step_harmonic: Generate harmonics
In jkennel/waterlevel: Well Water Level Analysis Tools

Description Usage Arguments Details Value See Also Examples

'step_harmonic' creates a *specification* of a recipe step for harmonics (sin and cos terms).

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step_harmonic(recipe, ..., role = "harmonic", trained = FALSE,
  freq = 1, prefix = "harmonic_", default = NA, columns = NULL,
  skip = FALSE, id = rand_id("harmonic"))

`recipe`	A recipe object. The step will be added to the sequence of operations for this recipe.
`...`	One or more selector functions to choose which variables are affected by the step. See [selections()] for more details. For the 'tidy' method, these are not currently used.
`role`	Defaults to "harmonic"
`trained`	A logical to indicate if the quantities for preprocessing have been estimated.
`freq`	`numeric vector` frequencies for sin and cos
`prefix`	A prefix for generated column names, default to "harmonic_".
`default`	Passed to `dplyr::lag`, determines what fills empty rows left by lagging (defaults to NA).
`columns`	A character string of variable names that will be populated (eventually) by the `terms` argument.
`skip`	A logical. Should the step be skipped when the recipe is baked by `bake.recipe()`? While all operations are baked when `prep.recipe()` is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using `skip = TRUE` as it may affect the computations for subsequent operations
`id`	A character string that is unique to this step to identify it.

'step_harmonic' calculates the Earth tide harmonics

An updated version of 'recipe' with the new step added to the sequence of existing steps (if any). For the 'tidy' method, a tibble with columns 'terms' which is the columns that will be affected and 'holiday'.

[step_earthtide()] [recipe()] [prep.recipe()] [bake.recipe()]

data(transducer)

rec <- recipe(wl ~ .,
              data = transducer[1:1000, list(datetime, wl)])

with_et <- rec %>%
  step_harmonic(datetime, freq = c(1, 1.93, 2)) %>% 
  prep() %>%
  juice()