/usr/include/ceres/autodiff_local_parameterization.h is in libceres-dev 1.11.0~dfsg0-2.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 | // Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2015 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
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sergey.vfx@gmail.com (Sergey Sharybin)
// mierle@gmail.com (Keir Mierle)
// sameeragarwal@google.com (Sameer Agarwal)
#ifndef CERES_PUBLIC_AUTODIFF_LOCAL_PARAMETERIZATION_H_
#define CERES_PUBLIC_AUTODIFF_LOCAL_PARAMETERIZATION_H_
#include "ceres/local_parameterization.h"
#include "ceres/internal/autodiff.h"
#include "ceres/internal/scoped_ptr.h"
namespace ceres {
// Create local parameterization with Jacobians computed via automatic
// differentiation. For more information on local parameterizations,
// see include/ceres/local_parameterization.h
//
// To get an auto differentiated local parameterization, you must define
// a class with a templated operator() (a functor) that computes
//
// x_plus_delta = Plus(x, delta);
//
// the template parameter T. The autodiff framework substitutes appropriate
// "Jet" objects for T in order to compute the derivative when necessary, but
// this is hidden, and you should write the function as if T were a scalar type
// (e.g. a double-precision floating point number).
//
// The function must write the computed value in the last argument (the only
// non-const one) and return true to indicate success.
//
// For example, Quaternions have a three dimensional local
// parameterization. It's plus operation can be implemented as (taken
// from internal/ceres/auto_diff_local_parameterization_test.cc)
//
// struct QuaternionPlus {
// template<typename T>
// bool operator()(const T* x, const T* delta, T* x_plus_delta) const {
// const T squared_norm_delta =
// delta[0] * delta[0] + delta[1] * delta[1] + delta[2] * delta[2];
//
// T q_delta[4];
// if (squared_norm_delta > T(0.0)) {
// T norm_delta = sqrt(squared_norm_delta);
// const T sin_delta_by_delta = sin(norm_delta) / norm_delta;
// q_delta[0] = cos(norm_delta);
// q_delta[1] = sin_delta_by_delta * delta[0];
// q_delta[2] = sin_delta_by_delta * delta[1];
// q_delta[3] = sin_delta_by_delta * delta[2];
// } else {
// // We do not just use q_delta = [1,0,0,0] here because that is a
// // constant and when used for automatic differentiation will
// // lead to a zero derivative. Instead we take a first order
// // approximation and evaluate it at zero.
// q_delta[0] = T(1.0);
// q_delta[1] = delta[0];
// q_delta[2] = delta[1];
// q_delta[3] = delta[2];
// }
//
// QuaternionProduct(q_delta, x, x_plus_delta);
// return true;
// }
// };
//
// Then given this struct, the auto differentiated local
// parameterization can now be constructed as
//
// LocalParameterization* local_parameterization =
// new AutoDiffLocalParameterization<QuaternionPlus, 4, 3>;
// | |
// Global Size ---------------+ |
// Local Size -------------------+
//
// WARNING: Since the functor will get instantiated with different types for
// T, you must to convert from other numeric types to T before mixing
// computations with other variables of type T. In the example above, this is
// seen where instead of using k_ directly, k_ is wrapped with T(k_).
template <typename Functor, int kGlobalSize, int kLocalSize>
class AutoDiffLocalParameterization : public LocalParameterization {
public:
AutoDiffLocalParameterization() :
functor_(new Functor()) {}
// Takes ownership of functor.
explicit AutoDiffLocalParameterization(Functor* functor) :
functor_(functor) {}
virtual ~AutoDiffLocalParameterization() {}
virtual bool Plus(const double* x,
const double* delta,
double* x_plus_delta) const {
return (*functor_)(x, delta, x_plus_delta);
}
virtual bool ComputeJacobian(const double* x, double* jacobian) const {
double zero_delta[kLocalSize];
for (int i = 0; i < kLocalSize; ++i) {
zero_delta[i] = 0.0;
}
double x_plus_delta[kGlobalSize];
for (int i = 0; i < kGlobalSize; ++i) {
x_plus_delta[i] = 0.0;
}
const double* parameter_ptrs[2] = {x, zero_delta};
double* jacobian_ptrs[2] = { NULL, jacobian };
return internal::AutoDiff<Functor, double, kGlobalSize, kLocalSize>
::Differentiate(*functor_,
parameter_ptrs,
kGlobalSize,
x_plus_delta,
jacobian_ptrs);
}
virtual int GlobalSize() const { return kGlobalSize; }
virtual int LocalSize() const { return kLocalSize; }
private:
internal::scoped_ptr<Functor> functor_;
};
} // namespace ceres
#endif // CERES_PUBLIC_AUTODIFF_LOCAL_PARAMETERIZATION_H_
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