DelayedSubsetSortedUnique.hpp

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#ifndef TATAMI_DELAYED_SUBSET_SORTED_UNIQUE_HPP
#define TATAMI_DELAYED_SUBSET_SORTED_UNIQUE_HPP
 
#include "../base/Matrix.hpp"
#include "utils.hpp"
 
#include <algorithm>
#include <memory>
 
namespace tatami {
 
namespace DelayedSubsetSortedUnique_internal {
 
template<typename Index_, class SubsetStorage_>
VectorPtr<Index_> create(const SubsetStorage_& subset) {
    return std::make_shared<std::vector<Index_> >(subset.begin(), subset.end());
}
 
template<typename Index_, class SubsetStorage_>
VectorPtr<Index_> create(const SubsetStorage_& subset, Index_ block_start, Index_ block_length) {
    auto pistart = subset.begin() + block_start;
    return std::make_shared<std::vector<Index_> >(pistart, pistart + block_length);
}
 
template<typename Index_, class SubsetStorage_>
VectorPtr<Index_> create(const SubsetStorage_& subset, const VectorPtr<Index_>& indices_ptr) {
    auto rawptr = std::make_shared<std::vector<Index_> >();
    VectorPtr<Index_> outptr(rawptr);
    auto& output = *rawptr;
 
    const auto& input = *indices_ptr;
    output.reserve(input.size());
    for (auto i : input) {
        output.push_back(subset[i]);
    }
 
    return outptr;
}
 
template<bool oracle_, typename Value_, typename Index_, class SubsetStorage_>
std::unique_ptr<DenseExtractor<oracle_, Value_, Index_> > create_parallel_dense(
    const Matrix<Value_, Index_>* matrix,
    const SubsetStorage_& subset, 
    bool row, 
    MaybeOracle<oracle_, Index_> oracle, 
    const Options& opt) 
{
    return new_extractor<false, oracle_>(matrix, row, std::move(oracle), create<Index_>(subset), opt);
}
 
template<bool oracle_, typename Value_, typename Index_, class SubsetStorage_>
std::unique_ptr<DenseExtractor<oracle_, Value_, Index_> > create_parallel_dense(
    const Matrix<Value_, Index_>* matrix,
    const SubsetStorage_& subset,
    bool row,
    MaybeOracle<oracle_, Index_> oracle,
    Index_ block_start,
    Index_ block_length,
    const Options& opt)
{
    return new_extractor<false, oracle_>(matrix, row, std::move(oracle), create<Index_>(subset, block_start, block_length), opt);
}
 
template<bool oracle_, typename Value_, typename Index_, class SubsetStorage_>
std::unique_ptr<DenseExtractor<oracle_, Value_, Index_> > create_parallel_dense(
    const Matrix<Value_, Index_>* matrix,
    const SubsetStorage_& subset,
    bool row,
    MaybeOracle<oracle_, Index_> oracle,
    VectorPtr<Index_> indices_ptr,
    const Options& opt) 
{
    return new_extractor<false, oracle_>(matrix, row, std::move(oracle), create<Index_>(subset, indices_ptr), opt);
}
 
template<bool oracle_, typename Value_, typename Index_>
class ParallelSparse : public SparseExtractor<oracle_, Value_, Index_> {
public:
    template<class SubsetStorage_>
    ParallelSparse(
        const Matrix<Value_, Index_>* matrix,
        const SubsetStorage_& subset,
        const std::vector<Index_>& remap,
        bool row,
        MaybeOracle<oracle_, Index_> oracle, 
        const Options& opt
    ) : 
        my_ext(new_extractor<true, oracle_>(matrix, row, std::move(oracle), create<Index_>(subset), opt)),
        my_remapping(remap)
    {}
 
    template<class SubsetStorage_>
    ParallelSparse(
        const Matrix<Value_, Index_>* matrix,
        const SubsetStorage_& subset,
        const std::vector<Index_>& remap,
        bool row, MaybeOracle<oracle_, Index_> oracle,
        Index_ block_start, 
        Index_ block_length, 
        const Options& opt
    ) : 
        my_ext(new_extractor<true, oracle_>(matrix, row, std::move(oracle), create<Index_>(subset, block_start, block_length), opt)),
        my_remapping(remap)
    {}
 
    template<class SubsetStorage_>
    ParallelSparse(
        const Matrix<Value_, Index_>* matrix,
        const SubsetStorage_& subset,
        const std::vector<Index_>& remap,
        bool row,
        MaybeOracle<oracle_, Index_> oracle,
        VectorPtr<Index_> indices_ptr,
        const Options& opt
    ) : 
        my_ext(new_extractor<true, oracle_>(matrix, row, std::move(oracle), create<Index_>(subset, indices_ptr), opt)),
        my_remapping(remap)
    {}
 
