internal/ceres/polynomial_test.cc - ceres-solver - Git at Google

 // Ceres Solver - A fast non-linear least squares minimizer
 // Copyright 2015 Google Inc. All rights reserved.
 // http://ceres-solver.org/
 //
 // Redistribution and use in source and binary forms, with or without
 // modification, are permitted provided that the following conditions are met:
 //
 // * Redistributions of source code must retain the above copyright notice,
 //   this list of conditions and the following disclaimer.
 // * Redistributions in binary form must reproduce the above copyright notice,
 //   this list of conditions and the following disclaimer in the documentation
 //   and/or other materials provided with the distribution.
 // * Neither the name of Google Inc. nor the names of its contributors may be
 //   used to endorse or promote products derived from this software without
 //   specific prior written permission.
 //
 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
 // POSSIBILITY OF SUCH DAMAGE.
 //
 // Author: moll.markus@arcor.de (Markus Moll)
 //         sameeragarwal@google.com (Sameer Agarwal)

 #include "ceres/polynomial.h"

 #include <limits>
 #include <cmath>
 #include <cstddef>
 #include <algorithm>
 #include "gtest/gtest.h"
 #include "ceres/test_util.h"

 namespace ceres {
 namespace internal {

 using std::vector;

 namespace {

 // For IEEE-754 doubles, machine precision is about 2e-16.
 const double kEpsilon = 1e-13;
 const double kEpsilonLoose = 1e-9;

 // Return the constant polynomial p(x) = 1.23.
 Vector ConstantPolynomial(double value) {
   Vector poly(1);
   poly(0) = value;
   return poly;
 }

 // Return the polynomial p(x) = poly(x) * (x - root).
 Vector AddRealRoot(const Vector& poly, double root) {
   Vector poly2(poly.size() + 1);
   poly2.setZero();
   poly2.head(poly.size()) += poly;
   poly2.tail(poly.size()) -= root * poly;
   return poly2;
 }

 // Return the polynomial
 // p(x) = poly(x) * (x - real - imag*i) * (x - real + imag*i).
 Vector AddComplexRootPair(const Vector& poly, double real, double imag) {
   Vector poly2(poly.size() + 2);
   poly2.setZero();
   // Multiply poly by x^2 - 2real + abs(real,imag)^2
   poly2.head(poly.size()) += poly;
   poly2.segment(1, poly.size()) -= 2 * real * poly;
   poly2.tail(poly.size()) += (real*real + imag*imag) * poly;
   return poly2;
 }

 // Sort the entries in a vector.
 // Needed because the roots are not returned in sorted order.
 Vector SortVector(const Vector& in) {
   Vector out(in);
   std::sort(out.data(), out.data() + out.size());
   return out;
 }

 // Run a test with the polynomial defined by the N real roots in roots_real.
 // If use_real is false, NULL is passed as the real argument to
 // FindPolynomialRoots. If use_imaginary is false, NULL is passed as the
 // imaginary argument to FindPolynomialRoots.
 template<int N>
 void RunPolynomialTestRealRoots(const double (&real_roots)[N],
                                 bool use_real,
                                 bool use_imaginary,
                                 double epsilon) {
   Vector real;
   Vector imaginary;
   Vector poly = ConstantPolynomial(1.23);
   for (int i = 0; i < N; ++i) {
     poly = AddRealRoot(poly, real_roots[i]);
   }
   Vector* const real_ptr = use_real ? &real : NULL;
   Vector* const imaginary_ptr = use_imaginary ? &imaginary : NULL;
   bool success = FindPolynomialRoots(poly, real_ptr, imaginary_ptr);

   EXPECT_EQ(success, true);
   if (use_real) {
     EXPECT_EQ(real.size(), N);
     real = SortVector(real);
     ExpectArraysClose(N, real.data(), real_roots, epsilon);
   }
   if (use_imaginary) {
     EXPECT_EQ(imaginary.size(), N);
     const Vector zeros = Vector::Zero(N);
     ExpectArraysClose(N, imaginary.data(), zeros.data(), epsilon);
   }
 }
 }  // namespace

