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			445 lines
		
	
	
		
			14 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			445 lines
		
	
	
		
			14 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
//!file
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//! \brief floating-point comparison from Boost.Test
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// Copyright Paul A. Bristow 2015.
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// Copyright John Maddock 2015.
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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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// Note that this file contains Quickbook mark-up as well as code
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// and comments, don't change any of the special comment mark-ups!
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#include <boost/math/special_functions/relative_difference.hpp>
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#include <boost/math/special_functions/next.hpp>
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#include <iostream>
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#include <limits> // for std::numeric_limits<T>::epsilon().
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int main()
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{
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  std::cout << "Compare floats using Boost.Math functions/classes" << std::endl;
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//[compare_floats_using
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/*`Some using statements will ensure that the functions we need are accessible.
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*/
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  using namespace boost::math;
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//`or
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  using boost::math::relative_difference;
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  using boost::math::epsilon_difference;
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  using boost::math::float_next;
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  using boost::math::float_prior;
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//] [/compare_floats_using]
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//[compare_floats_example_1
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/*`The following examples display values with all possibly significant digits.
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Newer compilers should provide `std::numeric_limitsFPT>::max_digits10`
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for this purpose, and here we use `float` precision where `max_digits10` = 9
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to avoid displaying a distracting number of decimal digits.
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[note Older compilers can use this formula to calculate `max_digits10`
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from `std::numeric_limits<FPT>::digits10`:[br]
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__spaces `int max_digits10 = 2 + std::numeric_limits<FPT>::digits10 * 3010/10000;`
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] [/note]
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One can set the display including all trailing zeros
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(helpful for this example to show all potentially significant digits),
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and also to display `bool` values as words rather than integers:
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*/
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  std::cout.precision(std::numeric_limits<float>::max_digits10);
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  std::cout << std::boolalpha << std::showpoint << std::endl;
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//] [/compare_floats_example_1]
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//[compare_floats_example_2]
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/*`
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When comparing values that are ['quite close] or ['approximately equal],
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we could use either `float_distance` or `relative_difference`/`epsilon_difference`, for example
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with type `float`, these two values are adjacent to each other:
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*/
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  float a = 1;
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  float b = 1 + std::numeric_limits<float>::epsilon();
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  std::cout << "a = " << a << std::endl;
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  std::cout << "b = " << b << std::endl;
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  std::cout << "float_distance = " << float_distance(a, b) << std::endl;
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  std::cout << "epsilon_difference = " << epsilon_difference(a, b) << std::endl;
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/*`
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Which produces the output:
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[pre
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a = 1.00000000
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b = 1.00000012
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float_distance = 1.00000000
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relative_difference = 1.19209290e-007
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epsilon_difference = 1.00000000
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]
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*/
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  //] [/compare_floats_example_2]
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//[compare_floats_example_3]
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/*`
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In the example above, it just so happens that the edit distance as measured by `float_distance`, and the
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difference measured in units of epsilon were equal.  However, due to the way floating point
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values are represented, that is not always the case:*/
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  a = 2.0f / 3.0f;   // 2/3 inexactly represented as a float
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  b = float_next(float_next(float_next(a))); // 3 floating point values above a
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  std::cout << "a = " << a << std::endl;
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  std::cout << "b = " << b << std::endl;
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  std::cout << "float_distance = " << float_distance(a, b) << std::endl;
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  std::cout << "epsilon_difference = " << epsilon_difference(a, b) << std::endl;
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/*`
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Which produces the output:
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[pre
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a = 0.666666687
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b = 0.666666865
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float_distance = 3.00000000
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relative_difference = 2.68220901e-007
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epsilon_difference = 2.25000000
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]
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There is another important difference between `float_distance` and the
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`relative_difference/epsilon_difference` functions in that `float_distance`
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returns a signed result that reflects which argument is larger in magnitude,
