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+// 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
+// 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: keir@google.com (Keir Mierle)
+//
+// Computation of the Jacobian matrix for vector-valued functions of multiple
+// variables, using automatic differentiation based on the implementation of
+// dual numbers in jet.h. Before reading the rest of this file, it is advisable
+// to read jet.h's header comment in detail.
+//
+// The helper wrapper AutoDifferentiate() computes the jacobian of
+// functors with templated operator() taking this form:
+//
+// struct F {
+// template<typename T>
+// bool operator()(const T *x, const T *y, ..., T *z) {
+// // Compute z[] based on x[], y[], ...
+// // return true if computation succeeded, false otherwise.
+// }
+// };
+//
+// All inputs and outputs may be vector-valued.
+//
+// To understand how jets are used to compute the jacobian, a
+// picture may help. Consider a vector-valued function, F, returning 3
+// dimensions and taking a vector-valued parameter of 4 dimensions:
+//
+// y x
+// [ * ] F [ * ]
+// [ * ] <--- [ * ]
+// [ * ] [ * ]
+// [ * ]
+//
+// Similar to the 2-parameter example for f described in jet.h, computing the
+// jacobian dy/dx is done by substituting a suitable jet object for x and all
+// intermediate steps of the computation of F. Since x is has 4 dimensions, use
+// a Jet<double, 4>.
+//
+// Before substituting a jet object for x, the dual components are set
+// appropriately for each dimension of x:
+//
+// y x
+// [ * | * * * * ] f [ * | 1 0 0 0 ] x0
+// [ * | * * * * ] <--- [ * | 0 1 0 0 ] x1
+// [ * | * * * * ] [ * | 0 0 1 0 ] x2
+// ---+--- [ * | 0 0 0 1 ] x3
+// | ^ ^ ^ ^
+// dy/dx | | | +----- infinitesimal for x3
+// | | +------- infinitesimal for x2
+// | +--------- infinitesimal for x1
+// +----------- infinitesimal for x0
+//
+// The reason to set the internal 4x4 submatrix to the identity is that we wish
+// to take the derivative of y separately with respect to each dimension of x.
+// Each column of the 4x4 identity is therefore for a single component of the
+// independent variable x.
+//
+// Then the jacobian of the mapping, dy/dx, is the 3x4 sub-matrix of the
+// extended y vector, indicated in the above diagram.
+//
+// Functors with multiple parameters
+// ---------------------------------
+// In practice, it is often convenient to use a function f of two or more
+// vector-valued parameters, for example, x[3] and z[6]. Unfortunately, the jet
+// framework is designed for a single-parameter vector-valued input. The wrapper
+// in this file addresses this issue adding support for functions with one or
+// more parameter vectors.
+//
+// To support multiple parameters, all the parameter vectors are concatenated
+// into one and treated as a single parameter vector, except that since the
+// functor expects different inputs, we need to construct the jets as if they
+// were part of a single parameter vector. The extended jets are passed
+// separately for each parameter.
+//
+// For example, consider a functor F taking two vector parameters, p[2] and
+// q[3], and producing an output y[4]:
+//
+// struct F {
+// template<typename T>
+// bool operator()(const T *p, const T *q, T *z) {
+// // ...
+// }
+// };
+//
+// In this case, the necessary jet type is Jet<double, 5>. Here is a
+// visualization of the jet objects in this case:
+//
+// Dual components for p ----+
+// |
+// -+-
+// y [ * | 1 0 | 0 0 0 ] --- p[0]
+// [ * | 0 1 | 0 0 0 ] --- p[1]
+// [ * | . . | + + + ] |
+// [ * | . . | + + + ] v
+// [ * | . . | + + + ] <--- F(p, q)
+// [ * | . . | + + + ] ^
+// ^^^ ^^^^^ |
+// dy/dp dy/dq [ * | 0 0 | 1 0 0 ] --- q[0]
+// [ * | 0 0 | 0 1 0 ] --- q[1]
+// [ * | 0 0 | 0 0 1 ] --- q[2]
+// --+--
+// |
+// Dual components for q --------------+
+//
+// where the 4x2 submatrix (marked with ".") and 4x3 submatrix (marked with "+"
+// of y in the above diagram are the derivatives of y with respect to p and q
+// respectively. This is how autodiff works for functors taking multiple vector
+// valued arguments (up to 6).
