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			392 lines
		
	
	
		
			15 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
		
		
			
		
	
	
			392 lines
		
	
	
		
			15 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
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								// Copyright Paul A. Bristow 2010.
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								// Copyright John Maddock 2007.
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								// Use, modification and distribution are subject to the
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								// Boost Software License, Version 1.0.
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								// (See accompanying file LICENSE_1_0.txt
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								// or copy at http://www.boost.org/LICENSE_1_0.txt)
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								// test_normal.cpp
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								// http://en.wikipedia.org/wiki/Normal_distribution
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								// http://www.itl.nist.gov/div898/handbook/eda/section3/eda3661.htm
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								// Also:
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								// Weisstein, Eric W. "Normal Distribution."
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								// From MathWorld--A Wolfram Web Resource.
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								// http://mathworld.wolfram.com/NormalDistribution.html
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								#include <pch.hpp> // include directory /libs/math/src/tr1/ is needed.
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								#ifdef _MSC_VER
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								#  pragma warning (disable: 4127) // conditional expression is constant
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								// caused by using   if(std::numeric_limits<RealType>::has_infinity)
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								// and   if (std::numeric_limits<RealType>::has_quiet_NaN)
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								#endif
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								#include <boost/math/tools/test.hpp>
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								#include <boost/math/concepts/real_concept.hpp> // for real_concept
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								#define BOOST_TEST_MAIN
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								#include <boost/test/unit_test.hpp> // Boost.Test
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								#include <boost/test/floating_point_comparison.hpp>
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								#include <boost/math/distributions/normal.hpp>
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								    using boost::math::normal_distribution;
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								#include <boost/math/tools/test.hpp>
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								#include "test_out_of_range.hpp"
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								#include <iostream>
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								#include <iomanip>
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								   using std::cout;
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								   using std::endl;
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								   using std::setprecision;
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								#include <limits>
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								  using std::numeric_limits;
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								template <class RealType>
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								RealType NaivePDF(RealType mean, RealType sd, RealType x)
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								{
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								   // Deliberately naive PDF calculator again which
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								   // we'll compare our pdf function.  However some
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								   // published values to compare against would be better....
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								   using namespace std;
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								   return exp(-(x-mean)*(x-mean)/(2*sd*sd))/(sd * sqrt(2*boost::math::constants::pi<RealType>()));
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								}
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								template <class RealType>
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								void check_normal(RealType mean, RealType sd, RealType x, RealType p, RealType q, RealType tol)
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								{
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								   BOOST_CHECK_CLOSE(
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								      ::boost::math::cdf(
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								         normal_distribution<RealType>(mean, sd),       // distribution.
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								         x),                                            // random variable.
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								         p,                                             // probability.
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								         tol);                                          // %tolerance.
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								   BOOST_CHECK_CLOSE(
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								      ::boost::math::cdf(
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								         complement(
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								            normal_distribution<RealType>(mean, sd),    // distribution.
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								            x)),                                        // random variable.
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								         q,                                             // probability complement.
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								         tol);                                          // %tolerance.
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								   BOOST_CHECK_CLOSE(
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								      ::boost::math::quantile(
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								         normal_distribution<RealType>(mean, sd),       // distribution.
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								         p),                                            // probability.
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								         x,                                             // random variable.
