Wiki

Setup of Submatrices
Element Access
Element Insertion
Common Operations
Arithmetic Operations
Aligned Submatrices
Submatrices on Symmetric Matrices

Submatrices provide views on a specific part of a dense or sparse matrix just as subvectors provide views on specific parts of vectors. As such, submatrices act as a reference to a specific block within a matrix. This reference is valid and can be used in evary way any other dense or sparse matrix can be used as long as the matrix containing the submatrix is not resized or entirely destroyed. The submatrix also acts as an alias to the matrix elements in the specified block: Changes made to the elements (e.g. modifying values, inserting or erasing elements) are immediately visible in the matrix and changes made via the matrix are immediately visible in the submatrix.

Setup of Submatrices

A view on a dense or sparse submatrix can be created very conveniently via the submatrix() function. It can be included via the header files

#include <blaze/Blaze.h>
// or
#include <blaze/Math.h>
// or
#include <blaze/math/Submatrix.h>

and forward declared via the header file

#include <blaze/Forward.h>

The first and second parameter specify the row and column of the first element of the submatrix. The third and fourth parameter specify the number of rows and columns, respectively. The four parameters can be specified either at compile time or at runtime:

blaze::DynamicMatrix<double,blaze::rowMajor> A;
// ... Resizing and initialization

// Creating a dense submatrix of size 4x8, starting in row 3 and column 0 (compile time arguments)
auto sm1 = submatrix<3UL,0UL,4UL,8UL>( A );

// Creating a dense submatrix of size 8x16, starting in row 0 and column 4 (runtime arguments)
auto sm2 = submatrix( A, 0UL, 4UL, 8UL, 16UL );

The submatrix() function returns an expression representing the submatrix view. The type of this expression depends on the given submatrix arguments, primarily the type of the matrix and the compile time arguments. If the type is required, it can be determined via the decltype specifier:

using MatrixType = blaze::DynamicMatrix<int>;
using SubmatrixType = decltype( blaze::submatrix<3UL,0UL,4UL,8UL>( std::declval<MatrixType>() ) );

The resulting view can be treated as any other dense or sparse matrix, i.e. it can be assigned to, it can be copied from, and it can be used in arithmetic operations. A submatrix created from a row-major matrix will itself be a row-major matrix, a submatrix created from a column-major matrix will be a column-major matrix. The view can also be used on both sides of an assignment: The submatrix can either be used as an alias to grant write access to a specific submatrix of a matrix primitive on the left-hand side of an assignment or to grant read-access to a specific submatrix of a matrix primitive or expression on the right-hand side of an assignment. The following example demonstrates this in detail:

blaze::DynamicMatrix<double,blaze::columnMajor> A, B;
blaze::CompressedMatrix<double,blaze::rowMajor> C;
// ... Resizing and initialization

// Creating a dense submatrix of size 8x4, starting in row 0 and column 2
auto sm = submatrix( A, 0UL, 2UL, 8UL, 4UL );

// Setting the submatrix of A to a 8x4 submatrix of B
sm = submatrix( B, 0UL, 0UL, 8UL, 4UL );

// Copying the sparse matrix C into another 8x4 submatrix of A
submatrix( A, 8UL, 2UL, 8UL, 4UL ) = C;

// Assigning part of the result of a matrix addition to the first submatrix
sm = submatrix( B + C, 0UL, 0UL, 8UL, 4UL );

Warning: It is the programmer's responsibility to ensure the submatrix does not outlive the viewed matrix:

// Creating a submatrix on a temporary matrix; results in a dangling reference!
auto sm = submatrix<1UL,0UL,2UL,3UL>( DynamicMatrix<int>{ { 1, 2, 3 }, { 4, 5, 6 }, { 7, 8, 9 } } );

Element Access

The elements of a submatrix can be directly accessed with the function call operator:

blaze::DynamicMatrix<double,blaze::rowMajor> A;
// ... Resizing and initialization

// Creating a 8x8 submatrix, starting from position (4,4)
auto sm = submatrix( A, 4UL, 4UL, 8UL, 8UL );

// Setting the element (0,0) of the submatrix, which corresponds to
// the element at position (4,4) in matrix A
sm(0,0) = 2.0;

