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| 1 | // -*- mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- | ||
| 2 | // vi: set et ts=4 sw=4 sts=4: | ||
| 3 | // | ||
| 4 | // SPDX-FileCopyrightInfo: Copyright © DuMux Project contributors, see AUTHORS.md in root folder | ||
| 5 | // SPDX-License-Identifier: GPL-3.0-or-later | ||
| 6 | // | ||
| 7 | /*! | ||
| 8 | * \file | ||
| 9 | * \ingroup Nonlinear | ||
| 10 | * \brief Root finding algorithms for scalar functions | ||
| 11 | */ | ||
| 12 | #ifndef DUMUX_COMMON_SCALAR_ROOT_FINDING_HH | ||
| 13 | #define DUMUX_COMMON_SCALAR_ROOT_FINDING_HH | ||
| 14 | |||
| 15 | #include <cmath> | ||
| 16 | #include <limits> | ||
| 17 | #include <type_traits> | ||
| 18 | |||
| 19 | #include <dumux/common/exceptions.hh> | ||
| 20 | #include <dumux/common/parameters.hh> | ||
| 21 | #include <dumux/common/numericdifferentiation.hh> | ||
| 22 | |||
| 23 | namespace Dumux { | ||
| 24 | |||
| 25 | /*! | ||
| 26 | * \ingroup Nonlinear | ||
| 27 | * \brief Newton's root finding algorithm for scalar functions (secant method) | ||
| 28 | * \param xOld initial guess | ||
| 29 | * \param residual Residual function | ||
| 30 | * \param derivative Derivative of the residual | ||
| 31 | * \param tol Relative shift tolerance | ||
| 32 | * \param maxIter Maximum number of iterations | ||
| 33 | */ | ||
| 34 | template<class Scalar, class ResFunc, class DerivFunc, | ||
| 35 | typename std::enable_if_t<std::is_invocable_r_v<Scalar, ResFunc, Scalar> && | ||
| 36 | std::is_invocable_r_v<Scalar, DerivFunc, Scalar>>...> | ||
| 37 | ✗ | Scalar findScalarRootNewton(Scalar xOld, const ResFunc& residual, const DerivFunc& derivative, | |
| 38 | const Scalar tol = 1e-13, const int maxIter = 200) | ||
| 39 | { | ||
| 40 | ✗ | Scalar xNew = xOld; | |
| 41 | ✗ | Scalar r = residual(xNew); | |
| 42 | |||
| 43 | ✗ | int n = maxIter; | |
| 44 | ✗ | Scalar relativeShift = std::numeric_limits<Scalar>::max(); | |
| 45 | ✗ | while (relativeShift > tol && n > 0) | |
| 46 | { | ||
| 47 | ✗ | xNew = xOld - r/derivative(xOld); | |
| 48 | ✗ | r = residual(xNew); | |
| 49 | |||
| 50 | using std::abs; using std::max; | ||
| 51 | ✗ | relativeShift = abs(xOld-xNew)/max(abs(xOld), abs(xNew)); | |
| 52 | ✗ | xOld = xNew; | |
| 53 | ✗ | n--; | |
| 54 | } | ||
| 55 | |||
| 56 | using std::isfinite; | ||
| 57 | ✗ | if (!isfinite(r)) | |
| 58 | ✗ | DUNE_THROW(NumericalProblem, "Residual is not finite: " << r << " after " << maxIter - n << " iterations!"); | |
| 59 | |||
| 60 | ✗ | if (relativeShift > tol) | |
| 61 | ✗ | DUNE_THROW(NumericalProblem, "Scalar newton solver did not converge after " << maxIter << " iterations!"); | |
| 62 | |||
| 63 | ✗ | return xNew; | |
| 64 | } | ||
| 65 | |||
| 66 | /*! | ||
| 67 | * \ingroup Nonlinear | ||
| 68 | * \brief Newton's root finding algorithm for scalar functions (secant method) | ||
| 69 | * \note The derivative is numerically computed. If the derivative is know use signature with derivative function. | ||
| 70 | * \param xOld initial guess | ||
| 71 | * \param residual Residual function | ||
| 72 | * \param tol Relative shift tolerance | ||
| 73 | * \param maxIter Maximum number of iterations | ||
| 74 | */ | ||
| 75 | template<class Scalar, class ResFunc, | ||
| 76 | typename std::enable_if_t<std::is_invocable_r_v<Scalar, ResFunc, Scalar>>...> | ||
| 77 | Scalar findScalarRootNewton(Scalar xOld, const ResFunc& residual, | ||
| 78 | const Scalar tol = 1e-13, const int maxIter = 200) | ||
| 79 | { | ||
| 80 | 1 | const auto eps = NumericDifferentiation::epsilon(xOld); | |
| 81 | ✗ | auto derivative = [&](const auto x){ return (residual(x + eps)-residual(x))/eps; }; | |
| 82 | 1 | return findScalarRootNewton(xOld, residual, derivative, tol, maxIter); | |
| 83 | } | ||
| 84 | |||
| 85 | /*! | ||
| 86 | * \ingroup Nonlinear | ||
| 87 | * \brief Brent's root finding algorithm for scalar functions | ||
| 88 | * \note Modified from pseudo-code on wikipedia: https://en.wikipedia.org/wiki/Brent%27s_method | ||
| 89 | * \note See also R.P. Brent "An algorithm with guaranteed convergence for finding a zero of a function", The Computer Journal (1971). | ||
| 90 | * \note This is usually more robust than Newton's method | ||
| 91 | * \param a Lower bound | ||
| 92 | * \param b Upper bound | ||
| 93 | * \param residual Residual function | ||