 TEST(Polynomial, InvalidPolynomialOfZeroLengthIsRejected) {
   // Vector poly(0) is an ambiguous constructor call, so
   // use the constructor with explicit column count.
   Vector poly(0, 1);
   Vector real;
   Vector imag;
   bool success = FindPolynomialRoots(poly, &real, &imag);

   EXPECT_EQ(success, false);
 }

 TEST(Polynomial, ConstantPolynomialReturnsNoRoots) {
   Vector poly = ConstantPolynomial(1.23);
   Vector real;
   Vector imag;
   bool success = FindPolynomialRoots(poly, &real, &imag);

   EXPECT_EQ(success, true);
   EXPECT_EQ(real.size(), 0);
   EXPECT_EQ(imag.size(), 0);
 }

 TEST(Polynomial, LinearPolynomialWithPositiveRootWorks) {
   const double roots[1] = { 42.42 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, LinearPolynomialWithNegativeRootWorks) {
   const double roots[1] = { -42.42 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, QuadraticPolynomialWithPositiveRootsWorks) {
   const double roots[2] = { 1.0, 42.42 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, QuadraticPolynomialWithOneNegativeRootWorks) {
   const double roots[2] = { -42.42, 1.0 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, QuadraticPolynomialWithTwoNegativeRootsWorks) {
   const double roots[2] = { -42.42, -1.0 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, QuadraticPolynomialWithCloseRootsWorks) {
   const double roots[2] = { 42.42, 42.43 };
   RunPolynomialTestRealRoots(roots, true, false, kEpsilonLoose);
 }

 TEST(Polynomial, QuadraticPolynomialWithComplexRootsWorks) {
   Vector real;
   Vector imag;

   Vector poly = ConstantPolynomial(1.23);
   poly = AddComplexRootPair(poly, 42.42, 4.2);
   bool success = FindPolynomialRoots(poly, &real, &imag);

   EXPECT_EQ(success, true);
   EXPECT_EQ(real.size(), 2);
   EXPECT_EQ(imag.size(), 2);
   ExpectClose(real(0), 42.42, kEpsilon);
   ExpectClose(real(1), 42.42, kEpsilon);
   ExpectClose(std::abs(imag(0)), 4.2, kEpsilon);
   ExpectClose(std::abs(imag(1)), 4.2, kEpsilon);
   ExpectClose(std::abs(imag(0) + imag(1)), 0.0, kEpsilon);
 }

 TEST(Polynomial, QuarticPolynomialWorks) {
   const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, QuarticPolynomialWithTwoClustersOfCloseRootsWorks) {
   const double roots[4] = { 1.23e-1, 2.46e-1, 1.23e+5, 2.46e+5 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilonLoose);
 }

 TEST(Polynomial, QuarticPolynomialWithTwoZeroRootsWorks) {
   const double roots[4] = { -42.42, 0.0, 0.0, 42.42 };
   RunPolynomialTestRealRoots(roots, true, true, 2 * kEpsilonLoose);
 }

 TEST(Polynomial, QuarticMonomialWorks) {
   const double roots[4] = { 0.0, 0.0, 0.0, 0.0 };
   RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
 }

 TEST(Polynomial, NullPointerAsImaginaryPartWorks) {
   const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
   RunPolynomialTestRealRoots(roots, true, false, kEpsilon);
 }

 TEST(Polynomial, NullPointerAsRealPartWorks) {
   const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
   RunPolynomialTestRealRoots(roots, false, true, kEpsilon);
 }

 TEST(Polynomial, BothOutputArgumentsNullWorks) {
   const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
   RunPolynomialTestRealRoots(roots, false, false, kEpsilon);
 }

 TEST(Polynomial, DifferentiateConstantPolynomial) {
   // p(x) = 1;
   Vector polynomial(1);
   polynomial(0) = 1.0;
   const Vector derivative = DifferentiatePolynomial(polynomial);
   EXPECT_EQ(derivative.rows(), 1);
   EXPECT_EQ(derivative(0), 0);
 }

