// (C) Copyright John Maddock 2006. // Use, modification and distribution are subject to the // Boost Software License, Version 1.0. (See accompanying file // LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) #ifndef BOOST_MATH_TOOLS_NEWTON_SOLVER_HPP #define BOOST_MATH_TOOLS_NEWTON_SOLVER_HPP #ifdef _MSC_VER #pragma once #endif #include // test for multiprecision types in complex Newton #include #include #include #include #include #include #include #include #include #include namespace boost { namespace math { namespace tools { namespace detail { namespace dummy { template typename T::value_type get(const T&) BOOST_MATH_NOEXCEPT(T); } template void unpack_tuple(const Tuple& t, T& a, T& b) BOOST_MATH_NOEXCEPT(T) { using dummy::get; // Use ADL to find the right overload for get: a = get<0>(t); b = get<1>(t); } template void unpack_tuple(const Tuple& t, T& a, T& b, T& c) BOOST_MATH_NOEXCEPT(T) { using dummy::get; // Use ADL to find the right overload for get: a = get<0>(t); b = get<1>(t); c = get<2>(t); } template inline void unpack_0(const Tuple& t, T& val) BOOST_MATH_NOEXCEPT(T) { using dummy::get; // Rely on ADL to find the correct overload of get: val = get<0>(t); } template inline void unpack_tuple(const std::pair& p, V& a, V& b) BOOST_MATH_NOEXCEPT(T) { a = p.first; b = p.second; } template inline void unpack_0(const std::pair& p, V& a) BOOST_MATH_NOEXCEPT(T) { a = p.first; } template void handle_zero_derivative(F f, T& last_f0, const T& f0, T& delta, T& result, T& guess, const T& min, const T& max) BOOST_NOEXCEPT_IF(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { if (last_f0 == 0) { // this must be the first iteration, pretend that we had a // previous one at either min or max: if (result == min) { guess = max; } else { guess = min; } unpack_0(f(guess), last_f0); delta = guess - result; } if (sign(last_f0) * sign(f0) < 0) { // we've crossed over so move in opposite direction to last step: if (delta < 0) { delta = (result - min) / 2; } else { delta = (result - max) / 2; } } else { // move in same direction as last step: if (delta < 0) { delta = (result - max) / 2; } else { delta = (result - min) / 2; } } } } // namespace template std::pair bisect(F f, T min, T max, Tol tol, boost::uintmax_t& max_iter, const Policy& pol) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { T fmin = f(min); T fmax = f(max); if (fmin == 0) { max_iter = 2; return std::make_pair(min, min); } if (fmax == 0) { max_iter = 2; return std::make_pair(max, max); } // // Error checking: // static const char* function = "boost::math::tools::bisect<%1%>"; if (min >= max) { return boost::math::detail::pair_from_single(policies::raise_evaluation_error(function, "Arguments in wrong order in boost::math::tools::bisect (first arg=%1%)", min, pol)); } if (fmin * fmax >= 0) { return boost::math::detail::pair_from_single(policies::raise_evaluation_error(function, "No change of sign in boost::math::tools::bisect, either there is no root to find, or there are multiple roots in the interval (f(min) = %1%).", fmin, pol)); } // // Three function invocations so far: // boost::uintmax_t count = max_iter; if (count < 3) count = 0; else count -= 3; while (count && (0 == tol(min, max))) { T mid = (min + max) / 2; T fmid = f(mid); if ((mid == max) || (mid == min)) break; if (fmid == 0) { min = max = mid; break; } else if (sign(fmid) * sign(fmin) < 0) { max = mid; } else { min = mid; fmin = fmid; } --count; } max_iter -= count; #ifdef BOOST_MATH_INSTRUMENT std::cout << "Bisection required " << max_iter << " iterations.