2009-04-02 Benjamin Kosnik <bkoz@redhat.com>

	* testsuite/20_util/shared_ptr/thread/default_weaktoshared.cc:
	Change to mersenne_twister_engine, add same defaults as
	mersenne_twister_engine/cons/default.cc.
	* testsuite/20_util/shared_ptr/thread/mutex_weaktoshared.cc: Same.

	* include/bits/random.tcc (seed_seq::seed_seq): Uglify parameter
	to __il.
	* include/bits/random.h (mersenne_twister_engine): Qualify
	_ShiftMin1 with namespace __detail.
	(__detail::_ShiftMin1): Use __gnu_cxx::__numeric_traits::max until
	constexpr std::numeric_limits::max() can be used.
	(mersenne_twister_engine): Split apart static asserts into one
	assert per message. Temporarily disable the last three.

2009-04-02  Edward Smith-Rowland  <3dw4rd@verizon.net>

	* include/Makefile.am: Update to N2836. Modified for new random headers.
	* include/Makefile.in: Ditto.
	* include/tr1_impl/random: Moved to tr1/random.h
	* include/tr1_impl/random.tcc: Moved to tr1
	* include/tr1/random: Just point to moved tr1 random headers.
	* include/tr1/random.tcc: Moved from tr1_impl.
	* include/tr1/random.h: Moved from tr1_impl/random.
	* include/std/random: Modified to point to std random headers.
	* include/bits/random.tcc: New implementation of std random facilities.
	* include/bits/random.h: Ditto.
	* testsuite/26_numerics/headers/random/std_c++0x_neg.cc: Changed.
	* testsuite/26_numerics/random/linear_congruential_engine/cons/
	seed1.cc: New.
	* testsuite/26_numerics/random/linear_congruential_engine/cons/
	seed2.cc: New.
	* testsuite/26_numerics/random/linear_congruential_engine/cons/
	default.cc: New.
	* testsuite/26_numerics/random/linear_congruential_engine/requirements/
	non_uint_neg.cc: New.
	* testsuite/26_numerics/random/linear_congruential_engine/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/linear_congruential_engine/operators/
	equal.cc: New.
	* testsuite/26_numerics/random/linear_congruential_engine/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/mersenne_twister_engine/cons/
	seed1.cc: New.
	* testsuite/26_numerics/random/mersenne_twister_engine/cons/
	seed2.cc: New.
	* testsuite/26_numerics/random/mersenne_twister_engine/cons/
	default.cc: New.
	* testsuite/26_numerics/random/mersenne_twister_engine/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/mersenne_twister_engine/operators/
	equal.cc: New.
	* testsuite/26_numerics/random/mersenne_twister_engine/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/subtract_with_carry_engine/cons/
	seed1.cc: New.
	* testsuite/26_numerics/random/subtract_with_carry_engine/cons/
	seed2.cc: New.
	* testsuite/26_numerics/random/subtract_with_carry_engine/cons/
	default.cc: New.
	* testsuite/26_numerics/random/subtract_with_carry_engine/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/subtract_with_carry_engine/operators/
	equal.cc: New.
	* testsuite/26_numerics/random/subtract_with_carry_engine/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/cons/
	base_move.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/cons/
	seed1.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/cons/
	seed2.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/cons/
	base_copy.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/cons/
	default.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/cons/
	seed_seq.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/operators/
	equal.cc: New.
	* testsuite/26_numerics/random/discard_block_engine/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/cons/
	base_move.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/cons/
	seed1.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/cons/
	seed2.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/cons/
	base_copy.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/cons/
	default.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/cons/
	seed_seq.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/operators/
	equal.cc: New.
	* testsuite/26_numerics/random/independent_bits_engine/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/cons/
	base_move.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/cons/
	seed1.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/cons/
	seed2.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/cons/
	base_copy.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/cons/
	default.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/cons/
	seed_seq.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/operators/
	equal.cc: New.
	* testsuite/26_numerics/random/shuffle_order_engine/operators/
	serialize.cc
	* testsuite/26_numerics/random/mt19937.cc: New.
	* testsuite/26_numerics/random/mt19937_64.cc: New.
	* testsuite/26_numerics/random/minstd_rand.cc: New.
	* testsuite/26_numerics/random/minstd_rand0.cc: New.
	* testsuite/26_numerics/random/ranlux24_base.cc: New.
	* testsuite/26_numerics/random/ranlux48_base.cc: New.
	* testsuite/26_numerics/random/ranlux24.cc: New.
	* testsuite/26_numerics/random/ranlux48.cc: New.
	* testsuite/26_numerics/random/knuth_b.cc: New.
	* testsuite/26_numerics/random/default_random_engine.cc: New.
	* testsuite/26_numerics/random/chi_squared_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/chi_squared_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/chi_squared_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/chi_squared_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/normal_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/normal_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/normal_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/normal_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/seed_seq/cons/range.cc: New.
	* testsuite/26_numerics/random/seed_seq/cons/default.cc: New.
	* testsuite/26_numerics/random/seed_seq/requirements/typedefs.cc: New.
	* testsuite/26_numerics/random/uniform_int_distribution/cons/
	parms_neg.cc: New.
	* testsuite/26_numerics/random/uniform_int_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/uniform_int_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/uniform_int_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/uniform_int_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/uniform_real_distribution/cons/
	parms_neg.cc: New.
	* testsuite/26_numerics/random/uniform_real_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/uniform_real_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/uniform_real_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/uniform_real_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/poisson_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/poisson_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/poisson_distribution/requirements/
	typedefs.cc
	* testsuite/26_numerics/random/poisson_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/bernoulli_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/bernoulli_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/bernoulli_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/bernoulli_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/discrete_distribution/cons/
	range.cc: New.
	* testsuite/26_numerics/random/discrete_distribution/cons/
	initlist.cc: New.
	* testsuite/26_numerics/random/discrete_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/discrete_distribution/cons/
	num_xbound_fun.cc: New.
	* testsuite/26_numerics/random/discrete_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/discrete_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/weibull_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/weibull_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/weibull_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/weibull_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/negative_binomial_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/negative_binomial_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/negative_binomial_distribution/
	requirements/typedefs.cc: New.
	* testsuite/26_numerics/random/negative_binomial_distribution/
	operators/serialize.cc: New.
	* testsuite/26_numerics/random/cauchy_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/cauchy_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/cauchy_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/cauchy_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/gamma_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/gamma_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/gamma_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/gamma_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/fisher_f_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/fisher_f_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/fisher_f_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/fisher_f_distribution/operators/
	serialize.cc: New.

	* testsuite/26_numerics/random/exponential_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/exponential_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/exponential_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/exponential_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/lognormal_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/lognormal_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/lognormal_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/lognormal_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/binomial_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/binomial_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/binomial_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/binomial_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/random_device/cons/
	token.cc: New.
	* testsuite/26_numerics/random/random_device/cons/
	default.cc: New.
	* testsuite/26_numerics/random/random_device/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/extreme_value_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/extreme_value_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/extreme_value_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/extreme_value_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/piecewise_linear_distribution/cons/
	range.cc: New.
	* testsuite/26_numerics/random/piecewise_linear_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/piecewise_linear_distribution/cons/
	num_xbound_fun.cc: New.
	* testsuite/26_numerics/random/piecewise_linear_distribution/cons/
	initlist_fun.cc: New.
	* testsuite/26_numerics/random/piecewise_linear_distribution/
	requirements/typedefs.cc: New.
	* testsuite/26_numerics/random/piecewise_linear_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/student_t_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/student_t_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/student_t_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/student_t_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/geometric_distribution/cons/
	parms.cc: New.
	* testsuite/26_numerics/random/geometric_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/geometric_distribution/requirements/
	typedefs.cc: New.
	* testsuite/26_numerics/random/geometric_distribution/operators/
	serialize.cc: New.
	* testsuite/26_numerics/random/piecewise_constant_distribution/cons/
	range.cc: New.
	* testsuite/26_numerics/random/piecewise_constant_distribution/cons/
	default.cc: New.
	* testsuite/26_numerics/random/piecewise_constant_distribution/cons/
	num_xbound_fun.cc: New.
	* testsuite/26_numerics/random/piecewise_constant_distribution/cons/
	initlist_fun.cc: New.
	* testsuite/26_numerics/random/piecewise_constant_distribution/
	requirements/typedefs.cc: New.
	* testsuite/26_numerics/random/piecewise_constant_distribution/
	operators/serialize.cc: New.



git-svn-id: svn+ssh://gcc.gnu.org/svn/gcc/trunk@145483 138bc75d-0d04-0410-961f-82ee72b054a4

3 files changed, 4021 insertions, 6 deletions

diff --git a/libstdc++-v3/include/tr1/random b/libstdc++-v3/include/tr1/random
index 49a3b21cd81..6f6e3234b89 100644
--- a/libstdc++-v3/include/tr1/random
+++ b/libstdc++-v3/include/tr1/random
@@ -55,16 +55,12 @@
 #include <tr1/cmath>
 
 #if defined(_GLIBCXX_INCLUDE_AS_TR1)
-#  include <tr1_impl/random>
+#  include <tr1/random.h>
 #else
 #  define _GLIBCXX_INCLUDE_AS_TR1
-#  define _GLIBCXX_BEGIN_NAMESPACE_TR1 namespace tr1 {
-#  define _GLIBCXX_END_NAMESPACE_TR1 }
 #  define _GLIBCXX_TR1 tr1::
-#  include <tr1_impl/random>
+#  include <tr1/random.h>
 #  undef _GLIBCXX_TR1
-#  undef _GLIBCXX_END_NAMESPACE_TR1
-#  undef _GLIBCXX_BEGIN_NAMESPACE_TR1
 #  undef _GLIBCXX_INCLUDE_AS_TR1
 #endif
 
diff --git a/libstdc++-v3/include/tr1/random.h b/libstdc++-v3/include/tr1/random.h
new file mode 100644
index 00000000000..5a0f6b741b6
--- /dev/null
+++ b/libstdc++-v3/include/tr1/random.h
@@ -0,0 +1,2436 @@
+// random number generation -*- C++ -*-
+
+// Copyright (C) 2007, 2008 Free Software Foundation, Inc.
+//
+// This file is part of the GNU ISO C++ Library.  This library is free
+// software; you can redistribute it and/or modify it under the
+// terms of the GNU General Public License as published by the
+// Free Software Foundation; either version 2, or (at your option)
+// any later version.
+
+// This library is distributed in the hope that it will be useful,
+// but WITHOUT ANY WARRANTY; without even the implied warranty of
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+// GNU General Public License for more details.
+
+// You should have received a copy of the GNU General Public License along
+// with this library; see the file COPYING.  If not, write to the Free
+// Software Foundation, 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301,
+// USA.
+
+// As a special exception, you may use this file as part of a free software
+// library without restriction.  Specifically, if other files instantiate
+// templates or use macros or inline functions from this file, or you compile
+// this file and link it with other files to produce an executable, this
+// file does not by itself cause the resulting executable to be covered by
+// the GNU General Public License.  This exception does not however
+// invalidate any other reasons why the executable file might be covered by
+// the GNU General Public License.
+
+/**
+ * @file tr1/random.h
+ *  This is an internal header file, included by other library headers.
+ *  You should not attempt to use it directly.
+ */
+
+#ifndef _GLIBCXX_TR1_RANDOM_H
+#define _GLIBCXX_TR1_RANDOM_H 1
+
+#pragma GCC system_header
+
+#if defined(_GLIBCXX_INCLUDE_AS_CXX0X)
+#  error TR1 header cannot be included from C++0x header
+#endif
+
+#include <cmath>
+#include <cstdio>
+#include <cstdlib>
+#include <string>
+#include <iosfwd>
+#include <limits>
+#include <ext/type_traits.h>
+#include <ext/numeric_traits.h>
+#include <bits/concept_check.h>
+#include <debug/debug.h>
+#include <tr1/type_traits>
+#include <tr1/cmath>
+
+namespace std
+{
+namespace tr1
+{
+
+  // [5.1] Random number generation
+
+  /**
+   * @addtogroup tr1_random Random Number Generation
+   * A facility for generating random numbers on selected distributions.
+   * @{
+   */
+
+  /*
+   * Implementation-space details.
+   */
+  namespace __detail
+  {
+    template<typename _UIntType, int __w, 
+	     bool = __w < std::numeric_limits<_UIntType>::digits>
+      struct _Shift
+      { static const _UIntType __value = 0; };
+
+    template<typename _UIntType, int __w>
+      struct _Shift<_UIntType, __w, true>
+      { static const _UIntType __value = _UIntType(1) << __w; };
+
+    template<typename _Tp, _Tp __a, _Tp __c, _Tp __m, bool>
+      struct _Mod;
+
+    // Dispatch based on modulus value to prevent divide-by-zero compile-time
+    // errors when m == 0.
+    template<typename _Tp, _Tp __a, _Tp __c, _Tp __m>
+      inline _Tp
+      __mod(_Tp __x)
+      { return _Mod<_Tp, __a, __c, __m, __m == 0>::__calc(__x); }
+
+    typedef __gnu_cxx::__conditional_type<(sizeof(unsigned) == 4),
+		    unsigned, unsigned long>::__type _UInt32Type;
+
+    /*
+     * An adaptor class for converting the output of any Generator into
+     * the input for a specific Distribution.
+     */
+    template<typename _Engine, typename _Distribution>
+      struct _Adaptor
+      { 
+	typedef typename remove_reference<_Engine>::type _BEngine;
+	typedef typename _BEngine::result_type           _Engine_result_type;
+	typedef typename _Distribution::input_type       result_type;
+
+      public:
+	_Adaptor(const _Engine& __g)
+	: _M_g(__g) { }
+
+	result_type
+	min() const
+	{
+	  result_type __return_value;
+	  if (is_integral<_Engine_result_type>::value
+	      && is_integral<result_type>::value)
+	    __return_value = _M_g.min();
+	  else
+	    __return_value = result_type(0);
+	  return __return_value;
+	}
+
+	result_type
+	max() const
+	{
+	  result_type __return_value;
+	  if (is_integral<_Engine_result_type>::value
+	      && is_integral<result_type>::value)
+	    __return_value = _M_g.max();
+	  else if (!is_integral<result_type>::value)
+	    __return_value = result_type(1);
+	  else
+	    __return_value = std::numeric_limits<result_type>::max() - 1;
+	  return __return_value;
+	}
+
+	/*
+	 * Converts a value generated by the adapted random number generator
+	 * into a value in the input domain for the dependent random number
+	 * distribution.
+	 *
+	 * Because the type traits are compile time constants only the
+	 * appropriate clause of the if statements will actually be emitted
+	 * by the compiler.