| 94 | * \param tol Relative shift tolerance | ||
| 95 | * \param maxIter Maximum number of iterations | ||
| 96 | */ | ||
| 97 | template<class Scalar, class ResFunc, | ||
| 98 | typename std::enable_if_t<std::is_invocable_r_v<Scalar, ResFunc, Scalar>>...> | ||
| 99 | 8490580 | Scalar findScalarRootBrent(Scalar a, Scalar b, const ResFunc& residual, | |
| 100 | const Scalar tol = 1e-13, const int maxIter = 200) | ||
| 101 | { | ||
| 102 | // precompute the residuals (minimize function evaluations) | ||
| 103 |
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8490580 | Scalar fa = residual(a); |
| 104 |
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8490580 | Scalar fb = residual(b); |
| 105 | 8490580 | Scalar fs = 0.0; | |
| 106 | |||
| 107 | // check if the root is inside the given interval | ||
| 108 | using std::signbit; | ||
| 109 |
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16981160 | if (!signbit(fa*fb)) |
| 110 |
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10 | DUNE_THROW(NumericalProblem, "Brent's algorithm failed: [a,b] does not contain any, or no uniquely defined root!"); |
| 111 | |||
| 112 | // sort bounds | ||
| 113 | using std::abs; using std::swap; | ||
| 114 |
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25471737 | if (abs(fa) < abs(fb)) |
| 115 | { | ||
| 116 | 7461190 | swap(a, b); | |
| 117 | 7461190 | swap(fa, fb); | |
| 118 | } | ||
| 119 | |||
| 120 | 8490579 | Scalar c = a; | |
| 121 | 8490579 | Scalar fc = fa; | |
| 122 | 8490579 | Scalar d = 0.0; | |
| 123 | 8490579 | Scalar s = 0.0; | |
| 124 | 8490579 | bool flag = true; | |
| 125 | |||
| 126 |
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216463103 | for (int i = 0; i < maxIter; ++i) |
| 127 | { | ||
| 128 | // stopping criterion | ||
| 129 | using std::max; | ||
| 130 |
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935415375 | if (abs(b-a) < tol*max(abs(a), abs(b))) |
| 131 | 8490579 | return b; | |
| 132 | |||
| 133 | // inverse quadratic interpolation | ||
| 134 |
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207972524 | if (fa != fc && fb != fc) |
| 135 | { | ||
| 136 | 23052975 | const auto fab = fa-fb; | |
| 137 | 23052975 | const auto fac = fa-fc; | |
| 138 | 23052975 | const auto fbc = fb-fc; | |
| 139 | 23052975 | s = a*fb*fc/(fab*fac) - b*fa*fc/(fab*fbc) + c*fa*fb/(fac*fbc); | |
| 140 | } | ||
| 141 | |||
| 142 | // secant method | ||
| 143 | else | ||
| 144 | { | ||
| 145 | 184919549 | s = b - fb*(b-a)/(fb-fa); | |
| 146 | } | ||
| 147 | |||
| 148 | // bisection method | ||
| 149 |
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36171226 | if ( (s < (3*a + b)*0.25 || s > b) |
| 150 |
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31137832 | || (flag && abs(s-b) >= abs(b-c)*0.5) |
| 151 |
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26398984 | || (!flag && abs(s-b) >= abs(c-d)*0.5) |
| 152 |
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29192920 | || (flag && abs(b-c) < tol*max(abs(b), abs(c))) |
| 153 |
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236036997 | || (!flag && abs(c-d) < tol*max(abs(c), abs(d))) ) |
| 154 | { | ||
| 155 | 181959664 | s = (a+b)*0.5; | |
| 156 | 181959664 | flag = true; | |
| 157 | } | ||
| 158 | else | ||
| 159 | flag = false; | ||
| 160 | |||
| 161 | // compute residual at new guess | ||
| 162 |
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207972524 | fs = residual(s); |
| 163 | 207972524 | d = c; | |
| 164 | 207972524 | c = b; | |
| 165 | 207972524 | fc = fb; | |
| 166 | |||
| 167 | // check on which side of the root s falls | ||
| 168 |
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207972524 | if (fa*fs < 0.0) |
| 169 | { | ||
| 170 | b = s; | ||
| 171 | fb = fs; | ||
| 172 | } | ||
| 173 | else | ||
| 174 | { | ||
| 175 | 184076402 | a = s; | |
| 176 | 184076402 | fa = fs; | |
| 177 | } | ||
| 178 | |||
| 179 | // sort if necessary | ||
| 180 |
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623917572 | if (abs(fa) < abs(fb)) |
| 181 | { | ||
| 182 | 28195287 | swap(a, b); | |
| 183 | 28195287 | swap(fa, fb); | |
| 184 | } | ||
| 185 | } | ||
| 186 | |||
| 187 | ✗ | DUNE_THROW(NumericalProblem, "Brent's algorithm didn't converge after " << maxIter << " iterations!"); | |
| 188 | } | ||
| 189 | |||
| 190 | } // end namespace Dumux | ||
| 191 | |||
| 192 | #endif | ||
| 193 |