\n"; #endif return std::make_pair(min, max); } template inline std::pair bisect(F f, T min, T max, Tol tol, boost::uintmax_t& max_iter) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { return bisect(f, min, max, tol, max_iter, policies::policy<>()); } template inline std::pair bisect(F f, T min, T max, Tol tol) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { boost::uintmax_t m = (std::numeric_limits::max)(); return bisect(f, min, max, tol, m, policies::policy<>()); } template T newton_raphson_iterate(F f, T guess, T min, T max, int digits, boost::uintmax_t& max_iter) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { BOOST_MATH_STD_USING static const char* function = "boost::math::tools::newton_raphson_iterate<%1%>"; if (min > max) { return policies::raise_evaluation_error(function, "Range arguments in wrong order in boost::math::tools::newton_raphson_iterate(first arg=%1%)", min, boost::math::policies::policy<>()); } T f0(0), f1, last_f0(0); T result = guess; T factor = static_cast(ldexp(1.0, 1 - digits)); T delta = tools::max_value(); T delta1 = tools::max_value(); T delta2 = tools::max_value(); // // We use these to sanity check that we do actually bracket a root, // we update these to the function value when we update the endpoints // of the range. Then, provided at some point we update both endpoints // checking that max_range_f * min_range_f <= 0 verifies there is a root // to be found somewhere. Note that if there is no root, and we approach // a local minima, then the derivative will go to zero, and hence the next // step will jump out of bounds (or at least past the minima), so this // check *should* happen in pathological cases. // T max_range_f = 0; T min_range_f = 0; boost::uintmax_t count(max_iter); #ifdef BOOST_MATH_INSTRUMENT std::cout << "Newton_raphson_iterate, guess = " << guess << ", min = " << min << ", max = " << max << ", digits = " << digits << ", max_iter = " << max_iter << "\n"; #endif do { last_f0 = f0; delta2 = delta1; delta1 = delta; detail::unpack_tuple(f(result), f0, f1); --count; if (0 == f0) break; if (f1 == 0) { // Oops zero derivative!!! detail::handle_zero_derivative(f, last_f0, f0, delta, result, guess, min, max); } else { delta = f0 / f1; } #ifdef BOOST_MATH_INSTRUMENT std::cout << "Newton iteration " << max_iter - count << ", delta = " << delta << ", residual = " << f0 << "\n"; #endif if (fabs(delta * 2) > fabs(delta2)) { // Last two steps haven't converged. T shift = (delta > 0) ? (result - min) / 2 : (result - max) / 2; if ((result != 0) && (fabs(shift) > fabs(result))) { delta = sign(delta) * fabs(result) * 1.1f; // Protect against huge jumps! //delta = sign(delta) * result; // Protect against huge jumps! Failed for negative result. https://github.com/boostorg/math/issues/216 } else delta = shift; // reset delta1/2 so we don't take this branch next time round: delta1 = 3 * delta; delta2 = 3 * delta; } guess = result; result -= delta; if (result <= min) { delta = 0.5F * (guess - min); result = guess - delta; if ((result == min) || (result == max)) break; } else if (result >= max) { delta = 0.5F * (guess - max); result = guess - delta; if ((result == min) || (result == max)) break; } // Update brackets: if (delta > 0) { max = guess; max_range_f = f0; } else { min = guess; min_range_f = f0; } // // Sanity check that we bracket the root: // if (max_range_f * min_range_f > 0) { return policies::raise_evaluation_error(function, "There appears to be no root to be found in boost::math::tools::newton_raphson_iterate, perhaps we have a local minima near current best guess of %1%", guess, boost::math::policies::policy<>()); } }while(count && (fabs(result * factor) < fabs(delta))); max_iter -= count; #ifdef BOOST_MATH_INSTRUMENT std::cout << "Newton Raphson required " << max_iter << " iterations\n"; #endif return result; } template inline T newton_raphson_iterate(F f, T guess, T min, T max, int digits) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { boost::uintmax_t m = (std::numeric_limits::max)(); return newton_raphson_iterate(f, guess, min, max, digits, m); } namespace detail { struct halley_step { template static T step(const T& /*x*/, const T& f0, const T& f1, const T& f2) BOOST_NOEXCEPT_IF(BOOST_MATH_IS_FLOAT(T)) { using std::fabs; T denom = 2 * f0; T num = 2 * f1 - f0 * (f2 / f1); T delta; BOOST_MATH_INSTRUMENT_VARIABLE(denom); BOOST_MATH_INSTRUMENT_VARIABLE(num); if ((fabs(num) < 1) && (fabs(denom) >= fabs(num) * tools::max_value())) { // possible overflow, use Newton step: delta = f0 / f1; } else delta = denom / num; return delta; } }; template T bracket_root_towards_min(F f, T guess, const T& f0, T& min, T& max, boost::uintmax_t& count) BOOST_NOEXCEPT_IF(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))); template