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								         tol);                                          // %tolerance.
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								   BOOST_CHECK_CLOSE(
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								      ::boost::math::quantile(
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								         complement(
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								            normal_distribution<RealType>(mean, sd),    // distribution.
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								            q)),                                        // probability complement.
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								         x,                                             // random variable.
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								         tol);                                          // %tolerance.
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								}
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								template <class RealType>
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								void test_spots(RealType)
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								{
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								   // Basic sanity checks
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								   RealType tolerance = 1e-2f; // 1e-4 (as %)
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								   // Some tests only pass at 1e-4 because values generated by
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								   // http://faculty.vassar.edu/lowry/VassarStats.html
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								   // give only 5 or 6 *fixed* places, so small values have fewer digits.
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								  // Check some bad parameters to the distribution,
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								#ifndef BOOST_NO_EXCEPTIONS
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								   BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType> nbad1(0, 0), std::domain_error); // zero sd
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								   BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType> nbad1(0, -1), std::domain_error); // negative sd
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								#else
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								   BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType>(0, 0), std::domain_error); // zero sd
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								   BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType>(0, -1), std::domain_error); // negative sd
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								#endif
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								  // Tests on extreme values of random variate x, if has std::numeric_limits infinity etc.
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								    normal_distribution<RealType> N01;
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								  if(std::numeric_limits<RealType>::has_infinity)
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								  {
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								    BOOST_CHECK_EQUAL(pdf(N01, +std::numeric_limits<RealType>::infinity()), 0); // x = + infinity, pdf = 0
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								    BOOST_CHECK_EQUAL(pdf(N01, -std::numeric_limits<RealType>::infinity()), 0); // x = - infinity, pdf = 0
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								    BOOST_CHECK_EQUAL(cdf(N01, +std::numeric_limits<RealType>::infinity()), 1); // x = + infinity, cdf = 1
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								    BOOST_CHECK_EQUAL(cdf(N01, -std::numeric_limits<RealType>::infinity()), 0); // x = - infinity, cdf = 0
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								    BOOST_CHECK_EQUAL(cdf(complement(N01, +std::numeric_limits<RealType>::infinity())), 0); // x = + infinity, c cdf = 0
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								    BOOST_CHECK_EQUAL(cdf(complement(N01, -std::numeric_limits<RealType>::infinity())), 1); // x = - infinity, c cdf = 1
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								#ifndef BOOST_NO_EXCEPTIONS
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								    BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType> nbad1(std::numeric_limits<RealType>::infinity(), static_cast<RealType>(1)), std::domain_error); // +infinite mean
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								     BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType> nbad1(-std::numeric_limits<RealType>::infinity(),  static_cast<RealType>(1)), std::domain_error); // -infinite mean
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								     BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType> nbad1(static_cast<RealType>(0), std::numeric_limits<RealType>::infinity()), std::domain_error); // infinite sd
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								#else
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								    BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType>(std::numeric_limits<RealType>::infinity(), static_cast<RealType>(1)), std::domain_error); // +infinite mean
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								     BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType>(-std::numeric_limits<RealType>::infinity(),  static_cast<RealType>(1)), std::domain_error); // -infinite mean
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								     BOOST_MATH_CHECK_THROW(boost::math::normal_distribution<RealType>(static_cast<RealType>(0), std::numeric_limits<RealType>::infinity()), std::domain_error); // infinite sd
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								#endif
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								  }
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								  if (std::numeric_limits<RealType>::has_quiet_NaN)
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								  {
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								    // No longer allow x to be NaN, then these tests should throw.
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								    BOOST_MATH_CHECK_THROW(pdf(N01, +std::numeric_limits<RealType>::quiet_NaN()), std::domain_error); // x = NaN
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								    BOOST_MATH_CHECK_THROW(cdf(N01, +std::numeric_limits<RealType>::quiet_NaN()), std::domain_error); // x = NaN
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								    BOOST_MATH_CHECK_THROW(cdf(complement(N01, +std::numeric_limits<RealType>::quiet_NaN())), std::domain_error); // x = + infinity
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								    BOOST_MATH_CHECK_THROW(quantile(N01, +std::numeric_limits<RealType>::quiet_NaN()), std::domain_error); // p = + infinity
