discrete_distribution
+
+template<class _IntType = int>
+class discrete_distribution
+{
+public:
+    // types
+    typedef _IntType result_type;
+
+    class param_type
+    {
+        vector<double> __p_;
+    public:
+        typedef discrete_distribution distribution_type;
+
+        param_type() {}
+        template<class _InputIterator>
+            param_type(_InputIterator __f, _InputIterator __l)
+            : __p_(__f, __l) {__init();}
+        param_type(initializer_list<double> __wl)
+            : __p_(__wl.begin(), __wl.end()) {__init();}
+        template<class _UnaryOperation>
+            param_type(size_t __nw, double __xmin, double __xmax,
+                       _UnaryOperation __fw);
+
+        vector<double> probabilities() const;
+
+        friend bool operator==(const param_type& __x, const param_type& __y)
+            {return __x.__p_ == __y.__p_;}
+        friend bool operator!=(const param_type& __x, const param_type& __y)
+            {return !(__x == __y);}
+
+    private:
+        void __init();
+
+        friend class discrete_distribution;
+
+        template <class _CharT, class _Traits, class _IT>
+        friend
+        basic_ostream<_CharT, _Traits>&
+        operator<<(basic_ostream<_CharT, _Traits>& __os,
+                   const discrete_distribution<_IT>& __x);
+        
+        template <class _CharT, class _Traits, class _IT>
+        friend
+        basic_istream<_CharT, _Traits>&
+        operator>>(basic_istream<_CharT, _Traits>& __is,
+                   discrete_distribution<_IT>& __x);
+    };
+
+private:
+    param_type __p_;
+
+public:
+    // constructor and reset functions
+    discrete_distribution() {}
+    template<class _InputIterator>
+        discrete_distribution(_InputIterator __f, _InputIterator __l)
+            : __p_(__f, __l) {}
+    discrete_distribution(initializer_list<double> __wl)
+        : __p_(__wl) {}
+    template<class _UnaryOperation>
+        discrete_distribution(size_t __nw, double __xmin, double __xmax,
+                              _UnaryOperation __fw)
+        : __p_(__nw, __xmin, __xmax, __fw) {}
+    explicit discrete_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<double> probabilities() const {return __p_.probabilities();}
+
+    param_type param() const {return __p_;}
+    void param(const param_type& __p) {__p_ = __p;}
+
+    result_type min() const {return 0;}
+    result_type max() const {return __p_.__p_.size();}
+
+    friend bool operator==(const discrete_distribution& __x,
+                           const discrete_distribution& __y)
+        {return __x.__p_ == __y.__p_;}
+    friend bool operator!=(const discrete_distribution& __x,
+                           const discrete_distribution& __y)
+        {return !(__x == __y);}
+
+    template <class _CharT, class _Traits, class _IT>
+    friend
+    basic_ostream<_CharT, _Traits>&
+    operator<<(basic_ostream<_CharT, _Traits>& __os,
+               const discrete_distribution<_IT>& __x);
+    
+    template <class _CharT, class _Traits, class _IT>
+    friend
+    basic_istream<_CharT, _Traits>&
+    operator>>(basic_istream<_CharT, _Traits>& __is,
+               discrete_distribution<_IT>& __x);
+};
+
+template<class _IntType>
+template<class _UnaryOperation>
+discrete_distribution<_IntType>::param_type::param_type(size_t __nw,
+                                                        double __xmin,
+                                                        double __xmax,
+                                                        _UnaryOperation __fw)
+{
+    if (__nw > 1)
+    {
+        __p_.reserve(__nw - 1);
+        double __d = (__xmax - __xmin) / __nw;
+        double __d2 = __d / 2;
+        for (size_t __k = 0; __k < __nw; ++__k)
+            __p_.push_back(__fw(__xmin + __k * __d + __d2));
+        __init();
+    }
+}
+
+template<class _IntType>
+void
+discrete_distribution<_IntType>::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 _IntType>
+vector<double>
+discrete_distribution<_IntType>::param_type::probabilities() const
+{
+    size_t __n = __p_.size();
+    _STD::vector<double> __p(__n+1);
+    _STD::adjacent_difference(__p_.begin(), __p_.end(), __p.begin());
+    if (__n > 0)
+        __p[__n] = 1 - __p_[__n-1];
+    else
+        __p[0] = 1;
+    return __p;
+}
+
+template<class _IntType>
+template<class _URNG>
+_IntType
+discrete_distribution<_IntType>::operator()(_URNG& __g, const param_type& __p)
+{
+    uniform_real_distribution<double> __gen;
+    return static_cast<_IntType>(
+           _STD::upper_bound(__p.__p_.begin(), __p.__p_.end(), __gen(__g)) -
+                                                              __p.__p_.begin());
+}
+
+template <class _CharT, class _Traits, class _IT>
+basic_ostream<_CharT, _Traits>&
+operator<<(basic_ostream<_CharT, _Traits>& __os,
+           const discrete_distribution<_IT>& __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];
+    return __os;
+}
+
+template <class _CharT, class _Traits, class _IT>
+basic_istream<_CharT, _Traits>&
+operator>>(basic_istream<_CharT, _Traits>& __is,
+           discrete_distribution<_IT>& __x)
+{
+    typedef discrete_distribution<_IT> _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;
+    std::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;
+}
+
 _LIBCPP_END_NAMESPACE_STD
 
 #endif  // _LIBCPP_RANDOM