sparse_vector template class: How do I clean it up?

I'm not sure if this is a good question or not — please close it if not.

I set out to write (using boost::coordinate_vector as a starting point) a sparse_vector template class that efficiently implements a vector-like interface, but is sparse. It implements all the usual vector operations and a fast sparse iterator that iterates over the set elements. It also has a fast version of rotate. I need this class because I have a write-once-read-many use case, and I use many of these sparse_vectors.

I have no experience writing template classes, so I know that there are things that I could be doing better. How can I improve this class?

// sparse_vector is a sparse version of std::vector.  It stores index-value pairs, and a size, which
// represents the size of the sparse_vector.

#include <algorithm>
#include <ostream>
#include <iostream>
#include <vector>
#include <boost/iterator.hpp>
#include <boost/iterator/iterator_adaptor.hpp>
#include <boost/iterator/iterator_facade.hpp>
#include <boost/iterator/reverse_iterator.hpp>
#include <boost/optional.hpp>
#include <glog/logging.h>

template<typename T>
class sparse_vector {
public:
    typedef T value_type;
    typedef T* pointer;
    typedef T& reference;
    typedef const T& const_reference;
    typedef size_t size_type;
private:
    struct ElementType {
        ElementType(size_type i, T const& t): index(i), value(t) {}
        ElementType(size_type i, T&& t): index(i), value(move(t)) {}
        ElementType(size_type i): index(i) {}  // allows lower_bound to work
        ElementType(ElementType const&) = default;
        size_type index;
        value_type value;
    };
    typedef std::vector<ElementType> array_type;
public:
    typedef typename array_type::difference_type difference_type;

private:
    typedef const T* const_pointer;
    typedef sparse_vector<T> self_type;
    typedef typename array_type::const_iterator const_subiterator_type;
    typedef typename array_type::iterator subiterator_type;

    struct IndexCompare {
        bool operator()(ElementType const& a, ElementType const& b) { return a.index < b.index; }
    };

public:
    // Construction and destruction
    inline sparse_vector(): size_(0), sorted_filled_(0), data_() {
            storage_invariants(); }
    explicit inline sparse_vector(size_type size): size_(size), sorted_filled_(0), data_() {
            storage_invariants(); }
    inline sparse_vector(const sparse_vector<T> &v):
        size_(v.size_), sorted_filled_(v.sorted_filled_), data_(v.data_) {
            storage_invariants(); }
    inline sparse_vector(sparse_vector<T>&& v):
        size_(v.size_), sorted_filled_(v.sorted_filled_), data_(move(v.data_)) {
            storage_invariants(); }
    sparse_vector(const optional<T> &o): size_(1), sorted_filled_(0) {
            if (o) {
                append_element(0, *o);
                sorted_filled_ = 1;
            }
            storage_invariants();
        }
    sparse_vector(const std::vector<T> &v):
        size_(v.size()), sorted_filled_(0) {
            data_.reserve(v.size());
            for (auto it = v.begin(); it != v.end(); ++it)
                append_element(it - v.begin(), *it);
            sorted_filled_ = v.size();
            storage_invariants();
        }
    sparse_vector(const sparse_vector<optional<T>> &sv):
        size_(sv.size()), sorted_filled_(0) {
        开发者_高级运维    for (auto it = sv.sparse_begin(); it != sv.sparse_end(); ++it)
                if (*it)
                    append_element(it.index(), **it);
            sorted_filled_ = data_.size();
            storage_invariants();
        }
    sparse_vector(size_type size, vector<pair<size_type, T>> init_list):
        size_(size), sorted_filled_(0) {
            for (auto it = init_list.begin(); it != init_list.end(); ++it)
                append_element(it->first, it->second);
            // require that the list be sorted?
            // sorted_filled_ = data_.size();
            storage_invariants();
        }
    /*template<class AE>
        inline sparse_vector(const sparse_vector<AE> &ae):
            size_(ae().size()), sorted_filled_(ae.nnz()), data_() {
                storage_invariants();
                for (auto it = ae.sparse_begin(); it != ae.sparse_end(); ++it) {
                    (*this)[it.index()] = static_cast<T>(*it);
                }
            }*/