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								    BOOST_MATH_CHECK_THROW(quantile(complement(N01, +std::numeric_limits<RealType>::quiet_NaN())), std::domain_error); // p = + infinity
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								  }
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								   cout << "Tolerance for type " << typeid(RealType).name()  << " is " << tolerance << " %" << endl;
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								   check_normal(
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(2),
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								      static_cast<RealType>(4.8),
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								      static_cast<RealType>(0.46017),
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								      static_cast<RealType>(1 - 0.46017),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(2),
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								      static_cast<RealType>(5.2),
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								      static_cast<RealType>(1 - 0.46017),
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								      static_cast<RealType>(0.46017),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(2),
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								      static_cast<RealType>(2.2),
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								      static_cast<RealType>(0.08076),
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								      static_cast<RealType>(1 - 0.08076),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(2),
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								      static_cast<RealType>(7.8),
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								      static_cast<RealType>(1 - 0.08076),
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								      static_cast<RealType>(0.08076),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(-3),
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(-4.5),
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								      static_cast<RealType>(0.38209),
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								      static_cast<RealType>(1 - 0.38209),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(-3),
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(-1.5),
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								      static_cast<RealType>(1 - 0.38209),
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								      static_cast<RealType>(0.38209),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(-3),
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(-8.5),
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								      static_cast<RealType>(0.13567),
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								      static_cast<RealType>(1 - 0.13567),
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								      tolerance);
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								   check_normal(
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								      static_cast<RealType>(-3),
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								      static_cast<RealType>(5),
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								      static_cast<RealType>(2.5),
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								      static_cast<RealType>(1 - 0.13567),
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								      static_cast<RealType>(0.13567),
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								      tolerance);
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								   //
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								   // Tests for PDF: we know that the peak value is at 1/sqrt(2*pi)
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								   //
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								   tolerance = boost::math::tools::epsilon<RealType>() * 5 * 100; // 5 eps as a percentage
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								   BOOST_CHECK_CLOSE(
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								      pdf(normal_distribution<RealType>(), static_cast<RealType>(0)),
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								      static_cast<RealType>(0.3989422804014326779399460599343818684759L), // 1/sqrt(2*pi)
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								      tolerance);
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								   BOOST_CHECK_CLOSE(
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								      pdf(normal_distribution<RealType>(3), static_cast<RealType>(3)),
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								      static_cast<RealType>(0.3989422804014326779399460599343818684759L),
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								      tolerance);
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								   BOOST_CHECK_CLOSE(
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								      pdf(normal_distribution<RealType>(3, 5), static_cast<RealType>(3)),
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								      static_cast<RealType>(0.3989422804014326779399460599343818684759L / 5),
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								      tolerance);
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								   //
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								   // Spot checks for mean = -5, sd = 6:
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								   //
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								   for(RealType x = -15; x < 5; x += 0.125)
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								   {
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								      BOOST_CHECK_CLOSE(
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								         pdf(normal_distribution<RealType>(-5, 6), x),
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								         NaivePDF(RealType(-5), RealType(6), x),
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								         tolerance);
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								   }
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								    RealType tol2 = boost::math::tools::epsilon<RealType>() * 5;
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								    normal_distribution<RealType> dist(8, 3);
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								    RealType x = static_cast<RealType>(0.125);
							 | 
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| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    BOOST_MATH_STD_USING // ADL of std math lib names
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    // mean:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       mean(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(8), tol2);
							 | 
						||
| 
								 | 
							
