tfbrackets: Accessing, evaluating, subsetting and subassigning 'tf'...

In tf: S3 Classes and Methods for Tidy Functional Data

Accessing, evaluating, subsetting and subassigning tf vectors

Description

These functions access, subset, replace and evaluate tf objects. For more information on creating tf objects and converting them to/from list, data.frame or matrix, see tfd() and tfb(). See details.

Usage

## S3 method for class 'tf'
x[i, j, interpolate = TRUE, matrix = TRUE]

## S3 replacement method for class 'tf'
x[i] <- value

Arguments

x	an tf.
i	index of the observations (integerish, character or logical, usual R rules apply). Can also be a two-column matrix for extracting specific (function, arg-value) pairs: the first column gives the function indices, the second column gives the arg values at which to evaluate each function. Returns a numeric vector in that case. j must not be provided when i is a matrix.
j	The arg used to evaluate the functions. A (list of) numeric vectors. NOT interpreted as a column number but as the argument value of the respective functional datum. If j is missing but matrix is explicitly given, j defaults to tf_arg(x).
interpolate	should functions be evaluated (i.e., inter-/extrapolated) for values in arg for which no original data is available? Only relevant for the raw data class tfd, for which it defaults to TRUE. Basis-represented tfb are always "interpolated".
matrix	should the result be returned as a matrix or as a list of data.frames? If TRUE, j has to be a (list of a) single vector of arg. See return value.
value	tf object for subassignment. This is typed more strictly than concatenation: subassignment only happens if the common type of value and x is the same as the type of x, so subassignment never changes the type of x but may do a potentially lossy cast of value to the type of x (with a warning).

Details

Note that these break certain (terrible) R conventions for vector-like objects:

• no argument recycling,

• no indexing with NA,

• no indexing with names not present in x,

• no indexing with integers ⁠> length(x)⁠

All of the above will trigger errors.

Value

If i is a two-column matrix, a numeric vector of pointwise evaluations (one per row of i).
If j is missing (and i is not a matrix), a subset of the functions in x as given by i.
If j is given and matrix == TRUE, a numeric matrix of function evaluations in which each row represents one function and each column represents one argval as given in argument j, with an attribute arg=j and row- and column-names derived from x[i] and j.
If j is given and matrix == FALSE, a list of tbl_dfs with columns arg = j and value = evaluations at j for each observation in i.

Examples

x <- 1:3 * tfd(data = 0:10, arg = 0:10)
plot(x)
# this operator's 2nd argument is quite overloaded -- you can:
# 1. simply extract elements from the vector if no second arg is given:
x[1]
x[c(TRUE, FALSE, FALSE)]
x[-(2:3)]
# 2. use the second argument and optional additional arguments to
#    extract specific function evaluations in a number of formats:
x[1:2, c(4.5, 9)] # returns a matrix of function evaluations
x[1:2, c(4.5, 9), interpolate = FALSE] # NA for arg-values not in the original data
x[-3, seq(1, 9, by = 2), matrix = FALSE] # list of data.frames for each function
# 3. use a 2-column matrix to extract specific (function, arg) pairs:
x[cbind(1:3, c(0, 5, 10))] # one value per function
# 4. use matrix= with a missing j to evaluate on the default arg grid:
x[1:2, , matrix = FALSE] # same as x[1:2, tf_arg(x), matrix = FALSE]
# in order to evaluate a set of observed functions on a new grid and
# save them as a functional data vector again, use `tfd` or `tfb` instead:
tfd(x, arg = seq(0, 10, by = 0.01))

tf documentation built on April 7, 2026, 5:07 p.m.