 TEST(Polynomial, DifferentiateQuadraticPolynomial) {
   // p(x) = x^2 + 2x + 3;
   Vector polynomial(3);
   polynomial(0) = 1.0;
   polynomial(1) = 2.0;
   polynomial(2) = 3.0;

   const Vector derivative = DifferentiatePolynomial(polynomial);
   EXPECT_EQ(derivative.rows(), 2);
   EXPECT_EQ(derivative(0), 2.0);
   EXPECT_EQ(derivative(1), 2.0);
 }

 TEST(Polynomial, MinimizeConstantPolynomial) {
   // p(x) = 1;
   Vector polynomial(1);
   polynomial(0) = 1.0;

   double optimal_x = 0.0;
   double optimal_value = 0.0;
   double min_x = 0.0;
   double max_x = 1.0;
   MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);

   EXPECT_EQ(optimal_value, 1.0);
   EXPECT_LE(optimal_x, max_x);
   EXPECT_GE(optimal_x, min_x);
 }

 TEST(Polynomial, MinimizeLinearPolynomial) {
   // p(x) = x - 2
   Vector polynomial(2);

   polynomial(0) = 1.0;
   polynomial(1) = 2.0;

   double optimal_x = 0.0;
   double optimal_value = 0.0;
   double min_x = 0.0;
   double max_x = 1.0;
   MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);

   EXPECT_EQ(optimal_x, 0.0);
   EXPECT_EQ(optimal_value, 2.0);
 }


 TEST(Polynomial, MinimizeQuadraticPolynomial) {
   // p(x) = x^2 - 3 x + 2
   // min_x = 3/2
   // min_value = -1/4;
   Vector polynomial(3);
   polynomial(0) = 1.0;
   polynomial(1) = -3.0;
   polynomial(2) = 2.0;

   double optimal_x = 0.0;
   double optimal_value = 0.0;
   double min_x = -2.0;
   double max_x = 2.0;
   MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
   EXPECT_EQ(optimal_x, 3.0/2.0);
   EXPECT_EQ(optimal_value, -1.0/4.0);

   min_x = -2.0;
   max_x = 1.0;
   MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
   EXPECT_EQ(optimal_x, 1.0);
   EXPECT_EQ(optimal_value, 0.0);

   min_x = 2.0;
   max_x = 3.0;
   MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
   EXPECT_EQ(optimal_x, 2.0);
   EXPECT_EQ(optimal_value, 0.0);
 }

 TEST(Polymomial, ConstantInterpolatingPolynomial) {
   // p(x) = 1.0
   Vector true_polynomial(1);
   true_polynomial << 1.0;

   vector<FunctionSample> samples;
   FunctionSample sample;
   sample.x = 1.0;
   sample.value = 1.0;
   sample.value_is_valid = true;
   samples.push_back(sample);

   const Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
 }

 TEST(Polynomial, LinearInterpolatingPolynomial) {
   // p(x) = 2x - 1
   Vector true_polynomial(2);
   true_polynomial << 2.0, -1.0;

   vector<FunctionSample> samples;
   FunctionSample sample;
   sample.x = 1.0;
   sample.value = 1.0;
   sample.value_is_valid = true;
   sample.gradient = 2.0;
   sample.gradient_is_valid = true;
   samples.push_back(sample);

   const Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
 }

 TEST(Polynomial, QuadraticInterpolatingPolynomial) {
   // p(x) = 2x^2 + 3x + 2
   Vector true_polynomial(3);
   true_polynomial << 2.0, 3.0, 2.0;

   vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = 1.0;
     sample.value = 7.0;
     sample.value_is_valid = true;
     sample.gradient = 7.0;
     sample.gradient_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = -3.0;
     sample.value = 11.0;
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
 }

 TEST(Polynomial, DeficientCubicInterpolatingPolynomial) {
   // p(x) = 2x^2 + 3x + 2
   Vector true_polynomial(4);
   true_polynomial << 0.0, 2.0, 3.0, 2.0;

   vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = 1.0;
     sample.value = 7.0;
     sample.value_is_valid = true;
     sample.gradient = 7.0;
     sample.gradient_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = -3.0;
     sample.value = 11.0;
     sample.value_is_valid = true;
     sample.gradient = -9;
     sample.gradient_is_valid = true;
     samples.push_back(sample);
   }

   const Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
 }


 TEST(Polynomial, CubicInterpolatingPolynomialFromValues) {
   // p(x) = x^3 + 2x^2 + 3x + 2
   Vector true_polynomial(4);
   true_polynomial << 1.0, 2.0, 3.0, 2.0;

   vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = 1.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = -3.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = 2.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = 0.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   const Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
 }

 TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndOneGradient) {
   // p(x) = x^3 + 2x^2 + 3x + 2
   Vector true_polynomial(4);
   true_polynomial << 1.0, 2.0, 3.0, 2.0;
   Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);

   vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = 1.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = -3.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = 2.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
     sample.gradient_is_valid = true;
     samples.push_back(sample);
   }

   const Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
 }

 TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndGradients) {
   // p(x) = x^3 + 2x^2 + 3x + 2
   Vector true_polynomial(4);
   true_polynomial << 1.0, 2.0, 3.0, 2.0;
   Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);

   vector<FunctionSample> samples;
   {
     FunctionSample sample;
     sample.x = -3.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
     sample.gradient_is_valid = true;
     samples.push_back(sample);
   }

   {
     FunctionSample sample;
     sample.x = 2.0;
     sample.value = EvaluatePolynomial(true_polynomial, sample.x);
     sample.value_is_valid = true;
     sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
     sample.gradient_is_valid = true;
     samples.push_back(sample);
   }

   const Vector polynomial = FindInterpolatingPolynomial(samples);
   EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
 }

 }  // namespace internal
 }  // namespace ceres
	// Ceres Solver - A fast non-linear least squares minimizer
	// Copyright 2015 Google Inc. All rights reserved.
	// http://ceres-solver.org/
	//
	// Redistribution and use in source and binary forms, with or without
	// modification, are permitted provided that the following conditions are met:
	//
	// * Redistributions of source code must retain the above copyright notice,
	// this list of conditions and the following disclaimer.
	// * Redistributions in binary form must reproduce the above copyright notice,
	// this list of conditions and the following disclaimer in the documentation
	// and/or other materials provided with the distribution.
	// * Neither the name of Google Inc. nor the names of its contributors may be
	// used to endorse or promote products derived from this software without
	// specific prior written permission.
	//
	// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
	// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
	// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
	// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
	// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
	// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
	// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
	// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
	// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
	// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
	// POSSIBILITY OF SUCH DAMAGE.
	//
	// Author: moll.markus@arcor.de (Markus Moll)
	// sameeragarwal@google.com (Sameer Agarwal)

	#include "ceres/polynomial.h"

	#include <limits>
	#include <cmath>
	#include <cstddef>
	#include <algorithm>
	#include "gtest/gtest.h"
	#include "ceres/test_util.h"

	namespace ceres {
	namespace internal {

	using std::vector;

	namespace {

	// For IEEE-754 doubles, machine precision is about 2e-16.
	const double kEpsilon = 1e-13;
	const double kEpsilonLoose = 1e-9;

	// Return the constant polynomial p(x) = 1.23.
	Vector ConstantPolynomial(double value) {
	Vector poly(1);
	poly(0) = value;
	return poly;
	}

	// Return the polynomial p(x) = poly(x) * (x - root).
	Vector AddRealRoot(const Vector& poly, double root) {
	Vector poly2(poly.size() + 1);
	poly2.setZero();
	poly2.head(poly.size()) += poly;
	poly2.tail(poly.size()) -= root * poly;
	return poly2;
	}

	// Return the polynomial
	// p(x) = poly(x) * (x - real - imagi) (x - real + imag*i).
	Vector AddComplexRootPair(const Vector& poly, double real, double imag) {
	Vector poly2(poly.size() + 2);
	poly2.setZero();
	// Multiply poly by x^2 - 2real + abs(real,imag)^2
	poly2.head(poly.size()) += poly;
	poly2.segment(1, poly.size()) -= 2 * real * poly;
	poly2.tail(poly.size()) += (realreal + imagimag) * poly;
	return poly2;
	}