T bracket_root_towards_max(F f, T guess, const T& f0, T& min, T& max, boost::uintmax_t& count) BOOST_NOEXCEPT_IF(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { using std::fabs; // // Move guess towards max until we bracket the root, updating min and max as we go: // T guess0 = guess; T multiplier = 2; T f_current = f0; if (fabs(min) < fabs(max)) { while (--count && ((f_current < 0) == (f0 < 0))) { min = guess; guess *= multiplier; if (guess > max) { guess = max; f_current = -f_current; // There must be a change of sign! break; } multiplier *= 2; unpack_0(f(guess), f_current); } } else { // // If min and max are negative we have to divide to head towards max: // while (--count && ((f_current < 0) == (f0 < 0))) { min = guess; guess /= multiplier; if (guess > max) { guess = max; f_current = -f_current; // There must be a change of sign! break; } multiplier *= 2; unpack_0(f(guess), f_current); } } if (count) { max = guess; if (multiplier > 16) return (guess0 - guess) + bracket_root_towards_min(f, guess, f_current, min, max, count); } return guess0 - (max + min) / 2; } template T bracket_root_towards_min(F f, T guess, const T& f0, T& min, T& max, boost::uintmax_t& count) BOOST_NOEXCEPT_IF(BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { using std::fabs; // // Move guess towards min until we bracket the root, updating min and max as we go: // T guess0 = guess; T multiplier = 2; T f_current = f0; if (fabs(min) < fabs(max)) { while (--count && ((f_current < 0) == (f0 < 0))) { max = guess; guess /= multiplier; if (guess < min) { guess = min; f_current = -f_current; // There must be a change of sign! break; } multiplier *= 2; unpack_0(f(guess), f_current); } } else { // // If min and max are negative we have to multiply to head towards min: // while (--count && ((f_current < 0) == (f0 < 0))) { max = guess; guess *= multiplier; if (guess < min) { guess = min; f_current = -f_current; // There must be a change of sign! break; } multiplier *= 2; unpack_0(f(guess), f_current); } } if (count) { min = guess; if (multiplier > 16) return (guess0 - guess) + bracket_root_towards_max(f, guess, f_current, min, max, count); } return guess0 - (max + min) / 2; } template T second_order_root_finder(F f, T guess, T min, T max, int digits, boost::uintmax_t& max_iter) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { BOOST_MATH_STD_USING #ifdef BOOST_MATH_INSTRUMENT std::cout << "Second order root iteration, guess = " << guess << ", min = " << min << ", max = " << max << ", digits = " << digits << ", max_iter = " << max_iter << "\n"; #endif static const char* function = "boost::math::tools::halley_iterate<%1%>"; if (min >= max) { return policies::raise_evaluation_error(function, "Range arguments in wrong order in boost::math::tools::halley_iterate(first arg=%1%)", min, boost::math::policies::policy<>()); } T f0(0), f1, f2; T result = guess; T factor = ldexp(static_cast(1.0), 1 - digits); T delta = (std::max)(T(10000000 * guess), T(10000000)); // arbitrarily large delta T last_f0 = 0; T delta1 = delta; T delta2 = delta; bool out_of_bounds_sentry = false; #ifdef BOOST_MATH_INSTRUMENT std::cout << "Second order root iteration, limit = " << factor << "\n"; #endif // // We use these to sanity check that we do actually bracket a root, // we update these to the function value when we update the endpoints // of the range. Then, provided at some point we update both endpoints // checking that max_range_f * min_range_f <= 0 verifies there is a root // to be found somewhere. Note that if there is no root, and we approach // a local minima, then the derivative will go to zero, and hence the next // step will jump out of bounds (or at least past the minima), so this // check *should* happen in pathological cases. // T max_range_f = 0; T min_range_f = 0; boost::uintmax_t count(max_iter); do { last_f0 = f0; delta2 = delta1; delta1 = delta; detail::unpack_tuple(f(result), f0, f1, f2); --count; BOOST_MATH_INSTRUMENT_VARIABLE(f0); BOOST_MATH_INSTRUMENT_VARIABLE(f1); BOOST_MATH_INSTRUMENT_VARIABLE(f2); if (0 == f0) break; if (f1 == 0) { // Oops zero