+	 */
+	result_type
+	operator()()
+	{
+	  result_type __return_value;
+	  if (is_integral<_Engine_result_type>::value
+	      && is_integral<result_type>::value)
+	    __return_value = _M_g();
+	  else if (!is_integral<_Engine_result_type>::value
+		   && !is_integral<result_type>::value)
+	    __return_value = result_type(_M_g() - _M_g.min())
+	      / result_type(_M_g.max() - _M_g.min());
+	  else if (is_integral<_Engine_result_type>::value
+		   && !is_integral<result_type>::value)
+	    __return_value = result_type(_M_g() - _M_g.min())
+	      / result_type(_M_g.max() - _M_g.min() + result_type(1));
+	  else
+	    __return_value = (((_M_g() - _M_g.min()) 
+			       / (_M_g.max() - _M_g.min()))
+			      * std::numeric_limits<result_type>::max());
+	  return __return_value;
+	}
+
+      private:
+	_Engine _M_g;
+      };
+
+    // Specialization for _Engine*.
+    template<typename _Engine, typename _Distribution>
+      struct _Adaptor<_Engine*, _Distribution>
+      {
+	typedef typename _Engine::result_type      _Engine_result_type;
+	typedef typename _Distribution::input_type result_type;
+
+      public:
+	_Adaptor(_Engine* __g)
+	: _M_g(__g) { }
+
+	result_type
+	min() const
+	{
+	  result_type __return_value;
+	  if (is_integral<_Engine_result_type>::value
+	      && is_integral<result_type>::value)
+	    __return_value = _M_g->min();
+	  else
+	    __return_value = result_type(0);
+	  return __return_value;
+	}
+
+	result_type
+	max() const
+	{
+	  result_type __return_value;
+	  if (is_integral<_Engine_result_type>::value
+	      && is_integral<result_type>::value)
+	    __return_value = _M_g->max();
+	  else if (!is_integral<result_type>::value)
+	    __return_value = result_type(1);
+	  else
+	    __return_value = std::numeric_limits<result_type>::max() - 1;
+	  return __return_value;
+	}
+
+	result_type
+	operator()()
+	{
+	  result_type __return_value;
+	  if (is_integral<_Engine_result_type>::value
+	      && is_integral<result_type>::value)
+	    __return_value = (*_M_g)();
+	  else if (!is_integral<_Engine_result_type>::value
+		   && !is_integral<result_type>::value)
+	    __return_value = result_type((*_M_g)() - _M_g->min())
+	      / result_type(_M_g->max() - _M_g->min());
+	  else if (is_integral<_Engine_result_type>::value
+		   && !is_integral<result_type>::value)
+	    __return_value = result_type((*_M_g)() - _M_g->min())
+	      / result_type(_M_g->max() - _M_g->min() + result_type(1));
+	  else
+	    __return_value = ((((*_M_g)() - _M_g->min()) 
+			       / (_M_g->max() - _M_g->min()))
+			      * std::numeric_limits<result_type>::max());
+	  return __return_value;
+	}
+
+      private:
+	_Engine* _M_g;
+      };
+  } // namespace __detail
+
+  /**
+   * Produces random numbers on a given distribution function using a
+   * non-uniform random number generation engine.
+   *
+   * @todo the engine_value_type needs to be studied more carefully.
+   */
+  template<typename _Engine, typename _Dist>
+    class variate_generator
+    {
+      // Concept requirements.
+      __glibcxx_class_requires(_Engine, _CopyConstructibleConcept)
+      //  __glibcxx_class_requires(_Engine, _EngineConcept)
+      //  __glibcxx_class_requires(_Dist, _EngineConcept)
+
+    public:
+      typedef _Engine                                engine_type;
+      typedef __detail::_Adaptor<_Engine, _Dist>     engine_value_type;
+      typedef _Dist                                  distribution_type;
+      typedef typename _Dist::result_type            result_type;
+
+      // tr1:5.1.1 table 5.1 requirement
+      typedef typename __gnu_cxx::__enable_if<
+	is_arithmetic<result_type>::value, result_type>::__type _IsValidType;
+
+      /**
+       * Constructs a variate generator with the uniform random number
+       * generator @p __eng for the random distribution @p __dist.
+       *
+       * @throws Any exceptions which may thrown by the copy constructors of
+       * the @p _Engine or @p _Dist objects.
+       */
+      variate_generator(engine_type __eng, distribution_type __dist)
+      : _M_engine(__eng), _M_dist(__dist) { }
+
+      /**
+       * Gets the next generated value on the distribution.
+       */
+      result_type
+      operator()()
+      { return _M_dist(_M_engine); }
+
+      /**
+       * WTF?
+       */
+      template<typename _Tp>
+        result_type
+        operator()(_Tp __value)
+        { return _M_dist(_M_engine, __value); }
+
+      /**
+       * Gets a reference to the underlying uniform random number generator
+       * object.
+       */
+      engine_value_type&
+      engine()
+      { return _M_engine; }
+
+      /**
+       * Gets a const reference to the underlying uniform random number
+       * generator object.
+       */
+      const engine_value_type&
+      engine() const
+      { return _M_engine; }
+
+      /**
+       * Gets a reference to the underlying random distribution.
+       */
+      distribution_type&
+      distribution()
+      { return _M_dist; }
+
+      /**
+       * Gets a const reference to the underlying random distribution.
+       */
+      const distribution_type&
+      distribution() const
+      { return _M_dist; }
+
+      /**
+       * Gets the closed lower bound of the distribution interval.
+       */
+      result_type
+      min() const
+      { return this->distribution().min(); }
+
+      /**
+       * Gets the closed upper bound of the distribution interval.
+       */
+      result_type
+      max() const
+      { return this->distribution().max(); }
+
+    private:
+      engine_value_type _M_engine;
+      distribution_type _M_dist;
+    };
+
+
+  /**
+   * @addtogroup tr1_random_generators Random Number Generators
+   * @ingroup tr1_random
+   *
+   * These classes define objects which provide random or pseudorandom
+   * numbers, either from a discrete or a continuous interval.  The
+   * random number generator supplied as a part of this library are
+   * all uniform random number generators which provide a sequence of
+   * random number uniformly distributed over their range.
+   *
+   * A number generator is a function object with an operator() that
+   * takes zero arguments and returns a number.
+   *
+   * A compliant random number generator must satisfy the following
+   * requirements.  <table border=1 cellpadding=10 cellspacing=0>
+   * <caption align=top>Random Number Generator Requirements</caption>
+   * <tr><td>To be documented.</td></tr> </table>
+   * 
+   * @{
+   */
+
+  /**
+   * @brief A model of a linear congruential random number generator.
+   *
+   * A random number generator that produces pseudorandom numbers using the
+   * linear function @f$x_{i+1}\leftarrow(ax_{i} + c) \bmod m @f$.
+   *
+   * The template parameter @p _UIntType must be an unsigned integral type
+   * large enough to store values up to (__m-1). If the template parameter
+   * @p __m is 0, the modulus @p __m used is
+   * std::numeric_limits<_UIntType>::max() plus 1. Otherwise, the template
+   * parameters @p __a and @p __c must be less than @p __m.
+   *
+   * The size of the state is @f$ 1 @f$.
+   */
+  template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+    class linear_congruential
+    {
+      __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept)
+      //  __glibcpp_class_requires(__a < __m && __c < __m)
+
+    public:
+      /** The type of the generated random value. */
+      typedef _UIntType result_type;
+
+      /** The multiplier. */
+      static const _UIntType multiplier = __a;
+      /** An increment. */
+      static const _UIntType increment = __c;
+      /** The modulus. */
+      static const _UIntType modulus = __m;
+
+      /**
+       * Constructs a %linear_congruential random number generator engine with
+       * seed @p __s.  The default seed value is 1.
+       *
+       * @param __s The initial seed value.
+       */
+      explicit
+      linear_congruential(unsigned long __x0 = 1)
+      { this->seed(__x0); }
+
+      /**
+       * Constructs a %linear_congruential random number generator engine
+       * seeded from the generator function @p __g.
+       *
+       * @param __g The seed generator function.
+       */
+      template<class _Gen>
+        linear_congruential(_Gen& __g)
+        { this->seed(__g); }
+
+      /**
+       * Reseeds the %linear_congruential random number generator engine
+       * sequence to the seed @g __s.
+       *
+       * @param __s The new seed.
+       */
+      void
+      seed(unsigned long __s = 1);
+
+      /**
+       * Reseeds the %linear_congruential random number generator engine
+       * sequence using values from the generator function @p __g.
+       *
+       * @param __g the seed generator function.
+       */
+      template<class _Gen>
+        void
+        seed(_Gen& __g)
+        { seed(__g, typename is_fundamental<_Gen>::type()); }
+
+      /**
+       * Gets the smallest possible value in the output range.
+       *
+       * The minimum depends on the @p __c parameter: if it is zero, the
+       * minimum generated must be > 0, otherwise 0 is allowed.
+       */
+      result_type
+      min() const
+      { return (__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0) ? 1 : 0; }
+
+      /**
+       * Gets the largest possible value in the output range.
+       */
+      result_type
+      max() const
+      { return __m - 1; }
+
+      /**
+       * Gets the next random number in the sequence.
+       */
+      result_type
+      operator()();
+
+      /**
+       * Compares two linear congruential random number generator
+       * objects of the same type for equality.
+       *  
+       * @param __lhs A linear congruential random number generator object.
+       * @param __rhs Another linear congruential random number generator obj.
+       *
+       * @returns true if the two objects are equal, false otherwise.
+       */
+      friend bool
+      operator==(const linear_congruential& __lhs,
+		 const linear_congruential& __rhs)
+      { return __lhs._M_x == __rhs._M_x; }
+
+      /**
+       * Compares two linear congruential random number generator
+       * objects of the same type for inequality.
+       *
+       * @param __lhs A linear congruential random number generator object.
+       * @param __rhs Another linear congruential random number generator obj.
+       *
+       * @returns true if the two objects are not equal, false otherwise.
+       */
+      friend bool
+      operator!=(const linear_congruential& __lhs,
+		 const linear_congruential& __rhs)
+      { return !(__lhs == __rhs); }
+
+      /**
+       * Writes the textual representation of the state x(i) of x to @p __os.
+       *
+       * @param __os  The output stream.
+       * @param __lcr A % linear_congruential random number generator.
+       * @returns __os.
+       */
+      template<class _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
+	       _UIntType1 __m1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const linear_congruential<_UIntType1, __a1, __c1,
+		   __m1>& __lcr);
+
+      /**
+       * Sets the state of the engine by reading its textual
+       * representation from @p __is.
+       *
+       * The textual representation must have been previously written using an
+       * output stream whose imbued locale and whose type's template
+       * specialization arguments _CharT and _Traits were the same as those of
+       * @p __is.
+       *
+       * @param __is  The input stream.
+       * @param __lcr A % linear_congruential random number generator.
+       * @returns __is.
+       */
+      template<class _UIntType1, _UIntType1 __a1, _UIntType1 __c1,
+	       _UIntType1 __m1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   linear_congruential<_UIntType1, __a1, __c1, __m1>& __lcr);
+
+    private:
+      template<class _Gen>
+        void
+        seed(_Gen& __g, true_type)
+        { return seed(static_cast<unsigned long>(__g)); }
+
+      template<class _Gen>
+        void
+        seed(_Gen& __g, false_type);
+
+      _UIntType _M_x;
+    };
+
+  /**
+   * The classic Minimum Standard rand0 of Lewis, Goodman, and Miller.
+   */
+  typedef linear_congruential<unsigned long, 16807, 0, 2147483647> minstd_rand0;
+
+  /**
+   * An alternative LCR (Lehmer Generator function) .
+   */
+  typedef linear_congruential<unsigned long, 48271, 0, 2147483647> minstd_rand;
+
+
+  /**
+   * A generalized feedback shift register discrete random number generator.
+   *
+   * This algorithm avoids multiplication and division and is designed to be
+   * friendly to a pipelined architecture.  If the parameters are chosen
+   * correctly, this generator will produce numbers with a very long period and
+   * fairly good apparent entropy, although still not cryptographically strong.
+   *
+   * The best way to use this generator is with the predefined mt19937 class.
+   *
+   * This algorithm was originally invented by Makoto Matsumoto and
+   * Takuji Nishimura.
+   *
+   * @var word_size   The number of bits in each element of the state vector.
+   * @var state_size  The degree of recursion.
+   * @var shift_size  The period parameter.
+   * @var mask_bits   The separation point bit index.
+   * @var parameter_a The last row of the twist matrix.
+   * @var output_u    The first right-shift tempering matrix parameter.
+   * @var output_s    The first left-shift tempering matrix parameter.
+   * @var output_b    The first left-shift tempering matrix mask.
+   * @var output_t    The second left-shift tempering matrix parameter.
+   * @var output_c    The second left-shift tempering matrix mask.
+   * @var output_l    The second right-shift tempering matrix parameter.
+   */
+  template<class _UIntType, int __w, int __n, int __m, int __r,
+	   _UIntType __a, int __u, int __s, _UIntType __b, int __t,
+	   _UIntType __c, int __l>
+    class mersenne_twister
+    {
+      __glibcxx_class_requires(_UIntType, _UnsignedIntegerConcept)
+
+    public:
+      // types
+      typedef _UIntType result_type;
+
+      // parameter values
+      static const int       word_size   = __w;
+      static const int       state_size  = __n;
+      static const int       shift_size  = __m;
+      static const int       mask_bits   = __r;
+      static const _UIntType parameter_a = __a;
+      static const int       output_u    = __u;
+      static const int       output_s    = __s;
+      static const _UIntType output_b    = __b;
+      static const int       output_t    = __t;
+      static const _UIntType output_c    = __c;
+      static const int       output_l    = __l;
+
+      // constructors and member function
+      mersenne_twister()
+      { seed(); }
+
+      explicit
+      mersenne_twister(unsigned long __value)
+      { seed(__value); }
+
+      template<class _Gen>
+        mersenne_twister(_Gen& __g)
+        { seed(__g); }
+
+      void
+      seed()
+      { seed(5489UL); }
+
+      void
+      seed(unsigned long __value);
+
+      template<class _Gen>
+        void
+        seed(_Gen& __g)
+        { seed(__g, typename is_fundamental<_Gen>::type()); }
+
+      result_type
+      min() const
+      { return 0; };
+
+      result_type
+      max() const
+      { return __detail::_Shift<_UIntType, __w>::__value - 1; }
+
+      result_type
+      operator()();
+
+      /**
+       * Compares two % mersenne_twister random number generator objects of
+       * the same type for equality.
+       *
+       * @param __lhs A % mersenne_twister random number generator object.
+       * @param __rhs Another % mersenne_twister random number generator
+       *              object.
+       *
+       * @returns true if the two objects are equal, false otherwise.
+       */
+      friend bool
+      operator==(const mersenne_twister& __lhs,
+		 const mersenne_twister& __rhs)
+      { return std::equal(__lhs._M_x, __lhs._M_x + state_size, __rhs._M_x); }
+
+      /**
+       * Compares two % mersenne_twister random number generator objects of
+       * the same type for inequality.
+       *
+       * @param __lhs A % mersenne_twister random number generator object.
+       * @param __rhs Another % mersenne_twister random number generator
+       *              object.
