mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
295ade1122
Eigen3 does not allow column vectors to be stored in row-major format. NumericDiffCostFunction by default stores its Jacobian matrices in row-major format. This works fine if the residual contains more than one variable. But if the residual block depends on one variable and has more than one residuals, the resulting Jacobian matrix is a column matrix in row-major format resulting in a compile time error. The fix is to check the template parameters and switch to column-major storage as needed. Thanks to Lena Gieseke for reporting this. Change-Id: Icc51c5b38e1f3609e0e1ecb3c4e4a02aecd72c3b
272 lines
10 KiB
C++
272 lines
10 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: keir@google.com (Keir Mierle)
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#include "ceres/numeric_diff_cost_function.h"
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#include <algorithm>
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#include <cmath>
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#include <string>
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#include <vector>
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#include "ceres/cost_function.h"
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#include "ceres/internal/macros.h"
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#include "ceres/internal/scoped_ptr.h"
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#include "ceres/sized_cost_function.h"
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#include "ceres/stringprintf.h"
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#include "ceres/test_util.h"
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#include "ceres/types.h"
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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namespace ceres {
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namespace internal {
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// y1 = x1'x2 -> dy1/dx1 = x2, dy1/dx2 = x1
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// y2 = (x1'x2)^2 -> dy2/dx1 = 2 * x2 * (x1'x2), dy2/dx2 = 2 * x1 * (x1'x2)
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// y3 = x2'x2 -> dy3/dx1 = 0, dy3/dx2 = 2 * x2
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class TestCostFunction : public CostFunction {
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public:
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TestCostFunction() {
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set_num_residuals(3);
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mutable_parameter_block_sizes()->push_back(5); // x1.
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mutable_parameter_block_sizes()->push_back(5); // x2.
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}
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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(void) jacobians; // Ignored.
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residuals[0] = residuals[1] = residuals[2] = 0;
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for (int i = 0; i < 5; ++i) {
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residuals[0] += parameters[0][i] * parameters[1][i];
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residuals[2] += parameters[1][i] * parameters[1][i];
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}
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residuals[1] = residuals[0] * residuals[0];
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return true;
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}
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};
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TEST(NumericDiffCostFunction, EasyCase) {
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// Try both central and forward difference.
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internal::scoped_ptr<CostFunction> cfs[2];
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cfs[0].reset(
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new NumericDiffCostFunction<TestCostFunction,
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CENTRAL,
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3, /* number of residuals */
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5, /* size of x1 */
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5 /* size of x2 */>(
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new TestCostFunction, TAKE_OWNERSHIP));
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cfs[1].reset(
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new NumericDiffCostFunction<TestCostFunction,
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FORWARD,
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3, /* number of residuals */
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5, /* size of x1 */
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5 /* size of x2 */>(
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new TestCostFunction, TAKE_OWNERSHIP));
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for (int c = 0; c < 2; ++c) {
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CostFunction *cost_function = cfs[c].get();
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double x1[] = { 1.0, 2.0, 3.0, 4.0, 5.0 };
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double x2[] = { 9.0, 9.0, 5.0, 5.0, 1.0 };
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double *parameters[] = { &x1[0], &x2[0] };
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double dydx1[15]; // 3 x 5, row major.
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double dydx2[15]; // 3 x 5, row major.
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double *jacobians[2] = { &dydx1[0], &dydx2[0] };
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double residuals[3] = {-1e-100, -2e-100, -3e-100 };
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ASSERT_TRUE(cost_function->Evaluate(¶meters[0],
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&residuals[0],
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&jacobians[0]));
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EXPECT_EQ(residuals[0], 67);
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EXPECT_EQ(residuals[1], 4489);
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EXPECT_EQ(residuals[2], 213);
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for (int i = 0; i < 5; ++i) {
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LOG(INFO) << "c = " << c << " i = " << i;
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const double kEps = c == 0 ? /* central */ 3e-9 : /* forward */ 2e-5;
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ExpectClose(x2[i], dydx1[5 * 0 + i], kEps); // y1
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ExpectClose(x1[i], dydx2[5 * 0 + i], kEps);
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ExpectClose(2 * x2[i] * residuals[0], dydx1[5 * 1 + i], kEps); // y2
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ExpectClose(2 * x1[i] * residuals[0], dydx2[5 * 1 + i], kEps);
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ExpectClose(0.0, dydx1[5 * 2 + i], kEps); // y3
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ExpectClose(2 * x2[i], dydx2[5 * 2 + i], kEps);
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}
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}
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}
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// y1 = sin(x1'x2)
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// y2 = exp(-x1'x2 / 10)
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//
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// dy1/dx1 = x2 * cos(x1'x2), dy1/dx2 = x1 * cos(x1'x2)
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// dy2/dx1 = -x2 * exp(-x1'x2 / 10) / 10, dy2/dx2 = -x2 * exp(-x1'x2 / 10) / 10
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class TranscendentalTestCostFunction : public CostFunction {
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public:
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TranscendentalTestCostFunction() {
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set_num_residuals(2);
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mutable_parameter_block_sizes()->push_back(5); // x1.
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mutable_parameter_block_sizes()->push_back(5); // x2.
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}
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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(void) jacobians; // Ignored.