derivative!!! detail::handle_zero_derivative(f, last_f0, f0, delta, result, guess, min, max); } else { if (f2 != 0) { delta = Stepper::step(result, f0, f1, f2); if (delta * f1 / f0 < 0) { // Oh dear, we have a problem as Newton and Halley steps // disagree about which way we should move. Probably // there is cancelation error in the calculation of the // Halley step, or else the derivatives are so small // that their values are basically trash. We will move // in the direction indicated by a Newton step, but // by no more than twice the current guess value, otherwise // we can jump way out of bounds if we're not careful. // See https://svn.boost.org/trac/boost/ticket/8314. delta = f0 / f1; if (fabs(delta) > 2 * fabs(guess)) delta = (delta < 0 ? -1 : 1) * 2 * fabs(guess); } } else delta = f0 / f1; } #ifdef BOOST_MATH_INSTRUMENT std::cout << "Second order root iteration, delta = " << delta << ", residual = " << f0 << "\n"; #endif T convergence = fabs(delta / delta2); if ((convergence > 0.8) && (convergence < 2)) { // last two steps haven't converged. delta = (delta > 0) ? (result - min) / 2 : (result - max) / 2; if ((result != 0) && (fabs(delta) > result)) delta = sign(delta) * fabs(result) * 0.9f; // protect against huge jumps! // reset delta2 so that this branch will *not* be taken on the // next iteration: delta2 = delta * 3; delta1 = delta * 3; BOOST_MATH_INSTRUMENT_VARIABLE(delta); } guess = result; result -= delta; BOOST_MATH_INSTRUMENT_VARIABLE(result); // check for out of bounds step: if (result < min) { T diff = ((fabs(min) < 1) && (fabs(result) > 1) && (tools::max_value() / fabs(result) < fabs(min))) ? T(1000) : (fabs(min) < 1) && (fabs(tools::max_value() * min) < fabs(result)) ? ((min < 0) != (result < 0)) ? -tools::max_value() : tools::max_value() : T(result / min); if (fabs(diff) < 1) diff = 1 / diff; if (!out_of_bounds_sentry && (diff > 0) && (diff < 3)) { // Only a small out of bounds step, lets assume that the result // is probably approximately at min: delta = 0.99f * (guess - min); result = guess - delta; out_of_bounds_sentry = true; // only take this branch once! } else { if (fabs(float_distance(min, max)) < 2) { result = guess = (min + max) / 2; break; } delta = bracket_root_towards_min(f, guess, f0, min, max, count); result = guess - delta; guess = min; continue; } } else if (result > max) { T diff = ((fabs(max) < 1) && (fabs(result) > 1) && (tools::max_value() / fabs(result) < fabs(max))) ? T(1000) : T(result / max); if (fabs(diff) < 1) diff = 1 / diff; if (!out_of_bounds_sentry && (diff > 0) && (diff < 3)) { // Only a small out of bounds step, lets assume that the result // is probably approximately at min: delta = 0.99f * (guess - max); result = guess - delta; out_of_bounds_sentry = true; // only take this branch once! } else { if (fabs(float_distance(min, max)) < 2) { result = guess = (min + max) / 2; break; } delta = bracket_root_towards_max(f, guess, f0, min, max, count); result = guess - delta; guess = min; continue; } } // update brackets: if (delta > 0) { max = guess; max_range_f = f0; } else { min = guess; min_range_f = f0; } // // Sanity check that we bracket the root: // if (max_range_f * min_range_f > 0) { return policies::raise_evaluation_error(function, "There appears to be no root to be found in boost::math::tools::newton_raphson_iterate, perhaps we have a local minima near current best guess of %1%", guess, boost::math::policies::policy<>()); } } while(count && (fabs(result * factor) < fabs(delta))); max_iter -= count; #ifdef BOOST_MATH_INSTRUMENT std::cout << "Second order root finder required " << max_iter << " iterations.