topolow (version 2.0.1)

table_to_matrix: Convert Table Format Data to Dissimilarity Matrix

Description

Converts data from table/matrix format (objects as rows, references as columns) to a symmetric dissimilarity matrix. The function creates a matrix where both rows and columns contain the union of all object and reference names.

Usage

table_to_matrix(data, is_similarity = FALSE)

Value

A symmetric matrix of dissimilarities with row and column names corresponding to the union of all object and reference names. NA values represent unmeasured pairs, and the diagonal is set to 0.

Arguments

data

Matrix or data frame where rownames represent objects, columnnames represent references, and cells contain (dis)similarity values.

is_similarity

Logical. Whether values are similarities (TRUE) or dissimilarities (FALSE). If TRUE, similarities will be converted to dissimilarities by subtracting from the maximum value per column (reference). Default: FALSE.

Details

The function takes a table where:

• Rows represent objects

• Columns represent references

• Values represent (dis)similarities

It creates a symmetric matrix where both rows and columns contain the union of all object names (row names) and reference names (column names). The original measurements are preserved, and the matrix is made symmetric by filling both (i,j) and (j,i) positions with the same value.

When is_similarity = TRUE, similarities are converted to dissimilarities by subtracting each value from the maximum value in its respective column (reference). Threshold indicators (< or >) are handled and inverted during conversion.

Examples

# Example with dissimilarity data in table format
dissim_table <- matrix(c(1.2, 2.1, 3.4, 1.8, 2.9, 4.1),
                      nrow = 2, ncol = 3,
                      dimnames = list(c("Obj1", "Obj2"),
                                    c("Ref1", "Ref2", "Ref3")))

mat_dissim <- table_to_matrix(dissim_table, is_similarity = FALSE)

# Example with similarity data (will be converted to dissimilarity)
sim_table <- matrix(c(8.8, 7.9, 6.6, 8.2, 7.1, 5.9),
                   nrow = 2, ncol = 3,
                   dimnames = list(c("Obj1", "Obj2"),
                                 c("Ref1", "Ref2", "Ref3")))

mat_from_sim <- table_to_matrix(sim_table, is_similarity = TRUE)