public:
    SparseRange<Value_, Index_> fetch(Index_ i, Value_* value_buffer, Index_* index_buffer) {
        auto out = my_ext->fetch(i, value_buffer, index_buffer);
        if (out.index) {
            for (Index_ i = 0; i < out.number; ++i) {
                index_buffer[i] = my_remapping[out.index[i]];
            }
            out.index = index_buffer;
        }
        return out;
    }
 
private:
    std::unique_ptr<SparseExtractor<oracle_, Value_, Index_> > my_ext;
    const std::vector<Index_>& my_remapping;
};
 
}
template<typename Value_, typename Index_, class SubsetStorage_>
class DelayedSubsetSortedUnique : public Matrix<Value_, Index_> {
public:
    DelayedSubsetSortedUnique(std::shared_ptr<const Matrix<Value_, Index_> > matrix, SubsetStorage_ subset, bool by_row, bool check = true) :
        my_matrix(std::move(matrix)), my_subset(std::move(subset)), my_by_row(by_row)
    {
        if (check) {
            for (Index_ i = 1, end = my_subset.size(); i < end; ++i) {
                if (my_subset[i] <= my_subset[i-1]) {
                    throw std::runtime_error("subset should be unique and sorted");
                }
            }
        }
 
        Index_ mapping_dim = my_by_row ? my_matrix->nrow() : my_matrix->ncol();
        my_mapping_single.resize(mapping_dim);
        for (Index_ i = 0, end = my_subset.size(); i < end; ++i) {
            my_mapping_single[my_subset[i]] = i;
        }
    }
 
private:
    std::shared_ptr<const Matrix<Value_, Index_> > my_matrix;
    SubsetStorage_ my_subset;
    bool my_by_row;
    std::vector<Index_> my_mapping_single;
 
public:
    Index_ nrow() const {
        if (my_by_row) {
            return my_subset.size();
        } else {
            return my_matrix->nrow();
        }
    }
 
    Index_ ncol() const {
        if (my_by_row) {
            return my_matrix->ncol();
        } else {
            return my_subset.size();
        }
    }
 
    bool is_sparse() const {
        return my_matrix->is_sparse();
    }
 
    double is_sparse_proportion() const {
        return my_matrix->is_sparse_proportion();
    }
 
    bool prefer_rows() const {
        return my_matrix->prefer_rows();
    }
 
    double prefer_rows_proportion() const {
        return my_matrix->prefer_rows_proportion();
    }
 
    bool uses_oracle(bool row) const {
        return my_matrix->uses_oracle(row);
    }
 
    using Matrix<Value_, Index_>::dense;
 
    using Matrix<Value_, Index_>::sparse;
 
    /********************
     *** Myopic dense ***
     ********************/
private:
    template<typename ... Args_>
    std::unique_ptr<MyopicDenseExtractor<Value_, Index_> > populate_myopic_dense(bool row, Args_&& ... args) const {
        if (row == my_by_row) {
            return std::make_unique<subset_utils::MyopicPerpendicularDense<Value_, Index_, SubsetStorage_> >(my_matrix.get(), my_subset, row, std::forward<Args_>(args)...); 
        } else {
            return DelayedSubsetSortedUnique_internal::create_parallel_dense<false>(my_matrix.get(), my_subset, row, false, std::forward<Args_>(args)...);
        }
    }
 
public:
    std::unique_ptr<MyopicDenseExtractor<Value_, Index_> > dense(bool row, const Options& opt) const {
        return populate_myopic_dense(row, opt);
    }
 
    std::unique_ptr<MyopicDenseExtractor<Value_, Index_> > dense(bool row, Index_ block_start, Index_ block_length, const Options& opt) const {
        return populate_myopic_dense(row, block_start, block_length, opt);
    }
 
    std::unique_ptr<MyopicDenseExtractor<Value_, Index_> > dense(bool row, VectorPtr<Index_> indices_ptr, const Options& opt) const {
        return populate_myopic_dense(row, std::move(indices_ptr), opt);
    }
 