								    // variance:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       variance(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(9), tol2);
							 | 
						||
| 
								 | 
							
								    // std deviation:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       standard_deviation(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(3), tol2);
							 | 
						||
| 
								 | 
							
								    // hazard:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       hazard(dist, x)
							 | 
						||
| 
								 | 
							
								       , pdf(dist, x) / cdf(complement(dist, x)), tol2);
							 | 
						||
| 
								 | 
							
								    // cumulative hazard:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       chf(dist, x)
							 | 
						||
| 
								 | 
							
								       , -log(cdf(complement(dist, x))), tol2);
							 | 
						||
| 
								 | 
							
								    // coefficient_of_variation:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       coefficient_of_variation(dist)
							 | 
						||
| 
								 | 
							
								       , standard_deviation(dist) / mean(dist), tol2);
							 | 
						||
| 
								 | 
							
								    // mode:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       mode(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(8), tol2);
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       median(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(8), tol2);
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    // skewness:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       skewness(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(0), tol2);
							 | 
						||
| 
								 | 
							
								    // kertosis:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       kurtosis(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(3), tol2);
							 | 
						||
| 
								 | 
							
								    // kertosis excess:
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       kurtosis_excess(dist)
							 | 
						||
| 
								 | 
							
								       , static_cast<RealType>(0), tol2);
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    normal_distribution<RealType> norm01(0, 1); // Test default (0, 1)
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       mean(norm01),
							 | 
						||
| 
								 | 
							
								       static_cast<RealType>(0), 0); // Mean == zero
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    normal_distribution<RealType> defsd_norm01(0); // Test default (0, sd = 1)
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       mean(defsd_norm01),
							 | 
						||
| 
								 | 
							
								       static_cast<RealType>(0), 0); // Mean == zero
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    normal_distribution<RealType> def_norm01; // Test default (0, sd = 1)
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       mean(def_norm01),
							 | 
						||
| 
								 | 
							
								       static_cast<RealType>(0), 0); // Mean == zero
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    BOOST_CHECK_CLOSE(
							 | 
						||
| 
								 | 
							
								       standard_deviation(def_norm01),
							 | 
						||
| 
								 | 
							
								       static_cast<RealType>(1), 0); // Mean == zero
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    // Error tests:
							 | 
						||
| 
								 | 
							
								    check_out_of_range<boost::math::normal_distribution<RealType> >(0, 1); // (All) valid constructor parameter values.
							 | 
						||
| 
								 | 
							
								    
							 | 
						||
| 
								 | 
							
								    BOOST_MATH_CHECK_THROW(pdf(normal_distribution<RealType>(0, 0), 0), std::domain_error);
							 | 
						||
| 
								 | 
							
								    BOOST_MATH_CHECK_THROW(pdf(normal_distribution<RealType>(0, -1), 0), std::domain_error);
							 | 
						||
| 
								 | 
							
								    BOOST_MATH_CHECK_THROW(quantile(normal_distribution<RealType>(0, 1), -1), std::domain_error);
							 | 
						||
| 
								 | 
							
								    BOOST_MATH_CHECK_THROW(quantile(normal_distribution<RealType>(0, 1), 2), std::domain_error);
							 | 
						||
| 
								 | 
							
								} // template <class RealType>void test_spots(RealType)
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								BOOST_AUTO_TEST_CASE( test_main )
							 | 
						||
| 
								 | 
							
								{
							 | 
						||
| 
								 | 
							
								    // Check that can generate normal distribution using the two convenience methods:
							 | 
						||
| 
								 | 
							
								   boost::math::normal myf1(1., 2); // Using typedef
							 | 
						||
| 
								 | 
							
								   normal_distribution<> myf2(1., 2); // Using default RealType double.
							 | 
						||
| 
								 | 
							
								  boost::math::normal myn01; // Use default values.
							 | 
						||
| 
								 | 
							
								  // Note NOT myn01() as the compiler will interpret as a function!
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								  // Check the synonyms, provided to allow generic use of find_location and find_scale.
							 | 
						||
| 
								 | 
							
								  BOOST_CHECK_EQUAL(myn01.mean(), myn01.location());
							 | 
						||
| 
								 | 
							
								  BOOST_CHECK_EQUAL(myn01.standard_deviation(), myn01.scale());
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								    // Basic sanity-check spot values.
							 | 
						||
| 
								 | 
							
								   // (Parameter value, arbitrarily zero, only communicates the floating point type).
							 | 
						||
| 
								 | 
							
								  test_spots(0.0F); // Test float. OK at decdigits = 0 tolerance = 0.0001 %
							 | 
						||
| 
								 | 
							
								  test_spots(0.0); // Test double. OK at decdigits 7, tolerance = 1e07 %
							 | 
						||
| 
								 | 
							
								#ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS
							 | 
						||
| 
								 | 
							
								  test_spots(0.0L); // Test long double.
							 | 
						||
| 
								 | 
							
								#if !BOOST_WORKAROUND(__BORLANDC__, BOOST_TESTED_AT(0x0582))
							 | 
						||
| 
								 | 
							
								  test_spots(boost::math::concepts::real_concept(0.)); // Test real concept.
							 | 
						||
| 
								 | 
							
								#endif
							 | 
						||
| 
								 | 
							
								#else
							 | 
						||
| 
								 | 
							
								   std::cout << "<note>The long double tests have been disabled on this platform "
							 | 
						||
| 
								 | 
							
