mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 00:50:37 +08:00
Sameer Agarwal
560940fa27
1. Push the boundary handling logic into the underlying array object. This has two very significant impacts: a. The interpolation code becomes extremely simple to write and to test. b. The user has more flexibility in implementing how out of bounds values are handled. We provide one default implementation. Change-Id: Ic2f6cf9257ce7110c62e492688e5a6c8be1e7df2
95 lines
3.5 KiB
C++
95 lines
3.5 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: sameeragarwal@google.com (Sameer Agarwal)
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//
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// A simple example of optimizing a sampled function by using cubic
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// interpolation.
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#include "ceres/ceres.h"
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#include "ceres/cubic_interpolation.h"
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#include "glog/logging.h"
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using ceres::Grid1D;
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using ceres::CubicInterpolator;
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using ceres::AutoDiffCostFunction;
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using ceres::CostFunction;
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using ceres::Problem;
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using ceres::Solver;
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using ceres::Solve;
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// A simple cost functor that interfaces an interpolated table of
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// values with automatic differentiation.
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struct InterpolatedCostFunctor {
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explicit InterpolatedCostFunctor(
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const CubicInterpolator<Grid1D<double> >& interpolator)
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: interpolator_(interpolator) {
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}
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template<typename T> bool operator()(const T* x, T* residuals) const {
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interpolator_.Evaluate(*x, residuals);
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return true;
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}
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static CostFunction* Create(
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const CubicInterpolator<Grid1D<double> >& interpolator) {
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return new AutoDiffCostFunction<InterpolatedCostFunctor, 1, 1>(
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new InterpolatedCostFunctor(interpolator));
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}
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private:
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const CubicInterpolator<Grid1D<double> >& interpolator_;
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};
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int main(int argc, char** argv) {
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google::InitGoogleLogging(argv[0]);
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// Evaluate the function f(x) = (x - 4.5)^2;
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const int kNumSamples = 10;
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double values[kNumSamples];
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for (int i = 0; i < kNumSamples; ++i) {
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values[i] = (i - 4.5) * (i - 4.5);
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}
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Grid1D<double> array(values, 0, kNumSamples);
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CubicInterpolator<Grid1D<double> > interpolator(array);
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double x = 1.0;
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Problem problem;
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CostFunction* cost_function = InterpolatedCostFunctor::Create(interpolator);
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problem.AddResidualBlock(cost_function, NULL, &x);
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Solver::Options options;
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options.minimizer_progress_to_stdout = true;
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Solver::Summary summary;
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Solve(options, &problem, &summary);
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std::cout << summary.BriefReport() << "\n";
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std::cout << "Expected x: 4.5. Actual x : " << x << std::endl;
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return 0;
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}
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