Description Usage Arguments Value Functions
A collection of functions that take a numeric / 0-1 integer matrix and calculate row-wise similarity.
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X |
A matrix, or an object that can be coerced into a matrix. Values depend on the type of metric used (numeric, 1/0 integers, etc.) |
metric |
One of the supported metrics. Currently |
thresh |
Float. Minimal similarity threshold to be returned. Values below are converted to 0 (to allow sparse representation). Default is 0.0 |
n_cpu |
Integer. Number of cores to use for the local cluster (using the |
cl |
A cluster object, pointing to the cluster to be used instead of a local cluster. This option overrides the |
include_diag |
Logical. Should the diagonal of 1 be included in the matrix? This can help save memory. Default is |
row_blocks |
Integer. How to divide matrix rows into blocks for block-wise similarity calculation (using matrix multiplication). Default is 1 which means similarity is calculated in a single step. |
col_block |
Integer. Not implemented yet |
An object of symmetricMatrix
class. Default is a sparse matrix but this can be modified using the sparse
parameter
sim_loopR
: Generate sparse similarity matrix using simple R loop in a single thread or a cluster
sim_blocksR
: Generate sparse similarity matrix using block-wise matrix multiplication
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