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where as `relative_difference/epsilon_difference` simply return an unsigned
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value that represents how far apart the values are.  For example if we swap
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the order of the arguments:
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*/
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  std::cout << "float_distance = " << float_distance(b, a) << std::endl;
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  std::cout << "relative_difference = " << relative_difference(b, a) << std::endl;
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  std::cout << "epsilon_difference = " << epsilon_difference(b, a) << std::endl;
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  /*`
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  The output is now:
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  [pre
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  float_distance = -3.00000000
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  relative_difference = 2.68220901e-007
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  epsilon_difference = 2.25000000
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  ]
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*/
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  //] [/compare_floats_example_3]
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//[compare_floats_example_4]
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/*`
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Zeros are always treated as equal, as are infinities as long as they have the same sign:*/
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  a = 0;
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  b = -0;  // signed zero
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  a = b = std::numeric_limits<float>::infinity();
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  std::cout << "relative_difference = " << relative_difference(a, -b) << std::endl;
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/*`
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Which produces the output:
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[pre
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relative_difference = 0.000000000
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relative_difference = 0.000000000
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relative_difference = 3.40282347e+038
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]
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*/
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//] [/compare_floats_example_4]
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//[compare_floats_example_5]
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/*`
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Note that finite values are always infinitely far away from infinities even if those finite values are very large:*/
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  a = (std::numeric_limits<float>::max)();
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  b = std::numeric_limits<float>::infinity();
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  std::cout << "a = " << a << std::endl;
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  std::cout << "b = " << b << std::endl;
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  std::cout << "epsilon_difference = " << epsilon_difference(a, b) << std::endl;
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/*`
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Which produces the output:
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[pre
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a = 3.40282347e+038
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b = 1.#INF0000
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relative_difference = 3.40282347e+038
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epsilon_difference = 3.40282347e+038
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]
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*/
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//] [/compare_floats_example_5]
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//[compare_floats_example_6]
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/*`
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Finally, all denormalized values and zeros are treated as being effectively equal:*/
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  a = std::numeric_limits<float>::denorm_min();
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  b = a * 2;
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  std::cout << "a = " << a << std::endl;
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  std::cout << "b = " << b << std::endl;
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  std::cout << "float_distance = " << float_distance(a, b) << std::endl;
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  std::cout << "epsilon_difference = " << epsilon_difference(a, b) << std::endl;
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  a = 0;
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  std::cout << "a = " << a << std::endl;
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  std::cout << "b = " << b << std::endl;
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  std::cout << "float_distance = " << float_distance(a, b) << std::endl;
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  std::cout << "relative_difference = " << relative_difference(a, b) << std::endl;
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  std::cout << "epsilon_difference = " << epsilon_difference(a, b) << std::endl;
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/*`
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Which produces the output:
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[pre
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a = 1.40129846e-045
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b = 2.80259693e-045
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float_distance = 1.00000000
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relative_difference = 0.000000000
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epsilon_difference = 0.000000000
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a = 0.000000000
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b = 2.80259693e-045
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float_distance = 2.00000000
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relative_difference = 0.000000000
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epsilon_difference = 0.000000000]
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Notice how, in the above example, two denormalized values that are a factor of 2 apart are
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none the less only one representation apart!
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*/
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//] [/compare_floats_example_6]
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#if 0
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//[old_compare_floats_example_3
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//`The simplest use is to compare two values with a tolerance thus:
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  bool is_close = is_close_to(1.F, 1.F + epsilon, epsilon); // One epsilon apart is close enough.
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  std::cout << "is_close_to(1.F, 1.F + epsilon, epsilon); is " << is_close << std::endl; // true
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  is_close = is_close_to(1.F, 1.F + 2 * epsilon, epsilon); // Two epsilon apart isn't close enough.
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  std::cout << "is_close_to(1.F, 1.F + epsilon, epsilon); is " << is_close << std::endl; // false
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/*`
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[note The type FPT of the tolerance and the type of the values [*must match].
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So `is_close(0.1F, 1., 1.)` will fail to compile because "template parameter 'FPT' is ambiguous".
