Generate a similarity matrix
get_similarity_matrix(
readouts,
self = NULL,
upper = TRUE,
method = "rsquared",
strategy = "atLeastOne",
min_measures = 3L,
post_norm = TRUE,
parallel = FALSE
)The readouts that are used to generate the similarity matrix
Values to set on the diagonal of the matrix. If NULL, the values that are returned by the method are used.
Only used with "rsquared". If TRUE, generates the upper triangle.
The method to use as a string. Possible values for the string are "rsquared" and any method that is accepted by stats::dist. In case of stats::dist we are using the change in the values over time / compartments (columns).
Defines the strategy how to treat 0 / NA values. Considering a pair (two lines), **atLeastOne** ignores all columns, where both are 0. **all** takes all measures into account, independent whether they are 0 or not.
Minimum number of measures to compare two integration sites (rows). If there are less measures, the similarity entry is NA.
Normalize the similarity matrix to [0,1] scale.
Whether parallelism should be used. Number of cores is set by option mc.cores. If unset, parallel::detectCores is used.
A similarity matrix.