\n"; #endif return result; } } // T second_order_root_finder template T halley_iterate(F f, T guess, T min, T max, int digits, boost::uintmax_t& max_iter) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { return detail::second_order_root_finder(f, guess, min, max, digits, max_iter); } template inline T halley_iterate(F f, T guess, T min, T max, int digits) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { boost::uintmax_t m = (std::numeric_limits::max)(); return halley_iterate(f, guess, min, max, digits, m); } namespace detail { struct schroder_stepper { template static T step(const T& x, const T& f0, const T& f1, const T& f2) BOOST_NOEXCEPT_IF(BOOST_MATH_IS_FLOAT(T)) { using std::fabs; T ratio = f0 / f1; T delta; if ((x != 0) && (fabs(ratio / x) < 0.1)) { delta = ratio + (f2 / (2 * f1)) * ratio * ratio; // check second derivative doesn't over compensate: if (delta * ratio < 0) delta = ratio; } else delta = ratio; // fall back to Newton iteration. return delta; } }; } template T schroder_iterate(F f, T guess, T min, T max, int digits, boost::uintmax_t& max_iter) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { return detail::second_order_root_finder(f, guess, min, max, digits, max_iter); } template inline T schroder_iterate(F f, T guess, T min, T max, int digits) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { boost::uintmax_t m = (std::numeric_limits::max)(); return schroder_iterate(f, guess, min, max, digits, m); } // // These two are the old spelling of this function, retained for backwards compatibility just in case: // template T schroeder_iterate(F f, T guess, T min, T max, int digits, boost::uintmax_t& max_iter) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { return detail::second_order_root_finder(f, guess, min, max, digits, max_iter); } template inline T schroeder_iterate(F f, T guess, T min, T max, int digits) BOOST_NOEXCEPT_IF(policies::is_noexcept_error_policy >::value&& BOOST_MATH_IS_FLOAT(T) && noexcept(std::declval()(std::declval()))) { boost::uintmax_t m = (std::numeric_limits::max)(); return schroder_iterate(f, guess, min, max, digits, m); } #ifndef BOOST_NO_CXX11_AUTO_DECLARATIONS /* * Why do we set the default maximum number of iterations to the number of digits in the type? * Because for double roots, the number of digits increases linearly with the number of iterations, * so this default should recover full precision even in this somewhat pathological case. * For isolated roots, the problem is so rapidly convergent that this doesn't matter at all. */ template Complex complex_newton(F g, Complex guess, int max_iterations = std::numeric_limits::digits) { typedef typename Complex::value_type Real; using std::norm; using std::abs; using std::max; // z0, z1, and z2 cannot be the same, in case we immediately need to resort to Muller's Method: Complex z0 = guess + Complex(1, 0); Complex z1 = guess + Complex(0, 1); Complex z2 = guess; do { auto pair = g(z2); if (norm(pair.second) == 0) { // Muller's method. Notation follows Numerical Recipes, 9.5.2: Complex q = (z2 - z1) / (z1 - z0); auto P0 = g(z0); auto P1 = g(z1); Complex qp1 = static_cast(1) + q; Complex A = q * (pair.first - qp1 * P1.first + q * P0.first); Complex B = (static_cast(2) * q + static_cast(1)) * pair.first - qp1 * qp1 * P1.first + q * q * P0.first; Complex C = qp1 * pair.first; Complex rad = sqrt(B * B - static_cast(4) * A * C); Complex denom1 = B + rad; Complex denom2 = B - rad; Complex correction = (z1 - z2) * static_cast(2) * C; if (norm(denom1) > norm(denom2)) { correction /= denom1; } else { correction /= denom2; } z0 = z1; z1 = z2; z2 = z2 + correction; } else { z0 = z1; z1 = z2; z2 = z2 - (pair.first / pair.second); } // See: https://math.stackexchange.com/questions/3017766/constructing-newton-iteration-converging-to-non-root // If f' is continuous, then convergence of x_n -> x* implies f(x*) = 0. // This condition approximates this convergence condition by requiring three consecutive iterates to be clustered. Real tol = (max)(abs(z2) * std::numeric_limits::epsilon(), std::numeric_limits::epsilon()); bool real_close = abs(z0.real() - z1.real()) < tol && abs(z0.real() - z2.real()) < tol && abs(z1.real() - z2.real()) < tol; bool imag_close = abs(z0.imag() - z1.imag()) < tol && abs(z0.imag() - z2.imag()) < tol && abs(z1.imag() - z2.imag()) < tol; if (real_close && imag_close) { return z2; } } while (max_iterations--); // The idea is that if we can get abs(f) < eps, we should, but if we go through all these iterations // and abs(f) < sqrt(eps), then roundoff error simply does not allow that we can evaluate f to < eps // This is somewhat awkward as it isn't scale invariant, but using the Daubechies coefficient example