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Always provide the same type, using `static_cast<FPT>` if necessary.]
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*/
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/*`An instance of class `close_at_tolerance` is more convenient
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when multiple tests with the same conditions are planned.
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A class that stores a tolerance of three epsilon (and the default ['strong] test) is:
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*/
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  close_at_tolerance<float> three_rounds(3 * epsilon); // 'strong' by default.
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//`and we can confirm these settings:
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  std::cout << "fraction_tolerance = "
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    << three_rounds.fraction_tolerance()
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    << std::endl; // +3.57627869e-007
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  std::cout << "strength = "
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    << (three_rounds.strength() == FPC_STRONG ? "strong" : "weak")
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    << std::endl; // strong
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//`To start, let us use two values that are truly equal (having identical bit patterns)
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  float a = 1.23456789F;
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  float b = 1.23456789F;
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//`and make a comparison using our 3*epsilon `three_rounds` functor:
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  bool close = three_rounds(a, b);
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  std::cout << "three_rounds(a, b) = " << close << std::endl; // true
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//`Unsurprisingly, the result is true, and the failed fraction is zero.
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  std::cout << "failed_fraction = " << three_rounds.failed_fraction() << std::endl;
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/*`To get some nearby values, it is convenient to use the Boost.Math __next_float functions,
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for which we need an include
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  #include <boost/math/special_functions/next.hpp>
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and some using declarations:
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*/
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  using boost::math::float_next;
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  using boost::math::float_prior;
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  using boost::math::nextafter;
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  using boost::math::float_distance;
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//`To add a few __ulp to one value:
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  b = float_next(a); // Add just one ULP to a.
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  b = float_next(b); // Add another one ULP.
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  b = float_next(b); // Add another one ULP.
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  // 3 epsilon would pass.
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  b = float_next(b); // Add another one ULP.
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//`and repeat our comparison:
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  close = three_rounds(a, b);
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  std::cout << "three_rounds(a, b) = " << close << std::endl; // false
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  std::cout << "failed_fraction = " << three_rounds.failed_fraction()
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    << std::endl;  // abs(u-v) / abs(v) = 3.86237957e-007
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//`We can also 'measure' the number of bits different using the `float_distance` function:
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  std::cout << "float_distance = " << float_distance(a, b) << std::endl; // 4
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/*`Now consider two values that are much further apart
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than one might expect from ['computational noise],
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perhaps the result of two measurements of some physical property like length
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where an uncertainty of a percent or so might be expected.
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*/
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  float fp1 = 0.01000F;
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  float fp2 = 0.01001F; // Slightly different.
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  float tolerance = 0.0001F;
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  close_at_tolerance<float> strong(epsilon); // Default is strong.
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  bool rs = strong(fp1, fp2);
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  std::cout << "strong(fp1, fp2) is " << rs << std::endl;
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//`Or we could contrast using the ['weak] criterion:
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  close_at_tolerance<float> weak(epsilon, FPC_WEAK); // Explicitly weak.
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  bool rw = weak(fp1, fp2); //
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  std::cout << "weak(fp1, fp2) is " << rw << std::endl;
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//`We can also construct, setting tolerance and strength, and compare in one statement:
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  std::cout << a << " #= " << b << " is "
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    << close_at_tolerance<float>(epsilon, FPC_STRONG)(a, b) << std::endl;
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  std::cout << a << " ~= " << b << " is "
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    << close_at_tolerance<float>(epsilon, FPC_WEAK)(a, b) << std::endl;
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//`but this has little advantage over using function `is_close_to` directly.
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//] [/old_compare_floats_example_3]
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/*When the floating-point values become very small and near zero, using
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//a relative test becomes unhelpful because one is dividing by zero or tiny,
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//Instead, an absolute test is needed, comparing one (or usually both) values with zero,
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//using a tolerance.
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//This is provided by the `small_with_tolerance` class and `is_small` function.