    /*********************
     *** Myopic sparse ***
     *********************/
private:
    template<typename ... Args_>
    std::unique_ptr<MyopicSparseExtractor<Value_, Index_> > populate_myopic_sparse(bool row, Args_&& ... args) const {
        if (row == my_by_row) {
            return std::make_unique<subset_utils::MyopicPerpendicularSparse<Value_, Index_, SubsetStorage_> >(my_matrix.get(), my_subset, row, std::forward<Args_>(args)...); 
        } else {
            return std::make_unique<DelayedSubsetSortedUnique_internal::ParallelSparse<false, Value_, Index_> >(my_matrix.get(), my_subset, my_mapping_single, row, false, std::forward<Args_>(args)...);
        }
    }
 
public:
    std::unique_ptr<MyopicSparseExtractor<Value_, Index_> > sparse(bool row, const Options& opt) const {
        return populate_myopic_sparse(row, opt);
    }
 
    std::unique_ptr<MyopicSparseExtractor<Value_, Index_> > sparse(bool row, Index_ block_start, Index_ block_length, const Options& opt) const {
        return populate_myopic_sparse(row, block_start, block_length, opt);
    }
 
    std::unique_ptr<MyopicSparseExtractor<Value_, Index_> > sparse(bool row, VectorPtr<Index_> indices_ptr, const Options& opt) const {
        return populate_myopic_sparse(row, std::move(indices_ptr), opt);
    }
 
    /**********************
     *** Oracular dense ***
     **********************/
private:
    template<typename ... Args_>
    std::unique_ptr<OracularDenseExtractor<Value_, Index_> > populate_oracular_dense(bool row, std::shared_ptr<const Oracle<Index_> > oracle, Args_&& ... args) const {
        if (row == my_by_row) {
            return std::make_unique<subset_utils::OracularPerpendicularDense<Value_, Index_> >(my_matrix.get(), my_subset, row, std::move(oracle), std::forward<Args_>(args)...); 
        } else {
            return DelayedSubsetSortedUnique_internal::create_parallel_dense<true>(my_matrix.get(), my_subset, row, std::move(oracle), std::forward<Args_>(args)...);
        }
    }
 
public:
    std::unique_ptr<OracularDenseExtractor<Value_, Index_> > dense(bool row, std::shared_ptr<const Oracle<Index_> > oracle, const Options& opt) const {
        return populate_oracular_dense(row, std::move(oracle), opt);
    }
 
    std::unique_ptr<OracularDenseExtractor<Value_, Index_> > dense(bool row, std::shared_ptr<const Oracle<Index_> > oracle, Index_ block_start, Index_ block_length, const Options& opt) const {
        return populate_oracular_dense(row, std::move(oracle), block_start, block_length, opt);
    }
 
    std::unique_ptr<OracularDenseExtractor<Value_, Index_> > dense(bool row, std::shared_ptr<const Oracle<Index_> > oracle, VectorPtr<Index_> indices_ptr, const Options& opt) const {
        return populate_oracular_dense(row, std::move(oracle), std::move(indices_ptr), opt);
    }
 
    /***********************
     *** Oracular sparse ***
     ***********************/
private:
    template<typename ... Args_>
    std::unique_ptr<OracularSparseExtractor<Value_, Index_> > populate_oracular_sparse(bool row, std::shared_ptr<const Oracle<Index_> > oracle, Args_&& ... args) const {
        if (row == my_by_row) {
            return std::make_unique<subset_utils::OracularPerpendicularSparse<Value_, Index_> >(my_matrix.get(), my_subset, row, std::move(oracle), std::forward<Args_>(args)...); 
        } else {
            return std::make_unique<DelayedSubsetSortedUnique_internal::ParallelSparse<true, Value_, Index_> >(my_matrix.get(), my_subset, my_mapping_single, row, std::move(oracle), std::forward<Args_>(args)...);
        }
    }
 
public:
    std::unique_ptr<OracularSparseExtractor<Value_, Index_> > sparse(bool row, std::shared_ptr<const Oracle<Index_> > oracle, const Options& opt) const {
        return populate_oracular_sparse(row, std::move(oracle), opt);
    }
 
    std::unique_ptr<OracularSparseExtractor<Value_, Index_> > sparse(bool row, std::shared_ptr<const Oracle<Index_> > oracle, Index_ block_start, Index_ block_length, const Options& opt) const {
        return populate_oracular_sparse(row, std::move(oracle), block_start, block_length, opt);
    }
 
    std::unique_ptr<OracularSparseExtractor<Value_, Index_> > sparse(bool row, std::shared_ptr<const Oracle<Index_> > oracle, VectorPtr<Index_> indices_ptr, const Options& opt) const {
        return populate_oracular_sparse(row, std::move(oracle), std::move(indices_ptr), opt);
    }
};
 
}
 
#endif