    // Conversion operators
    // Copy sparse_vector to a vector filling in uninitialized elements with T()
    operator std::vector<T>() {
        std::vector<T> retval(size_);
        for (auto it = data_.begin(); it != data_.end(); ++it)
            retval[it.index()] = *it;
        return retval; 
    }
    // Copy sparse_vector to a vector filling in uninitialized elements with a default value.
    void CopyToVector(std::vector<T>* v, T const& default_value = T()) {
        size_type last_index = 0;
        for (auto it = sparse_begin(); it != sparse_end(); ++it) {
            for (size_type i = last_index; i < it.index(); ++i) {
                (*v)[i] = default_value;
            }
            (*v)[it.index()] = *it;
            last_index = it.index() + 1;
        }
    }

    // Accessors
    inline size_type size() const {
        return size_;
    }
    inline size_type nnz_capacity() const {
        return data_.capacity();
    }
    inline size_type nnz() const {
        return data_.size();
    }

    // Resizing
    inline void resize(size_type size, bool preserve = true) {
        if (preserve) {
            sort();    // remove duplicate elements.
            subiterator_type it(lower_bound(data_.begin(), data_.end(), size, IndexCompare()));
            data_.erase(it, data_.end());
        } else {
            data_.clear();
        }
        size_ = size;
        sorted_filled_ = nnz();
        storage_invariants();
    }

    // Reserving
    inline void reserve(size_type non_zeros, bool preserve = true) {
        if (preserve)
            sort();    // remove duplicate elements.
        else
            data_.clear();
        data_.reserve(non_zeros);
        sorted_filled_ = nnz();
        storage_invariants();
    }

    // Element support
    // find_element returns a pointer to element i or NULL -- it never creates an element
    inline pointer find_element(size_type i) {
        return const_cast<pointer> (const_cast<const self_type&>(*this).find_element(i)); }
    inline const_pointer find_element(size_type i) const {
        sort();
        const_subiterator_type it(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
        if (it == data_.end() || it->index != i)
            return NULL;
        return &it->value;
    }
    // find_element_optional returns a boost::optional<T>
    inline boost::optional<value_type> find_element_optional(size_type i) const {
        CHECK_LT(i, size_);
        sort();
        const_subiterator_type it(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
        if (it == data_.end() || it->index != i)
            return boost::optional<value_type>();
        return boost::optional<value_type>(it->value);
    }

    // Element access
    // operator[] returns a reference to element i -- the const version returns a reference to
    // a zero_ element if it doesn't exist; the non-const version creates it in that case.
    inline const_reference operator[] (size_type i) const {
        CHECK_LT(i, size_);
        sort();
        const_subiterator_type it(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
        if (it == data_.end() || it->index != i)
            return zero_;
        return it->value;
    }
    inline reference operator[] (size_type i) {
        CHECK_LT(i, size_);
        sort();
        subiterator_type it(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
        if (it == data_.end() || it->index != i)
            return insert_element(i, value_type/*zero*/());
        else
            return it->value;
    }

    // Element assignment
    inline void append_element(size_type i, const_reference t) {
        data_.emplace_back(i, t);
        storage_invariants();
    }
    inline void append_element(size_type i, T&& t) {
        data_.emplace_back(i, move(t));
        storage_invariants();
    }
    inline void sorted_append_element(size_type i, const_reference t) {
        // must maintain sort order
        CHECK(sorted());
        if (data_.size() > 0)
            CHECK_LT(data_.back().index, i);
        data_.emplace_back(i, t);
        sorted_filled_ = data_.size();
        storage_invariants();
    }
    /* This function is probably not useful.
     * inline void sparse_pop_back() {
        // ISSUE invariants could be simpilfied if sorted required as precondition
        CHECK_GT(data_.size(), 0);
        data_.pop_back();
        sorted_filled_ = (std::min)(sorted_filled_, data_.size());
        storage_invariants();
    }*/
    inline reference insert_element(size_type i, const_reference t) {
        DCHECK(find_element(i) == NULL);  // duplicate element
        append_element(i, t);
        return data_.back().value;
    }

