conversions: Conversions between matrix types

In MatrixExtra: Extra Methods for Sparse Matrices

Conversions between matrix types

Description

Convenience functions for converting to different sparse matrix formats, between pairs of classes which might not be supported in the 'Matrix' package.

These come in the form of explicit functions 'as.<type>.matrix' (see below), as well as registered conversion methods to use along with 'as(object, type)', adding extra conversion routes which are missing in the 'Matrix' package for output types 'dgRMatrix', 'lgRMatrix', and 'ngRMatrix'.

Usage

as.csr.matrix(x, binary = FALSE, logical = FALSE, sort = FALSE)

as.csc.matrix(x, binary = FALSE, logical = FALSE, sort = FALSE)

as.coo.matrix(x, binary = FALSE, logical = FALSE, sort = FALSE)

as.sparse.vector(x, binary = FALSE, logical = FALSE, integer = FALSE)

Arguments

x	A matrix which is to be converted to a different format. Supported input types are: Sparse matrices from 'Matrix' package, in any format. Sparse vectors from 'Matrix' in any format. Dense matrices from base R (class 'matrix'). Dense vectors from base R (classes 'numeric', 'integer', 'logical'). Dense matrix or vector from package 'float' (class 'float32'). 'data.frame', 'data.table', and 'tibble'.
binary	Whether the result should be a binary-only matrix/vector (inheriting from class ‘nsparseMatrix'/'nsparseVector' - these don’t have slot 'x'). Can only pass one of 'binary' or 'logical'.
logical	Whether the result should be a matrix/vector with logical (boolean) type (inheriting from 'lsparseMatrix'/'lsparseVector'). Can only pass one of 'binary' or 'logical'.
sort	Whether to sort the indices in case they are not sorted. Note that it will perform deep copies of the indices and values along the way.
integer	Whether the result should be a vector with integer type ('isparseVector').

Details

The functions internally might use some routes of 'as(x, "?sparseMatrix")', so they might work with other object classes if they register a conversion method for 'Matrix' base types.

When passed a vector, the functions 'as.csr.matrix' and 'as.coo.matrix' will assume that it is a row vector, while ‘as.csc.matrix' will assume it’s a column vector.

Value

A sparse matrix/vector, with format:

• CSR (a.k.a. 'RsparseMatrix') when calling 'as.csr.matrix' (class 'dgRMatrix', 'ngRMatrix', or 'lgRMatrix', depending on parameters 'binary' and 'logical').

• CSC (a.k.a. 'CsparseMatrix') when calling 'as.csc.matrix' (class 'dgCMatrix', 'ngCMatrix', or 'lgCMatrix', depending on parameters 'binary' and 'logical').

• COO (a.k.a. 'TsparseMatrix') when calling 'as.coo.matrix' (class 'dgTMatrix', 'ngTMatrix', or 'lgTMatrix', depending on parameters 'binary' and 'logical').

• sparse vector (class dependant on input) when calling 'as.sparse.vector'.

Examples

library(Matrix)
library(MatrixExtra)

m.coo <- as(matrix(1:3), "TsparseMatrix")
as.csr.matrix(m.coo)
as.csr.matrix(1:3) # <- assumes it's a row vector
as.csc.matrix(1:3) # <- assumes it's a column vector

### Using the new conversion methods
### (these would fail if 'MatrixExtra' is not loaded)
as(matrix(1:3), "ngRMatrix")
as(as.csc.matrix(m.coo), "dgRMatrix")

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