By I. S. Duff, A. M. Erisman, J. K. Reid
The topic of sparse matrices has its root in such different fields as administration technological know-how, energy structures research, surveying, circuit thought, and structural research. effective use of sparsity is a key to fixing huge difficulties in lots of fields. This publication presents either perception and solutions for these trying to remedy those problems.
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Additional info for Direct methods for sparse matrices
If the swap was done, do the same for the swapped node and its children. Continue until no swap is needed or the leaf level is reached. At this point, we have a new a binary tree with the value at 32 SPARSE MATRICES: STORAGE SCHEMES AND SIMPLE OPERATIONS Fig. 1. A binary tree with 12 nodes. each node less than or equal to that at a child. Restoring this property will have taken at most log2 n swaps. The second sorted value can be taken from the root. Continuing, the sorted list can be constructed with less than n log2 n swaps.
A very useful algorithm in such a case is the heap sort. It can be performed in place, that is, without temporary storage. For a list of length n, the computational effort is proportional to n log n. The algorithm is based on regarding the items as being held in a special binary tree. Node 1 is the root and nodes 2 and 3 are its children. In general, node i has nodes 2i and 2i + 1 as its children unless 2i > n or 2i + 1 > n, in which case node i is a leaf or has one child. 1. 1). Suppose that it desired to order the items in ascending order and they have already been associated with such a binary tree so that the value at each node is less than or equal to that at any child.
Derived type for sparse vectors, using integers and reals. The disadvantage is that the sizes of the columns vary during the execution. Each change of size will involve allocating a new array, copying the data, and deallocating the old array. It is therefore usual to pack the data into an integer and a real array or into an array of derived type. For each member of the collection, we store the position of its start (in either array) and the number of entries. 1. 1) stored as a collection of sparse column vectors.