	// Sort the entries in a vector.
	// Needed because the roots are not returned in sorted order.
	Vector SortVector(const Vector& in) {
	Vector out(in);
	std::sort(out.data(), out.data() + out.size());
	return out;
	}

	// Run a test with the polynomial defined by the N real roots in roots_real.
	// If use_real is false, NULL is passed as the real argument to
	// FindPolynomialRoots. If use_imaginary is false, NULL is passed as the
	// imaginary argument to FindPolynomialRoots.
	template<int N>
	void RunPolynomialTestRealRoots(const double (&real_roots)[N],
	bool use_real,
	bool use_imaginary,
	double epsilon) {
	Vector real;
	Vector imaginary;
	Vector poly = ConstantPolynomial(1.23);
	for (int i = 0; i < N; ++i) {
	poly = AddRealRoot(poly, real_roots[i]);
	}
	Vector* const real_ptr = use_real ? &real : NULL;
	Vector* const imaginary_ptr = use_imaginary ? &imaginary : NULL;
	bool success = FindPolynomialRoots(poly, real_ptr, imaginary_ptr);

	EXPECT_EQ(success, true);
	if (use_real) {
	EXPECT_EQ(real.size(), N);
	real = SortVector(real);
	ExpectArraysClose(N, real.data(), real_roots, epsilon);
	}
	if (use_imaginary) {
	EXPECT_EQ(imaginary.size(), N);
	const Vector zeros = Vector::Zero(N);
	ExpectArraysClose(N, imaginary.data(), zeros.data(), epsilon);
	}
	}
	} // namespace

	TEST(Polynomial, InvalidPolynomialOfZeroLengthIsRejected) {
	// Vector poly(0) is an ambiguous constructor call, so
	// use the constructor with explicit column count.
	Vector poly(0, 1);
	Vector real;
	Vector imag;
	bool success = FindPolynomialRoots(poly, &real, &imag);

	EXPECT_EQ(success, false);
	}

	TEST(Polynomial, ConstantPolynomialReturnsNoRoots) {
	Vector poly = ConstantPolynomial(1.23);
	Vector real;
	Vector imag;
	bool success = FindPolynomialRoots(poly, &real, &imag);

	EXPECT_EQ(success, true);
	EXPECT_EQ(real.size(), 0);
	EXPECT_EQ(imag.size(), 0);
	}

	TEST(Polynomial, LinearPolynomialWithPositiveRootWorks) {
	const double roots[1] = { 42.42 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, LinearPolynomialWithNegativeRootWorks) {
	const double roots[1] = { -42.42 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, QuadraticPolynomialWithPositiveRootsWorks) {
	const double roots[2] = { 1.0, 42.42 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, QuadraticPolynomialWithOneNegativeRootWorks) {
	const double roots[2] = { -42.42, 1.0 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, QuadraticPolynomialWithTwoNegativeRootsWorks) {
	const double roots[2] = { -42.42, -1.0 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, QuadraticPolynomialWithCloseRootsWorks) {
	const double roots[2] = { 42.42, 42.43 };
	RunPolynomialTestRealRoots(roots, true, false, kEpsilonLoose);
	}

	TEST(Polynomial, QuadraticPolynomialWithComplexRootsWorks) {
	Vector real;
	Vector imag;

	Vector poly = ConstantPolynomial(1.23);
	poly = AddComplexRootPair(poly, 42.42, 4.2);
	bool success = FindPolynomialRoots(poly, &real, &imag);

	EXPECT_EQ(success, true);
	EXPECT_EQ(real.size(), 2);
	EXPECT_EQ(imag.size(), 2);
	ExpectClose(real(0), 42.42, kEpsilon);
	ExpectClose(real(1), 42.42, kEpsilon);
	ExpectClose(std::abs(imag(0)), 4.2, kEpsilon);
	ExpectClose(std::abs(imag(1)), 4.2, kEpsilon);
	ExpectClose(std::abs(imag(0) + imag(1)), 0.0, kEpsilon);
	}

	TEST(Polynomial, QuarticPolynomialWorks) {
	const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, QuarticPolynomialWithTwoClustersOfCloseRootsWorks) {
	const double roots[4] = { 1.23e-1, 2.46e-1, 1.23e+5, 2.46e+5 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilonLoose);
	}

	TEST(Polynomial, QuarticPolynomialWithTwoZeroRootsWorks) {
	const double roots[4] = { -42.42, 0.0, 0.0, 42.42 };
	RunPolynomialTestRealRoots(roots, true, true, 2 * kEpsilonLoose);
	}

	TEST(Polynomial, QuarticMonomialWorks) {
	const double roots[4] = { 0.0, 0.0, 0.0, 0.0 };
	RunPolynomialTestRealRoots(roots, true, true, kEpsilon);
	}

	TEST(Polynomial, NullPointerAsImaginaryPartWorks) {
	const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
	RunPolynomialTestRealRoots(roots, true, false, kEpsilon);
	}

	TEST(Polynomial, NullPointerAsRealPartWorks) {
	const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
	RunPolynomialTestRealRoots(roots, false, true, kEpsilon);
	}

	TEST(Polynomial, BothOutputArgumentsNullWorks) {
	const double roots[4] = { 1.23e-4, 1.23e-1, 1.23e+2, 1.23e+5 };
	RunPolynomialTestRealRoots(roots, false, false, kEpsilon);
	}

	TEST(Polynomial, DifferentiateConstantPolynomial) {
	// p(x) = 1;
	Vector polynomial(1);
	polynomial(0) = 1.0;
	const Vector derivative = DifferentiatePolynomial(polynomial);
	EXPECT_EQ(derivative.rows(), 1);
	EXPECT_EQ(derivative(0), 0);
	}

	TEST(Polynomial, DifferentiateQuadraticPolynomial) {
	// p(x) = x^2 + 2x + 3;
	Vector polynomial(3);
	polynomial(0) = 1.0;
	polynomial(1) = 2.0;
	polynomial(2) = 3.0;

	const Vector derivative = DifferentiatePolynomial(polynomial);
	EXPECT_EQ(derivative.rows(), 2);
	EXPECT_EQ(derivative(0), 2.0);
	EXPECT_EQ(derivative(1), 2.0);
	}

	TEST(Polynomial, MinimizeConstantPolynomial) {
	// p(x) = 1;
	Vector polynomial(1);
	polynomial(0) = 1.0;

	double optimal_x = 0.0;
	double optimal_value = 0.0;
	double min_x = 0.0;
	double max_x = 1.0;
	MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);

	EXPECT_EQ(optimal_value, 1.0);
	EXPECT_LE(optimal_x, max_x);
	EXPECT_GE(optimal_x, min_x);
	}

	TEST(Polynomial, MinimizeLinearPolynomial) {
	// p(x) = x - 2
	Vector polynomial(2);

	polynomial(0) = 1.0;
	polynomial(1) = 2.0;

	double optimal_x = 0.0;
	double optimal_value = 0.0;
	double min_x = 0.0;
	double max_x = 1.0;
	MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);

	EXPECT_EQ(optimal_x, 0.0);
	EXPECT_EQ(optimal_value, 2.0);
	}


	TEST(Polynomial, MinimizeQuadraticPolynomial) {
	// p(x) = x^2 - 3 x + 2
	// min_x = 3/2
	// min_value = -1/4;
	Vector polynomial(3);
	polynomial(0) = 1.0;
	polynomial(1) = -3.0;
	polynomial(2) = 2.0;

	double optimal_x = 0.0;
	double optimal_value = 0.0;
	double min_x = -2.0;
	double max_x = 2.0;
	MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
	EXPECT_EQ(optimal_x, 3.0/2.0);
	EXPECT_EQ(optimal_value, -1.0/4.0);

	min_x = -2.0;
	max_x = 1.0;
	MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
	EXPECT_EQ(optimal_x, 1.0);
	EXPECT_EQ(optimal_value, 0.0);

	min_x = 2.0;
	max_x = 3.0;
	MinimizePolynomial(polynomial, min_x, max_x, &optimal_x, &optimal_value);
	EXPECT_EQ(optimal_x, 2.0);
	EXPECT_EQ(optimal_value, 0.0);
	}