+       *
+       * @returns true if the two objects are not equal, false otherwise.
+       */
+      friend bool
+      operator!=(const mersenne_twister& __lhs,
+		 const mersenne_twister& __rhs)
+      { return !(__lhs == __rhs); }
+
+      /**
+       * Inserts the current state of a % mersenne_twister random number
+       * generator engine @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A % mersenne_twister random number generator engine.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<class _UIntType1, int __w1, int __n1, int __m1, int __r1,
+	       _UIntType1 __a1, int __u1, int __s1, _UIntType1 __b1, int __t1,
+	       _UIntType1 __c1, int __l1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const mersenne_twister<_UIntType1, __w1, __n1, __m1, __r1,
+		   __a1, __u1, __s1, __b1, __t1, __c1, __l1>& __x);
+
+      /**
+       * Extracts the current state of a % mersenne_twister random number
+       * generator engine @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A % mersenne_twister random number generator engine.
+       *
+       * @returns The input stream with the state of @p __x extracted or in
+       * an error state.
+       */
+      template<class _UIntType1, int __w1, int __n1, int __m1, int __r1,
+	       _UIntType1 __a1, int __u1, int __s1, _UIntType1 __b1, int __t1,
+	       _UIntType1 __c1, int __l1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   mersenne_twister<_UIntType1, __w1, __n1, __m1, __r1,
+		   __a1, __u1, __s1, __b1, __t1, __c1, __l1>& __x);
+
+    private:
+      template<class _Gen>
+        void
+        seed(_Gen& __g, true_type)
+        { return seed(static_cast<unsigned long>(__g)); }
+
+      template<class _Gen>
+        void
+        seed(_Gen& __g, false_type);
+
+      _UIntType _M_x[state_size];
+      int       _M_p;
+    };
+
+  /**
+   * The classic Mersenne Twister.
+   *
+   * Reference:
+   * M. Matsumoto and T. Nishimura, "Mersenne Twister: A 623-Dimensionally
+   * Equidistributed Uniform Pseudo-Random Number Generator", ACM Transactions
+   * on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3-30.
+   */
+  typedef mersenne_twister<
+    unsigned long, 32, 624, 397, 31,
+    0x9908b0dful, 11, 7,
+    0x9d2c5680ul, 15,
+    0xefc60000ul, 18
+    > mt19937;
+
+
+  /**
+   * @brief The Marsaglia-Zaman generator.
+   * 
+   * This is a model of a Generalized Fibonacci discrete random number
+   * generator, sometimes referred to as the SWC generator.
+   *
+   * A discrete random number generator that produces pseudorandom
+   * numbers using @f$x_{i}\leftarrow(x_{i - s} - x_{i - r} -
+   * carry_{i-1}) \bmod m @f$.
+   *
+   * The size of the state is @f$ r @f$
+   * and the maximum period of the generator is @f$ m^r - m^s -1 @f$.
+   *
+   * N1688[4.13] says "the template parameter _IntType shall denote an integral
+   * type large enough to store values up to m."
+   *
+   * @var _M_x     The state of the generator.  This is a ring buffer.
+   * @var _M_carry The carry.
+   * @var _M_p     Current index of x(i - r).
+   */
+  template<typename _IntType, _IntType __m, int __s, int __r>
+    class subtract_with_carry
+    {
+      __glibcxx_class_requires(_IntType, _IntegerConcept)
+
+    public:
+      /** The type of the generated random value. */
+      typedef _IntType result_type;
+      
+      // parameter values
+      static const _IntType modulus   = __m;
+      static const int      long_lag  = __r;
+      static const int      short_lag = __s;
+
+      /**
+       * Constructs a default-initialized % subtract_with_carry random number
+       * generator.
+       */
+      subtract_with_carry()
+      { this->seed(); }
+
+      /**
+       * Constructs an explicitly seeded % subtract_with_carry random number
+       * generator.
+       */
+      explicit
+      subtract_with_carry(unsigned long __value)
+      { this->seed(__value); }
+
+      /**
+       * Constructs a %subtract_with_carry random number generator engine
+       * seeded from the generator function @p __g.
+       *
+       * @param __g The seed generator function.
+       */
+      template<class _Gen>
+        subtract_with_carry(_Gen& __g)
+        { this->seed(__g); }
+
+      /**
+       * Seeds the initial state @f$ x_0 @f$ of the random number generator.
+       *
+       * N1688[4.19] modifies this as follows.  If @p __value == 0,
+       * sets value to 19780503.  In any case, with a linear
+       * congruential generator lcg(i) having parameters @f$ m_{lcg} =
+       * 2147483563, a_{lcg} = 40014, c_{lcg} = 0, and lcg(0) = value
+       * @f$, sets @f$ x_{-r} \dots x_{-1} @f$ to @f$ lcg(1) \bmod m
+       * \dots lcg(r) \bmod m @f$ respectively.  If @f$ x_{-1} = 0 @f$
+       * set carry to 1, otherwise sets carry to 0.
+       */
+      void
+      seed(unsigned long __value = 19780503);
+
+      /**
+       * Seeds the initial state @f$ x_0 @f$ of the % subtract_with_carry
+       * random number generator.
+       */
+      template<class _Gen>
+        void
+        seed(_Gen& __g)
+        { seed(__g, typename is_fundamental<_Gen>::type()); }
+
+      /**
+       * Gets the inclusive minimum value of the range of random integers
+       * returned by this generator.
+       */
+      result_type
+      min() const
+      { return 0; }
+
+      /**
+       * Gets the inclusive maximum value of the range of random integers
+       * returned by this generator.
+       */
+      result_type
+      max() const
+      { return this->modulus - 1; }
+
+      /**
+       * Gets the next random number in the sequence.
+       */
+      result_type
+      operator()();
+
+      /**
+       * Compares two % subtract_with_carry random number generator objects of
+       * the same type for equality.
+       *
+       * @param __lhs A % subtract_with_carry random number generator object.
+       * @param __rhs Another % subtract_with_carry random number generator
+       *              object.
+       *
+       * @returns true if the two objects are equal, false otherwise.
+       */
+      friend bool
+      operator==(const subtract_with_carry& __lhs,
+		 const subtract_with_carry& __rhs)
+      { return std::equal(__lhs._M_x, __lhs._M_x + long_lag, __rhs._M_x); }
+
+      /**
+       * Compares two % subtract_with_carry random number generator objects of
+       * the same type for inequality.
+       *
+       * @param __lhs A % subtract_with_carry random number generator object.
+       * @param __rhs Another % subtract_with_carry random number generator
+       *              object.
+       *
+       * @returns true if the two objects are not equal, false otherwise.
+       */
+      friend bool
+      operator!=(const subtract_with_carry& __lhs,
+		 const subtract_with_carry& __rhs)
+      { return !(__lhs == __rhs); }
+
+      /**
+       * Inserts the current state of a % subtract_with_carry random number
+       * generator engine @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A % subtract_with_carry random number generator engine.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _IntType1, _IntType1 __m1, int __s1, int __r1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const subtract_with_carry<_IntType1, __m1, __s1,
+		   __r1>& __x);
+
+      /**
+       * Extracts the current state of a % subtract_with_carry random number
+       * generator engine @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A % subtract_with_carry random number generator engine.
+       *
+       * @returns The input stream with the state of @p __x extracted or in
+       * an error state.
+       */
+      template<typename _IntType1, _IntType1 __m1, int __s1, int __r1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   subtract_with_carry<_IntType1, __m1, __s1, __r1>& __x);
+
+    private:
+      template<class _Gen>
+        void
+        seed(_Gen& __g, true_type)
+        { return seed(static_cast<unsigned long>(__g)); }
+
+      template<class _Gen>
+        void
+        seed(_Gen& __g, false_type);
+
+      typedef typename __gnu_cxx::__add_unsigned<_IntType>::__type _UIntType;
+
+      _UIntType  _M_x[long_lag];
+      _UIntType  _M_carry;
+      int        _M_p;
+    };
+
+
+  /**
+   * @brief The Marsaglia-Zaman generator (floats version).
+   *
+   * @var _M_x     The state of the generator.  This is a ring buffer.
+   * @var _M_carry The carry.
+   * @var _M_p     Current index of x(i - r).
+   * @var _M_npows Precomputed negative powers of 2.   
+   */
+  template<typename _RealType, int __w, int __s, int __r>
+    class subtract_with_carry_01
+    {
+    public:
+      /** The type of the generated random value. */
+      typedef _RealType result_type;
+      
+      // parameter values
+      static const int      word_size = __w;
+      static const int      long_lag  = __r;
+      static const int      short_lag = __s;
+
+      /**
+       * Constructs a default-initialized % subtract_with_carry_01 random
+       * number generator.
+       */
+      subtract_with_carry_01()
+      {
+	this->seed();
+	_M_initialize_npows();
+      }
+
+      /**
+       * Constructs an explicitly seeded % subtract_with_carry_01 random number
+       * generator.
+       */
+      explicit
+      subtract_with_carry_01(unsigned long __value)
+      {
+	this->seed(__value);
+	_M_initialize_npows();
+      }
+
+      /**
+       * Constructs a % subtract_with_carry_01 random number generator engine
+       * seeded from the generator function @p __g.
+       *
+       * @param __g The seed generator function.
+       */
+      template<class _Gen>
+        subtract_with_carry_01(_Gen& __g)
+        {
+	  this->seed(__g);
+	  _M_initialize_npows();	  
+	}
+
+      /**
+       * Seeds the initial state @f$ x_0 @f$ of the random number generator.
+       */
+      void
+      seed(unsigned long __value = 19780503);
+
+      /**
+       * Seeds the initial state @f$ x_0 @f$ of the % subtract_with_carry_01
+       * random number generator.
+       */
+      template<class _Gen>
+        void
+        seed(_Gen& __g)
+        { seed(__g, typename is_fundamental<_Gen>::type()); }
+
+      /**
+       * Gets the minimum value of the range of random floats
+       * returned by this generator.
+       */
+      result_type
+      min() const
+      { return 0.0; }
+
+      /**
+       * Gets the maximum value of the range of random floats
+       * returned by this generator.
+       */
+      result_type
+      max() const
+      { return 1.0; }
+
+      /**
+       * Gets the next random number in the sequence.
+       */
+      result_type
+      operator()();
+
+      /**
+       * Compares two % subtract_with_carry_01 random number generator objects
+       * of the same type for equality.
+       *
+       * @param __lhs A % subtract_with_carry_01 random number
+       *              generator object.
+       * @param __rhs Another % subtract_with_carry_01 random number generator
+       *              object.
+       *
+       * @returns true if the two objects are equal, false otherwise.
+       */
+      friend bool
+      operator==(const subtract_with_carry_01& __lhs,
+		 const subtract_with_carry_01& __rhs)
+      {
+	for (int __i = 0; __i < long_lag; ++__i)
+	  if (!std::equal(__lhs._M_x[__i], __lhs._M_x[__i] + __n,
+			  __rhs._M_x[__i]))
+	    return false;
+	return true;
+      }
+
+      /**
+       * Compares two % subtract_with_carry_01 random number generator objects
+       * of the same type for inequality.
+       *
+       * @param __lhs A % subtract_with_carry_01 random number
+       *              generator object.
+       *
+       * @param __rhs Another % subtract_with_carry_01 random number generator
+       *              object.
+       *
+       * @returns true if the two objects are not equal, false otherwise.
+       */
+      friend bool
+      operator!=(const subtract_with_carry_01& __lhs,
+		 const subtract_with_carry_01& __rhs)
+      { return !(__lhs == __rhs); }
+
+      /**
+       * Inserts the current state of a % subtract_with_carry_01 random number
+       * generator engine @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A % subtract_with_carry_01 random number generator engine.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _RealType1, int __w1, int __s1, int __r1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const subtract_with_carry_01<_RealType1, __w1, __s1,
+		   __r1>& __x);
+
+      /**
+       * Extracts the current state of a % subtract_with_carry_01 random number
+       * generator engine @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A % subtract_with_carry_01 random number generator engine.
+       *
+       * @returns The input stream with the state of @p __x extracted or in
+       * an error state.
+       */
+      template<typename _RealType1, int __w1, int __s1, int __r1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   subtract_with_carry_01<_RealType1, __w1, __s1, __r1>& __x);
+
+    private:
+      template<class _Gen>
+        void
+        seed(_Gen& __g, true_type)
+        { return seed(static_cast<unsigned long>(__g)); }
+
+      template<class _Gen>
+        void
+        seed(_Gen& __g, false_type);
+
+      void
+      _M_initialize_npows();
+
+      static const int __n = (__w + 31) / 32;
+
+      typedef __detail::_UInt32Type _UInt32Type;
+      _UInt32Type  _M_x[long_lag][__n];
+      _RealType    _M_npows[__n];
+      _UInt32Type  _M_carry;
+      int          _M_p;
+    };
+
+  typedef subtract_with_carry_01<float, 24, 10, 24>   ranlux_base_01;
+
+  // _GLIBCXX_RESOLVE_LIB_DEFECTS
+  // 508. Bad parameters for ranlux64_base_01.
+  typedef subtract_with_carry_01<double, 48, 5, 12> ranlux64_base_01;  
+
+
+  /**
+   * Produces random numbers from some base engine by discarding blocks of
+   * data.
+   *
+   * 0 <= @p __r <= @p __p
+   */
+  template<class _UniformRandomNumberGenerator, int __p, int __r>
+    class discard_block
+    {
+      // __glibcxx_class_requires(typename base_type::result_type,
+      //                          ArithmeticTypeConcept)
+
+    public:
+      /** The type of the underlying generator engine. */
+      typedef _UniformRandomNumberGenerator   base_type;
+      /** The type of the generated random value. */
+      typedef typename base_type::result_type result_type;
+
+      // parameter values
+      static const int block_size = __p;
+      static const int used_block = __r;
+
+      /**
+       * Constructs a default %discard_block engine.
+       *
+       * The underlying engine is default constructed as well.
+       */
+      discard_block()
+      : _M_n(0) { }
+
+      /**
+       * Copy constructs a %discard_block engine.
+       *
+       * Copies an existing base class random number generator.
+       * @param rng An existing (base class) engine object.
+       */
+      explicit
+      discard_block(const base_type& __rng)
+      : _M_b(__rng), _M_n(0) { }
+
+      /**
+       * Seed constructs a %discard_block engine.
+       *
+       * Constructs the underlying generator engine seeded with @p __s.
+       * @param __s A seed value for the base class engine.
+       */
+      explicit
+      discard_block(unsigned long __s)
+      : _M_b(__s), _M_n(0) { }
+
+      /**
+       * Generator construct a %discard_block engine.
+       *
+       * @param __g A seed generator function.
+       */
+      template<class _Gen>
+        discard_block(_Gen& __g)
+	: _M_b(__g), _M_n(0) { }
+
+      /**
+       * Reseeds the %discard_block object with the default seed for the
+       * underlying base class generator engine.
+       */
+      void seed()
+      {
+	_M_b.seed();
+	_M_n = 0;
+      }
+
+      /**
+       * Reseeds the %discard_block object with the given seed generator
+       * function.
