mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
c8202e6926
1. Replace LineSearch::Summary::optimal_step_size with LineSearch:Summary::optimal_point which is a FunctionSample. 2. Add the actual vector position and vector gradient of the point in the FunctionSample 3. Use the above two to get rid of an extraneous function evalation in LineSearchMinimizer. Runtime performance is almost 2x improved as a result. Thanks to @svenpilz for reporting this. https://github.com/ceres-solver/ceres-solver/issues/296 Change-Id: Iebf2db7acecb2c95c9b1683b73cdc5faab78b02e
95 lines
3.4 KiB
C++
95 lines
3.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2017 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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#ifndef CERES_INTERNAL_FUNCTION_SAMPLE_H_
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#define CERES_INTERNAL_FUNCTION_SAMPLE_H_
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#include <string>
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#include "ceres/internal/eigen.h"
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namespace ceres {
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namespace internal {
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// FunctionSample is used by the line search routines to store and
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// communicate the value and (optionally) the gradient of the function
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// being minimized.
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//
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// Since line search as the name implies happens along a certain
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// line/direction. FunctionSample contains the information in two
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// ways. Information in the ambient space and information along the
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// direction of search.
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struct FunctionSample {
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FunctionSample();
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FunctionSample(double x, double value);
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FunctionSample(double x, double value, double gradient);
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std::string ToDebugString() const;
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// x is the location of the sample along the search direction.
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double x;
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// Let p be a point and d be the search direction then
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//
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// vector_x = p + x * d;
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Vector vector_x;
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// True if vector_x has been assigned a valid value.
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bool vector_x_is_valid;
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// value = f(vector_x)
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double value;
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// True of the evaluation was successful and value is a finite
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// number.
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bool value_is_valid;
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// vector_gradient = Df(vector_position);
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//
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// D is the derivative operator.
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Vector vector_gradient;
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// True if the vector gradient was evaluated and the evaluation was
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// successful (the value is a finite number).
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bool vector_gradient_is_valid;
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// gradient = d.transpose() * vector_gradient
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//
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// where d is the search direction.
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double gradient;
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// True if the evaluation of the gradient was sucessful and the
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// value is a finite number.
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bool gradient_is_valid;
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};
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_FUNCTION_SAMPLE_H_
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