Operators acting on objects to extract or replace parts.

# S4 method for Matrix
[(x, i, j) <- value

# S4 method for Matrix
[[(x, i, j) <- value

## Arguments

x An object from which to extract element(s) or in which to replace element(s). Indices specifying elements to extract or replace. Indices are numeric, integer or character vectors or empty (missing) or NULL. Numeric values are coerced to integer as by as.integer (and hence truncated towards zero). Character vectors will be matched to the name of the elements. An empty index (a comma separated blank) indicates that all entries in that dimension are selected. A possible value for the element(s) of x.

## Value

A subsetted object.

Other mutator: mutator

## Examples

## Create a count data matrix
A1 <- CountMatrix(data = sample(0:10, 100, TRUE), nrow = 10, ncol = 10)

## Access
get_id(A1)#> [1] "22c2305c-ca61-4323-962c-adf137fd5cea"dim(A1) # Get the matrix dimensions#> [1] 10 10colnames(A1) <- letters[11:20] # Set the column names
colnames(A1) # Get the column names#>  [1] "k" "l" "m" "n" "o" "p" "q" "r" "s" "t"rownames(A1) <- LETTERS[1:10] # Set the row names
rownames(A1) # Get the rownames#>  [1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J"
## Subset
A1[[1]] # Get the first value#> [1] 2A1[, ] # Get all values#>   k  l m  n  o  p q r  s  t
#> A 2  8 7  9  4  9 8 3  7  6
#> B 0  6 6  9 10  0 2 0  7  8
#> C 9  0 4 10  1  6 7 9  8  9
#> D 8  6 4  5  2  1 3 4  5 10
#> E 0  4 8 10  1  6 9 0 10 10
#> F 7  9 0  4  9  3 8 0  0  9
#> G 3  3 5  3  4  6 7 9  8  2
#> H 1 10 2  5  6  2 0 6  6  4
#> I 9  8 4  4  0  2 2 5  2  6
#> J 1  9 3  0  5 10 6 8  7  9A1[1, ] # Get the first row#> k l m n o p q r s t
#> 2 8 7 9 4 9 8 3 7 6 A1[c("A", "B", "C"), ] # Get the first three rows#>   k l m  n  o p q r s t
#> A 2 8 7  9  4 9 8 3 7 6
#> B 0 6 6  9 10 0 2 0 7 8
#> C 9 0 4 10  1 6 7 9 8 9A1[c("A", "B", "C"), 1] # Get the first three rows of the first column#> A B C
#> 2 0 9 A1[, 1, drop = FALSE] # Get the first column#>   k
#> A 2
#> B 0
#> C 9
#> D 8
#> E 0
#> F 7
#> G 3
#> H 1
#> I 9
#> J 1
## Coerce counts to relative frequencies
B <- as_abundance(A1)
## Row sums are internally stored before coercing to a frequency matrix
get_totals(B) # Get row sums#>  A  B  C  D  E  F  G  H  I  J
#> 63 48 63 48 58 49 50 42 42 58 ## This allows to restore the source data
A2 <- as_count(B)
all(A1 == A2)#> [1] TRUE## Coerce to a co-occurrence matrix
B <- as_occurrence(A1)