make_jacobian.h

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/*
 * Copyright 2021 MusicScience37 (Kenta Kabashima)
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
#pragma once
 
#include <type_traits>  // IWYU pragma: keep
 
#include <Eigen/Core>
 
#include "num_collect/base/concepts/dense_vector.h"
#include "num_collect/base/exception.h"
#include "num_collect/base/index_type.h"
#include "num_collect/base/precondition.h"
#include "num_collect/logging/logging_macros.h"
#include "num_collect/util/assert.h"
 
namespace num_collect::auto_diff::forward {
 
namespace impl {
 
template <base::concepts::dense_vector VectorType>
class make_jacobian_functor {
public:
    using variable_vector_type = VectorType;
 
    using variable_type = typename variable_vector_type::Scalar;
 
    using value_type = typename variable_type::value_type;
 
    using diff_type = typename variable_type::diff_type;
 
    static_assert(std::is_same_v<typename diff_type::Scalar, value_type>);
 
    using result_type = Eigen::Matrix<value_type,
        variable_vector_type::RowsAtCompileTime, diff_type::RowsAtCompileTime,
        Eigen::ColMajor, variable_vector_type::MaxRowsAtCompileTime,
        diff_type::MaxRowsAtCompileTime>;
 
    explicit make_jacobian_functor(const variable_vector_type& vector)
        : vector_(vector) {}
 
    [[nodiscard]] auto operator()(index_type row, index_type col) const
        -> value_type {
        return vector_(row).diff()(col);
    }
 
private:
    const variable_vector_type& vector_;
};
 
}  // namespace impl
 
template <base::concepts::dense_vector VectorType>
[[nodiscard]] inline auto make_jacobian(
    const Eigen::MatrixBase<VectorType>& vector)
    -> Eigen::CwiseNullaryOp<impl::make_jacobian_functor<VectorType>,
        typename impl::make_jacobian_functor<VectorType>::result_type> {
    using result_type =
        typename impl::make_jacobian_functor<VectorType>::result_type;
 
    NUM_COLLECT_PRECONDITION(vector.cols() == 1,
        "differentiate function requires a vector as the argument.");
    NUM_COLLECT_PRECONDITION(vector.rows() >= 2,
        "differentiate function requires a vector with at least two "
        "elements.");
 
    for (index_type i = 0; i < vector.rows(); ++i) {
        NUM_COLLECT_ASSERT(vector(i).diff().cols() == 1);
    }
    const auto result_rows = vector.rows();
    const auto result_cols = vector(0).diff().rows();
 
    return result_type::NullaryExpr(result_rows, result_cols,
        impl::make_jacobian_functor<VectorType>(vector.derived()));
}
 
}  // namespace num_collect::auto_diff::forward