1 /*
2  * Copyright Nick Thompson, 2017
3  * Use, modification and distribution are subject to the
4  * Boost Software License, Version 1.0. (See accompanying file
5  * LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
6  *
7  * Use the adaptive trapezoidal rule to estimate the integral of periodic functions over a period,
8  * or to integrate a function whose derivative vanishes at the endpoints.
9  *
10  * If your function does not satisfy these conditions, and instead is simply continuous and bounded
11  * over the whole interval, then this routine will still converge, albeit slowly. However, there
12  * are much more efficient methods in this case, including Romberg, Simpson, and double exponential quadrature.
13  */
14 
15 #ifndef BOOST_MATH_QUADRATURE_TRAPEZOIDAL_HPP
16 #define BOOST_MATH_QUADRATURE_TRAPEZOIDAL_HPP
17 
18 #include <cmath>
19 #include <limits>
20 #include <utility>
21 #include <stdexcept>
22 #include <boost/math/constants/constants.hpp>
23 #include <boost/math/special_functions/fpclassify.hpp>
24 #include <boost/math/policies/error_handling.hpp>
25 #include <boost/math/tools/cxx03_warn.hpp>
26 
27 namespace boost{ namespace math{ namespace quadrature {
28 
29 template<class F, class Real, class Policy>
trapezoidal(F f,Real a,Real b,Real tol,std::size_t max_refinements,Real * error_estimate,Real * L1,const Policy & pol)30 auto trapezoidal(F f, Real a, Real b, Real tol, std::size_t max_refinements, Real* error_estimate, Real* L1, const Policy& pol)->decltype(std::declval<F>()(std::declval<Real>()))
31 {
32     static const char* function = "boost::math::quadrature::trapezoidal<%1%>(F, %1%, %1%, %1%)";
33     using std::abs;
34     using boost::math::constants::half;
35     // In many math texts, K represents the field of real or complex numbers.
36     // Too bad we can't put blackboard bold into C++ source!
37     typedef decltype(f(a)) K;
38     static_assert(!std::is_integral<K>::value,
39                   "The return type cannot be integral, it must be either a real or complex floating point type.");
40     if (!(boost::math::isfinite)(a))
41     {
42        return static_cast<K>(boost::math::policies::raise_domain_error(function, "Left endpoint of integration must be finite for adaptive trapezoidal integration but got a = %1%.\n", a, pol));
43     }
44     if (!(boost::math::isfinite)(b))
45     {
46        return static_cast<K>(boost::math::policies::raise_domain_error(function, "Right endpoint of integration must be finite for adaptive trapezoidal integration but got b = %1%.\n", b, pol));
47     }
48 
49     if (a == b)
50     {
51         return static_cast<K>(0);
52     }
53     if(a > b)
54     {
55         return -trapezoidal(f, b, a, tol, max_refinements, error_estimate, L1, pol);
56     }
57 
58 
59     K ya = f(a);
60     K yb = f(b);
61     Real h = (b - a)*half<Real>();
62     K I0 = (ya + yb)*h;
63     Real IL0 = (abs(ya) + abs(yb))*h;
64 
65     K yh = f(a + h);
66     K I1;
67     I1 = I0*half<Real>() + yh*h;
68     Real IL1 = IL0*half<Real>() + abs(yh)*h;
69 
70     // The recursion is:
71     // I_k = 1/2 I_{k-1} + 1/2^k \sum_{j=1; j odd, j < 2^k} f(a + j(b-a)/2^k)
72     std::size_t k = 2;
73     // We want to go through at least 5 levels so we have sampled the function at least 20 times.
74     // Otherwise, we could terminate prematurely and miss essential features.
75     // This is of course possible anyway, but 20 samples seems to be a reasonable compromise.
76     Real error = abs(I0 - I1);
77     // I take k < 5, rather than k < 4, or some other smaller minimum number,
78     // because I hit a truly exceptional bug where the k = 2 and k =3 refinement were bitwise equal,
79     // but the quadrature had not yet converged.
80     while (k < 5 || (k < max_refinements && error > tol*IL1) )
81     {
82         I0 = I1;
83         IL0 = IL1;
84 
85         I1 = I0*half<Real>();
86         IL1 = IL0*half<Real>();
87         std::size_t p = static_cast<std::size_t>(1u) << k;
88         h *= half<Real>();
89         K sum = 0;
90         Real absum = 0;
91 
92         for(std::size_t j = 1; j < p; j += 2)
93         {
94             K y = f(a + j*h);
95             sum += y;
96             absum += abs(y);
97         }
98 
99         I1 += sum*h;
100         IL1 += absum*h;
101         ++k;
102         error = abs(I0 - I1);
103     }
104 
105     if (error_estimate)
106     {
107         *error_estimate = error;
108     }
109 
110     if (L1)
111     {
112         *L1 = IL1;
113     }
114 
115     return static_cast<K>(I1);
116 }
117 
118 template<class F, class Real>
trapezoidal(F f,Real a,Real b,Real tol=boost::math::tools::root_epsilon<Real> (),std::size_t max_refinements=12,Real * error_estimate=nullptr,Real * L1=nullptr)119 auto trapezoidal(F f, Real a, Real b, Real tol = boost::math::tools::root_epsilon<Real>(), std::size_t max_refinements = 12, Real* error_estimate = nullptr, Real* L1 = nullptr)->decltype(std::declval<F>()(std::declval<Real>()))
120 {
121    return trapezoidal(f, a, b, tol, max_refinements, error_estimate, L1, boost::math::policies::policy<>());
122 }
123 
124 }}}
125 #endif
126