tf-objects — tf_nest" />

Similar in spirit to tidyr::nest(). This turns tables in "long" format, where one column (.id) defines the unit of observation, one column (.arg) defines the evaluation of the functional observations, and other columns (...) define the values of the functions into a (much shorter) table containing tfd-objects. All other variables are checked for constancy over .id and appended as well.

tf_nest(
  data,
  ...,
  .id = "id",
  .arg = "arg",
  domain = NULL,
  evaluator = "tf_approx_linear",
  resolution = NULL
)

Arguments

data

a data frame

...

A selection of columns. If empty, all variables except the .id and .arg columns are selected. You can supply bare variable names, select all variables between x and z with x:z, exclude y with -y. For more options, see the dplyr::select() documentation.

.id

the (bare or quoted) name of the column defining the different observations

.arg

the (bare or quoted) name of the column defining the arg-values of the observed functions

domain

range of the arg.

evaluator

a function accepting arguments x, arg, evaluations. See details for tfd().

resolution

resolution of the evaluation grid. See details for tfd().

Value

a data frame with (at least) .id and tfd columns

Details

domain, resolution and evaluator can be speficied as lists or vectors if you're nesting multiple functional data columns with different properties. Because quasi-quotation is such a bitch, you can only specify the evaluator functions as strings and not as bare names here.

See also

tf_gather(), tf_unnest(), tfd() for domain, evaluator, resolution