+       * @param __g A seed generator function.
+       */
+      template<class _Gen>
+        void seed(_Gen& __g)
+        {
+	  _M_b.seed(__g);
+	  _M_n = 0;
+	}
+
+      /**
+       * Gets a const reference to the underlying generator engine object.
+       */
+      const base_type&
+      base() const
+      { return _M_b; }
+
+      /**
+       * Gets the minimum value in the generated random number range.
+       */
+      result_type
+      min() const
+      { return _M_b.min(); }
+
+      /**
+       * Gets the maximum value in the generated random number range.
+       */
+      result_type
+      max() const
+      { return _M_b.max(); }
+
+      /**
+       * Gets the next value in the generated random number sequence.
+       */
+      result_type
+      operator()();
+
+      /**
+       * Compares two %discard_block random number generator objects of
+       * the same type for equality.
+       *
+       * @param __lhs A %discard_block random number generator object.
+       * @param __rhs Another %discard_block random number generator
+       *              object.
+       *
+       * @returns true if the two objects are equal, false otherwise.
+       */
+      friend bool
+      operator==(const discard_block& __lhs, const discard_block& __rhs)
+      { return (__lhs._M_b == __rhs._M_b) && (__lhs._M_n == __rhs._M_n); }
+
+      /**
+       * Compares two %discard_block random number generator objects of
+       * the same type for inequality.
+       *
+       * @param __lhs A %discard_block random number generator object.
+       * @param __rhs Another %discard_block random number generator
+       *              object.
+       *
+       * @returns true if the two objects are not equal, false otherwise.
+       */
+      friend bool
+      operator!=(const discard_block& __lhs, const discard_block& __rhs)
+      { return !(__lhs == __rhs); }
+
+      /**
+       * Inserts the current state of a %discard_block random number
+       * generator engine @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %discard_block random number generator engine.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<class _UniformRandomNumberGenerator1, int __p1, int __r1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const discard_block<_UniformRandomNumberGenerator1,
+		   __p1, __r1>& __x);
+
+      /**
+       * Extracts the current state of a % subtract_with_carry random number
+       * generator engine @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %discard_block random number generator engine.
+       *
+       * @returns The input stream with the state of @p __x extracted or in
+       * an error state.
+       */
+      template<class _UniformRandomNumberGenerator1, int __p1, int __r1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   discard_block<_UniformRandomNumberGenerator1,
+		   __p1, __r1>& __x);
+
+    private:
+      base_type _M_b;
+      int       _M_n;
+    };
+
+
+  /**
+   * James's luxury-level-3 integer adaptation of Luescher's generator.
+   */
+  typedef discard_block<
+    subtract_with_carry<unsigned long, (1UL << 24), 10, 24>,
+      223,
+      24
+      > ranlux3;
+
+  /**
+   * James's luxury-level-4 integer adaptation of Luescher's generator.
+   */
+  typedef discard_block<
+    subtract_with_carry<unsigned long, (1UL << 24), 10, 24>,
+      389,
+      24
+      > ranlux4;
+
+  typedef discard_block<
+    subtract_with_carry_01<float, 24, 10, 24>,
+      223,
+      24
+      > ranlux3_01;
+
+  typedef discard_block<
+    subtract_with_carry_01<float, 24, 10, 24>,
+      389,
+      24
+      > ranlux4_01;
+
+
+  /**
+   * A random number generator adaptor class that combines two random number
+   * generator engines into a single output sequence.
+   */
+  template<class _UniformRandomNumberGenerator1, int __s1,
+	   class _UniformRandomNumberGenerator2, int __s2>
+    class xor_combine
+    {
+      // __glibcxx_class_requires(typename _UniformRandomNumberGenerator1::
+      //                          result_type, ArithmeticTypeConcept)
+      // __glibcxx_class_requires(typename _UniformRandomNumberGenerator2::
+      //                          result_type, ArithmeticTypeConcept)
+
+    public:
+      /** The type of the first underlying generator engine. */
+      typedef _UniformRandomNumberGenerator1   base1_type;
+      /** The type of the second underlying generator engine. */
+      typedef _UniformRandomNumberGenerator2   base2_type;
+
+    private:
+      typedef typename base1_type::result_type _Result_type1;
+      typedef typename base2_type::result_type _Result_type2;
+
+    public:
+      /** The type of the generated random value. */
+      typedef typename __gnu_cxx::__conditional_type<(sizeof(_Result_type1)
+						      > sizeof(_Result_type2)),
+	_Result_type1, _Result_type2>::__type result_type;
+
+      // parameter values
+      static const int shift1 = __s1;
+      static const int shift2 = __s2;
+
+      // constructors and member function
+      xor_combine()
+      : _M_b1(), _M_b2()	
+      { _M_initialize_max(); }
+
+      xor_combine(const base1_type& __rng1, const base2_type& __rng2)
+      : _M_b1(__rng1), _M_b2(__rng2)
+      { _M_initialize_max(); }
+
+      xor_combine(unsigned long __s)
+      : _M_b1(__s), _M_b2(__s + 1)
+      { _M_initialize_max(); }
+
+      template<class _Gen>
+        xor_combine(_Gen& __g)
+	: _M_b1(__g), _M_b2(__g)
+        { _M_initialize_max(); }
+
+      void
+      seed()
+      {
+	_M_b1.seed();
+	_M_b2.seed();
+      }
+
+      template<class _Gen>
+        void
+        seed(_Gen& __g)
+        {
+	  _M_b1.seed(__g);
+	  _M_b2.seed(__g);
+	}
+
+      const base1_type&
+      base1() const
+      { return _M_b1; }
+
+      const base2_type&
+      base2() const
+      { return _M_b2; }
+
+      result_type
+      min() const
+      { return 0; }
+
+      result_type
+      max() const
+      { return _M_max; }
+
+      /**
+       * Gets the next random number in the sequence.
+       */
+      // NB: Not exactly the TR1 formula, per N2079 instead.
+      result_type
+      operator()()
+      {
+	return ((result_type(_M_b1() - _M_b1.min()) << shift1)
+		^ (result_type(_M_b2() - _M_b2.min()) << shift2));
+      }
+
+      /**
+       * Compares two %xor_combine random number generator objects of
+       * the same type for equality.
+       *
+       * @param __lhs A %xor_combine random number generator object.
+       * @param __rhs Another %xor_combine random number generator
+       *              object.
+       *
+       * @returns true if the two objects are equal, false otherwise.
+       */
+      friend bool
+      operator==(const xor_combine& __lhs, const xor_combine& __rhs)
+      {
+	return (__lhs.base1() == __rhs.base1())
+	        && (__lhs.base2() == __rhs.base2());
+      }
+
+      /**
+       * Compares two %xor_combine random number generator objects of
+       * the same type for inequality.
+       *
+       * @param __lhs A %xor_combine random number generator object.
+       * @param __rhs Another %xor_combine random number generator
+       *              object.
+       *
+       * @returns true if the two objects are not equal, false otherwise.
+       */
+      friend bool
+      operator!=(const xor_combine& __lhs, const xor_combine& __rhs)
+      { return !(__lhs == __rhs); }
+
+      /**
+       * Inserts the current state of a %xor_combine random number
+       * generator engine @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %xor_combine random number generator engine.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<class _UniformRandomNumberGenerator11, int __s11,
+	       class _UniformRandomNumberGenerator21, int __s21,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const xor_combine<_UniformRandomNumberGenerator11, __s11,
+		   _UniformRandomNumberGenerator21, __s21>& __x);
+
+      /**
+       * Extracts the current state of a %xor_combine random number
+       * generator engine @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %xor_combine random number generator engine.
+       *
+       * @returns The input stream with the state of @p __x extracted or in
+       * an error state.
+       */
+      template<class _UniformRandomNumberGenerator11, int __s11,
+	       class _UniformRandomNumberGenerator21, int __s21,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   xor_combine<_UniformRandomNumberGenerator11, __s11,
+		   _UniformRandomNumberGenerator21, __s21>& __x);
+
+    private:
+      void
+      _M_initialize_max();
+
+      result_type
+      _M_initialize_max_aux(result_type, result_type, int);
+
+      base1_type  _M_b1;
+      base2_type  _M_b2;
+      result_type _M_max;
+    };
+
+
+  /**
+   * A standard interface to a platform-specific non-deterministic
+   * random number generator (if any are available).
+   */
+  class random_device
+  {
+  public:
+    // types
+    typedef unsigned int result_type;
+
+    // constructors, destructors and member functions
+
+#ifdef _GLIBCXX_USE_RANDOM_TR1
+
+    explicit
+    random_device(const std::string& __token = "/dev/urandom")
+    {
+      if ((__token != "/dev/urandom" && __token != "/dev/random")
+	  || !(_M_file = std::fopen(__token.c_str(), "rb")))
+	std::__throw_runtime_error(__N("random_device::"
+				       "random_device(const std::string&)"));
+    }
+
+    ~random_device()
+    { std::fclose(_M_file); }
+
+#else
+
+    explicit
+    random_device(const std::string& __token = "mt19937")
+    : _M_mt(_M_strtoul(__token)) { }
+
+  private:
+    static unsigned long
+    _M_strtoul(const std::string& __str)
+    {
+      unsigned long __ret = 5489UL;
+      if (__str != "mt19937")
+	{
+	  const char* __nptr = __str.c_str();
+	  char* __endptr;
+	  __ret = std::strtoul(__nptr, &__endptr, 0);
+	  if (*__nptr == '\0' || *__endptr != '\0')
+	    std::__throw_runtime_error(__N("random_device::_M_strtoul"
+					   "(const std::string&)"));
+	}
+      return __ret;
+    }
+
+  public:
+
+#endif
+
+    result_type
+    min() const
+    { return std::numeric_limits<result_type>::min(); }
+
+    result_type
+    max() const
+    { return std::numeric_limits<result_type>::max(); }
+
+    double
+    entropy() const
+    { return 0.0; }
+
+    result_type
+    operator()()
+    {
+#ifdef _GLIBCXX_USE_RANDOM_TR1
+      result_type __ret;
+      std::fread(reinterpret_cast<void*>(&__ret), sizeof(result_type),
+		 1, _M_file);
+      return __ret;
+#else
+      return _M_mt();
+#endif
+    }
+
+  private:
+    random_device(const random_device&);
+    void operator=(const random_device&);
+
+#ifdef _GLIBCXX_USE_RANDOM_TR1
+    FILE*        _M_file;
+#else
+    mt19937      _M_mt;
+#endif
+  };
+
+  /* @} */ // group tr1_random_generators
+
+  /**
+   * @addtogroup tr1_random_distributions Random Number Distributions
+   * @ingroup tr1_random
+   * @{
+   */
+
+  /**
+   * @addtogroup tr1_random_distributions_discrete Discrete Distributions
+   * @ingroup tr1_random_distributions
+   * @{
+   */
+
+  /**
+   * @brief Uniform discrete distribution for random numbers.
+   * A discrete random distribution on the range @f$[min, max]@f$ with equal
+   * probability throughout the range.
+   */
+  template<typename _IntType = int>
+    class uniform_int
+    {
+      __glibcxx_class_requires(_IntType, _IntegerConcept)
+ 
+    public:
+      /** The type of the parameters of the distribution. */
+      typedef _IntType input_type;
+      /** The type of the range of the distribution. */
+      typedef _IntType result_type;
+
+    public:
+      /**
+       * Constructs a uniform distribution object.
+       */
+      explicit
+      uniform_int(_IntType __min = 0, _IntType __max = 9)
+      : _M_min(__min), _M_max(__max)
+      {
+	_GLIBCXX_DEBUG_ASSERT(_M_min <= _M_max);
+      }
+
+      /**
+       * Gets the inclusive lower bound of the distribution range.
+       */
+      result_type
+      min() const
+      { return _M_min; }
+
+      /**
+       * Gets the inclusive upper bound of the distribution range.
+       */
+      result_type
+      max() const
+      { return _M_max; }
+
+      /**
+       * Resets the distribution state.
+       *
+       * Does nothing for the uniform integer distribution.
+       */
+      void
+      reset() { }
+
+      /**
+       * Gets a uniformly distributed random number in the range
+       * @f$(min, max)@f$.
+       */
+      template<typename _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng)
+        {
+	  typedef typename _UniformRandomNumberGenerator::result_type
+	    _UResult_type;
+	  return _M_call(__urng, _M_min, _M_max,
+			 typename is_integral<_UResult_type>::type());
+	}
+
+      /**
+       * Gets a uniform random number in the range @f$[0, n)@f$.
+       *
+       * This function is aimed at use with std::random_shuffle.
+       */
+      template<typename _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng, result_type __n)
+        {
+	  typedef typename _UniformRandomNumberGenerator::result_type
+	    _UResult_type;
+	  return _M_call(__urng, 0, __n - 1,
+			 typename is_integral<_UResult_type>::type());
+	}
+
+      /**
+       * Inserts a %uniform_int random number distribution @p __x into the
+       * output stream @p os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %uniform_int random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _IntType1, typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const uniform_int<_IntType1>& __x);
+
+      /**
+       * Extracts a %uniform_int random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %uniform_int random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _IntType1, typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   uniform_int<_IntType1>& __x);
+
+    private:
+      template<typename _UniformRandomNumberGenerator>
+        result_type
+        _M_call(_UniformRandomNumberGenerator& __urng,
+		result_type __min, result_type __max, true_type);
+
+      template<typename _UniformRandomNumberGenerator>
+        result_type
+        _M_call(_UniformRandomNumberGenerator& __urng,
+		result_type __min, result_type __max, false_type)
+        {
+	  return result_type((__urng() - __urng.min())
+			     / (__urng.max() - __urng.min())
+			     * (__max - __min + 1)) + __min;
+	}
+
+      _IntType _M_min;
+      _IntType _M_max;
+    };
+
+
+  /**
+   * @brief A Bernoulli random number distribution.
+   *
+   * Generates a sequence of true and false values with likelihood @f$ p @f$
+   * that true will come up and @f$ (1 - p) @f$ that false will appear.
+   */
+  class bernoulli_distribution
+  {
+  public:
+    typedef int  input_type;
+    typedef bool result_type;
+
+  public:
+    /**
+     * Constructs a Bernoulli distribution with likelihood @p p.
+     *
+     * @param __p  [IN]  The likelihood of a true result being returned.  Must
+     * be in the interval @f$ [0, 1] @f$.
+     */
+    explicit
+    bernoulli_distribution(double __p = 0.5)
+    : _M_p(__p)
+    { 
+      _GLIBCXX_DEBUG_ASSERT((_M_p >= 0.0) && (_M_p <= 1.0));
+    }
+
+    /**
+     * Gets the @p p parameter of the distribution.
+     */
+    double
+    p() const
+    { return _M_p; }
+
+    /**
+     * Resets the distribution state.
+     *
+     * Does nothing for a Bernoulli distribution.
+     */
+    void
+    reset() { }
+
+    /**
+     * Gets the next value in the Bernoullian sequence.
