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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 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.
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/normal_prior.h"
#include <cstddef>
#include <utility>
#include <vector>
#include "absl/log/check.h"
#include "ceres/internal/eigen.h"
#include "ceres/types.h"
namespace ceres {
NormalPrior::NormalPrior(const Matrix& A, Vector b) : A_(A), b_(std::move(b)) {
CHECK_GT(b_.rows(), 0);
CHECK_GT(A_.rows(), 0);
CHECK_EQ(b_.rows(), A.cols());
set_num_residuals(A_.rows());
mutable_parameter_block_sizes()->push_back(b_.rows());
}
bool NormalPrior::Evaluate(double const* const* parameters,
double* residuals,
double** jacobians) const {
ConstVectorRef p(parameters[0], parameter_block_sizes()[0]);
VectorRef r(residuals, num_residuals());
// The following line should read
// r = A_ * (p - b_);
// The extra eval is to get around a bug in the Eigen library.
r = A_ * (p - b_).eval();
if ((jacobians != nullptr) && (jacobians[0] != nullptr)) {
MatrixRef(jacobians[0], num_residuals(), parameter_block_sizes()[0]) = A_;
}
return true;
}
} // namespace ceres