    // Element clearing
    // TODO(neil): consider replacing size_type functions with iterator functions
    // replaces elements in the range [i, i] with "zero" (by erasing them from the map)
    inline void clear_element(size_type i) {
        sort();
        subiterator_type it(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
        if (it == data_.end() || it->index != i)
            return;
        data_.erase(it);
        --sorted_filled_;
        storage_invariants();
    }
    // replaces elements in the range [first, last) with "zero" (by erasing them from the map)
    inline void clear_elements(size_type first, size_type last) {
        CHECK_LE(first, last);
        sort();
        subiterator_type it_first(lower_bound(data_.begin(), data_.end(), first, IndexCompare()));
        subiterator_type it_last(lower_bound(data_.begin(), data_.end(), last, IndexCompare()));
        sorted_filled_ -= it_last - it_first;
        data_.erase(it_first, it_last);
        storage_invariants();
    }

    // Zeroing
    inline void clear() { data_.clear(); sorted_filled_ = 0; storage_invariants(); }

    // Comparison
    inline bool operator==(const sparse_vector &v) const {
        if (this == &v)
            return true;
        if (size_ != v.size_)
            return false;
        auto it_this = sparse_begin();
        for (auto it = v.sparse_begin(); it != v.sparse_end(); ++it) {
            if (it_this == sparse_end()
                || it_this.index() != it.index()
                || *it_this != *it)
                return false;
            ++it_this;
        }
        return true;
    }

    // Assignment
    inline sparse_vector& operator=(const sparse_vector &v) {
        if (this != &v) {
            size_ = v.size_;
            sorted_filled_ = v.sorted_filled_;
            data_ = v.data_;
        }
        storage_invariants();
        return *this;
    }
    inline sparse_vector &assign_temporary(sparse_vector &v) {
        swap(v);
        return *this;
    }
    template<class AE>
        inline sparse_vector& operator=(const sparse_vector<AE> &ae) {
            self_type temporary(ae);
            return assign_temporary(temporary);
        }

    // Swapping
    inline void swap(sparse_vector &v) {
        if (this != &v) {
            std::swap(size_, v.size_);
            std::swap(sorted_filled_, v.sorted_filled_);
            data_.swap(v.data_);
        }
        storage_invariants();
    }
    inline friend void swap(sparse_vector &v1, sparse_vector &v2) { v1.swap(v2); }

    // Sorting and summation of duplicates
    inline bool sorted() const { return sorted_filled_ == data_.size(); }
    inline void sort() const {
        if (!sorted() && data_.size() > 0) {
            // sort new elements and merge
            std::sort(data_.begin() + sorted_filled_, data_.end(), IndexCompare());
            std::inplace_merge(data_.begin(), data_.begin() + sorted_filled_, data_.end(),
                               IndexCompare());

            // check for duplicates
            size_type filled = 0;
            for(size_type i = 1; i < data_.size(); ++i) {
                if (data_[filled].index != data_[i].index) {
                    ++filled;
                    if (filled != i) {
                        data_[filled] = data_[i];
                    }
                } else {
                    CHECK(false);  // duplicates
                    // value_data_[filled] += value_data_[i];
                }
            }
            ++filled;
            sorted_filled_ = filled;
            data_.erase(data_.begin() + filled, data_.end());
            storage_invariants();
        }
    }

    // Back element insertion and erasure
    inline void push_back(const_reference t) {
        CHECK(sorted());
        data_.emplace_back(size(), t);
        if (sorted_filled_ == data_.size())
            ++sorted_filled_;
        ++size_;
        storage_invariants();
    }
    inline void pop_back() {
        CHECK_GT(size_, 0);
        clear_element(size_ - 1);
        if (sorted_filled_ == size_)
            --sorted_filled_;
        --size_;
        storage_invariants();
    }