+//
+// Jacobian NULL pointers
+// ----------------------
+// In general, the functions below will accept NULL pointers for all or some of
+// the Jacobian parameters, meaning that those Jacobians will not be computed.
+
+#ifndef CERES_PUBLIC_INTERNAL_AUTODIFF_H_
+#define CERES_PUBLIC_INTERNAL_AUTODIFF_H_
+
+#include <stddef.h>
+
+#include <array>
+
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/fixed_array.h"
+#include "ceres/internal/parameter_dims.h"
+#include "ceres/internal/variadic_evaluate.h"
+#include "ceres/jet.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+
+// Extends src by a 1st order perturbation for every dimension and puts it in
+// dst. The size of src is N. Since this is also used for perturbations in
+// blocked arrays, offset is used to shift which part of the jet the
+// perturbation occurs. This is used to set up the extended x augmented by an
+// identity matrix. The JetT type should be a Jet type, and T should be a
+// numeric type (e.g. double). For example,
+//
+// 0 1 2 3 4 5 6 7 8
+// dst[0] [ * | . . | 1 0 0 | . . . ]
+// dst[1] [ * | . . | 0 1 0 | . . . ]
+// dst[2] [ * | . . | 0 0 1 | . . . ]
+//
+// is what would get put in dst if N was 3, offset was 3, and the jet type JetT
+// was 8-dimensional.
+template <int Offset, int N, typename T, typename JetT>
+inline void Make1stOrderPerturbation(const T* src, JetT* dst) {
+ DCHECK(src);
+ DCHECK(dst);
+ for (int j = 0; j < N; ++j) {
+ dst[j].a = src[j];
+ dst[j].v.setZero();
+ dst[j].v[Offset + j] = T(1.0);
+ }
+}
+
+// Calls Make1stOrderPerturbation for every parameter block.
+//
+// Example:
+// If one having three parameter blocks with dimensions (3, 2, 4), the call
+// Make1stOrderPerturbations<integer_sequence<3, 2, 4>::Apply(params, x);
+// will result in the following calls to Make1stOrderPerturbation:
+// Make1stOrderPerturbation<0, 3>(params[0], x + 0);
+// Make1stOrderPerturbation<3, 2>(params[1], x + 3);
+// Make1stOrderPerturbation<5, 4>(params[2], x + 5);
+template <typename Seq, int ParameterIdx = 0, int Offset = 0>
+struct Make1stOrderPerturbations;
+
+template <int N, int... Ns, int ParameterIdx, int Offset>
+struct Make1stOrderPerturbations<integer_sequence<int, N, Ns...>, ParameterIdx,
+ Offset> {
+ template <typename T, typename JetT>
+ static void Apply(T const* const* parameters, JetT* x) {
+ Make1stOrderPerturbation<Offset, N>(parameters[ParameterIdx], x + Offset);
+ Make1stOrderPerturbations<integer_sequence<int, Ns...>, ParameterIdx + 1,
+ Offset + N>::Apply(parameters, x);
+ }
+};
+
+// End of 'recursion'. Nothing more to do.
+template <int ParameterIdx, int Total>
+struct Make1stOrderPerturbations<integer_sequence<int>, ParameterIdx, Total> {
+ template <typename T, typename JetT>
+ static void Apply(T const* const* /* NOT USED */, JetT* /* NOT USED */) {}
+};
+
+// Takes the 0th order part of src, assumed to be a Jet type, and puts it in
+// dst. This is used to pick out the "vector" part of the extended y.
+template <typename JetT, typename T>
+inline void Take0thOrderPart(int M, const JetT* src, T dst) {
+ DCHECK(src);
+ for (int i = 0; i < M; ++i) {
+ dst[i] = src[i].a;
+ }
+}
+
+// Takes N 1st order parts, starting at index N0, and puts them in the M x N
+// matrix 'dst'. This is used to pick out the "matrix" parts of the extended y.