								      "either because the long double overloads of the usual math functions are "
							 | 
						||
| 
								 | 
							
								      "not available at all, or because they are too inaccurate for these tests "
							 | 
						||
| 
								 | 
							
								      "to pass.</note>" << std::endl;
							 | 
						||
| 
								 | 
							
								#endif
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								   
							 | 
						||
| 
								 | 
							
								} // BOOST_AUTO_TEST_CASE( test_main )
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								/*
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								Output:
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								Autorun "i:\boost-06-05-03-1300\libs\math\test\Math_test\debug\test_normal.exe"
							 | 
						||
| 
								 | 
							
								Running 1 test case...
							 | 
						||
| 
								 | 
							
								Tolerance for type float is 0.01 %
							 | 
						||
| 
								 | 
							
								Tolerance for type double is 0.01 %
							 | 
						||
| 
								 | 
							
								Tolerance for type long double is 0.01 %
							 | 
						||
| 
								 | 
							
								Tolerance for type class boost::math::concepts::real_concept is 0.01 %
							 | 
						||
| 
								 | 
							
								*** No errors detected
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								------ Build started: Project: test_normal, Configuration: Release Win32 ------
							 | 
						||
| 
								 | 
							
								  test_normal.cpp
							 | 
						||
| 
								 | 
							
								  Generating code
							 | 
						||
| 
								 | 
							
								  Finished generating code
							 | 
						||
| 
								 | 
							
								  test_normal.vcxproj -> J:\Cpp\MathToolkit\test\Math_test\Release\test_normal.exe
							 | 
						||
| 
								 | 
							
								  Running 1 test case...
							 | 
						||
| 
								 | 
							
								  Tolerance for type float is 0.01 %
							 | 
						||
| 
								 | 
							
								  Tolerance for type double is 0.01 %
							 | 
						||
| 
								 | 
							
								  Tolerance for type long double is 0.01 %
							 | 
						||
| 
								 | 
							
								  Tolerance for type class boost::math::concepts::real_concept is 0.01 %
							 | 
						||
| 
								 | 
							
								  
							 | 
						||
| 
								 | 
							
								  *** No errors detected
							 | 
						||
| 
								 | 
							
								  Detected memory leaks!
							 | 
						||
| 
								 | 
							
								  Dumping objects ->
							 | 
						||
| 
								 | 
							
								  {2413} normal block at 0x00321190, 42 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: <class boost::mat> 63 6C 61 73 73 20 62 6F 6F 73 74 3A 3A 6D 61 74 
							 | 
						||
| 
								 | 
							
								  {2412} normal block at 0x003231F0, 8 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: <  2  22 > 90 11 32 00 98 32 32 00 
							 | 
						||
| 
								 | 
							
								  {1824} normal block at 0x00323180, 12 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: <long double > 6C 6F 6E 67 20 64 6F 75 62 6C 65 00 
							 | 
						||
| 
								 | 
							
								  {1823} normal block at 0x00323298, 8 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: < 12 `22 > 80 31 32 00 60 32 32 00 
							 | 
						||
| 
								 | 
							
								  {1227} normal block at 0x00323148, 7 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: <double > 64 6F 75 62 6C 65 00 
							 | 
						||
| 
								 | 
							
								  {1226} normal block at 0x00323260, 8 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: <H12  02 > 48 31 32 00 A0 30 32 00 
							 | 
						||
| 
								 | 
							
								  {633} normal block at 0x003230D8, 6 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: <float > 66 6C 6F 61 74 00 
							 | 
						||
| 
								 | 
							
								  {632} normal block at 0x003230A0, 8 bytes long.
							 | 
						||
| 
								 | 
							
								   Data: < 02     > D8 30 32 00 00 00 00 00 
							 | 
						||
| 
								 | 
							
								  Object dump complete.
							 | 
						||
| 
								 | 
							
								========== Build: 1 succeeded, 0 failed, 0 up-to-date, 0 skipped ==========
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								*/
							 | 
						||
| 
								 | 
							
								
							 | 
						||
| 
								 | 
							
								
							 |