+     */
+    template<class _UniformRandomNumberGenerator>
+      result_type
+      operator()(_UniformRandomNumberGenerator& __urng)
+      {
+	if ((__urng() - __urng.min()) < _M_p * (__urng.max() - __urng.min()))
+	  return true;
+	return false;
+      }
+
+    /**
+     * Inserts a %bernoulli_distribution random number distribution
+     * @p __x into the output stream @p __os.
+     *
+     * @param __os An output stream.
+     * @param __x  A %bernoulli_distribution random number distribution.
+     *
+     * @returns The output stream with the state of @p __x inserted or in
+     * an error state.
+     */
+    template<typename _CharT, typename _Traits>
+      friend std::basic_ostream<_CharT, _Traits>&
+      operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		 const bernoulli_distribution& __x);
+
+    /**
+     * Extracts a %bernoulli_distribution random number distribution
+     * @p __x from the input stream @p __is.
+     *
+     * @param __is An input stream.
+     * @param __x  A %bernoulli_distribution random number generator engine.
+     *
+     * @returns The input stream with @p __x extracted or in an error state.
+     */
+    template<typename _CharT, typename _Traits>
+      friend std::basic_istream<_CharT, _Traits>&
+      operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		 bernoulli_distribution& __x)
+      { return __is >> __x._M_p; }
+
+  private:
+    double _M_p;
+  };
+
+
+  /**
+   * @brief A discrete geometric random number distribution.
+   *
+   * The formula for the geometric probability mass function is 
+   * @f$ p(i) = (1 - p)p^{i-1} @f$ where @f$ p @f$ is the parameter of the
+   * distribution.
+   */
+  template<typename _IntType = int, typename _RealType = double>
+    class geometric_distribution
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _IntType  result_type;
+
+      // constructors and member function
+      explicit
+      geometric_distribution(const _RealType& __p = _RealType(0.5))
+      : _M_p(__p)
+      {
+	_GLIBCXX_DEBUG_ASSERT((_M_p > 0.0) && (_M_p < 1.0));
+	_M_initialize();
+      }
+
+      /**
+       * Gets the distribution parameter @p p.
+       */
+      _RealType
+      p() const
+      { return _M_p; }
+
+      void
+      reset() { }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng);
+
+      /**
+       * Inserts a %geometric_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %geometric_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _IntType1, typename _RealType1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const geometric_distribution<_IntType1, _RealType1>& __x);
+
+      /**
+       * Extracts a %geometric_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %geometric_distribution random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   geometric_distribution& __x)
+        {
+	  __is >> __x._M_p;
+	  __x._M_initialize();
+	  return __is;
+	}
+
+    private:
+      void
+      _M_initialize()
+      { _M_log_p = std::log(_M_p); }
+
+      _RealType _M_p;
+      _RealType _M_log_p;
+    };
+
+
+  template<typename _RealType>
+    class normal_distribution;
+
+  /**
+   * @brief A discrete Poisson random number distribution.
+   *
+   * The formula for the Poisson probability mass function is
+   * @f$ p(i) = \frac{mean^i}{i!} e^{-mean} @f$ where @f$ mean @f$ is the
+   * parameter of the distribution.
+   */
+  template<typename _IntType = int, typename _RealType = double>
+    class poisson_distribution
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _IntType  result_type;
+
+      // constructors and member function
+      explicit
+      poisson_distribution(const _RealType& __mean = _RealType(1))
+      : _M_mean(__mean), _M_nd()
+      {
+	_GLIBCXX_DEBUG_ASSERT(_M_mean > 0.0);
+	_M_initialize();
+      }
+
+      /**
+       * Gets the distribution parameter @p mean.
+       */
+      _RealType
+      mean() const
+      { return _M_mean; }
+
+      void
+      reset()
+      { _M_nd.reset(); }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng);
+
+      /**
+       * Inserts a %poisson_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %poisson_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _IntType1, typename _RealType1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const poisson_distribution<_IntType1, _RealType1>& __x);
+
+      /**
+       * Extracts a %poisson_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %poisson_distribution random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _IntType1, typename _RealType1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   poisson_distribution<_IntType1, _RealType1>& __x);
+
+    private:
+      void
+      _M_initialize();
+
+      // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
+      normal_distribution<_RealType> _M_nd;
+
+      _RealType _M_mean;
+
+      // Hosts either log(mean) or the threshold of the simple method.
+      _RealType _M_lm_thr;
+#if _GLIBCXX_USE_C99_MATH_TR1
+      _RealType _M_lfm, _M_sm, _M_d, _M_scx, _M_1cx, _M_c2b, _M_cb;
+#endif
+    };
+
+
+  /**
+   * @brief A discrete binomial random number distribution.
+   *
+   * The formula for the binomial probability mass function is 
+   * @f$ p(i) = \binom{n}{i} p^i (1 - p)^{t - i} @f$ where @f$ t @f$
+   * and @f$ p @f$ are the parameters of the distribution.
+   */
+  template<typename _IntType = int, typename _RealType = double>
+    class binomial_distribution
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _IntType  result_type;
+
+      // constructors and member function
+      explicit
+      binomial_distribution(_IntType __t = 1,
+			    const _RealType& __p = _RealType(0.5))
+      : _M_t(__t), _M_p(__p), _M_nd()
+      {
+	_GLIBCXX_DEBUG_ASSERT((_M_t >= 0) && (_M_p >= 0.0) && (_M_p <= 1.0));
+	_M_initialize();
+      }
+
+      /**
+       * Gets the distribution @p t parameter.
+       */
+      _IntType
+      t() const
+      { return _M_t; }
+      
+      /**
+       * Gets the distribution @p p parameter.
+       */
+      _RealType
+      p() const
+      { return _M_p; }
+
+      void
+      reset()
+      { _M_nd.reset(); }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng);
+
+      /**
+       * Inserts a %binomial_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %binomial_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _IntType1, typename _RealType1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const binomial_distribution<_IntType1, _RealType1>& __x);
+
+      /**
+       * Extracts a %binomial_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %binomial_distribution random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _IntType1, typename _RealType1,
+	       typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   binomial_distribution<_IntType1, _RealType1>& __x);
+
+    private:
+      void
+      _M_initialize();
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t);
+
+      // NB: Unused when _GLIBCXX_USE_C99_MATH_TR1 is undefined.
+      normal_distribution<_RealType> _M_nd;
+
+      _RealType _M_q;
+#if _GLIBCXX_USE_C99_MATH_TR1
+      _RealType _M_d1, _M_d2, _M_s1, _M_s2, _M_c,
+	        _M_a1, _M_a123, _M_s, _M_lf, _M_lp1p;
+#endif
+      _RealType _M_p;
+      _IntType  _M_t;
+
+      bool      _M_easy;
+    };
+
+  /* @} */ // group tr1_random_distributions_discrete
+
+  /**
+   * @addtogroup tr1_random_distributions_continuous Continuous Distributions
+   * @ingroup tr1_random_distributions
+   * @{
+   */
+
+  /**
+   * @brief Uniform continuous distribution for random numbers.
+   *
+   * A continuous random distribution on the range [min, max) with equal
+   * probability throughout the range.  The URNG should be real-valued and
+   * deliver number in the range [0, 1).
+   */
+  template<typename _RealType = double>
+    class uniform_real
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _RealType result_type;
+
+    public:
+      /**
+       * Constructs a uniform_real object.
+       *
+       * @param __min [IN]  The lower bound of the distribution.
+       * @param __max [IN]  The upper bound of the distribution.
+       */
+      explicit
+      uniform_real(_RealType __min = _RealType(0),
+		   _RealType __max = _RealType(1))
+      : _M_min(__min), _M_max(__max)
+      {
+	_GLIBCXX_DEBUG_ASSERT(_M_min <= _M_max);
+      }
+
+      result_type
+      min() const
+      { return _M_min; }
+
+      result_type
+      max() const
+      { return _M_max; }
+
+      void
+      reset() { }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng)
+        { return (__urng() * (_M_max - _M_min)) + _M_min; }
+
+      /**
+       * Inserts a %uniform_real random number distribution @p __x into the
+       * output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %uniform_real random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const uniform_real<_RealType1>& __x);
+
+      /**
+       * Extracts a %uniform_real random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %uniform_real random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   uniform_real<_RealType1>& __x);
+
+    private:
+      _RealType _M_min;
+      _RealType _M_max;
+    };
+
+
+  /**
+   * @brief An exponential continuous distribution for random numbers.
+   *
+   * The formula for the exponential probability mass function is 
+   * @f$ p(x) = \lambda e^{-\lambda x} @f$.
+   *
+   * <table border=1 cellpadding=10 cellspacing=0>
+   * <caption align=top>Distribution Statistics</caption>
+   * <tr><td>Mean</td><td>@f$ \frac{1}{\lambda} @f$</td></tr>
+   * <tr><td>Median</td><td>@f$ \frac{\ln 2}{\lambda} @f$</td></tr>
+   * <tr><td>Mode</td><td>@f$ zero @f$</td></tr>
+   * <tr><td>Range</td><td>@f$[0, \infty]@f$</td></tr>
+   * <tr><td>Standard Deviation</td><td>@f$ \frac{1}{\lambda} @f$</td></tr>
+   * </table>
+   */
+  template<typename _RealType = double>
+    class exponential_distribution
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _RealType result_type;
+
+    public:
+      /**
+       * Constructs an exponential distribution with inverse scale parameter
+       * @f$ \lambda @f$.
+       */
+      explicit
+      exponential_distribution(const result_type& __lambda = result_type(1))
+      : _M_lambda(__lambda)
+      { 
+	_GLIBCXX_DEBUG_ASSERT(_M_lambda > 0);
+      }
+
+      /**
+       * Gets the inverse scale parameter of the distribution.
+       */
+      _RealType
+      lambda() const
+      { return _M_lambda; }
+
+      /**
+       * Resets the distribution.
+       *
+       * Has no effect on exponential distributions.
+       */
+      void
+      reset() { }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng)
+        { return -std::log(__urng()) / _M_lambda; }
+
+      /**
+       * Inserts a %exponential_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %exponential_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const exponential_distribution<_RealType1>& __x);
+
+      /**
+       * Extracts a %exponential_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x A %exponential_distribution random number
+       *            generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   exponential_distribution& __x)
+        { return __is >> __x._M_lambda; }
+
+    private:
+      result_type _M_lambda;
+    };
+
+
+  /**
+   * @brief A normal continuous distribution for random numbers.
+   *
+   * The formula for the normal probability mass function is 
+   * @f$ p(x) = \frac{1}{\sigma \sqrt{2 \pi}} 
+   *            e^{- \frac{{x - mean}^ {2}}{2 \sigma ^ {2}} } @f$.
+   */
+  template<typename _RealType = double>
+    class normal_distribution
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _RealType result_type;
+
+    public:
+      /**
+       * Constructs a normal distribution with parameters @f$ mean @f$ and
+       * @f$ \sigma @f$.
+       */
+      explicit
+      normal_distribution(const result_type& __mean = result_type(0),
+			  const result_type& __sigma = result_type(1))
+      : _M_mean(__mean), _M_sigma(__sigma), _M_saved_available(false)
+      { 
+	_GLIBCXX_DEBUG_ASSERT(_M_sigma > 0);
+      }
+
+      /**
+       * Gets the mean of the distribution.
+       */
+      _RealType
+      mean() const
+      { return _M_mean; }
+
+      /**
+       * Gets the @f$ \sigma @f$ of the distribution.
+       */
+      _RealType
+      sigma() const
+      { return _M_sigma; }
+
+      /**
+       * Resets the distribution.
+       */
+      void
+      reset()
+      { _M_saved_available = false; }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng);
+
+      /**
+       * Inserts a %normal_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %normal_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const normal_distribution<_RealType1>& __x);
+
+      /**
+       * Extracts a %normal_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %normal_distribution random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   normal_distribution<_RealType1>& __x);
+
+    private:
+      result_type _M_mean;
+      result_type _M_sigma;
+      result_type _M_saved;
+      bool        _M_saved_available;     
+    };
+
+
+  /**
+   * @brief A gamma continuous distribution for random numbers.
+   *
+   * The formula for the gamma probability mass function is 
+   * @f$ p(x) = \frac{1}{\Gamma(\alpha)} x^{\alpha - 1} e^{-x} @f$.
+   */
+  template<typename _RealType = double>
+    class gamma_distribution
+    {
+    public:
+      // types
+      typedef _RealType input_type;
+      typedef _RealType result_type;
+
+    public:
+      /**
+       * Constructs a gamma distribution with parameters @f$ \alpha @f$.
+       */
+      explicit
+      gamma_distribution(const result_type& __alpha_val = result_type(1))
+      : _M_alpha(__alpha_val)
+      { 
+	_GLIBCXX_DEBUG_ASSERT(_M_alpha > 0);
+	_M_initialize();
+      }
+
+      /**
+       * Gets the @f$ \alpha @f$ of the distribution.
+       */
+      _RealType
+      alpha() const
+      { return _M_alpha; }
+
+      /**
+       * Resets the distribution.
+       */
+      void
+      reset() { }
+
+      template<class _UniformRandomNumberGenerator>
+        result_type
+        operator()(_UniformRandomNumberGenerator& __urng);
+
+      /**
+       * Inserts a %gamma_distribution random number distribution
+       * @p __x into the output stream @p __os.
+       *
+       * @param __os An output stream.
+       * @param __x  A %gamma_distribution random number distribution.
+       *
+       * @returns The output stream with the state of @p __x inserted or in
+       * an error state.
+       */
+      template<typename _RealType1, typename _CharT, typename _Traits>
+        friend std::basic_ostream<_CharT, _Traits>&
+        operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+		   const gamma_distribution<_RealType1>& __x);
+
+      /**
+       * Extracts a %gamma_distribution random number distribution
+       * @p __x from the input stream @p __is.
+       *
+       * @param __is An input stream.
+       * @param __x  A %gamma_distribution random number generator engine.
+       *
+       * @returns The input stream with @p __x extracted or in an error state.
+       */
+      template<typename _CharT, typename _Traits>
+        friend std::basic_istream<_CharT, _Traits>&
+        operator>>(std::basic_istream<_CharT, _Traits>& __is,
+		   gamma_distribution& __x)
+        {
+	  __is >> __x._M_alpha;
+	  __x._M_initialize();
+	  return __is;
+	}
+
+    private:
+      void
+      _M_initialize();
+
+      result_type _M_alpha;
+
+      // Hosts either lambda of GB or d of modified Vaduva's.
+      result_type _M_l_d;
+    };
+
+  /* @} */ // group tr1_random_distributions_continuous
+  /* @} */ // group tr1_random_distributions
+  /* @} */ // group tr1_random
+
+}
+}
+
+#include <tr1/random.tcc>
+
+#endif // _GLIBCXX_TR1_RANDOM_H
diff --git a/libstdc++-v3/include/tr1/random.tcc b/libstdc++-v3/include/tr1/random.tcc
new file mode 100644
index 00000000000..ec06ae31a6c
--- /dev/null
+++ b/libstdc++-v3/include/tr1/random.tcc
@@ -0,0 +1,1583 @@
+// random number generation (out of line) -*- C++ -*-
+
+// Copyright (C) 2007 Free Software Foundation, Inc.