Alternatively, the elements of a submatrix can be traversed via (const) iterators. Just as with matrices, in case of non-const submatrices, begin() and end() return an iterator, which allows to manipuate the elements, in case of constant submatrices an iterator to immutable elements is returned:

blaze::DynamicMatrix<int,blaze::rowMajor> A( 256UL, 512UL );
// ... Resizing and initialization

// Creating a reference to a specific submatrix of matrix A
auto sm = submatrix( A, 16UL, 16UL, 64UL, 128UL );

// Traversing the elements of the 0th row via iterators to non-const elements
for( auto it=sm.begin(0); it!=sm.end(0); ++it ) {
   *it = ...;  // OK: Write access to the dense submatrix value.
   ... = *it;  // OK: Read access to the dense submatrix value.
}

// Traversing the elements of the 1st row via iterators to const elements
for( auto it=sm.cbegin(1); it!=sm.cend(1); ++it ) {
   *it = ...;  // Compilation error: Assignment to the value via iterator-to-const is invalid.
   ... = *it;  // OK: Read access to the dense submatrix value.
}

blaze::CompressedMatrix<int,blaze::rowMajor> A( 256UL, 512UL );
// ... Resizing and initialization

// Creating a reference to a specific submatrix of matrix A
auto sm = submatrix( A, 16UL, 16UL, 64UL, 128UL );

// Traversing the elements of the 0th row via iterators to non-const elements
for( auto it=sm.begin(0); it!=sm.end(0); ++it ) {
   it->value() = ...;  // OK: Write access to the value of the non-zero element.
   ... = it->value();  // OK: Read access to the value of the non-zero element.
   it->index() = ...;  // Compilation error: The index of a non-zero element cannot be changed.
   ... = it->index();  // OK: Read access to the index of the sparse element.
}

// Traversing the elements of the 1st row via iterators to const elements
for( auto it=sm.cbegin(1); it!=sm.cend(1); ++it ) {
   it->value() = ...;  // Compilation error: Assignment to the value via iterator-to-const is invalid.
   ... = it->value();  // OK: Read access to the value of the non-zero element.
   it->index() = ...;  // Compilation error: The index of a non-zero element cannot be changed.
   ... = it->index();  // OK: Read access to the index of the sparse element.
}

Element Insertion

Inserting/accessing elements in a sparse submatrix can be done by several alternative functions. The following example demonstrates all options:

blaze::CompressedMatrix<double,blaze::rowMajor> A( 256UL, 512UL );  // Non-initialized matrix of size 256x512

auto sm = submatrix( A, 10UL, 10UL, 16UL, 16UL );  // View on a 16x16 submatrix of A

// The function call operator provides access to all possible elements of the sparse submatrix,
// including the zero elements. In case the function call operator is used to access an element
// that is currently not stored in the sparse submatrix, the element is inserted into the
// submatrix.
sm(2,4) = 2.0;

// The second operation for inserting elements is the set() function. In case the element is
// not contained in the submatrix it is inserted into the submatrix, if it is already contained
// in the submatrix its value is modified.
sm.set( 2UL, 5UL, -1.2 );

// An alternative for inserting elements into the submatrix is the insert() function. However,
// it inserts the element only in case the element is not already contained in the submatrix.
sm.insert( 2UL, 6UL, 3.7 );

// Just as in the case of sparse matrices, elements can also be inserted via the append()
// function. In case of submatrices, append() also requires that the appended element's
// index is strictly larger than the currently largest non-zero index in the according row
// or column of the submatrix and that the according row's or column's capacity is large
// enough to hold the new element. Note however that due to the nature of a submatrix, which
// may be an alias to the middle of a sparse matrix, the append() function does not work as
// efficiently for a submatrix as it does for a matrix.
sm.reserve( 2UL, 10UL );
sm.append( 2UL, 10UL, -2.1 );

Common Operations

A submatrix view can be used like any other dense or sparse matrix. This means that with only a few exceptions all Matrix Operations and Arithmetic Operations can be used. For instance, the current size of the matrix, i.e. the number of rows or columns can be obtained via the rows() and columns() functions, the current total capacity via the capacity() function, and the number of non-zero elements via the nonZeros() function. However, since submatrices are views on a specific submatrix of a matrix, several operations are not possible, such as resizing and swapping:

blaze::DynamicMatrix<int,blaze::rowMajor> A( 42UL, 42UL );
// ... Resizing and initialization