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double x1x2 = 0;
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for (int i = 0; i < 5; ++i) {
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x1x2 += parameters[0][i] * parameters[1][i];
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}
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residuals[0] = sin(x1x2);
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residuals[1] = exp(-x1x2 / 10);
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return true;
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}
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};
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TEST(NumericDiffCostFunction, TransendentalOperationsInCostFunction) {
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// Try both central and forward difference.
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internal::scoped_ptr<CostFunction> cfs[2];
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cfs[0].reset(
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new NumericDiffCostFunction<TranscendentalTestCostFunction,
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CENTRAL,
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2, /* number of residuals */
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5, /* size of x1 */
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5 /* size of x2 */>(
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new TranscendentalTestCostFunction, TAKE_OWNERSHIP));
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cfs[1].reset(
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new NumericDiffCostFunction<TranscendentalTestCostFunction,
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FORWARD,
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2, /* number of residuals */
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5, /* size of x1 */
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5 /* size of x2 */>(
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new TranscendentalTestCostFunction, TAKE_OWNERSHIP));
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for (int c = 0; c < 2; ++c) {
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CostFunction *cost_function = cfs[c].get();
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struct {
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double x1[5];
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double x2[5];
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} kTests[] = {
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{ { 1.0, 2.0, 3.0, 4.0, 5.0 }, // No zeros.
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{ 9.0, 9.0, 5.0, 5.0, 1.0 },
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},
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{ { 0.0, 2.0, 3.0, 0.0, 5.0 }, // Some zeros x1.
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{ 9.0, 9.0, 5.0, 5.0, 1.0 },
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},
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{ { 1.0, 2.0, 3.0, 1.0, 5.0 }, // Some zeros x2.
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{ 0.0, 9.0, 0.0, 5.0, 0.0 },
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},
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{ { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros x1.
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{ 9.0, 9.0, 5.0, 5.0, 1.0 },
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},
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{ { 1.0, 2.0, 3.0, 4.0, 5.0 }, // All zeros x2.
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{ 0.0, 0.0, 0.0, 0.0, 0.0 },
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},
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{ { 0.0, 0.0, 0.0, 0.0, 0.0 }, // All zeros.
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{ 0.0, 0.0, 0.0, 0.0, 0.0 },
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},
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};
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for (int k = 0; k < CERES_ARRAYSIZE(kTests); ++k) {
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double *x1 = &(kTests[k].x1[0]);
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double *x2 = &(kTests[k].x2[0]);
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double *parameters[] = { x1, x2 };
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double dydx1[10];
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double dydx2[10];
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double *jacobians[2] = { &dydx1[0], &dydx2[0] };
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double residuals[2];
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ASSERT_TRUE(cost_function->Evaluate(¶meters[0],
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&residuals[0],
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&jacobians[0]));
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LOG(INFO) << "Ran evaluate for test k=" << k << " c=" << c;
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double x1x2 = 0;
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for (int i = 0; i < 5; ++i) {
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x1x2 += x1[i] * x2[i];
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}
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for (int i = 0; i < 5; ++i) {
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const double kEps = c == 0 ? /* central */ 3e-9 : /* forward */ 2e-5;
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ExpectClose( x2[i] * cos(x1x2), dydx1[5 * 0 + i], kEps);
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ExpectClose( x1[i] * cos(x1x2), dydx2[5 * 0 + i], kEps);
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ExpectClose(-x2[i] * exp(-x1x2 / 10.) / 10., dydx1[5 * 1 + i], kEps);
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ExpectClose(-x1[i] * exp(-x1x2 / 10.) / 10., dydx2[5 * 1 + i], kEps);
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}
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}
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}
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}
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template<int num_rows, int num_cols>
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class SizeTestingCostFunction : public SizedCostFunction<num_rows, num_cols> {
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public:
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const {
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return true;
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}
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};
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// As described in
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// http://forum.kde.org/viewtopic.php?f=74&t=98536#p210774
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// Eigen3 has restrictions on the Row/Column major storage of vectors,
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// depending on their dimensions. This test ensures that the correct
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// templates are instantiated for various shapes of the Jacobian
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// matrix.
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TEST(NumericDiffCostFunction, EigenRowMajorColMajorTest) {
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scoped_ptr<CostFunction> cost_function;
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cost_function.reset(
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new NumericDiffCostFunction<SizeTestingCostFunction<1,1>, CENTRAL, 1, 1>(
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new SizeTestingCostFunction<1,1>, ceres::TAKE_OWNERSHIP));
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cost_function.reset(
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new NumericDiffCostFunction<SizeTestingCostFunction<2,1>, CENTRAL, 2, 1>(
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new SizeTestingCostFunction<2,1>, ceres::TAKE_OWNERSHIP));
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cost_function.reset(
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new NumericDiffCostFunction<SizeTestingCostFunction<1,2>, CENTRAL, 1, 2>(
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new SizeTestingCostFunction<1,2>, ceres::TAKE_OWNERSHIP));
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cost_function.reset(
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new NumericDiffCostFunction<SizeTestingCostFunction<2,2>, CENTRAL, 2, 2>(
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new SizeTestingCostFunction<2,2>, ceres::TAKE_OWNERSHIP));
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}
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} // namespace internal
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} // namespace ceres
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