spalloc - Allocate space for sparse matrix - MATLAB (original) (raw)

Allocate space for sparse matrix

Syntax

Description

`S` = spalloc([m](#mw%5F7d46c77a-953c-4565-8c3d-c16b71e936da),[n](#mw%5Fa66f1fe6-4939-4a29-a4f1-3c8636ce2a42),[nz](#mw%5F7fff94d1-afe2-4ffd-a8a1-041f77b19036)) creates an all-zero sparse matrix S of sizem-by-n with room to hold nz nonzero elements, where nz >= 1.

example

Examples

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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.

Define several elements in the matrix.

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.

Show the amount of storage allocated for nonzero matrix elements.

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.

Show the number of nonzero elements in the matrix.

Show the amount of storage allocated for nonzero matrix elements.

Input Arguments

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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 withspalloc, 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