dist.matrix object (wordspace)Mark an arbitrary dense or sparse matrix as a pre-computed dist.matrix object, so it can be used with nearest.neighbours and pair.distances. Default methods are provided for a regular dense matrix, any type of sparseMatrix from the Matrix package, as well as a dsm object (from which the raw or scored co-occurrence matrix is extracted).
as.distmat(x, ...)# S3 method for matrix
as.distmat(x, similarity=FALSE, symmetric=FALSE, ...)
# S3 method for sparseMatrix
as.distmat(x, similarity=FALSE, symmetric=FALSE, force.dense=FALSE, ...)
# S3 method for dsm
as.distmat(x, similarity=FALSE, symmetric=FALSE, force.dense=FALSE, ...)
If x is a dense matrix or force.dense=TRUE, it is assigned to class dist.matrix so it can be used with nearest.neighbours and pair.distances as well as the plot and head methods.
If x is a sparse matrix, it is marked with an attribute dist.matrix recognized by nearest.neighbours and pair.distances; however, method implementations for dist.matrix objects will not apply. Important note: In this case, x must be a non-negative similarity matrix and empty cells are treated as zeroes.
In either case, attributes similarity and symmetric are set as specified.
a matrix-like object of a suitable class (for which a method implementation is available) or a DSM object of class dsm
whether the matrix contains similarity or distance values. Note that sparse distance matrices (similarity=FALSE) are not supported.
whether the distance or similarity is symmetric (i.e. it has the same rows and columns in the same order and \(d(x, y) = d(y, x)\)). Methods trust the specified value and do not check whether this is actually true.
whether to convert a sparse distance matrix into a dense matrix object. Keep in mind that the resulting matrix may be extremely large.
additional arguments passed on to the method implementations (see respective manpages for details)
Stephanie Evert (https://purl.org/stephanie.evert)
This method is called as.distmat because the regular name as.dist.matrix would collide with the as.dist method for matrix objects.
The method has two main purposes:
enable the use of pre-computed distance information from external sources in wordspace;
disguise a (scored) co-occurrence matrix as a similarity matrix so that nearest.neighbours and pair.distances can be used for lookup of first-order co-occurrence data.
plot and head methods for distances matrices; nearest.neighbours and pair.distances
# interpret co-occurrence frequency as similarity measure
M <- as.distmat(DSM_HieroglyphsMatrix, similarity=TRUE)
nearest.neighbours(M, "cat")
nearest.neighbours(M, "hear", byrow=FALSE)
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