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  namespace boost {
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  namespace math {
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  namespace fpc {
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  template<typename FPT>
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  class small_with_tolerance
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  {
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  public:
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  // Public typedefs.
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  typedef bool result_type;
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  // Constructor.
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  explicit small_with_tolerance(FPT tolerance); // tolerance >= 0
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  // Functor
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  bool operator()(FPT value) const; // return true if <= absolute tolerance (near zero).
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  };
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  template<typename FPT>
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  bool
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  is_small(FPT value, FPT tolerance); // return true if value <= absolute tolerance (near zero).
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  }}} // namespaces.
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/*`
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[note The type FPT of the tolerance and the type of the value [*must match].
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So `is_small(0.1F, 0.000001)` will fail to compile because "template parameter 'FPT' is ambiguous".
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Always provide the same type, using `static_cast<FPT>` if necessary.]
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A few values near zero are tested with varying tolerance below.
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*/
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//[compare_floats_small_1
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  float c = 0;
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  std::cout << "0 is_small " << is_small(c, epsilon) << std::endl; // true
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  c = std::numeric_limits<float>::denorm_min(); // 1.40129846e-045
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  std::cout << "denorm_ min =" << c << ", is_small is " << is_small(c, epsilon) << std::endl; // true
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  c = (std::numeric_limits<float>::min)(); // 1.17549435e-038
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  std::cout << "min = " << c << ", is_small is " << is_small(c, epsilon) << std::endl; // true
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  c = 1 * epsilon; // 1.19209290e-007
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  std::cout << "epsilon = " << c << ", is_small is " << is_small(c, epsilon) << std::endl; // false
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  c = 1 * epsilon; // 1.19209290e-007
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  std::cout << "2 epsilon = " << c << ", is_small is " << is_small(c, 2 * epsilon) << std::endl; // true
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  c = 2 * epsilon; //2.38418579e-007
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  std::cout << "4 epsilon = " << c << ", is_small is " << is_small(c, 2 * epsilon) << std::endl; // false
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  c = 0.00001F;
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  std::cout << "0.00001 = " << c << ", is_small is " << is_small(c, 0.0001F) << std::endl; // true
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  c = -0.00001F;
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  std::cout << "0.00001 = " << c << ", is_small is " << is_small(c, 0.0001F) << std::endl; // true
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/*`Using the class `small_with_tolerance` allows storage of the tolerance,
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convenient if you make repeated tests with the same tolerance.
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*/
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  small_with_tolerance<float>my_test(0.01F);
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  std::cout << "my_test(0.001F) is " << my_test(0.001F) << std::endl; // true
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  std::cout << "my_test(0.001F) is " << my_test(0.01F) << std::endl; // false
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  //] [/compare_floats_small_1]
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#endif
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  return 0;
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}  // int main()
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/*
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Example output is:
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//[compare_floats_output
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Compare floats using Boost.Test functions/classes
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float epsilon = 1.19209290e-007
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is_close_to(1.F, 1.F + epsilon, epsilon); is true
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is_close_to(1.F, 1.F + epsilon, epsilon); is false
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fraction_tolerance = 3.57627869e-007
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strength = strong
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three_rounds(a, b) = true
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failed_fraction = 0.000000000
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three_rounds(a, b) = false
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failed_fraction = 3.86237957e-007
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float_distance = 4.00000000
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strong(fp1, fp2) is false
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weak(fp1, fp2) is false
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1.23456788 #= 1.23456836 is false
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1.23456788 ~= 1.23456836 is false
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0 is_small true
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denorm_ min =1.40129846e-045, is_small is true
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min = 1.17549435e-038, is_small is true
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epsilon = 1.19209290e-007, is_small is false
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2 epsilon = 1.19209290e-007, is_small is true
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4 epsilon = 2.38418579e-007, is_small is false
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0.00001 = 9.99999975e-006, is_small is true
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0.00001 = -9.99999975e-006, is_small is true
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my_test(0.001F) is true
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my_test(0.001F) is false//] [/compare_floats_output]
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*/
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