// Creating a view on the a 8x12 submatrix of matrix A
auto sm = submatrix( A, 0UL, 0UL, 8UL, 12UL );

sm.rows();      // Returns the number of rows of the submatrix
sm.columns();   // Returns the number of columns of the submatrix
sm.capacity();  // Returns the capacity of the submatrix
sm.nonZeros();  // Returns the number of non-zero elements contained in the submatrix

sm.resize( 10UL, 8UL );  // Compilation error: Cannot resize a submatrix of a matrix

auto sm2 = submatrix( A, 8UL, 0UL, 12UL, 8UL );
swap( sm, sm2 );  // Compilation error: Swap operation not allowed

Arithmetic Operations

Both dense and sparse submatrices can be used in all arithmetic operations that any other dense or sparse matrix can be used in. The following example gives an impression of the use of dense submatrices within arithmetic operations. All operations (addition, subtraction, multiplication, scaling, ...) can be performed on all possible combinations of dense and sparse matrices with fitting element types:

blaze::DynamicMatrix<double,blaze::rowMajor> D1, D2, D3;
blaze::CompressedMatrix<double,blaze::rowMajor> S1, S2;

blaze::CompressedVector<double,blaze::columnVector> a, b;

// ... Resizing and initialization

auto sm = submatrix( D1, 0UL, 0UL, 8UL, 8UL );  // View on the 8x8 submatrix of matrix D1
                                                // starting from row 0 and column 0

submatrix( D1, 0UL, 8UL, 8UL, 8UL ) = D2;  // Dense matrix initialization of the 8x8 submatrix
                                           // starting in row 0 and column 8
sm = S1;                                   // Sparse matrix initialization of the second 8x8 submatrix

D3 = sm + D2;                                   // Dense matrix/dense matrix addition
S2 = S1 - submatrix( D1, 8UL, 0UL, 8UL, 8UL );  // Sparse matrix/dense matrix subtraction
D2 = sm * submatrix( D1, 8UL, 8UL, 8UL, 8UL );  // Dense matrix/dense matrix multiplication

submatrix( D1, 8UL, 0UL, 8UL, 8UL ) *= 2.0;      // In-place scaling of a submatrix of D1
D2 = submatrix( D1, 8UL, 8UL, 8UL, 8UL ) * 2.0;  // Scaling of the a submatrix of D1
D2 = 2.0 * sm;                                   // Scaling of the a submatrix of D1

submatrix( D1, 0UL, 8UL, 8UL, 8UL ) += D2;  // Addition assignment
submatrix( D1, 8UL, 0UL, 8UL, 8UL ) -= S1;  // Subtraction assignment
submatrix( D1, 8UL, 8UL, 8UL, 8UL ) *= sm;  // Multiplication assignment

a = submatrix( D1, 4UL, 4UL, 8UL, 8UL ) * b;  // Dense matrix/sparse vector multiplication

Aligned Submatrices

Usually submatrices can be defined anywhere within a matrix. They may start at any position and may have an arbitrary extension (only restricted by the extension of the underlying matrix). However, in contrast to matrices themselves, which are always properly aligned in memory and therefore can provide maximum performance, this means that submatrices in general have to be considered to be unaligned. This can be made explicit by the blaze::unaligned flag:

using blaze::unaligned;

blaze::DynamicMatrix<double,blaze::rowMajor> A;
// ... Resizing and initialization

// Identical creations of an unaligned submatrix of size 8x8, starting in row 0 and column 0
auto sm1 = submatrix           ( A, 0UL, 0UL, 8UL, 8UL );
auto sm2 = submatrix<unaligned>( A, 0UL, 0UL, 8UL, 8UL );
auto sm3 = submatrix<0UL,0UL,8UL,8UL>          ( A );
auto sm4 = submatrix<unaligned,0UL,0UL,8UL,8UL>( A );

All of these calls to the submatrix() function are identical. Whether the alignment flag is explicitly specified or not, it always returns an unaligned submatrix. Whereas this may provide full flexibility in the creation of submatrices, this might result in performance disadvantages in comparison to matrix primitives (even in case the specified submatrix could be aligned). Whereas matrix primitives are guaranteed to be properly aligned and therefore provide maximum performance in all operations, a general view on a matrix might not be properly aligned. This may cause a performance penalty on some platforms and/or for some operations.

