mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sergey Sharybin
54ba6c27b5
This commit includes the following: - Changes to CMake to make it safer to see which compiler flags are supported, so this way we do not need to worry about version checks in CMake. - Unix platforms (which includes both Linux and Apple as far as i can tell) will now enable -Wmissing-declarations warning for the whole Ceres. - Changes in all sources to solve missing declaration warning. In most cases it was either matter of using static qualifier or moving functions to an anonymous namespace. In one case the function got removed, since it seems to be unused. Additionally, in slam examples there was a non-inlined function implementation in a header, which is a direct way to cause linking errors if other .cc file will include that helper header. - All third party sources (which is currently only gmock) has this extra paranoid warning disabled. This warning is important in the following cases: - Detect helper functions which are not needed anymore. - Avoid unnoticed pollution of namespace. - Avoid bad level calls. - Avoid missing updates in header files after changes in implementation file. - Helps integrating Ceres into software where paranoid warnings are important. Change-Id: I9b1044aced3910d8c6b2356cfe2bf57f3c8c58db
222 lines
6.9 KiB
C++
222 lines
6.9 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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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: mierle@gmail.com (Keir Mierle)
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#include "ceres/c_api.h"
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#include <cmath>
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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// Duplicated from curve_fitting.cc.
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int num_observations = 67;
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double data[] = {
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0.000000e+00, 1.133898e+00,
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7.500000e-02, 1.334902e+00,
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1.500000e-01, 1.213546e+00,
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2.250000e-01, 1.252016e+00,
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3.000000e-01, 1.392265e+00,
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3.750000e-01, 1.314458e+00,
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4.500000e-01, 1.472541e+00,
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5.250000e-01, 1.536218e+00,
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6.000000e-01, 1.355679e+00,
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6.750000e-01, 1.463566e+00,
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7.500000e-01, 1.490201e+00,
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8.250000e-01, 1.658699e+00,
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9.000000e-01, 1.067574e+00,
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9.750000e-01, 1.464629e+00,
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1.050000e+00, 1.402653e+00,
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1.125000e+00, 1.713141e+00,
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1.200000e+00, 1.527021e+00,
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1.275000e+00, 1.702632e+00,
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1.350000e+00, 1.423899e+00,
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1.425000e+00, 1.543078e+00,
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1.500000e+00, 1.664015e+00,
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1.575000e+00, 1.732484e+00,
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1.650000e+00, 1.543296e+00,
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1.725000e+00, 1.959523e+00,
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1.800000e+00, 1.685132e+00,
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1.875000e+00, 1.951791e+00,
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1.950000e+00, 2.095346e+00,
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2.025000e+00, 2.361460e+00,
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2.100000e+00, 2.169119e+00,
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2.175000e+00, 2.061745e+00,
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2.250000e+00, 2.178641e+00,
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2.325000e+00, 2.104346e+00,
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2.400000e+00, 2.584470e+00,
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2.475000e+00, 1.914158e+00,
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2.550000e+00, 2.368375e+00,
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2.625000e+00, 2.686125e+00,
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2.700000e+00, 2.712395e+00,
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2.775000e+00, 2.499511e+00,
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2.850000e+00, 2.558897e+00,
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2.925000e+00, 2.309154e+00,
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3.000000e+00, 2.869503e+00,
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3.075000e+00, 3.116645e+00,
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3.150000e+00, 3.094907e+00,
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3.225000e+00, 2.471759e+00,
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3.300000e+00, 3.017131e+00,
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3.375000e+00, 3.232381e+00,
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3.450000e+00, 2.944596e+00,
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3.525000e+00, 3.385343e+00,
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3.600000e+00, 3.199826e+00,
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3.675000e+00, 3.423039e+00,
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3.750000e+00, 3.621552e+00,
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3.825000e+00, 3.559255e+00,
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3.900000e+00, 3.530713e+00,
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3.975000e+00, 3.561766e+00,
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4.050000e+00, 3.544574e+00,
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4.125000e+00, 3.867945e+00,
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4.200000e+00, 4.049776e+00,
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4.275000e+00, 3.885601e+00,
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4.350000e+00, 4.110505e+00,
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4.425000e+00, 4.345320e+00,
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4.500000e+00, 4.161241e+00,
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4.575000e+00, 4.363407e+00,
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4.650000e+00, 4.161576e+00,
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4.725000e+00, 4.619728e+00,
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4.800000e+00, 4.737410e+00,
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4.875000e+00, 4.727863e+00,
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4.950000e+00, 4.669206e+00,
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};
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// A test cost function, similar to the one in curve_fitting.c.