    // Iterator types
private:
    template<typename base_type, typename iterator_value_type>
        class sparse_iterator_private
            : public boost::iterator_adaptor<
              sparse_iterator_private<base_type, iterator_value_type>,  // Derived
              base_type,                                                // Base
              iterator_value_type,                                      // Value
              boost::random_access_traversal_tag                        // CategoryOrTraversal
              > {
        private:
            struct enabler {};  // a private type avoids misuse

        public:
            sparse_iterator_private()
                : sparse_iterator_private<base_type, iterator_value_type>::iterator_adaptor_() {}

            explicit sparse_iterator_private(base_type&& p)
                : sparse_iterator_private<base_type, iterator_value_type>::iterator_adaptor_(p) {}

            size_type index() const { return this->base()->index; }
            iterator_value_type& value() const { return this->base()->value; }

        private:
            friend class boost::iterator_core_access;

            iterator_value_type& dereference() const { return this->base()->value; }
        };

    template<typename container_type, typename iterator_value_type>
        class iterator_private
        : public boost::iterator_facade<
          iterator_private<container_type, iterator_value_type>,    // Derived
          iterator_value_type,                                      // Value
          boost::random_access_traversal_tag,                       // CategoryOrTraversal
          iterator_value_type&,                                     // Reference
          difference_type                                           // Difference
          > {
          private:
              struct enabler {};  // a private type avoids misuse

          public:
              iterator_private(): container_(NULL), index_(0) {}

              iterator_private(container_type* container, size_type index)
                  : container_(container), index_(index) {}

              iterator_private(iterator_private const& other)
                  : container_(other.container_), index_(other.index_) {}

              iterator_private& operator=(iterator_private const& other) {
                  container_ = other.container_;
                  index_ = other.index_;
              }

              container_type& container() const { return *container_; }
              size_type index() const { return index_; }
              iterator_value_type& value() const { return dereference(); }
              /* TODO(neil): how do you make this work?
                 template<typename U>
                 sparse_iterator_private<U> subsequent_sparse_iterator() {
                 return sparse_iterator_private<T>(lower_bound(container_.data_.begin(),
                 container_.data_.end(),
                 index_, IndexCompare()));
                 }
                 */

          private:
              friend class boost::iterator_core_access;
              iterator_value_type& dereference() const { return (*container_)[index_]; }
              bool equal(iterator_private<container_type, iterator_value_type> const& other) const {
                  return index_ == other.index_ && container_ == other.container_; }
              void increment() { ++index_; }
              void decrement() { --index_; }
              void advance(int n) { index_ += n; }
              difference_type distance_to(iterator_private<container_type,
                                          iterator_value_type> const& other) {
                  return index_ - other.index_; }

              container_type*       container_;
              size_type             index_;
          };

public:
    typedef sparse_iterator_private<typename array_type::iterator, value_type> sparse_iterator;
    typedef sparse_iterator_private<
        typename array_type::const_iterator, const value_type> const_sparse_iterator;
    typedef iterator_private<sparse_vector, value_type> iterator;
    typedef iterator_private<const sparse_vector, const value_type> const_iterator;
    typedef boost::reverse_iterator<sparse_iterator> reverse_sparse_iterator;
    typedef boost::reverse_iterator<const_sparse_iterator> const_reverse_sparse_iterator;
    typedef boost::reverse_iterator<iterator> reverse_iterator;
    typedef boost::reverse_iterator<const_iterator> const_reverse_iterator;

    // Element lookup
    // inline This function seems to be big. So we do not let the compiler inline it.    
    sparse_iterator sparse_find(size_type i) {
        sort();
        return sparse_iterator(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
    }
    // inline This function seems to be big. So we do not let the compiler inline it.    
    const_sparse_iterator sparse_find(size_type i) const {
        sort();
        return const_sparse_iterator(lower_bound(data_.begin(), data_.end(), i, IndexCompare()));
    }
    // the nth non-zero element
    const_sparse_iterator nth_nonzero(size_type i) const {
        CHECK_LE(data_.size(), i);
        sort();
        return const_sparse_iterator(data_.begin() + i);
    }

    // Forward iterators
    inline sparse_iterator sparse_begin() { return sparse_find(0); }
    inline sparse_iterator sparse_end() { return sparse_find(size_); }
    inline const_sparse_iterator sparse_begin() const { return sparse_find(0); }
    inline const_sparse_iterator sparse_end() const { return sparse_find(size_); }
    inline iterator begin() { return iterator(this, 0); }
    inline iterator end() { return iterator(this, size()); }
    inline const_iterator begin() const { return const_iterator(this, 0); }
    inline const_iterator end() const { return const_iterator(this, size()); }