+//
+// This file is part of the GNU ISO C++ Library.  This library is free
+// software; you can redistribute it and/or modify it under the
+// terms of the GNU General Public License as published by the
+// Free Software Foundation; either version 2, or (at your option)
+// any later version.
+
+// This library is distributed in the hope that it will be useful,
+// but WITHOUT ANY WARRANTY; without even the implied warranty of
+// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+// GNU General Public License for more details.
+
+// You should have received a copy of the GNU General Public License along
+// with this library; see the file COPYING.  If not, write to the Free
+// Software Foundation, 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301,
+// USA.
+
+// As a special exception, you may use this file as part of a free software
+// library without restriction.  Specifically, if other files instantiate
+// templates or use macros or inline functions from this file, or you compile
+// this file and link it with other files to produce an executable, this
+// file does not by itself cause the resulting executable to be covered by
+// the GNU General Public License.  This exception does not however
+// invalidate any other reasons why the executable file might be covered by
+// the GNU General Public License.
+
+/** @file tr1/random.tcc
+ *  This is an internal header file, included by other library headers.
+ *  You should not attempt to use it directly.
+ */
+
+namespace std
+{
+namespace tr1
+{
+
+  /*
+   * (Further) implementation-space details.
+   */
+  namespace __detail
+  {
+    // General case for x = (ax + c) mod m -- use Schrage's algorithm to avoid
+    // integer overflow.
+    //
+    // Because a and c are compile-time integral constants the compiler kindly
+    // elides any unreachable paths.
+    //
+    // Preconditions:  a > 0, m > 0.
+    //
+    template<typename _Tp, _Tp __a, _Tp __c, _Tp __m, bool>
+      struct _Mod
+      {
+	static _Tp
+	__calc(_Tp __x)
+	{
+	  if (__a == 1)
+	    __x %= __m;
+	  else
+	    {
+	      static const _Tp __q = __m / __a;
+	      static const _Tp __r = __m % __a;
+	      
+	      _Tp __t1 = __a * (__x % __q);
+	      _Tp __t2 = __r * (__x / __q);
+	      if (__t1 >= __t2)
+		__x = __t1 - __t2;
+	      else
+		__x = __m - __t2 + __t1;
+	    }
+
+	  if (__c != 0)
+	    {
+	      const _Tp __d = __m - __x;
+	      if (__d > __c)
+		__x += __c;
+	      else
+		__x = __c - __d;
+	    }
+	  return __x;
+	}
+      };
+
+    // Special case for m == 0 -- use unsigned integer overflow as modulo
+    // operator.
+    template<typename _Tp, _Tp __a, _Tp __c, _Tp __m>
+      struct _Mod<_Tp, __a, __c, __m, true>
+      {
+	static _Tp
+	__calc(_Tp __x)
+	{ return __a * __x + __c; }
+      };
+  } // namespace __detail
+
+  /**
+   * Seeds the LCR with integral value @p __x0, adjusted so that the 
+   * ring identity is never a member of the convergence set.
+   */
+  template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+    void
+    linear_congruential<_UIntType, __a, __c, __m>::
+    seed(unsigned long __x0)
+    {
+      if ((__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0)
+	  && (__detail::__mod<_UIntType, 1, 0, __m>(__x0) == 0))
+	_M_x = __detail::__mod<_UIntType, 1, 0, __m>(1);
+      else
+	_M_x = __detail::__mod<_UIntType, 1, 0, __m>(__x0);
+    }
+
+  /**
+   * Seeds the LCR engine with a value generated by @p __g.
+   */
+  template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+    template<class _Gen>
+      void
+      linear_congruential<_UIntType, __a, __c, __m>::
+      seed(_Gen& __g, false_type)
+      {
+	_UIntType __x0 = __g();
+	if ((__detail::__mod<_UIntType, 1, 0, __m>(__c) == 0)
+	    && (__detail::__mod<_UIntType, 1, 0, __m>(__x0) == 0))
+	  _M_x = __detail::__mod<_UIntType, 1, 0, __m>(1);
+	else
+	  _M_x = __detail::__mod<_UIntType, 1, 0, __m>(__x0);
+      }
+
+  /**
+   * Gets the next generated value in sequence.
+   */
+  template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m>
+    typename linear_congruential<_UIntType, __a, __c, __m>::result_type
+    linear_congruential<_UIntType, __a, __c, __m>::
+    operator()()
+    {
+      _M_x = __detail::__mod<_UIntType, __a, __c, __m>(_M_x);
+      return _M_x;
+    }
+
+  template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const linear_congruential<_UIntType, __a, __c, __m>& __lcr)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
+      __os.fill(__os.widen(' '));
+
+      __os << __lcr._M_x;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os;
+    }
+
+  template<class _UIntType, _UIntType __a, _UIntType __c, _UIntType __m,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       linear_congruential<_UIntType, __a, __c, __m>& __lcr)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec);
+
+      __is >> __lcr._M_x;
+
+      __is.flags(__flags);
+      return __is;
+    } 
+
+
+  template<class _UIntType, int __w, int __n, int __m, int __r,
+	   _UIntType __a, int __u, int __s,
+	   _UIntType __b, int __t, _UIntType __c, int __l>
+    void
+    mersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,
+		     __b, __t, __c, __l>::
+    seed(unsigned long __value)
+    {
+      _M_x[0] = __detail::__mod<_UIntType, 1, 0,
+	__detail::_Shift<_UIntType, __w>::__value>(__value);
+
+      for (int __i = 1; __i < state_size; ++__i)
+	{
+	  _UIntType __x = _M_x[__i - 1];
+	  __x ^= __x >> (__w - 2);
+	  __x *= 1812433253ul;
+	  __x += __i;
+	  _M_x[__i] = __detail::__mod<_UIntType, 1, 0,
+	    __detail::_Shift<_UIntType, __w>::__value>(__x);	  
+	}
+      _M_p = state_size;
+    }
+
+  template<class _UIntType, int __w, int __n, int __m, int __r,
+	   _UIntType __a, int __u, int __s,
+	   _UIntType __b, int __t, _UIntType __c, int __l>
+    template<class _Gen>
+      void
+      mersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,
+		       __b, __t, __c, __l>::
+      seed(_Gen& __gen, false_type)
+      {
+	for (int __i = 0; __i < state_size; ++__i)
+	  _M_x[__i] = __detail::__mod<_UIntType, 1, 0,
+	    __detail::_Shift<_UIntType, __w>::__value>(__gen());
+	_M_p = state_size;
+      }
+
+  template<class _UIntType, int __w, int __n, int __m, int __r,
+	   _UIntType __a, int __u, int __s,
+	   _UIntType __b, int __t, _UIntType __c, int __l>
+    typename
+    mersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,
+		     __b, __t, __c, __l>::result_type
+    mersenne_twister<_UIntType, __w, __n, __m, __r, __a, __u, __s,
+		     __b, __t, __c, __l>::
+    operator()()
+    {
+      // Reload the vector - cost is O(n) amortized over n calls.
+      if (_M_p >= state_size)
+	{
+	  const _UIntType __upper_mask = (~_UIntType()) << __r;
+	  const _UIntType __lower_mask = ~__upper_mask;
+
+	  for (int __k = 0; __k < (__n - __m); ++__k)
+	    {
+	      _UIntType __y = ((_M_x[__k] & __upper_mask)
+			       | (_M_x[__k + 1] & __lower_mask));
+	      _M_x[__k] = (_M_x[__k + __m] ^ (__y >> 1)
+			   ^ ((__y & 0x01) ? __a : 0));
+	    }
+
+	  for (int __k = (__n - __m); __k < (__n - 1); ++__k)
+	    {
+	      _UIntType __y = ((_M_x[__k] & __upper_mask)
+			       | (_M_x[__k + 1] & __lower_mask));
+	      _M_x[__k] = (_M_x[__k + (__m - __n)] ^ (__y >> 1)
+			   ^ ((__y & 0x01) ? __a : 0));
+	    }
+
+	  _UIntType __y = ((_M_x[__n - 1] & __upper_mask)
+			   | (_M_x[0] & __lower_mask));
+	  _M_x[__n - 1] = (_M_x[__m - 1] ^ (__y >> 1)
+			   ^ ((__y & 0x01) ? __a : 0));
+	  _M_p = 0;
+	}
+
+      // Calculate o(x(i)).
+      result_type __z = _M_x[_M_p++];
+      __z ^= (__z >> __u);
+      __z ^= (__z << __s) & __b;
+      __z ^= (__z << __t) & __c;
+      __z ^= (__z >> __l);
+
+      return __z;
+    }
+
+  template<class _UIntType, int __w, int __n, int __m, int __r,
+	   _UIntType __a, int __u, int __s, _UIntType __b, int __t,
+	   _UIntType __c, int __l,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const mersenne_twister<_UIntType, __w, __n, __m,
+	       __r, __a, __u, __s, __b, __t, __c, __l>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
+      __os.fill(__space);
+
+      for (int __i = 0; __i < __n - 1; ++__i)
+	__os << __x._M_x[__i] << __space;
+      __os << __x._M_x[__n - 1];
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os;
+    }
+
+  template<class _UIntType, int __w, int __n, int __m, int __r,
+	   _UIntType __a, int __u, int __s, _UIntType __b, int __t,
+	   _UIntType __c, int __l,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       mersenne_twister<_UIntType, __w, __n, __m,
+	       __r, __a, __u, __s, __b, __t, __c, __l>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      for (int __i = 0; __i < __n; ++__i)
+	__is >> __x._M_x[__i];
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _IntType, _IntType __m, int __s, int __r>
+    void
+    subtract_with_carry<_IntType, __m, __s, __r>::
+    seed(unsigned long __value)
+    {
+      if (__value == 0)
+	__value = 19780503;
+
+      std::_GLIBCXX_TR1 linear_congruential<unsigned long, 40014, 0, 2147483563>
+	__lcg(__value);
+
+      for (int __i = 0; __i < long_lag; ++__i)
+	_M_x[__i] = __detail::__mod<_UIntType, 1, 0, modulus>(__lcg());
+
+      _M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
+      _M_p = 0;
+    }
+
+  template<typename _IntType, _IntType __m, int __s, int __r>
+    template<class _Gen>
+      void
+      subtract_with_carry<_IntType, __m, __s, __r>::
+      seed(_Gen& __gen, false_type)
+      {
+	const int __n = (std::numeric_limits<_UIntType>::digits + 31) / 32;
+
+	for (int __i = 0; __i < long_lag; ++__i)
+	  {
+	    _UIntType __tmp = 0;
+	    _UIntType __factor = 1;
+	    for (int __j = 0; __j < __n; ++__j)
+	      {
+		__tmp += __detail::__mod<__detail::_UInt32Type, 1, 0, 0>
+		         (__gen()) * __factor;
+		__factor *= __detail::_Shift<_UIntType, 32>::__value;
+	      }
+	    _M_x[__i] = __detail::__mod<_UIntType, 1, 0, modulus>(__tmp);
+	  }
+	_M_carry = (_M_x[long_lag - 1] == 0) ? 1 : 0;
+	_M_p = 0;
+      }
+
+  template<typename _IntType, _IntType __m, int __s, int __r>
+    typename subtract_with_carry<_IntType, __m, __s, __r>::result_type
+    subtract_with_carry<_IntType, __m, __s, __r>::
+    operator()()
+    {
+      // Derive short lag index from current index.
+      int __ps = _M_p - short_lag;
+      if (__ps < 0)
+	__ps += long_lag;
+
+      // Calculate new x(i) without overflow or division.
+      // NB: Thanks to the requirements for _IntType, _M_x[_M_p] + _M_carry
+      // cannot overflow.
+      _UIntType __xi;
+      if (_M_x[__ps] >= _M_x[_M_p] + _M_carry)
+	{
+	  __xi = _M_x[__ps] - _M_x[_M_p] - _M_carry;
+	  _M_carry = 0;
+	}
+      else
+	{
+	  __xi = modulus - _M_x[_M_p] - _M_carry + _M_x[__ps];
+	  _M_carry = 1;
+	}
+      _M_x[_M_p] = __xi;
+
+      // Adjust current index to loop around in ring buffer.
+      if (++_M_p >= long_lag)
+	_M_p = 0;
+
+      return __xi;
+    }
+
+  template<typename _IntType, _IntType __m, int __s, int __r,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const subtract_with_carry<_IntType, __m, __s, __r>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
+      __os.fill(__space);
+
+      for (int __i = 0; __i < __r; ++__i)
+	__os << __x._M_x[__i] << __space;
+      __os << __x._M_carry;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os;
+    }
+
+  template<typename _IntType, _IntType __m, int __s, int __r,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       subtract_with_carry<_IntType, __m, __s, __r>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      for (int __i = 0; __i < __r; ++__i)
+	__is >> __x._M_x[__i];
+      __is >> __x._M_carry;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _RealType, int __w, int __s, int __r>
+    void
+    subtract_with_carry_01<_RealType, __w, __s, __r>::
+    _M_initialize_npows()
+    {
+      for (int __j = 0; __j < __n; ++__j)
+#if _GLIBCXX_USE_C99_MATH_TR1
+	_M_npows[__j] = std::_GLIBCXX_TR1 ldexp(_RealType(1), -__w + __j * 32);
+#else
+        _M_npows[__j] = std::pow(_RealType(2), -__w + __j * 32);
+#endif
+    }
+
+  template<typename _RealType, int __w, int __s, int __r>
+    void
+    subtract_with_carry_01<_RealType, __w, __s, __r>::
+    seed(unsigned long __value)
+    {
+      if (__value == 0)
+	__value = 19780503;
+
+      // _GLIBCXX_RESOLVE_LIB_DEFECTS
+      // 512. Seeding subtract_with_carry_01 from a single unsigned long.
+      std::_GLIBCXX_TR1 linear_congruential<unsigned long, 40014, 0, 2147483563>
+	__lcg(__value);
+
+      this->seed(__lcg);
+    }
+
+  template<typename _RealType, int __w, int __s, int __r>
+    template<class _Gen>
+      void
+      subtract_with_carry_01<_RealType, __w, __s, __r>::
+      seed(_Gen& __gen, false_type)
+      {
+	for (int __i = 0; __i < long_lag; ++__i)
+	  {
+	    for (int __j = 0; __j < __n - 1; ++__j)
+	      _M_x[__i][__j] = __detail::__mod<_UInt32Type, 1, 0, 0>(__gen());
+	    _M_x[__i][__n - 1] = __detail::__mod<_UInt32Type, 1, 0,
+	      __detail::_Shift<_UInt32Type, __w % 32>::__value>(__gen());
+	  }
+
+	_M_carry = 1;
+	for (int __j = 0; __j < __n; ++__j)
+	  if (_M_x[long_lag - 1][__j] != 0)
+	    {
+	      _M_carry = 0;
+	      break;
+	    }
+
+	_M_p = 0;
+      }
+
+  template<typename _RealType, int __w, int __s, int __r>
+    typename subtract_with_carry_01<_RealType, __w, __s, __r>::result_type
+    subtract_with_carry_01<_RealType, __w, __s, __r>::
+    operator()()
+    {
+      // Derive short lag index from current index.