code, // I found this condition generates correct roots, whereas the scale invariant condition discussed here: // https://scicomp.stackexchange.com/questions/30597/defining-a-condition-number-and-termination-criteria-for-newtons-method // allows nonroots to be passed off as roots. auto pair = g(z2); if (abs(pair.first) < sqrt(std::numeric_limits::epsilon())) { return z2; } return { std::numeric_limits::quiet_NaN(), std::numeric_limits::quiet_NaN() }; } #endif #if !defined(BOOST_NO_CXX17_IF_CONSTEXPR) // https://stackoverflow.com/questions/48979861/numerically-stable-method-for-solving-quadratic-equations/50065711 namespace detail { #if defined(BOOST_GNU_STDLIB) && !defined(_GLIBCXX_USE_C99_MATH_TR1) inline float fma_workaround(float x, float y, float z) { return ::fmaf(x, y, z); } inline double fma_workaround(double x, double y, double z) { return ::fma(x, y, z); } #ifndef BOOST_MATH_NO_LONG_DOUBLE_MATH_FUNCTIONS inline long double fma_workaround(long double x, long double y, long double z) { return ::fmal(x, y, z); } #endif #endif template inline T discriminant(T const& a, T const& b, T const& c) { T w = 4 * a * c; #if defined(BOOST_GNU_STDLIB) && !defined(_GLIBCXX_USE_C99_MATH_TR1) T e = fma_workaround(-c, 4 * a, w); T f = fma_workaround(b, b, -w); #else T e = std::fma(-c, 4 * a, w); T f = std::fma(b, b, -w); #endif return f + e; } template std::pair quadratic_roots_imp(T const& a, T const& b, T const& c) { #if defined(BOOST_GNU_STDLIB) && !defined(_GLIBCXX_USE_C99_MATH_TR1) using boost::math::copysign; #else using std::copysign; #endif using std::sqrt; if constexpr (std::is_floating_point::value) { T nan = std::numeric_limits::quiet_NaN(); if (a == 0) { if (b == 0 && c != 0) { return std::pair(nan, nan); } else if (b == 0 && c == 0) { return std::pair(0, 0); } return std::pair(-c / b, -c / b); } if (b == 0) { T x0_sq = -c / a; if (x0_sq < 0) { return std::pair(nan, nan); } T x0 = sqrt(x0_sq); return std::pair(-x0, x0); } T discriminant = detail::discriminant(a, b, c); // Is there a sane way to flush very small negative values to zero? // If there is I don't know of it. if (discriminant < 0) { return std::pair(nan, nan); } T q = -(b + copysign(sqrt(discriminant), b)) / T(2); T x0 = q / a; T x1 = c / q; if (x0 < x1) { return std::pair(x0, x1); } return std::pair(x1, x0); } else if constexpr (boost::math::tools::is_complex_type::value) { typename T::value_type nan = std::numeric_limits::quiet_NaN(); if (a.real() == 0 && a.imag() == 0) { using std::norm; if (b.real() == 0 && b.imag() && norm(c) != 0) { return std::pair({ nan, nan }, { nan, nan }); } else if (b.real() == 0 && b.imag() && c.real() == 0 && c.imag() == 0) { return std::pair({ 0,0 }, { 0,0 }); } return std::pair(-c / b, -c / b); } if (b.real() == 0 && b.imag() == 0) { T x0_sq = -c / a; T x0 = sqrt(x0_sq); return std::pair(-x0, x0); } // There's no fma for complex types: T discriminant = b * b - T(4) * a * c; T q = -(b + sqrt(discriminant)) / T(2); return std::pair(q / a, c / q); } else // Most likely the type is a boost.multiprecision. { //There is no fma for multiprecision, and in addition it doesn't seem to be useful, so revert to the naive computation. T nan = std::numeric_limits::quiet_NaN(); if (a == 0) { if (b == 0 && c != 0) { return std::pair(nan, nan); } else if (b == 0 && c == 0) { return std::pair(0, 0); } return std::pair(-c / b, -c / b); } if (b == 0) { T x0_sq = -c / a; if (x0_sq < 0) { return std::pair(nan, nan); } T x0 = sqrt(x0_sq); return std::pair(-x0, x0); } T discriminant = b * b - 4 * a * c; if (discriminant < 0) { return std::pair(nan, nan); } T q = -(b + copysign(sqrt(discriminant), b)) / T(2); T x0 = q / a; T x1 = c / q; if (x0 < x1) { return std::pair(x0, x1); } return std::pair(x1, x0); } } } // namespace detail template inline std::pair::type, typename tools::promote_args::type> quadratic_roots(T1 const& a, T2 const& b, T3 const& c) { typedef typename tools::promote_args::type value_type; return detail::quadratic_roots_imp(static_cast(a), static_cast(b), static_cast(c)); } #endif } // namespace tools } // namespace math } // namespace boost #endif // BOOST_MATH_TOOLS_NEWTON_SOLVER_HPP