    // Reverse iterators
    inline reverse_sparse_iterator sparse_rbegin() {
        return reverse_sparse_iterator(sparse_end()); }
    inline reverse_sparse_iterator sparse_rend() {
        return reverse_sparse_iterator(sparse_begin()); }
    inline const_reverse_sparse_iterator sparse_rbegin() const {
        return const_reverse_sparse_iterator(sparse_end()); }
    inline const_reverse_sparse_iterator sparse_rend() const {
        return const_reverse_sparse_iterator(sparse_begin()); }
    inline reverse_iterator rbegin() {
        return reverse_iterator(end()); }
    inline reverse_iterator rend() {
        return reverse_iterator(begin()); }
    inline const_reverse_iterator rbegin() const {
        return const_reverse_iterator(end()); }
    inline const_reverse_iterator rend() const {
        return const_reverse_iterator(begin()); }

    // Mutating algorithms
    // like vector::erase (erases the elements from the container and shrinks the container)
    inline void erase(iterator const& first, iterator const& last) {
        clear_elements(first.index(), last.index());
        CHECK(sorted());
        subiterator_type it_first(lower_bound(data_.begin(), data_.end(),
                                              first.index(), IndexCompare()));
        size_t n = last.index() - first.index();
        for (auto it = it_first; it != data_.end(); ++it)
            it->index -= n;
        size_ -= n;
    }

    // like vector::insert (insert elements into the container and causes the container to grow)
    inline void insert(iterator const& index, size_type n) {
        sort();
        subiterator_type it_first(lower_bound(data_.begin(), data_.end(),
                                              index.index(), IndexCompare()));
        for (auto it = it_first; it != data_.end(); ++it)
            it->index += n;
        size_ += n;
    }

    // Removes all "zero" elements
    void remove_zeros() {
        size_type filled = 0;
        for(size_type i = 0; i < data_.size(); ++i) {
            if (i == sorted_filled_) {
                // Once we've processed sorted_filled_ items, we know that whatever we've filled so
                // far is sorted.
                CHECK_LE(filled, sorted_filled_);
                // Since sorted_filled_ only shrinks here, and i only grows, we won't enter this
                // condition twice.
                sorted_filled_ = filled;
            }
            if (data_[i].value != value_type/*zero*/()) {
                if (filled != i) {
                    data_[filled] = data_[i];
                }
                ++filled;
            }
        }
        data_.erase(data_.begin() + filled, data_.end());
        storage_invariants();
    }

    void rotate(size_type first, size_type middle, size_type last) {
        CHECK_LT(first, middle);
        CHECK_LT(middle, last);
        sort();
        subiterator_type it_first(lower_bound(data_.begin(), data_.end(),
                                              first, IndexCompare()));
        subiterator_type it_middle(lower_bound(data_.begin(), data_.end(),
                                               middle, IndexCompare()));
        subiterator_type it_last(lower_bound(data_.begin(), data_.end(),
                                             last, IndexCompare()));

        for (auto it = it_first; it != it_middle; ++it)
            it->index += last - middle;
        for (auto it = it_middle; it != it_last; ++it)
            it->index -= middle - first;
        std::rotate(it_first, it_middle, it_last);
        // array remains sorted
    }

    sparse_vector<value_type> concatenate(sparse_vector<value_type> const& other) const {
        sparse_vector<value_type> retval(size() + other.size());
        for (auto it = sparse_begin(); it != sparse_end(); ++it) {
            retval[it.index()] = *it;
        }
        for (auto it = other.sparse_begin(); it != other.sparse_end(); ++it) {
            retval[it.index() + size()] = *it;
        }
        return retval;
    }

private:
    void storage_invariants() const {
        CHECK_LE(sorted_filled_, data_.size());
        if (sorted())
            CHECK_EQ(sorted_filled_, data_.size());
        else
            CHECK_LT(sorted_filled_, data_.size());
        if (!data_.empty())
            CHECK_LT(data_.back().index, size_);
        for (size_type i = 1; i < sorted_filled_; ++i)
            CHECK_GT(data_[i].index, data_[i - 1].index);
    }

