Struct SparseMat

Source

pub struct SparseMat { /* private fields */ }

Expand description

The class SparseMat represents multi-dimensional sparse numerical arrays.

Such a sparse array can store elements of any type that Mat can store. Sparse means that only non-zero elements are stored (though, as a result of operations on a sparse matrix, some of its stored elements can actually become 0. It is up to you to detect such elements and delete them using SparseMat::erase ). The non-zero elements are stored in a hash table that grows when it is filled so that the search time is O(1) in average (regardless of whether element is there or not). Elements can be accessed using the following methods:

Query operations (SparseMat::ptr and the higher-level SparseMat::ref, SparseMat::value and SparseMat::find), for example:

    const int dims = 5;
    int size[5] = {10, 10, 10, 10, 10};
    SparseMat sparse_mat(dims, size, CV_32F);
    for(int i = 0; i < 1000; i++)
    {
        int idx[dims];
        for(int k = 0; k < dims; k++)
            idx[k] = rand() % size[k];
        sparse_mat.ref<float>(idx) += 1.f;
    }
    cout << "nnz = " << sparse_mat.nzcount() << endl;

Sparse matrix iterators. They are similar to MatIterator but different from NAryMatIterator. That is, the iteration loop is familiar to STL users:

    // prints elements of a sparse floating-point matrix
    // and the sum of elements.
    SparseMatConstIterator_<float>
        it = sparse_mat.begin<float>(),
        it_end = sparse_mat.end<float>();
    double s = 0;
    int dims = sparse_mat.dims();
    for(; it != it_end; ++it)
    {
        // print element indices and the element value
        const SparseMat::Node* n = it.node();
        printf("(");
        for(int i = 0; i < dims; i++)
            printf("%d%s", n->idx[i], i < dims-1 ? ", " : ")");
        printf(": %g\n", it.value<float>());
        s += *it;
    }
    printf("Element sum is %g\n", s);

If you run this loop, you will notice that elements are not enumerated in a logical order (lexicographical, and so on). They come in the same order as they are stored in the hash table (semi-randomly). You may collect pointers to the nodes and sort them to get the proper ordering. Note, however, that pointers to the nodes may become invalid when you add more elements to the matrix. This may happen due to possible buffer reallocation.

Combination of the above 2 methods when you need to process 2 or more sparse matrices simultaneously. For example, this is how you can compute unnormalized cross-correlation of the 2 floating-point sparse matrices:

    double cross_corr(const SparseMat& a, const SparseMat& b)
    {
        const SparseMat *_a = &a, *_b = &b;
        // if b contains less elements than a,
        // it is faster to iterate through b
        if(_a->nzcount() > _b->nzcount())
            std::swap(_a, _b);
        SparseMatConstIterator_<float> it = _a->begin<float>(),
                                        it_end = _a->end<float>();
        double ccorr = 0;
        for(; it != it_end; ++it)
        {
            // take the next element from the first matrix
            float avalue = *it;
            const Node* anode = it.node();
            // and try to find an element with the same index in the second matrix.
            // since the hash value depends only on the element index,
            // reuse the hash value stored in the node
            float bvalue = _b->value<float>(anode->idx,&anode->hashval);
            ccorr += avalue*bvalue;
        }
        return ccorr;
    }

SparseMat

Struct SparseMat Copy item path

Implementations§

impl SparseMat

pub fn default() -> Result<SparseMat>

pub fn new(_sizes: &[i32], _type: i32) -> Result<SparseMat>

§Overloaded parameters

§Parameters

pub fn copy(m: &impl SparseMatTraitConst) -> Result<SparseMat>

§Overloaded parameters

§Parameters

pub fn from_mat(m: &impl MatTraitConst) -> Result<SparseMat>

§Overloaded parameters

§Parameters

Trait Implementations§

impl Boxed for SparseMat

unsafe fn from_raw(ptr: <SparseMat as OpenCVFromExtern>::ExternReceive) -> Self

fn into_raw(self) -> <SparseMat as OpenCVTypeExternContainer>::ExternSendMut

fn as_raw(&self) -> <SparseMat as OpenCVTypeExternContainer>::ExternSend

fn as_raw_mut( &mut self, ) -> <SparseMat as OpenCVTypeExternContainer>::ExternSendMut

impl Clone for SparseMat

fn clone(&self) -> Self

fn clone_from(&mut self, source: &Self)

impl Debug for SparseMat

fn fmt(&self, f: &mut Formatter<'_>) -> Result

impl Drop for SparseMat

fn drop(&mut self)

