calc_si: Compute similarity index
In biogram: N-Gram Analysis of Biological Sequences

Description Usage Arguments Details Value References See Also Examples

Computes similarity index between two encodings.

1	calc_si(a, b)

`a`	encoding (see `validate_encoding` for more information about the required structure of encoding).
`b`	encoding to which `a` should be compared. Must have equal number of groups or less than `a`. Both `a` and b must have the the same number of elements.

Briefly, the similarity index is a fraction of elements that have the same pairing in both encodings. Pairing is a binary variable, that has value 1 if two elements are in the same group and 0 if not. For more details, see references.

the value of similarity index.

Stephenson, J.D., and Freeland, S.J. (2013). Unearthing the Root of Amino Acid Similarity. J Mol Evol 77, 159-169.

calc_ed: calculate the encoding distance between two encodings.

# example from Stephenson & Freeland, 2013 (Fig. 6)
enc1 <- list(`1` = "A",
             `2` = c("F", "E"),
             `3` = c("C", "D", "G"))

enc2 <- list(`1` = c("A", "G"),
             `2` = c("C", "D", "E", "F"))

enc3 <- list(`1` = c("D", "G"),
             `2` = c("E", "F"),
             `3` = c("A", "C"))
             
calc_si(enc1, enc2)
calc_si(enc2, enc3)
calc_si(enc1, enc3)