+      int __ps = _M_p - short_lag;
+      if (__ps < 0)
+	__ps += long_lag;
+
+      _UInt32Type __new_carry;
+      for (int __j = 0; __j < __n - 1; ++__j)
+	{
+	  if (_M_x[__ps][__j] > _M_x[_M_p][__j]
+	      || (_M_x[__ps][__j] == _M_x[_M_p][__j] && _M_carry == 0))
+	    __new_carry = 0;
+	  else
+	    __new_carry = 1;
+
+	  _M_x[_M_p][__j] = _M_x[__ps][__j] - _M_x[_M_p][__j] - _M_carry;
+	  _M_carry = __new_carry;
+	}
+
+      if (_M_x[__ps][__n - 1] > _M_x[_M_p][__n - 1]
+	  || (_M_x[__ps][__n - 1] == _M_x[_M_p][__n - 1] && _M_carry == 0))
+	__new_carry = 0;
+      else
+	__new_carry = 1;
+      
+      _M_x[_M_p][__n - 1] = __detail::__mod<_UInt32Type, 1, 0,
+	__detail::_Shift<_UInt32Type, __w % 32>::__value>
+	(_M_x[__ps][__n - 1] - _M_x[_M_p][__n - 1] - _M_carry);
+      _M_carry = __new_carry;
+
+      result_type __ret = 0.0;
+      for (int __j = 0; __j < __n; ++__j)
+	__ret += _M_x[_M_p][__j] * _M_npows[__j];
+
+      // Adjust current index to loop around in ring buffer.
+      if (++_M_p >= long_lag)
+	_M_p = 0;
+
+      return __ret;
+    }
+
+  template<typename _RealType, int __w, int __s, int __r,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const subtract_with_carry_01<_RealType, __w, __s, __r>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
+      __os.fill(__space);
+
+      for (int __i = 0; __i < __r; ++__i)
+	for (int __j = 0; __j < __x.__n; ++__j)
+	  __os << __x._M_x[__i][__j] << __space;
+      __os << __x._M_carry;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os;
+    }
+
+  template<typename _RealType, int __w, int __s, int __r,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       subtract_with_carry_01<_RealType, __w, __s, __r>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      for (int __i = 0; __i < __r; ++__i)
+	for (int __j = 0; __j < __x.__n; ++__j)
+	  __is >> __x._M_x[__i][__j];
+      __is >> __x._M_carry;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<class _UniformRandomNumberGenerator, int __p, int __r>
+    typename discard_block<_UniformRandomNumberGenerator,
+			   __p, __r>::result_type
+    discard_block<_UniformRandomNumberGenerator, __p, __r>::
+    operator()()
+    {
+      if (_M_n >= used_block)
+	{
+	  while (_M_n < block_size)
+	    {
+	      _M_b();
+	      ++_M_n;
+	    }
+	  _M_n = 0;
+	}
+      ++_M_n;
+      return _M_b();
+    }
+
+  template<class _UniformRandomNumberGenerator, int __p, int __r,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const discard_block<_UniformRandomNumberGenerator,
+	       __p, __r>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::dec | __ios_base::fixed
+		 | __ios_base::left);
+      __os.fill(__space);
+
+      __os << __x._M_b << __space << __x._M_n;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os;
+    }
+
+  template<class _UniformRandomNumberGenerator, int __p, int __r,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       discard_block<_UniformRandomNumberGenerator, __p, __r>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      __is >> __x._M_b >> __x._M_n;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<class _UniformRandomNumberGenerator1, int __s1,
+	   class _UniformRandomNumberGenerator2, int __s2>
+    void
+    xor_combine<_UniformRandomNumberGenerator1, __s1,
+		_UniformRandomNumberGenerator2, __s2>::
+    _M_initialize_max()
+    {
+      const int __w = std::numeric_limits<result_type>::digits;
+
+      const result_type __m1 =
+	std::min(result_type(_M_b1.max() - _M_b1.min()),
+		 __detail::_Shift<result_type, __w - __s1>::__value - 1);
+
+      const result_type __m2 =
+	std::min(result_type(_M_b2.max() - _M_b2.min()),
+		 __detail::_Shift<result_type, __w - __s2>::__value - 1);
+
+      // NB: In TR1 s1 is not required to be >= s2.
+      if (__s1 < __s2)
+	_M_max = _M_initialize_max_aux(__m2, __m1, __s2 - __s1) << __s1;
+      else
+	_M_max = _M_initialize_max_aux(__m1, __m2, __s1 - __s2) << __s2;
+    }
+
+  template<class _UniformRandomNumberGenerator1, int __s1,
+	   class _UniformRandomNumberGenerator2, int __s2>
+    typename xor_combine<_UniformRandomNumberGenerator1, __s1,
+			 _UniformRandomNumberGenerator2, __s2>::result_type
+    xor_combine<_UniformRandomNumberGenerator1, __s1,
+		_UniformRandomNumberGenerator2, __s2>::
+    _M_initialize_max_aux(result_type __a, result_type __b, int __d)
+    {
+      const result_type __two2d = result_type(1) << __d;
+      const result_type __c = __a * __two2d;
+
+      if (__a == 0 || __b < __two2d)
+	return __c + __b;
+
+      const result_type __t = std::max(__c, __b);
+      const result_type __u = std::min(__c, __b);
+
+      result_type __ub = __u;
+      result_type __p;
+      for (__p = 0; __ub != 1; __ub >>= 1)
+	++__p;
+
+      const result_type __two2p = result_type(1) << __p;
+      const result_type __k = __t / __two2p;
+
+      if (__k & 1)
+	return (__k + 1) * __two2p - 1;
+
+      if (__c >= __b)
+	return (__k + 1) * __two2p + _M_initialize_max_aux((__t % __two2p)
+							   / __two2d,
+							   __u % __two2p, __d);
+      else
+	return (__k + 1) * __two2p + _M_initialize_max_aux((__u % __two2p)
+							   / __two2d,
+							   __t % __two2p, __d);
+    }
+
+  template<class _UniformRandomNumberGenerator1, int __s1,
+	   class _UniformRandomNumberGenerator2, int __s2,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const xor_combine<_UniformRandomNumberGenerator1, __s1,
+	       _UniformRandomNumberGenerator2, __s2>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::dec | __ios_base::fixed | __ios_base::left);
+      __os.fill(__space);
+
+      __os << __x.base1() << __space << __x.base2();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os; 
+    }
+
+  template<class _UniformRandomNumberGenerator1, int __s1,
+	   class _UniformRandomNumberGenerator2, int __s2,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       xor_combine<_UniformRandomNumberGenerator1, __s1,
+	       _UniformRandomNumberGenerator2, __s2>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::skipws);
+
+      __is >> __x._M_b1 >> __x._M_b2;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _IntType>
+    template<typename _UniformRandomNumberGenerator>
+      typename uniform_int<_IntType>::result_type
+      uniform_int<_IntType>::
+      _M_call(_UniformRandomNumberGenerator& __urng,
+	      result_type __min, result_type __max, true_type)
+      {
+	// XXX Must be fixed to work well for *arbitrary* __urng.max(),
+	// __urng.min(), __max, __min.  Currently works fine only in the
+	// most common case __urng.max() - __urng.min() >= __max - __min,
+	// with __urng.max() > __urng.min() >= 0.
+	typedef typename __gnu_cxx::__add_unsigned<typename
+	  _UniformRandomNumberGenerator::result_type>::__type __urntype;
+	typedef typename __gnu_cxx::__add_unsigned<result_type>::__type
+	                                                      __utype;
+	typedef typename __gnu_cxx::__conditional_type<(sizeof(__urntype)
+							> sizeof(__utype)),
+	  __urntype, __utype>::__type                         __uctype;
+
+	result_type __ret;
+
+	const __urntype __urnmin = __urng.min();
+	const __urntype __urnmax = __urng.max();
+	const __urntype __urnrange = __urnmax - __urnmin;
+	const __uctype __urange = __max - __min;
+	const __uctype __udenom = (__urnrange <= __urange
+				   ? 1 : __urnrange / (__urange + 1));
+	do
+	  __ret = (__urntype(__urng()) -  __urnmin) / __udenom;
+	while (__ret > __max - __min);
+
+	return __ret + __min;
+      }
+
+  template<typename _IntType, typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const uniform_int<_IntType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__space);
+
+      __os << __x.min() << __space << __x.max();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      return __os;
+    }
+
+  template<typename _IntType, typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       uniform_int<_IntType>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      __is >> __x._M_min >> __x._M_max;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+  
+  template<typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const bernoulli_distribution& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__os.widen(' '));
+      __os.precision(__gnu_cxx::__numeric_traits<double>::__max_digits10);
+
+      __os << __x.p();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+
+  template<typename _IntType, typename _RealType>
+    template<class _UniformRandomNumberGenerator>
+      typename geometric_distribution<_IntType, _RealType>::result_type
+      geometric_distribution<_IntType, _RealType>::
+      operator()(_UniformRandomNumberGenerator& __urng)
+      {
+	// About the epsilon thing see this thread:
+        // http://gcc.gnu.org/ml/gcc-patches/2006-10/msg00971.html
+	const _RealType __naf =
+	  (1 - std::numeric_limits<_RealType>::epsilon()) / 2;
+	// The largest _RealType convertible to _IntType.
+	const _RealType __thr =
+	  std::numeric_limits<_IntType>::max() + __naf;
+
+	_RealType __cand;
+	do
+	  __cand = std::ceil(std::log(__urng()) / _M_log_p);
+	while (__cand >= __thr);
+
+	return result_type(__cand + __naf);
+      }
+
+  template<typename _IntType, typename _RealType,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const geometric_distribution<_IntType, _RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__os.widen(' '));
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x.p();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+
+  template<typename _IntType, typename _RealType>
+    void
+    poisson_distribution<_IntType, _RealType>::
+    _M_initialize()
+    {
+#if _GLIBCXX_USE_C99_MATH_TR1
+      if (_M_mean >= 12)
+	{
+	  const _RealType __m = std::floor(_M_mean);
+	  _M_lm_thr = std::log(_M_mean);
+	  _M_lfm = std::_GLIBCXX_TR1 lgamma(__m + 1);
+	  _M_sm = std::sqrt(__m);
+
+	  const _RealType __pi_4 = 0.7853981633974483096156608458198757L;
+	  const _RealType __dx = std::sqrt(2 * __m * std::log(32 * __m
+							      / __pi_4));
+	  _M_d = std::_GLIBCXX_TR1 round(std::max(_RealType(6),
+						  std::min(__m, __dx)));
+	  const _RealType __cx = 2 * __m + _M_d;
+	  _M_scx = std::sqrt(__cx / 2);
+	  _M_1cx = 1 / __cx;
+
+	  _M_c2b = std::sqrt(__pi_4 * __cx) * std::exp(_M_1cx);
+	  _M_cb = 2 * __cx * std::exp(-_M_d * _M_1cx * (1 + _M_d / 2)) / _M_d;
+	}
+      else
+#endif
+	_M_lm_thr = std::exp(-_M_mean);
+      }
+
+  /**
+   * A rejection algorithm when mean >= 12 and a simple method based
+   * upon the multiplication of uniform random variates otherwise.
+   * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1
+   * is defined.
+   *
+   * Reference:
+   * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+   * New York, 1986, Ch. X, Sects. 3.3 & 3.4 (+ Errata!).
+   */
+  template<typename _IntType, typename _RealType>
+    template<class _UniformRandomNumberGenerator>
+      typename poisson_distribution<_IntType, _RealType>::result_type
+      poisson_distribution<_IntType, _RealType>::
+      operator()(_UniformRandomNumberGenerator& __urng)
+      {
+#if _GLIBCXX_USE_C99_MATH_TR1
+	if (_M_mean >= 12)
+	  {
+	    _RealType __x;
+
+	    // See comments above...
+	    const _RealType __naf =
+	      (1 - std::numeric_limits<_RealType>::epsilon()) / 2;
+	    const _RealType __thr =
+	      std::numeric_limits<_IntType>::max() + __naf;
+
+	    const _RealType __m = std::floor(_M_mean);
+	    // sqrt(pi / 2)
+	    const _RealType __spi_2 = 1.2533141373155002512078826424055226L;
+	    const _RealType __c1 = _M_sm * __spi_2;
+	    const _RealType __c2 = _M_c2b + __c1; 
+	    const _RealType __c3 = __c2 + 1;
+	    const _RealType __c4 = __c3 + 1;
+	    // e^(1 / 78)
+	    const _RealType __e178 = 1.0129030479320018583185514777512983L;
+	    const _RealType __c5 = __c4 + __e178;
+	    const _RealType __c = _M_cb + __c5;
+	    const _RealType __2cx = 2 * (2 * __m + _M_d);
+
+	    bool __reject = true;
+	    do
+	      {
+		const _RealType __u = __c * __urng();
+		const _RealType __e = -std::log(__urng());
+
+		_RealType __w = 0.0;
+		
+		if (__u <= __c1)
+		  {
+		    const _RealType __n = _M_nd(__urng);
+		    const _RealType __y = -std::abs(__n) * _M_sm - 1;
+		    __x = std::floor(__y);
+		    __w = -__n * __n / 2;
+		    if (__x < -__m)
+		      continue;
+		  }
+		else if (__u <= __c2)
+		  {
+		    const _RealType __n = _M_nd(__urng);
+		    const _RealType __y = 1 + std::abs(__n) * _M_scx;
+		    __x = std::ceil(__y);
+		    __w = __y * (2 - __y) * _M_1cx;
+		    if (__x > _M_d)
+		      continue;
+		  }
+		else if (__u <= __c3)
+		  // NB: This case not in the book, nor in the Errata,
+		  // but should be ok...
