Add NumericDiffFirstOrderFunction
This has been a long requested feature so that users can minimize
functions using numeric differentiation.
As part of this, I have also redone rosenbrock.cc, which now has three
variants.
rosenbrock.cc now uses automatic differentiation.
rosenbrock_numeric_diff.cc uses numeric differentiation.
rosenbrock_analytic_diff.cc uses analytic derivatives.
This is analogus to how the helloworld example code is structured.
The tutorial for GradientProblemSolver has also been updated to reflect
this.
https://github.com/ceres-solver/ceres-solver/issues/691
Change-Id: Ib0fb9e35127fe4c8299d4793bea3558722c70dd7
diff --git a/examples/rosenbrock_analytic_diff.cc b/examples/rosenbrock_analytic_diff.cc
new file mode 100644
index 0000000..b133f5a
--- /dev/null
+++ b/examples/rosenbrock_analytic_diff.cc
@@ -0,0 +1,75 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2021 Google Inc. All rights reserved.
+// http://ceres-solver.org/
+//
+// 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: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/ceres.h"
+#include "glog/logging.h"
+
+// f(x,y) = (1-x)^2 + 100(y - x^2)^2;
+class Rosenbrock final : public ceres::FirstOrderFunction {
+ public:
+ ~Rosenbrock() override {}
+
+ bool Evaluate(const double* parameters,
+ double* cost,
+ double* gradient) const override {
+ const double x = parameters[0];
+ const double y = parameters[1];
+
+ cost[0] = (1.0 - x) * (1.0 - x) + 100.0 * (y - x * x) * (y - x * x);
+
+ if (gradient) {
+ gradient[0] = -2.0 * (1.0 - x) - 200.0 * (y - x * x) * 2.0 * x;
+ gradient[1] = 200.0 * (y - x * x);
+ }
+
+ return true;
+ }
+
+ int NumParameters() const override { return 2; }
+};
+
+int main(int argc, char** argv) {
+ google::InitGoogleLogging(argv[0]);
+
+ double parameters[2] = {-1.2, 1.0};
+
+ ceres::GradientProblemSolver::Options options;
+ options.minimizer_progress_to_stdout = true;
+
+ ceres::GradientProblemSolver::Summary summary;
+ ceres::GradientProblem problem(new Rosenbrock());
+ ceres::Solve(options, problem, parameters, &summary);
+
+ std::cout << summary.FullReport() << "\n";
+ std::cout << "Initial x: " << -1.2 << " y: " << 1.0 << "\n";
+ std::cout << "Final x: " << parameters[0] << " y: " << parameters[1]
+ << "\n";
+ return 0;
+}
