Operators acting on objects to extract or replace parts.
Usage
# S4 method for class 'CompositionMatrix,missing,missing,missing'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,missing,missing,logical'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,index,missing,missing'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,index,missing,logical'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,missing,index,missing'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,missing,index,logical'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,index,index,missing'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix,index,index,logical'
x[i, j, ..., drop = TRUE]
# S4 method for class 'CompositionMatrix'
x[i, j, ...] <- value
# S4 method for class 'CompositionMatrix'
x[[i, j, ...]] <- value
Arguments
- x
An object from which to extract element(s) or in which to replace element(s).
- i, j
Indices specifying elements to extract or replace. Indices are
numeric
,integer
orcharacter
vectors or empty (missing) orNULL
. Numeric values are coerced tointeger
as byas.integer()
. 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.- ...
Currently not used.
- drop
A
logical
scalar: should the result be coerced to the lowest possible dimension? This only works for extracting elements, not for the replacement. Defaults toFALSE
.- value
A possible value for the element(s) of
x
.
Examples
## Data from Aitchison 1986
data("hongite")
## Coerce to compositional data
coda <- as_composition(hongite)
head(coda)
#> <CompositionMatrix: 6 x 5>
#> A B C D E
#> H1 0.488 0.317 0.038 0.064 0.093
#> H2 0.482 0.238 0.090 0.092 0.098
#> H3 0.370 0.091 0.342 0.095 0.102
#> H4 0.509 0.238 0.072 0.101 0.080
#> H5 0.442 0.383 0.029 0.077 0.069
#> H6 0.523 0.262 0.042 0.125 0.048
## Subset
coda[[1, 1]] # Get the first value
#> [1] 0.488
coda[1] # Get the first value
#> [1] 0.488
coda[, ] # Get all values
#> <CompositionMatrix: 25 x 5>
#> A B C D E
#> H1 0.4880000 0.3170000 0.03800000 0.06400000 0.09300000
#> H2 0.4820000 0.2380000 0.09000000 0.09200000 0.09800000
#> H3 0.3700000 0.0910000 0.34200000 0.09500000 0.10200000
#> H4 0.5090000 0.2380000 0.07200000 0.10100000 0.08000000
#> H5 0.4420000 0.3830000 0.02900000 0.07700000 0.06900000
#> H6 0.5230000 0.2620000 0.04200000 0.12500000 0.04800000
#> H7 0.4460000 0.3300000 0.04600000 0.12200000 0.05600000
#> H8 0.3460000 0.0520000 0.42900000 0.09600000 0.07700000
#> H9 0.4120000 0.1170000 0.26700000 0.09600000 0.10800000
#> H10 0.4260000 0.4660000 0.00700000 0.05600000 0.04500000
#> H11 0.4990000 0.1950000 0.11400000 0.09500000 0.09700000
#> H12 0.4520000 0.3730000 0.02700000 0.05500000 0.09300000
#> H13 0.3270000 0.0850000 0.38900000 0.08000000 0.11900000
#> H14 0.4140000 0.1290000 0.23400000 0.15800000 0.06500000
#> H15 0.4620000 0.1750000 0.15800000 0.08300000 0.12200000
#> H16 0.3230000 0.0730000 0.40900000 0.12900000 0.06600000
#> H17 0.4320000 0.4430000 0.01000000 0.07800000 0.03700000
#> H18 0.4954955 0.3233233 0.03103103 0.08708709 0.06306306
#> H19 0.4230000 0.1580000 0.20400000 0.08300000 0.13200000
#> H20 0.4460000 0.1150000 0.23800000 0.11600000 0.08500000
#> H21 0.4580000 0.1660000 0.16800000 0.12000000 0.08800000
#> H22 0.4990000 0.2500000 0.06800000 0.10900000 0.07400000
#> H23 0.4860000 0.3400000 0.02500000 0.09400000 0.05500000
#> H24 0.4550000 0.1660000 0.17600000 0.09600000 0.10700000
#> H25 0.4590000 0.2490000 0.09700000 0.09800000 0.09700000
coda[1, ] # Get the first row
#> <CompositionMatrix: 1 x 5>
#> A B C D E
#> H1 0.488 0.317 0.038 0.064 0.093
## Subcomposition
subcoda <- coda[, 1:3] # Get the first three column
head(subcoda)
#> <CompositionMatrix: 6 x 3>
#> A B C
#> H1 0.488 0.317 0.038
#> H2 0.482 0.238 0.090
#> H3 0.370 0.091 0.342
#> H4 0.509 0.238 0.072
#> H5 0.442 0.383 0.029
#> H6 0.523 0.262 0.042