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ceres-solver/include/ceres/conditioned_cost_function.h
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2019 Google Inc. All rights reserved.
// http://ceres-solver.org/
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//
// 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: wjr@google.com (William Rucklidge)
//
// This file contains a cost function that can apply a transformation to
// each residual value before they are square-summed.
#ifndef CERES_PUBLIC_CONDITIONED_COST_FUNCTION_H_
#define CERES_PUBLIC_CONDITIONED_COST_FUNCTION_H_
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#include <memory>
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#include <vector>
#include "ceres/cost_function.h"
#include "ceres/internal/disable_warnings.h"
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#include "ceres/types.h"
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namespace ceres {
// This class allows you to apply different conditioning to the residual
// values of a wrapped cost function. An example where this is useful is
// where you have an existing cost function that produces N values, but you
// want the total cost to be something other than just the sum of these
// squared values - maybe you want to apply a different scaling to some
// values, to change their contribution to the cost.
//
// Usage:
//
// // my_cost_function produces N residuals
// CostFunction* my_cost_function = ...
// CHECK_EQ(N, my_cost_function->num_residuals());
// vector<CostFunction*> conditioners;
//
// // Make N 1x1 cost functions (1 parameter, 1 residual)
// CostFunction* f_1 = ...
// conditioners.push_back(f_1);
// ...
// CostFunction* f_N = ...
// conditioners.push_back(f_N);
// ConditionedCostFunction* ccf =
// new ConditionedCostFunction(my_cost_function, conditioners);
//
// Now ccf's residual i (i=0..N-1) will be passed though the i'th conditioner.
//
// ccf_residual[i] = f_i(my_cost_function_residual[i])
//
// and the Jacobian will be affected appropriately.
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class CERES_EXPORT ConditionedCostFunction : public CostFunction {
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public:
// Builds a cost function based on a wrapped cost function, and a
// per-residual conditioner. Takes ownership of all of the wrapped cost
// functions, or not, depending on the ownership parameter. Conditioners
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// may be nullptr, in which case the corresponding residual is not modified.
//
// The conditioners can repeat.
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ConditionedCostFunction(CostFunction* wrapped_cost_function,
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const std::vector<CostFunction*>& conditioners,
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Ownership ownership);
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~ConditionedCostFunction() override;
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bool Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const override;
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private:
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std::unique_ptr<CostFunction> wrapped_cost_function_;
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std::vector<CostFunction*> conditioners_;
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Ownership ownership_;
};
} // namespace ceres
#include "ceres/internal/reenable_warnings.h"
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#endif // CERES_PUBLIC_CONDITIONED_COST_FUNCTION_H_