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static int exponential_residual(void* user_data,
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double** parameters,
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double* residuals,
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double** jacobians) {
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double* measurement = (double*) user_data;
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double x = measurement[0];
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double y = measurement[1];
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double m = parameters[0][0];
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double c = parameters[1][0];
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residuals[0] = y - exp(m * x + c);
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if (jacobians == NULL) {
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return 1;
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}
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if (jacobians[0] != NULL) {
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jacobians[0][0] = - x * exp(m * x + c); // dr/dm
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}
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if (jacobians[1] != NULL) {
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jacobians[1][0] = - exp(m * x + c); // dr/dc
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}
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return 1;
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}
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namespace ceres {
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namespace internal {
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TEST(C_API, SimpleEndToEndTest) {
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double m = 0.0;
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double c = 0.0;
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double *parameter_pointers[] = { &m, &c };
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int parameter_sizes[] = { 1, 1 };
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ceres_problem_t* problem = ceres_create_problem();
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for (int i = 0; i < num_observations; ++i) {
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ceres_problem_add_residual_block(
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problem,
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exponential_residual, // Cost function
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&data[2 * i], // Points to the (x,y) measurement
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NULL, // Loss function
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NULL, // Loss function user data
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1, // Number of residuals
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2, // Number of parameter blocks
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parameter_sizes,
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parameter_pointers);
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}
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ceres_solve(problem);
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EXPECT_NEAR(0.3, m, 0.02);
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EXPECT_NEAR(0.1, c, 0.04);
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ceres_free_problem(problem);
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}
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template<typename T>
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class ScopedSetValue {
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public:
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ScopedSetValue(T* variable, T new_value)
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: variable_(variable), old_value_(*variable) {
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*variable = new_value;
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}
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~ScopedSetValue() {
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*variable_ = old_value_;
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}
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private:
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T* variable_;
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T old_value_;
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};
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TEST(C_API, LossFunctions) {
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double m = 0.2;
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double c = 0.03;
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double *parameter_pointers[] = { &m, &c };
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int parameter_sizes[] = { 1, 1 };
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// Create two outliers, but be careful to leave the data intact.
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ScopedSetValue<double> outlier1x(&data[12], 2.5);
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ScopedSetValue<double> outlier1y(&data[13], 1.0e3);
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ScopedSetValue<double> outlier2x(&data[14], 3.2);
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ScopedSetValue<double> outlier2y(&data[15], 30e3);
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// Create a cauchy cost function, and reuse it many times.
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void* cauchy_loss_data =
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ceres_create_cauchy_loss_function_data(5.0);
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ceres_problem_t* problem = ceres_create_problem();
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for (int i = 0; i < num_observations; ++i) {
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ceres_problem_add_residual_block(
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problem,
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exponential_residual, // Cost function
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&data[2 * i], // Points to the (x,y) measurement
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ceres_stock_loss_function,
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cauchy_loss_data, // Loss function user data
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1, // Number of residuals
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2, // Number of parameter blocks
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parameter_sizes,
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parameter_pointers);
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}
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ceres_solve(problem);
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EXPECT_NEAR(0.3, m, 0.02);
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EXPECT_NEAR(0.1, c, 0.04);
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ceres_free_stock_loss_function_data(cauchy_loss_data);
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ceres_free_problem(problem);
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}
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} // namespace internal
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} // namespace ceres
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