However, it is also possible to create aligned submatrices. Aligned submatrices are identical to unaligned submatrices in all aspects, except that they may pose additional alignment restrictions and therefore have less flexibility during creation, but don't suffer from performance penalties and provide the same performance as the underlying matrix. Aligned submatrices are created by explicitly specifying the blaze::aligned flag:

using blaze::aligned;

// Creating an aligned submatrix of size 8x8, starting in row 0 and column 0
auto sv1 = submatrix<aligned>( A, 0UL, 0UL, 8UL, 8UL );
auto sv2 = submatrix<aligned,0UL,0UL,8UL,8UL>( A );

The alignment restrictions refer to system dependent address restrictions for the used element type and the available vectorization mode (SSE, AVX, ...). In order to be properly aligned the first element of each row/column of the submatrix must be aligned. The following source code gives some examples for a double precision row-major dynamic matrix, assuming that padding is enabled and that AVX is available, which packs 4 double values into a SIMD vector:

using blaze::aligned;

blaze::DynamicMatrix<double,blaze::rowMajor> D( 13UL, 17UL );
// ... Resizing and initialization

// OK: Starts at position (0,0), i.e. the first element of each row is aligned (due to padding)
auto dsm1 = submatrix<aligned>( D, 0UL, 0UL, 7UL, 11UL );

// OK: First column is a multiple of 4, i.e. the first element of each row is aligned (due to padding)
auto dsm2 = submatrix<aligned>( D, 3UL, 12UL, 8UL, 16UL );

// OK: First column is a multiple of 4 and the submatrix includes the last row and column
auto dsm3 = submatrix<aligned>( D, 4UL, 0UL, 9UL, 17UL );

// Error: First column is not a multiple of 4, i.e. the first element is not aligned
auto dsm4 = submatrix<aligned>( D, 2UL, 3UL, 12UL, 12UL );

Note that the discussed alignment restrictions are only valid for aligned dense submatrices. In contrast, aligned sparse submatrices at this time don't pose any additional restrictions. Therefore aligned and unaligned sparse submatrices are truly fully identical. Still, in case the blaze::aligned flag is specified during setup, an aligned submatrix is created:

using blaze::aligned;

blaze::CompressedMatrix<double,blaze::rowMajor> A;
// ... Resizing and initialization

// Creating an aligned submatrix of size 8x8, starting in row 0 and column 0
auto sv = submatrix<aligned>( A, 0UL, 0UL, 8UL, 8UL );

Submatrices on Symmetric Matrices

Submatrices can also be created on symmetric matrices (see the SymmetricMatrix class template):

using blaze::DynamicMatrix;
using blaze::SymmetricMatrix;

// Setup of a 16x16 symmetric matrix
SymmetricMatrix< DynamicMatrix<int> > A( 16UL );

// Creating a dense submatrix of size 8x12, starting in row 2 and column 4
auto sm = submatrix( A, 2UL, 4UL, 8UL, 12UL );

It is important to note, however, that (compound) assignments to such submatrices have a special restriction: The symmetry of the underlying symmetric matrix must not be broken! Since the modification of element a_ij of a symmetric matrix also modifies the element a_ji, the matrix to be assigned must be structured such that the symmetry of the symmetric matrix is preserved. Otherwise a std::invalid_argument exception is thrown:

using blaze::DynamicMatrix;
using blaze::SymmetricMatrix;

// Setup of two default 4x4 symmetric matrices
SymmetricMatrix< DynamicMatrix<int> > A1( 4 ), A2( 4 );

// Setup of the 3x2 dynamic matrix
//
//       ( 1 2 )
//   B = ( 3 4 )
//       ( 5 6 )
//
DynamicMatrix<int> B{ { 1, 2 }, { 3, 4 }, { 5, 6 } };

// OK: Assigning B to a submatrix of A1 such that the symmetry can be preserved
//
//        ( 0 0 1 2 )
//   A1 = ( 0 0 3 4 )
//        ( 1 3 5 6 )
//        ( 2 4 6 0 )
//
submatrix( A1, 0UL, 2UL, 3UL, 2UL ) = B;  // OK

// Error: Assigning B to a submatrix of A2 such that the symmetry cannot be preserved!
//   The elements marked with X cannot be assigned unambiguously!
//
//        ( 0 1 2 0 )
//   A2 = ( 1 3 X 0 )
//        ( 2 X 6 0 )
//        ( 0 0 0 0 )
//
submatrix( A2, 0UL, 1UL, 3UL, 2UL ) = B;  // Assignment throws an exception!

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