The size of mathematical problems that can be treated at any particular time is generally limited by the available computing resources. Both, the speed of the computer and its available memory place limitation on the problem size.
There are many classes of mathematical problems which give rise to matrices, where a large number of the elements are zero. In this case it makes sense to have a special matrix type to handle this class of problems where only the nonzero elements of the matrix are stored. Not only does this reduce the amount of memory to store the matrix, but it also means that operations on this type of matrix can take advantage of the a priori knowledge of the positions of the nonzero elements to accelerate their calculations.
A matrix type that stores only the nonzero elements is generally called sparse. It is the purpose of this document to discuss the basics of the storage and creation of sparse matrices and the fundamental operations on them.
| • Storage of Sparse Matrices: |
| • Creating Sparse Matrices: |
| • Information: |
| • Operators and Functions: |
© 1996–2018 John W. Eaton
Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies.
Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one.Permission is granted to copy and distribute translations of this manual into another language, under the above conditions for modified versions.
https://octave.org/doc/interpreter/Basics.html