// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// 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.
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// used to endorse or promote products derived from this software without
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//
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: keir@google.com (Keir Mierle)
// tbennun@gmail.com (Tal Ben-Nun)
#include "ceres/numeric_diff_cost_function.h"
#include <algorithm>
#include <cmath>
#include <string>
#include <vector>
#include "ceres/internal/macros.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/array_utils.h"
#include "ceres/numeric_diff_test_utils.h"
#include "ceres/test_util.h"
#include "ceres/types.h"
#include "glog/logging.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
TEST(NumericDiffCostFunction, EasyCaseFunctorCentralDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor,
CENTRAL,
3, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new EasyFunctor));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, CENTRAL);
}
TEST(NumericDiffCostFunction, EasyCaseFunctorForwardDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor,
FORWARD,
3, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new EasyFunctor));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, FORWARD);
}
TEST(NumericDiffCostFunction, EasyCaseFunctorRidders) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor,
RIDDERS,
3, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new EasyFunctor));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, RIDDERS);
}
TEST(NumericDiffCostFunction, EasyCaseCostFunctionCentralDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyCostFunction,
CENTRAL,
3, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new EasyCostFunction, TAKE_OWNERSHIP));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, CENTRAL);
}
TEST(NumericDiffCostFunction, EasyCaseCostFunctionForwardDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyCostFunction,
FORWARD,
3, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new EasyCostFunction, TAKE_OWNERSHIP));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, FORWARD);
}
TEST(NumericDiffCostFunction, EasyCaseCostFunctionRidders) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyCostFunction,
RIDDERS,
3, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new EasyCostFunction, TAKE_OWNERSHIP));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, RIDDERS);
}
TEST(NumericDiffCostFunction,
TranscendentalCaseFunctorCentralDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<TranscendentalFunctor,
CENTRAL,
2, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new TranscendentalFunctor));
TranscendentalFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, CENTRAL);
}
TEST(NumericDiffCostFunction,
TranscendentalCaseFunctorForwardDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<TranscendentalFunctor,
FORWARD,
2, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new TranscendentalFunctor));
TranscendentalFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, FORWARD);
}
TEST(NumericDiffCostFunction,
TranscendentalCaseFunctorRidders) {
NumericDiffOptions options;
// Using a smaller initial step size to overcome oscillatory function
// behavior.
options.ridders_relative_initial_step_size = 1e-3;
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<TranscendentalFunctor,
RIDDERS,
2, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new TranscendentalFunctor, TAKE_OWNERSHIP, 2, options));
TranscendentalFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, RIDDERS);
}
TEST(NumericDiffCostFunction,
TranscendentalCaseCostFunctionCentralDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<TranscendentalCostFunction,
CENTRAL,
2, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new TranscendentalCostFunction, TAKE_OWNERSHIP));
TranscendentalFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, CENTRAL);
}
TEST(NumericDiffCostFunction,
TranscendentalCaseCostFunctionForwardDifferences) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<TranscendentalCostFunction,
FORWARD,
2, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new TranscendentalCostFunction, TAKE_OWNERSHIP));
TranscendentalFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, FORWARD);
}
TEST(NumericDiffCostFunction,
TranscendentalCaseCostFunctionRidders) {
NumericDiffOptions options;
// Using a smaller initial step size to overcome oscillatory function
// behavior.
options.ridders_relative_initial_step_size = 1e-3;
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<TranscendentalCostFunction,
RIDDERS,
2, /* number of residuals */
5, /* size of x1 */
5 /* size of x2 */>(
new TranscendentalCostFunction, TAKE_OWNERSHIP, 2, options));
TranscendentalFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, RIDDERS);
}
template<int num_rows, int num_cols>
class SizeTestingCostFunction : public SizedCostFunction<num_rows, num_cols> {
public:
virtual bool Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const {
return true;
}
};
// As described in
// http://forum.kde.org/viewtopic.php?f=74&t=98536#p210774
// Eigen3 has restrictions on the Row/Column major storage of vectors,
// depending on their dimensions. This test ensures that the correct
// templates are instantiated for various shapes of the Jacobian
// matrix.
TEST(NumericDiffCostFunction, EigenRowMajorColMajorTest) {
scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<SizeTestingCostFunction<1,1>, CENTRAL, 1, 1>(
new SizeTestingCostFunction<1,1>, ceres::TAKE_OWNERSHIP));
cost_function.reset(
new NumericDiffCostFunction<SizeTestingCostFunction<2,1>, CENTRAL, 2, 1>(
new SizeTestingCostFunction<2,1>, ceres::TAKE_OWNERSHIP));
cost_function.reset(
new NumericDiffCostFunction<SizeTestingCostFunction<1,2>, CENTRAL, 1, 2>(
new SizeTestingCostFunction<1,2>, ceres::TAKE_OWNERSHIP));
cost_function.reset(
new NumericDiffCostFunction<SizeTestingCostFunction<2,2>, CENTRAL, 2, 2>(
new SizeTestingCostFunction<2,2>, ceres::TAKE_OWNERSHIP));
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor, CENTRAL, ceres::DYNAMIC, 1, 1>(
new EasyFunctor, TAKE_OWNERSHIP, 1));
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor, CENTRAL, ceres::DYNAMIC, 1, 1>(
new EasyFunctor, TAKE_OWNERSHIP, 2));
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor, CENTRAL, ceres::DYNAMIC, 1, 2>(
new EasyFunctor, TAKE_OWNERSHIP, 1));
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor, CENTRAL, ceres::DYNAMIC, 1, 2>(
new EasyFunctor, TAKE_OWNERSHIP, 2));
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor, CENTRAL, ceres::DYNAMIC, 2, 1>(
new EasyFunctor, TAKE_OWNERSHIP, 1));
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor, CENTRAL, ceres::DYNAMIC, 2, 1>(
new EasyFunctor, TAKE_OWNERSHIP, 2));
}
TEST(NumericDiffCostFunction,
EasyCaseFunctorCentralDifferencesAndDynamicNumResiduals) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<EasyFunctor,
CENTRAL,
ceres::DYNAMIC,
5, /* size of x1 */
5 /* size of x2 */>(
new EasyFunctor, TAKE_OWNERSHIP, 3));
EasyFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function, CENTRAL);
}
TEST(NumericDiffCostFunction, ExponentialFunctorRidders) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<ExponentialFunctor,
RIDDERS,
1, /* number of residuals */
1 /* size of x1 */>(
new ExponentialFunctor));
ExponentialFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function);
}
TEST(NumericDiffCostFunction, ExponentialCostFunctionRidders) {
internal::scoped_ptr<CostFunction> cost_function;
cost_function.reset(
new NumericDiffCostFunction<ExponentialCostFunction,
RIDDERS,
1, /* number of residuals */
1 /* size of x1 */>(
new ExponentialCostFunction));
ExponentialFunctor functor;
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function);
}
TEST(NumericDiffCostFunction, RandomizedFunctorRidders) {
internal::scoped_ptr<CostFunction> cost_function;
NumericDiffOptions options;
// Larger initial step size is chosen to produce robust results in the
// presence of random noise.
options.ridders_relative_initial_step_size = 10.0;
cost_function.reset(
new NumericDiffCostFunction<RandomizedFunctor,
RIDDERS,
1, /* number of residuals */
1 /* size of x1 */>(
new RandomizedFunctor(kNoiseFactor, kRandomSeed), TAKE_OWNERSHIP,
1, options));
RandomizedFunctor functor (kNoiseFactor, kRandomSeed);
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function);
}
TEST(NumericDiffCostFunction, RandomizedCostFunctionRidders) {
internal::scoped_ptr<CostFunction> cost_function;
NumericDiffOptions options;
// Larger initial step size is chosen to produce robust results in the
// presence of random noise.
options.ridders_relative_initial_step_size = 10.0;
cost_function.reset(
new NumericDiffCostFunction<RandomizedCostFunction,
RIDDERS,
1, /* number of residuals */
1 /* size of x1 */>(
new RandomizedCostFunction(kNoiseFactor, kRandomSeed),
TAKE_OWNERSHIP, 1, options));
RandomizedFunctor functor (kNoiseFactor, kRandomSeed);
functor.ExpectCostFunctionEvaluationIsNearlyCorrect(*cost_function);
}
struct OnlyFillsOneOutputFunctor {
bool operator()(const double* x, double* output) const {
output[0] = x[0];
return true;
}
};
TEST(NumericDiffCostFunction, PartiallyFilledResidualShouldFailEvaluation) {
double parameter = 1.0;
double jacobian[2];
double residuals[2];
double* parameters[] = {¶meter};
double* jacobians[] = {jacobian};
scoped_ptr<CostFunction> cost_function(
new NumericDiffCostFunction<OnlyFillsOneOutputFunctor, CENTRAL, 2, 1>(
new OnlyFillsOneOutputFunctor));
InvalidateArray(2, jacobian);
InvalidateArray(2, residuals);
EXPECT_TRUE(cost_function->Evaluate(parameters, residuals, jacobians));
EXPECT_FALSE(IsArrayValid(2, residuals));
InvalidateArray(2, residuals);
EXPECT_TRUE(cost_function->Evaluate(parameters, residuals, NULL));
// We are only testing residuals here, because the Jacobians are
// computed using finite differencing from the residuals, so unless
// we introduce a validation step after every evaluation of
// residuals inside NumericDiffCostFunction, there is no way of
// ensuring that the Jacobian array is invalid.
EXPECT_FALSE(IsArrayValid(2, residuals));
}
} // namespace internal
} // namespace ceres