+		  __x = -1;
+		else if (__u <= __c4)
+		  __x = 0;
+		else if (__u <= __c5)
+		  __x = 1;
+		else
+		  {
+		    const _RealType __v = -std::log(__urng());
+		    const _RealType __y = _M_d + __v * __2cx / _M_d;
+		    __x = std::ceil(__y);
+		    __w = -_M_d * _M_1cx * (1 + __y / 2);
+		  }
+
+		__reject = (__w - __e - __x * _M_lm_thr
+			    > _M_lfm - std::_GLIBCXX_TR1 lgamma(__x + __m + 1));
+
+		__reject |= __x + __m >= __thr;
+
+	      } while (__reject);
+
+	    return result_type(__x + __m + __naf);
+	  }
+	else
+#endif
+	  {
+	    _IntType     __x = 0;
+	    _RealType __prod = 1.0;
+
+	    do
+	      {
+		__prod *= __urng();
+		__x += 1;
+	      }
+	    while (__prod > _M_lm_thr);
+
+	    return __x - 1;
+	  }
+      }
+
+  template<typename _IntType, typename _RealType,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const poisson_distribution<_IntType, _RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__space);
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x.mean() << __space << __x._M_nd;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+  template<typename _IntType, typename _RealType,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       poisson_distribution<_IntType, _RealType>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::skipws);
+
+      __is >> __x._M_mean >> __x._M_nd;
+      __x._M_initialize();
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _IntType, typename _RealType>
+    void
+    binomial_distribution<_IntType, _RealType>::
+    _M_initialize()
+    {
+      const _RealType __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p;
+
+      _M_easy = true;
+
+#if _GLIBCXX_USE_C99_MATH_TR1
+      if (_M_t * __p12 >= 8)
+	{
+	  _M_easy = false;
+	  const _RealType __np = std::floor(_M_t * __p12);
+	  const _RealType __pa = __np / _M_t;
+	  const _RealType __1p = 1 - __pa;
+	  
+	  const _RealType __pi_4 = 0.7853981633974483096156608458198757L;
+	  const _RealType __d1x =
+	    std::sqrt(__np * __1p * std::log(32 * __np
+					     / (81 * __pi_4 * __1p)));
+	  _M_d1 = std::_GLIBCXX_TR1 round(std::max(_RealType(1), __d1x));
+	  const _RealType __d2x =
+	    std::sqrt(__np * __1p * std::log(32 * _M_t * __1p
+					     / (__pi_4 * __pa)));
+	  _M_d2 = std::_GLIBCXX_TR1 round(std::max(_RealType(1), __d2x));
+	  
+	  // sqrt(pi / 2)
+	  const _RealType __spi_2 = 1.2533141373155002512078826424055226L;
+	  _M_s1 = std::sqrt(__np * __1p) * (1 + _M_d1 / (4 * __np));
+	  _M_s2 = std::sqrt(__np * __1p) * (1 + _M_d2 / (4 * _M_t * __1p));
+	  _M_c = 2 * _M_d1 / __np;
+	  _M_a1 = std::exp(_M_c) * _M_s1 * __spi_2;
+	  const _RealType __a12 = _M_a1 + _M_s2 * __spi_2;
+	  const _RealType __s1s = _M_s1 * _M_s1;
+	  _M_a123 = __a12 + (std::exp(_M_d1 / (_M_t * __1p))
+			     * 2 * __s1s / _M_d1
+			     * std::exp(-_M_d1 * _M_d1 / (2 * __s1s)));
+	  const _RealType __s2s = _M_s2 * _M_s2;
+	  _M_s = (_M_a123 + 2 * __s2s / _M_d2
+		  * std::exp(-_M_d2 * _M_d2 / (2 * __s2s)));
+	  _M_lf = (std::_GLIBCXX_TR1 lgamma(__np + 1)
+		   + std::_GLIBCXX_TR1 lgamma(_M_t - __np + 1));
+	  _M_lp1p = std::log(__pa / __1p);
+
+	  _M_q = -std::log(1 - (__p12 - __pa) / __1p);
+	}
+      else
+#endif
+	_M_q = -std::log(1 - __p12);
+    }
+
+  template<typename _IntType, typename _RealType>
+    template<class _UniformRandomNumberGenerator>
+      typename binomial_distribution<_IntType, _RealType>::result_type
+      binomial_distribution<_IntType, _RealType>::
+      _M_waiting(_UniformRandomNumberGenerator& __urng, _IntType __t)
+      {
+	_IntType    __x = 0;
+	_RealType __sum = 0;
+
+	do
+	  {
+	    const _RealType __e = -std::log(__urng());
+	    __sum += __e / (__t - __x);
+	    __x += 1;
+	  }
+	while (__sum <= _M_q);
+
+	return __x - 1;
+      }
+
+  /**
+   * A rejection algorithm when t * p >= 8 and a simple waiting time
+   * method - the second in the referenced book - otherwise.
+   * NB: The former is available only if _GLIBCXX_USE_C99_MATH_TR1
+   * is defined.
+   *
+   * Reference:
+   * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+   * New York, 1986, Ch. X, Sect. 4 (+ Errata!).
+   */
+  template<typename _IntType, typename _RealType>
+    template<class _UniformRandomNumberGenerator>
+      typename binomial_distribution<_IntType, _RealType>::result_type
+      binomial_distribution<_IntType, _RealType>::
+      operator()(_UniformRandomNumberGenerator& __urng)
+      {
+	result_type __ret;
+	const _RealType __p12 = _M_p <= 0.5 ? _M_p : 1.0 - _M_p;
+
+#if _GLIBCXX_USE_C99_MATH_TR1
+	if (!_M_easy)
+	  {
+	    _RealType __x;
+
+	    // See comments above...
+	    const _RealType __naf =
+	      (1 - std::numeric_limits<_RealType>::epsilon()) / 2;
+	    const _RealType __thr =
+	      std::numeric_limits<_IntType>::max() + __naf;
+
+	    const _RealType __np = std::floor(_M_t * __p12);
+	    const _RealType __pa = __np / _M_t;
+
+	    // sqrt(pi / 2)
+	    const _RealType __spi_2 = 1.2533141373155002512078826424055226L;
+	    const _RealType __a1 = _M_a1;
+	    const _RealType __a12 = __a1 + _M_s2 * __spi_2;
+	    const _RealType __a123 = _M_a123;
+	    const _RealType __s1s = _M_s1 * _M_s1;
+	    const _RealType __s2s = _M_s2 * _M_s2;
+
+	    bool __reject;
+	    do
+	      {
+		const _RealType __u = _M_s * __urng();
+
+		_RealType __v;
+
+		if (__u <= __a1)
+		  {
+		    const _RealType __n = _M_nd(__urng);
+		    const _RealType __y = _M_s1 * std::abs(__n);
+		    __reject = __y >= _M_d1;
+		    if (!__reject)
+		      {
+			const _RealType __e = -std::log(__urng());
+			__x = std::floor(__y);
+			__v = -__e - __n * __n / 2 + _M_c;
+		      }
+		  }
+		else if (__u <= __a12)
+		  {
+		    const _RealType __n = _M_nd(__urng);
+		    const _RealType __y = _M_s2 * std::abs(__n);
+		    __reject = __y >= _M_d2;
+		    if (!__reject)
+		      {
+			const _RealType __e = -std::log(__urng());
+			__x = std::floor(-__y);
+			__v = -__e - __n * __n / 2;
+		      }
+		  }
+		else if (__u <= __a123)
+		  {
+		    const _RealType __e1 = -std::log(__urng());		    
+		    const _RealType __e2 = -std::log(__urng());
+
+		    const _RealType __y = _M_d1 + 2 * __s1s * __e1 / _M_d1;
+		    __x = std::floor(__y);
+		    __v = (-__e2 + _M_d1 * (1 / (_M_t - __np)
+					    -__y / (2 * __s1s)));
+		    __reject = false;
+		  }
+		else
+		  {
+		    const _RealType __e1 = -std::log(__urng());		    
+		    const _RealType __e2 = -std::log(__urng());
+
+		    const _RealType __y = _M_d2 + 2 * __s2s * __e1 / _M_d2;
+		    __x = std::floor(-__y);
+		    __v = -__e2 - _M_d2 * __y / (2 * __s2s);
+		    __reject = false;
+		  }
+
+		__reject = __reject || __x < -__np || __x > _M_t - __np;
+		if (!__reject)
+		  {
+		    const _RealType __lfx =
+		      std::_GLIBCXX_TR1 lgamma(__np + __x + 1)
+		      + std::_GLIBCXX_TR1 lgamma(_M_t - (__np + __x) + 1);
+		    __reject = __v > _M_lf - __lfx + __x * _M_lp1p;
+		  }
+
+		__reject |= __x + __np >= __thr;
+	      }
+	    while (__reject);
+
+	    __x += __np + __naf;
+
+	    const _IntType __z = _M_waiting(__urng, _M_t - _IntType(__x)); 
+	    __ret = _IntType(__x) + __z;
+	  }
+	else
+#endif
+	  __ret = _M_waiting(__urng, _M_t);
+
+	if (__p12 != _M_p)
+	  __ret = _M_t - __ret;
+	return __ret;
+      }
+
+  template<typename _IntType, typename _RealType,
+	   typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const binomial_distribution<_IntType, _RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__space);
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x.t() << __space << __x.p() 
+	   << __space << __x._M_nd;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+  template<typename _IntType, typename _RealType,
+	   typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       binomial_distribution<_IntType, _RealType>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      __is >> __x._M_t >> __x._M_p >> __x._M_nd;
+      __x._M_initialize();
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _RealType, typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const uniform_real<_RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__space);
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x.min() << __space << __x.max();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+  template<typename _RealType, typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       uniform_real<_RealType>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::skipws);
+
+      __is >> __x._M_min >> __x._M_max;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _RealType, typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const exponential_distribution<_RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__os.widen(' '));
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x.lambda();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+
+  /**
+   * Polar method due to Marsaglia.
+   *
+   * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+   * New York, 1986, Ch. V, Sect. 4.4.
+   */
+  template<typename _RealType>
+    template<class _UniformRandomNumberGenerator>
+      typename normal_distribution<_RealType>::result_type
+      normal_distribution<_RealType>::
+      operator()(_UniformRandomNumberGenerator& __urng)
+      {
+	result_type __ret;
+
+	if (_M_saved_available)
+	  {
+	    _M_saved_available = false;
+	    __ret = _M_saved;
+	  }
+	else
+	  {
+	    result_type __x, __y, __r2;
+	    do
+	      {
+		__x = result_type(2.0) * __urng() - 1.0;
+		__y = result_type(2.0) * __urng() - 1.0;
+		__r2 = __x * __x + __y * __y;
+	      }
+	    while (__r2 > 1.0 || __r2 == 0.0);
+
+	    const result_type __mult = std::sqrt(-2 * std::log(__r2) / __r2);
+	    _M_saved = __x * __mult;
+	    _M_saved_available = true;
+	    __ret = __y * __mult;
+	  }
+	
+	__ret = __ret * _M_sigma + _M_mean;
+	return __ret;
+      }
+
+  template<typename _RealType, typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const normal_distribution<_RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      const _CharT __space = __os.widen(' ');
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__space);
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x._M_saved_available << __space
+	   << __x.mean() << __space
+	   << __x.sigma();
+      if (__x._M_saved_available)
+	__os << __space << __x._M_saved;
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+  template<typename _RealType, typename _CharT, typename _Traits>
+    std::basic_istream<_CharT, _Traits>&
+    operator>>(std::basic_istream<_CharT, _Traits>& __is,
+	       normal_distribution<_RealType>& __x)
+    {
+      typedef std::basic_istream<_CharT, _Traits>  __istream_type;
+      typedef typename __istream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __is.flags();
+      __is.flags(__ios_base::dec | __ios_base::skipws);
+
+      __is >> __x._M_saved_available >> __x._M_mean
+	   >> __x._M_sigma;
+      if (__x._M_saved_available)
+	__is >> __x._M_saved;
+
+      __is.flags(__flags);
+      return __is;
+    }
+
+
+  template<typename _RealType>
+    void
+    gamma_distribution<_RealType>::
+    _M_initialize()
+    {
+      if (_M_alpha >= 1)
+	_M_l_d = std::sqrt(2 * _M_alpha - 1);
+      else
+	_M_l_d = (std::pow(_M_alpha, _M_alpha / (1 - _M_alpha))
+		  * (1 - _M_alpha));
+    }
+
+  /**
+   * Cheng's rejection algorithm GB for alpha >= 1 and a modification
+   * of Vaduva's rejection from Weibull algorithm due to Devroye for
+   * alpha < 1.
+   *
+   * References:
+   * Cheng, R. C. "The Generation of Gamma Random Variables with Non-integral
+   * Shape Parameter." Applied Statistics, 26, 71-75, 1977.
+   *
+   * Vaduva, I. "Computer Generation of Gamma Gandom Variables by Rejection
+   * and Composition Procedures." Math. Operationsforschung and Statistik,
+   * Series in Statistics, 8, 545-576, 1977.
+   *
+   * Devroye, L. "Non-Uniform Random Variates Generation." Springer-Verlag,
+   * New York, 1986, Ch. IX, Sect. 3.4 (+ Errata!).
+   */
+  template<typename _RealType>
+    template<class _UniformRandomNumberGenerator>
+      typename gamma_distribution<_RealType>::result_type
+      gamma_distribution<_RealType>::
+      operator()(_UniformRandomNumberGenerator& __urng)
+      {
+	result_type __x;
+
+	bool __reject;
+	if (_M_alpha >= 1)
+	  {
+	    // alpha - log(4)
+	    const result_type __b = _M_alpha
+	      - result_type(1.3862943611198906188344642429163531L);
+	    const result_type __c = _M_alpha + _M_l_d;
+	    const result_type __1l = 1 / _M_l_d;
+
+	    // 1 + log(9 / 2)
+	    const result_type __k = 2.5040773967762740733732583523868748L;
+
+	    do
+	      {
+		const result_type __u = __urng();
+		const result_type __v = __urng();
+
+		const result_type __y = __1l * std::log(__v / (1 - __v));
+		__x = _M_alpha * std::exp(__y);
+
+		const result_type __z = __u * __v * __v;
+		const result_type __r = __b + __c * __y - __x;
+
+		__reject = __r < result_type(4.5) * __z - __k;
+		if (__reject)
+		  __reject = __r < std::log(__z);
+	      }
+	    while (__reject);
+	  }
+	else
+	  {
+	    const result_type __c = 1 / _M_alpha;
+
+	    do
+	      {
+		const result_type __z = -std::log(__urng());
+		const result_type __e = -std::log(__urng());
+
+		__x = std::pow(__z, __c);
+
+		__reject = __z + __e < _M_l_d + __x;
+	      }
+	    while (__reject);
+	  }
+
+	return __x;
+      }
+
+  template<typename _RealType, typename _CharT, typename _Traits>
+    std::basic_ostream<_CharT, _Traits>&
+    operator<<(std::basic_ostream<_CharT, _Traits>& __os,
+	       const gamma_distribution<_RealType>& __x)
+    {
+      typedef std::basic_ostream<_CharT, _Traits>  __ostream_type;
+      typedef typename __ostream_type::ios_base    __ios_base;
+
+      const typename __ios_base::fmtflags __flags = __os.flags();
+      const _CharT __fill = __os.fill();
+      const std::streamsize __precision = __os.precision();
+      __os.flags(__ios_base::scientific | __ios_base::left);
+      __os.fill(__os.widen(' '));
+      __os.precision(__gnu_cxx::__numeric_traits<_RealType>::__max_digits10);
+
+      __os << __x.alpha();
+
+      __os.flags(__flags);
+      __os.fill(__fill);
+      __os.precision(__precision);
+      return __os;
+    }
+
+}
+}