+template <int N0, int N, typename JetT, typename T>
+inline void Take1stOrderPart(const int M, const JetT* src, T* dst) {
+ DCHECK(src);
+ DCHECK(dst);
+ for (int i = 0; i < M; ++i) {
+ Eigen::Map<Eigen::Matrix<T, N, 1>>(dst + N * i, N) =
+ src[i].v.template segment<N>(N0);
+ }
+}
+
+// Calls Take1stOrderPart for every parameter block.
+//
+// Example:
+// If one having three parameter blocks with dimensions (3, 2, 4), the call
+// Take1stOrderParts<integer_sequence<3, 2, 4>::Apply(num_outputs,
+// output,
+// jacobians);
+// will result in the following calls to Take1stOrderPart:
+// if (jacobians[0]) {
+// Take1stOrderPart<0, 3>(num_outputs, output, jacobians[0]);
+// }
+// if (jacobians[1]) {
+// Take1stOrderPart<3, 2>(num_outputs, output, jacobians[1]);
+// }
+// if (jacobians[2]) {
+// Take1stOrderPart<5, 4>(num_outputs, output, jacobians[2]);
+// }
+template <typename Seq, int ParameterIdx = 0, int Offset = 0>
+struct Take1stOrderParts;
+
+template <int N, int... Ns, int ParameterIdx, int Offset>
+struct Take1stOrderParts<integer_sequence<int, N, Ns...>, ParameterIdx,
+ Offset> {
+ template <typename JetT, typename T>
+ static void Apply(int num_outputs, JetT* output, T** jacobians) {
+ if (jacobians[ParameterIdx]) {
+ Take1stOrderPart<Offset, N>(num_outputs, output, jacobians[ParameterIdx]);
+ }
+ Take1stOrderParts<integer_sequence<int, Ns...>, ParameterIdx + 1,
+ Offset + N>::Apply(num_outputs, output, jacobians);
+ }
+};
+
+// End of 'recursion'. Nothing more to do.
+template <int ParameterIdx, int Offset>
+struct Take1stOrderParts<integer_sequence<int>, ParameterIdx, Offset> {
+ template <typename T, typename JetT>
+ static void Apply(int /* NOT USED*/, JetT* /* NOT USED*/,
+ T** /* NOT USED */) {}
+};
+
+template <typename ParameterDims, typename Functor, typename T>
+inline bool AutoDifferentiate(const Functor& functor,
+ T const *const *parameters,
+ int num_outputs,
+ T* function_value,
+ T** jacobians) {
+ DCHECK_GT(num_outputs, 0);
+
+ typedef Jet<T, ParameterDims::kNumParameters> JetT;
+ FixedArray<JetT, (256 * 7) / sizeof(JetT)> x(ParameterDims::kNumParameters +
+ num_outputs);
+
+ using Parameters = typename ParameterDims::Parameters;
+
+ // These are the positions of the respective jets in the fixed array x.
+ std::array<JetT*, ParameterDims::kNumParameterBlocks> unpacked_parameters =
+ ParameterDims::GetUnpackedParameters(x.get());
+ JetT* output = x.get() + ParameterDims::kNumParameters;
+
+ // Invalidate the output Jets, so that we can detect if the user
+ // did not assign values to all of them.
+ for (int i = 0; i < num_outputs; ++i) {
+ output[i].a = kImpossibleValue;
+ output[i].v.setConstant(kImpossibleValue);
+ }
+
+ Make1stOrderPerturbations<Parameters>::Apply(parameters, x.get());
+
+ if (!VariadicEvaluate<ParameterDims>(functor, unpacked_parameters.data(),
+ output)) {
+ return false;
+ }
+
+ Take0thOrderPart(num_outputs, output, function_value);
+ Take1stOrderParts<Parameters>::Apply(num_outputs, output, jacobians);
+
+ return true;
+}
+
+} // namespace internal
+} // namespace ceres
+
+#endif // CERES_PUBLIC_INTERNAL_AUTODIFF_H_