spalloc

Allocate space for sparse matrix

Syntax

S = spalloc(m,n,nz)

Description

S = spalloc(m,n,nz) creates an all-zero sparse matrix S of size m-by-n with room to hold nz nonzero elements, where nz >= 1.

Examples

Create Sparse Matrix with Specified Size and Preallocation

Use spalloc to initialize a 10-by-10 all-zero sparse matrix with room for up to 20 nonzero elements.

S = spalloc(10,10,20);

Define several elements in the matrix.

S(1:3,1:3) = magic(3)

S = 10x10 sparse double matrix (9 nonzeros)
   (1,1)        8
   (2,1)        3
   (3,1)        4
   (1,2)        1
   (2,2)        5
   (3,2)        9
   (1,3)        6
   (2,3)        7
   (3,3)        2

Show the number of nonzero elements in the matrix.

n1 = nnz(S)

n1 = 
9

Show the amount of storage allocated for nonzero matrix elements.

n2 = nzmax(S)

n2 = 
20

Create Sparse Matrix with Nonzero Columns

Use spalloc to initialize a 20-by-20 all-zero sparse matrix with space for 100 nonzero elements.

n = 20;
S = spalloc(n,n,5*n);

Then use a for loop to fill in the columns of S one at a time with an average of at most five nonzero elements per column.

for j = 1:n
    S(:,j) = [zeros(n-5,1); round(rand(5,1))];
end

Plot the sparsity pattern of matrix S. The dots represent the nonzero elements.

spy(S)

Show the number of nonzero elements in the matrix.

n1 = nnz(S)

n1 = 
54

Show the amount of storage allocated for nonzero matrix elements.

n2 = nzmax(S)

n2 = 
100

Input Arguments

m — Number of matrix rows

nonnegative integer

Number of matrix rows, specified as a nonnegative integer.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

n — Number of matrix columns

nonnegative integer

Number of matrix columns, specified as a nonnegative integer.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

nz — Storage allocation for nonzero elements

nonnegative integer

Storage allocation for nonzero elements, specified as a nonnegative integer. If you specify a value of 0 for nz, then spalloc instead sets the value of nz to 1.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

Limitations

• Both matrix dimensions, m and n, must be smaller than 2^31-1 on 32-bit platforms, or 2^48-1 on 64-bit platforms.

Tips

• When you assign several times into a matrix you created with spalloc, the preallocated memory can prevent repeated reallocations. However, assigning into a sparse matrix is still a relatively expensive operation, which should usually be avoided if it can easily be replaced by one of the following:

  • a one-time call to the sparse function

  • a one-time call to the spdiags function

  • a one-time concatenation of a set of matrices, which can be sparse, dense, or both

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Usage notes and limitations:

• See distributed.spalloc (Parallel Computing Toolbox).

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a