    size_type                                   size_;
    mutable typename array_type::size_type      sorted_filled_; 
    mutable array_type                          data_;

    static const value_type                     zero_;
};

template<typename T>
const typename sparse_vector<T>::value_type sparse_vector<T>::zero_ = T();

template<typename T>
ostream& operator<<(ostream& os, const sparse_vector<T>& v) {
    os << "[" << v.size() << ": ";
    for (auto it = v.sparse_begin(); it != v.sparse_end(); ++it) {
        os << "(" << it.index() << ": " << it.value() << ") ";
    }
    return os << "]";
}

For someone with little experience writing class templates, you've created something fairly sophisticated. Unfortunately I can't do a in-depth analysis at the moment: it would take too much time giving the amount of code presented and the generality of the question. I can only briefly respond to an overview.

For a start, sorting mutable data on operator[] const and begin/end methods is kind of scary. This class won't be thread-safe even for concurrent read access. Dealing with multiple threads is probably beyond the scope of this class, but this behavior is very peculiar so it should probably be well-documented if the class is intended for very general-purpose use.

Another alternative is to require the client sort the vector explicitly and use linear access methods to fetch data until this is done. This isn't quite as automagic as your solution, but it will make your class safer to use across threads for read-purposes.

It also seems apparent to me that you did not inline this code with the aid of a profiler. Don't do this without the profiler's help. I'm not just spouting generalities here; I work with raytracers and profile code with vtune and parallel studio on a daily basis as part of my job and inlining code like this has a detrimental effect on performance. The most obvious case is due to code bloat, but there's a second, less obvious case that most people seem to overlook.

Even for things like single line accessors, if you inline them all, you'll interfere with the optimizer's ability to make the best use of registers and other optimizations. Optimizing compilers work best on a function-by-function basis with small, well-written functions. They generally don't do as good a job at an inter-function level and if you start inlining everything, the result is akin to one big flat function accessing all kinds of data which even ICC (Intel's optimizing compiler) doesn't do such a great job at dealing with. For a start, the compiler can't read your mind, so inlining everything makes less-executed branches optimized equally as well as more commonly executed ones (basically compromising the compiler's ability to optimize the common branches).

With the profiler, you can see these more commonly executed branches and inline them selectively, but never start by inlining: profilers do a good job at telling you what to consider inlining, but never what shouldn't be inlined. In fact, you'll wreak havoc on your ability to profile your code by inlining almost everything when you start.

As for public interface, I can see that the whole point of this is to implement contiguity and reduce memory and access times (using std::vector for the backend), but given its nature, I think you would do better to provide an interface similar to map<int, T>. The push_back and pop_back behavior, for instance, is rather confusing. Consider an alternative with insert and erase methods only and a non-const operator[] which can create new indices (keys), or do this at least as a first step. You could provide an insert method which only takes const_reference which chooses an available index to be assigned and returns it (it could just be size() - 1 if you don't care about gaps).

From an implementation standpoint, the code seems straightforward enough. I don't have much to suggest there other than 'de-inlining' your code.

Since it appears as though speed is one of the motivating factors for creating this, here's a small tip. Instead of:

inline void sort() const {
    if (!sorted() && data_.size() > 0) {
        ...
}

Consider taking that initial 'if' out and don't inline this function. Put it outside of the class definition. You use sort for all kinds of read-only access cases but it's an exceptional case: most read access should be operating on already sorted data. When you have exceptional cases like this, your optimizing compiler will generally do a much better job if the function isn't inlined and you put your check outside:

inline const_reference operator[] (size_type i) const {
    CHECK_LT(i, size_);
    if (need_sort() )
        sort();
    ...
}

Having done micro-optimizations on a daily basis and with the aid of a profiler, I can assure you that this will generally be faster on most optimizing compilers including latest versions of GCC, ICC, and MSVC. Roughly speaking, the reason is because your operator[] function will be doing less and accessing less memory as a result (no inlined sort to deal with which should only be executed in exceptional circumstances).

Most importantly, I recommend that you grab a profiler and do some tests and see where your bottlenecks are with this.