impl SparseMatTrait for SparseMat

fn as_raw_mut_SparseMat(&mut self) -> *mut c_void

fn set_flags(&mut self, val: i32)

fn hdr(&mut self) -> SparseMat_Hdr

fn set_hdr(&mut self, val: &impl SparseMat_HdrTraitConst)

fn set(&mut self, m: &impl SparseMatTraitConst) -> Result<()>

fn set_mat(&mut self, m: &impl MatTraitConst) -> Result<()>

fn create(&mut self, _sizes: &[i32], _type: i32) -> Result<()>

fn clear(&mut self) -> Result<()>

unsafe fn addref(&mut self) -> Result<()>

unsafe fn release(&mut self) -> Result<()>

fn ptr( &mut self, i0: i32, create_missing: bool, hashval: &mut size_t, ) -> Result<*mut u8>

fn ptr_def(&mut self, i0: i32, create_missing: bool) -> Result<*mut u8>

fn ptr_1( &mut self, i0: i32, i1: i32, create_missing: bool, hashval: &mut size_t, ) -> Result<*mut u8>

fn ptr_def_1( &mut self, i0: i32, i1: i32, create_missing: bool, ) -> Result<*mut u8>

fn ptr_2( &mut self, i0: i32, i1: i32, i2: i32, create_missing: bool, hashval: &mut size_t, ) -> Result<*mut u8>

fn ptr_def_2( &mut self, i0: i32, i1: i32, i2: i32, create_missing: bool, ) -> Result<*mut u8>

fn ptr_3( &mut self, idx: &i32, create_missing: bool, hashval: &mut size_t, ) -> Result<*mut u8>

fn ptr_def_3(&mut self, idx: &i32, create_missing: bool) -> Result<*mut u8>

fn erase(&mut self, i0: i32, i1: i32, hashval: &mut size_t) -> Result<()>

fn erase_def(&mut self, i0: i32, i1: i32) -> Result<()>

fn erase_1( &mut self, i0: i32, i1: i32, i2: i32, hashval: &mut size_t, ) -> Result<()>

fn erase_def_1(&mut self, i0: i32, i1: i32, i2: i32) -> Result<()>

fn erase_2(&mut self, idx: &i32, hashval: &mut size_t) -> Result<()>

fn erase_def_2(&mut self, idx: &i32) -> Result<()>

fn begin_mut(&mut self) -> Result<SparseMatIterator>

fn end_mut(&mut self) -> Result<SparseMatIterator>

fn node_1(&mut self, nidx: size_t) -> Result<SparseMat_Node>

fn new_node(&mut self, idx: &i32, hashval: size_t) -> Result<*mut u8>

fn remove_node( &mut self, hidx: size_t, nidx: size_t, previdx: size_t, ) -> Result<()>

fn resize_hash_tab(&mut self, newsize: size_t) -> Result<()>

impl SparseMatTraitConst for SparseMat

fn as_raw_SparseMat(&self) -> *const c_void

fn flags(&self) -> i32

fn try_clone(&self) -> Result<SparseMat>

fn copy_to(&self, m: &mut impl SparseMatTrait) -> Result<()>

fn copy_to_mat(&self, m: &mut impl MatTrait) -> Result<()>

fn convert_to( &self, m: &mut impl SparseMatTrait, rtype: i32, alpha: f64, ) -> Result<()>

fn convert_to_def(&self, m: &mut impl SparseMatTrait, rtype: i32) -> Result<()>

fn convert_to_1( &self, m: &mut impl MatTrait, rtype: i32, alpha: f64, beta: f64, ) -> Result<()>

fn convert_to_def_1(&self, m: &mut impl MatTrait, rtype: i32) -> Result<()>

fn assign_to(&self, m: &mut impl SparseMatTrait, typ: i32) -> Result<()>

fn assign_to_def(&self, m: &mut impl SparseMatTrait) -> Result<()>

fn elem_size(&self) -> size_t

fn elem_size1(&self) -> size_t

fn typ(&self) -> i32

fn depth(&self) -> i32

fn channels(&self) -> i32

fn size(&self) -> Result<*const i32>

fn size_1(&self, i: i32) -> Result<i32>

fn dims(&self) -> Result<i32>

fn nzcount(&self) -> Result<size_t>

fn hash(&self, i0: i32) -> Result<size_t>

Struct SparseMat

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

impl<Mat> ModifyInplace for Mat
where Mat: Boxed,

impl<T> ToOwned for T
where T: Clone,

impl<T, U> TryFrom<U> for T
where U: Into<T>,

impl<T, U> TryInto<U> for T
where U: TryFrom<T>,