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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_POLYNOMIALS_MODULE_H
+#define EIGEN_POLYNOMIALS_MODULE_H
+
+#include <Eigen/Core>
+
+#include <Eigen/src/Core/util/DisableStupidWarnings.h>
+
+#include <Eigen/Eigenvalues>
+
+// Note that EIGEN_HIDE_HEAVY_CODE has to be defined per module
+#if (defined EIGEN_EXTERN_INSTANTIATIONS) && (EIGEN_EXTERN_INSTANTIATIONS>=2)
+ #ifndef EIGEN_HIDE_HEAVY_CODE
+ #define EIGEN_HIDE_HEAVY_CODE
+ #endif
+#elif defined EIGEN_HIDE_HEAVY_CODE
+ #undef EIGEN_HIDE_HEAVY_CODE
+#endif
+
+/**
+ * \defgroup Polynomials_Module Polynomials module
+ * \brief This module provides a QR based polynomial solver.
+ *
+ * To use this module, add
+ * \code
+ * #include <unsupported/Eigen/Polynomials>
+ * \endcode
+ * at the start of your source file.
+ */
+
+#include "src/Polynomials/PolynomialUtils.h"
+#include "src/Polynomials/Companion.h"
+#include "src/Polynomials/PolynomialSolver.h"
+
+/**
+ \page polynomials Polynomials defines functions for dealing with polynomials
+ and a QR based polynomial solver.
+ \ingroup Polynomials_Module
+
+ The remainder of the page documents first the functions for evaluating, computing
+ polynomials, computing estimates about polynomials and next the QR based polynomial
+ solver.
+
+ \section polynomialUtils convenient functions to deal with polynomials
+ \subsection roots_to_monicPolynomial
+ The function
+ \code
+ void roots_to_monicPolynomial( const RootVector& rv, Polynomial& poly )
+ \endcode
+ computes the coefficients \f$ a_i \f$ of
+
+ \f$ p(x) = a_0 + a_{1}x + ... + a_{n-1}x^{n-1} + x^n \f$
+
+ where \f$ p \f$ is known through its roots i.e. \f$ p(x) = (x-r_1)(x-r_2)...(x-r_n) \f$.
+
+ \subsection poly_eval
+ The function
+ \code
+ T poly_eval( const Polynomials& poly, const T& x )
+ \endcode
+ evaluates a polynomial at a given point using stabilized H&ouml;rner method.
+
+ The following code: first computes the coefficients in the monomial basis of the monic polynomial that has the provided roots;
+ then, it evaluates the computed polynomial, using a stabilized H&ouml;rner method.
+
+ \include PolynomialUtils1.cpp
+ Output: \verbinclude PolynomialUtils1.out
+
+ \subsection Cauchy bounds
+ The function
+ \code
+ Real cauchy_max_bound( const Polynomial& poly )
+ \endcode
+ provides a maximum bound (the Cauchy one: \f$C(p)\f$) for the absolute value of a root of the given polynomial i.e.
+ \f$ \forall r_i \f$ root of \f$ p(x) = \sum_{k=0}^d a_k x^k \f$,
+ \f$ |r_i| \le C(p) = \sum_{k=0}^{d} \left | \frac{a_k}{a_d} \right | \f$
+ The leading coefficient \f$ p \f$: should be non zero \f$a_d \neq 0\f$.
+
+
+ The function
+ \code
+ Real cauchy_min_bound( const Polynomial& poly )
+ \endcode
+ provides a minimum bound (the Cauchy one: \f$c(p)\f$) for the absolute value of a non zero root of the given polynomial i.e.
+ \f$ \forall r_i \neq 0 \f$ root of \f$ p(x) = \sum_{k=0}^d a_k x^k \f$,
+ \f$ |r_i| \ge c(p) = \left( \sum_{k=0}^{d} \left | \frac{a_k}{a_0} \right | \right)^{-1} \f$
+
+
+
+
+ \section QR polynomial solver class
+ Computes the complex roots of a polynomial by computing the eigenvalues of the associated companion matrix with the QR algorithm.
+
+ The roots of \f$ p(x) = a_0 + a_1 x + a_2 x^2 + a_{3} x^3 + x^4 \f$ are the eigenvalues of
+ \f$
+ \left [
+ \begin{array}{cccc}
+ 0 & 0 & 0 & a_0 \\
+ 1 & 0 & 0 & a_1 \\
+ 0 & 1 & 0 & a_2 \\
+ 0 & 0 & 1 & a_3
+ \end{array} \right ]
+ \f$
+
+ However, the QR algorithm is not guaranteed to converge when there are several eigenvalues with same modulus.
+
+ Therefore the current polynomial solver is guaranteed to provide a correct result only when the complex roots \f$r_1,r_2,...,r_d\f$ have distinct moduli i.e.
+
+ \f$ \forall i,j \in [1;d],~ \| r_i \| \neq \| r_j \| \f$.
+
+ With 32bit (float) floating types this problem shows up frequently.
+ However, almost always, correct accuracy is reached even in these cases for 64bit
+ (double) floating types and small polynomial degree (<20).
+
+ \include PolynomialSolver1.cpp
+
+ In the above example:
+
+ -# a simple use of the polynomial solver is shown;
+ -# the accuracy problem with the QR algorithm is presented: a polynomial with almost conjugate roots is provided to the solver.
+ Those roots have almost same module therefore the QR algorithm failed to converge: the accuracy
+ of the last root is bad;
+ -# a simple way to circumvent the problem is shown: use doubles instead of floats.
+
+ Output: \verbinclude PolynomialSolver1.out
+*/
+
+#include <Eigen/src/Core/util/ReenableStupidWarnings.h>
+
+#endif // EIGEN_POLYNOMIALS_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */