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-// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
-// http://code.google.com/p/ceres-solver/
-//
-// 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: keir@google.com (Keir Mierle)
-//
-// Based on the tests in numeric_diff_cost_function.cc.
-//
-// TODO(keir): See about code duplication.
-
-#include "ceres/runtime_numeric_diff_cost_function.h"
-
-#include <algorithm>
-#include <cmath>
-#include <string>
-#include <vector>
-#include "ceres/cost_function.h"
-#include "ceres/internal/macros.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/stringprintf.h"
-#include "ceres/test_util.h"
-#include "glog/logging.h"
-#include "gtest/gtest.h"
-
-namespace ceres {
-namespace internal {
-
-const double kRelativeEps = 1e-6;
-
-// y1 = x1'x2 -> dy1/dx1 = x2, dy1/dx2 = x1
-// y2 = (x1'x2)^2 -> dy2/dx1 = 2 * x2 * (x1'x2), dy2/dx2 = 2 * x1 * (x1'x2)
-// y3 = x2'x2 -> dy3/dx1 = 0, dy3/dx2 = 2 * x2
-class TestCostFunction : public CostFunction {
- public:
- TestCostFunction() {
- set_num_residuals(3);
- mutable_parameter_block_sizes()->push_back(5); // x1.
- mutable_parameter_block_sizes()->push_back(5); // x2.
- }
- virtual bool Evaluate(double const* const* parameters,
- double* residuals,
- double** jacobians) const {
- (void) jacobians; // Ignored.
-
- residuals[0] = residuals[1] = residuals[2] = 0;
- for (int i = 0; i < 5; ++i) {
- residuals[0] += parameters[0][i] * parameters[1][i];
- residuals[2] += parameters[1][i] * parameters[1][i];
- }
- residuals[1] = residuals[0] * residuals[0];
- return true;
- }
-};
-
-TEST(NumericDiffCostFunction, EasyCase) {
- // Try both central and forward difference.
- TestCostFunction term;
- scoped_ptr<CostFunction> cfs[2];
- cfs[0].reset(
- CreateRuntimeNumericDiffCostFunction(&term, CENTRAL, kRelativeEps));
-
- cfs[1].reset(
- CreateRuntimeNumericDiffCostFunction(&term, FORWARD, kRelativeEps));
-
-
- for (int c = 0; c < 2; ++c) {
- CostFunction *cost_function = cfs[c].get();
-
- double x1[] = { 1.0, 2.0, 3.0, 4.0, 5.0 };
- double x2[] = { 9.0, 9.0, 5.0, 5.0, 1.0 };
- double *parameters[] = { &x1[0], &x2[0] };
-
- double dydx1[15]; // 3 x 5, row major.
- double dydx2[15]; // 3 x 5, row major.
- double *jacobians[2] = { &dydx1[0], &dydx2[0] };
-
- double residuals[3] = {-1e-100, -2e-100, -3e-100 };
-
- ASSERT_TRUE(cost_function->Evaluate(&parameters[0],
- &residuals[0],
- &jacobians[0]));
-
- EXPECT_EQ(residuals[0], 67);
- EXPECT_EQ(residuals[1], 4489);
- EXPECT_EQ(residuals[2], 213);
-
- for (int i = 0; i < 5; ++i) {
- LOG(INFO) << "c = " << c << " i = " << i;
- const double kEps = c == 0 ? /* central */ 3e-9 : /* forward */ 2e-5;
-
- ExpectClose(x2[i], dydx1[5 * 0 + i], kEps); // y1
- ExpectClose(x1[i], dydx2[5 * 0 + i], kEps);
- ExpectClose(2 * x2[i] * residuals[0], dydx1[5 * 1 + i], kEps); // y2
- ExpectClose(2 * x1[i] * residuals[0], dydx2[5 * 1 + i], kEps);
- ExpectClose(0.0, dydx1[5 * 2 + i], kEps); // y3
- ExpectClose(2 * x2[i], dydx2[5 * 2 + i], kEps);
- }
- }
-}
-
-// y1 = sin(x1'x2)
-// y2 = exp(-x1'x2 / 10)
-//
-// dy1/dx1 = x2 * cos(x1'x2), dy1/dx2 = x1 * cos(x1'x2)
-// dy2/dx1 = -x2 * exp(-x1'x2 / 10) / 10, dy2/dx2 = -x2 * exp(-x1'x2 / 10) / 10
-class TranscendentalTestCostFunction : public CostFunction {
- public:
- TranscendentalTestCostFunction() {
- set_num_residuals(2);
- mutable_parameter_block_sizes()->push_back(5); // x1.
- mutable_parameter_block_sizes()->push_back(5); // x2.
- }
- virtual bool Evaluate(double const* const* parameters,
- double* residuals,
- double** jacobians) const {
- (void) jacobians; // Ignored.
-
- double x1x2 = 0;
- for (int i = 0; i < 5; ++i) {
- x1x2 += parameters[0][i] * parameters[1][i];
- }
- residuals[0] = sin(x1x2);
- residuals[1] = exp(-x1x2 / 10);
- return true;
- }
-};
-
-TEST(NumericDiffCostFunction, TransendentalOperationsInCostFunction) {
- // Try both central and forward difference.
- TranscendentalTestCostFunction term;
- scoped_ptr<CostFunction> cfs[2];
- cfs[0].reset(
- CreateRuntimeNumericDiffCostFunction(&term, CENTRAL, kRelativeEps));
-
- cfs[1].reset(
- CreateRuntimeNumericDiffCostFunction(&term, FORWARD, kRelativeEps));
-
- for (int c = 0; c < 2; ++c) {
- CostFunction *cost_function = cfs[c].get();
-
- struct {
- double x1[5];
- double x2[5];
- } kTests[] = {
- { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // No zeros.
- { 9.0, 9.0, 5.0, 5.0, 1.0 },
- },
- { { 0.0, 2.0, 3.0, 0.0, 5.0 }, // Some zeros x1.
- { 9.0, 9.0, 5.0, 5.0, 1.0 },
- },
- { { 1.0, 2.0, 3.0, 1.0, 5.0 }, // Some zeros x2.
- { 0.0, 9.0, 0.0, 5.0, 0.0 },
- },
- { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros x1.
- { 9.0, 9.0, 5.0, 5.0, 1.0 },
- },
- { { 1.0, 2.0, 3.0, 4.0, 5.0 }, // All zeros x2.
- { 0.0, 0.0, 0.0, 0.0, 0.0 },
- },
- { { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros.
- { 0.0, 0.0, 0.0, 0.0, 0.0 },
- },
- };
- for (int k = 0; k < CERES_ARRAYSIZE(kTests); ++k) {
- double *x1 = &(kTests[k].x1[0]);
- double *x2 = &(kTests[k].x2[0]);
- double *parameters[] = { x1, x2 };
-
- double dydx1[10];
- double dydx2[10];
- double *jacobians[2] = { &dydx1[0], &dydx2[0] };
-
- double residuals[2];
-
- ASSERT_TRUE(cost_function->Evaluate(&parameters[0],
- &residuals[0],
- &jacobians[0]));
- LOG(INFO) << "Ran evaluate for test k=" << k << " c=" << c;
-
- double x1x2 = 0;
- for (int i = 0; i < 5; ++i) {
- x1x2 += x1[i] * x2[i];
- }
-
- for (int i = 0; i < 5; ++i) {
- const double kEps = (c == 0 ? /* central */ 3e-9 : /* forward */ 2e-5);
-
- ExpectClose( x2[i] * cos(x1x2), dydx1[5 * 0 + i], kEps); // NOLINT
- ExpectClose( x1[i] * cos(x1x2), dydx2[5 * 0 + i], kEps); // NOLINT
- ExpectClose(-x2[i] * exp(-x1x2 / 10.) / 10., dydx1[5 * 1 + i], kEps);
- ExpectClose(-x1[i] * exp(-x1x2 / 10.) / 10., dydx2[5 * 1 + i], kEps);
- }
- }
- }
-}
-
-} // namespace internal
-} // namespace ceres
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