	TEST(Polymomial, ConstantInterpolatingPolynomial) {
	// p(x) = 1.0
	Vector true_polynomial(1);
	true_polynomial << 1.0;

	vector<FunctionSample> samples;
	FunctionSample sample;
	sample.x = 1.0;
	sample.value = 1.0;
	sample.value_is_valid = true;
	samples.push_back(sample);

	const Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
	}

	TEST(Polynomial, LinearInterpolatingPolynomial) {
	// p(x) = 2x - 1
	Vector true_polynomial(2);
	true_polynomial << 2.0, -1.0;

	vector<FunctionSample> samples;
	FunctionSample sample;
	sample.x = 1.0;
	sample.value = 1.0;
	sample.value_is_valid = true;
	sample.gradient = 2.0;
	sample.gradient_is_valid = true;
	samples.push_back(sample);

	const Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
	}

	TEST(Polynomial, QuadraticInterpolatingPolynomial) {
	// p(x) = 2x^2 + 3x + 2
	Vector true_polynomial(3);
	true_polynomial << 2.0, 3.0, 2.0;

	vector<FunctionSample> samples;
	{
	FunctionSample sample;
	sample.x = 1.0;
	sample.value = 7.0;
	sample.value_is_valid = true;
	sample.gradient = 7.0;
	sample.gradient_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = -3.0;
	sample.value = 11.0;
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-15);
	}

	TEST(Polynomial, DeficientCubicInterpolatingPolynomial) {
	// p(x) = 2x^2 + 3x + 2
	Vector true_polynomial(4);
	true_polynomial << 0.0, 2.0, 3.0, 2.0;

	vector<FunctionSample> samples;
	{
	FunctionSample sample;
	sample.x = 1.0;
	sample.value = 7.0;
	sample.value_is_valid = true;
	sample.gradient = 7.0;
	sample.gradient_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = -3.0;
	sample.value = 11.0;
	sample.value_is_valid = true;
	sample.gradient = -9;
	sample.gradient_is_valid = true;
	samples.push_back(sample);
	}

	const Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
	}


	TEST(Polynomial, CubicInterpolatingPolynomialFromValues) {
	// p(x) = x^3 + 2x^2 + 3x + 2
	Vector true_polynomial(4);
	true_polynomial << 1.0, 2.0, 3.0, 2.0;

	vector<FunctionSample> samples;
	{
	FunctionSample sample;
	sample.x = 1.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = -3.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = 2.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = 0.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	const Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
	}

	TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndOneGradient) {
	// p(x) = x^3 + 2x^2 + 3x + 2
	Vector true_polynomial(4);
	true_polynomial << 1.0, 2.0, 3.0, 2.0;
	Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);

	vector<FunctionSample> samples;
	{
	FunctionSample sample;
	sample.x = 1.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = -3.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = 2.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
	sample.gradient_is_valid = true;
	samples.push_back(sample);
	}

	const Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
	}

	TEST(Polynomial, CubicInterpolatingPolynomialFromValuesAndGradients) {
	// p(x) = x^3 + 2x^2 + 3x + 2
	Vector true_polynomial(4);
	true_polynomial << 1.0, 2.0, 3.0, 2.0;
	Vector true_gradient_polynomial = DifferentiatePolynomial(true_polynomial);

	vector<FunctionSample> samples;
	{
	FunctionSample sample;
	sample.x = -3.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
	sample.gradient_is_valid = true;
	samples.push_back(sample);
	}

	{
	FunctionSample sample;
	sample.x = 2.0;
	sample.value = EvaluatePolynomial(true_polynomial, sample.x);
	sample.value_is_valid = true;
	sample.gradient = EvaluatePolynomial(true_gradient_polynomial, sample.x);
	sample.gradient_is_valid = true;
	samples.push_back(sample);
	}

	const Vector polynomial = FindInterpolatingPolynomial(samples);
	EXPECT_NEAR((true_polynomial - polynomial).norm(), 0.0, 1e-14);
	}

	} // namespace internal
	} // namespace ceres