check_sparse_matrix: Check if the underlying data behind a sparse matrix...

In MatrixExtra: Extra Methods for Sparse Matrices

Check if the underlying data behind a sparse matrix constitutes a valid object

Description

Check if the underlying data behind a sparse matrix constitutes a valid object

Usage

check_sparse_matrix(X, sort = TRUE, remove_zeros = TRUE)

Arguments

X	A sparse matrix or sparse vector whose underlying arrays are to be checked.
sort	Whether to sort the indices of 'X' along the way. For this, will make deep copies of the indices and values so that there are no issues with external references being updated along the way.
remove_zeros	Whether to remove entries in 'X' which have a value of zero but are nevertheless still present in the sparse representation.

Details

Makes checks on the data contained in the sparse matrix or sparse vector object for whether the data constitutes a valid matrix - e.g. indices must not be negative or larger than the dimensions, index pointer must match with the indices, etc.

As a short-hand, can also sort the matrix and remove zeros by calling the respective functions sort_sparse_indices and remove_sparse_zeros.

A sparse matrix or sparse vector should never come out with invalid data from functions from 'Matrix' and 'MatrixExtra', with one exception: some 'MatrixExtra' functions might modify indices in-place, which can cause problems if the same array of indices / values is also used by another matrix or R object elsewhere.

Otherwise, this function is aimed at making checks on matrices that are manually constructed.

Value

The same matrix or vector 'X' (perhaps sorted or with zeros removed depending on the parameters). If ‘X' contains data that doesn’t make for a valid sparse matrix (e.g. different number of values and indices), it will throw an error.

MatrixExtra documentation built on May 29, 2024, 2:53 a.m.