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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2019 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
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//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/autodiff_first_order_function.h"
#include <memory>
#include "ceres/array_utils.h"
#include "ceres/first_order_function.h"
#include "gtest/gtest.h"
namespace ceres {
namespace internal {
class QuadraticCostFunctor {
public:
explicit QuadraticCostFunctor(double a) : a_(a) {}
template <typename T>
bool operator()(const T* const x, T* cost) const {
cost[0] = x[0] * x[1] + x[2] * x[3] - T(a_);
return true;
}
private:
double a_;
};
TEST(AutoDiffFirstOrderFunction, BilinearDifferentiationTest) {
std::unique_ptr<FirstOrderFunction> function(
new AutoDiffFirstOrderFunction<QuadraticCostFunctor, 4>(
new QuadraticCostFunctor(1.0)));
double parameters[4] = {1.0, 2.0, 3.0, 4.0};
double gradient[4];
double cost;
function->Evaluate(parameters, &cost, nullptr);
EXPECT_EQ(cost, 13.0);
cost = -1.0;
function->Evaluate(parameters, &cost, gradient);
EXPECT_EQ(cost, 13.0);
EXPECT_EQ(gradient[0], parameters[1]);
EXPECT_EQ(gradient[1], parameters[0]);
EXPECT_EQ(gradient[2], parameters[3]);
EXPECT_EQ(gradient[3], parameters[2]);
}
} // namespace internal
} // namespace ceres