A prototype for the model_fun argument to mm_model_by_ply — mm_model_by_ply

This function does nothing but has the proper form for a model_fun passed to mm_model_by_ply Other functions to be used as model_fun may call inheritParams to use the parameter definitions given here.

Usage

mm_model_by_ply_prototype(
  data_ply = v(mm_data(NULL)),
  data_daily_ply = v(mm_data(NULL)),
  day_start = NA,
  day_end = NA,
  ply_date = NA,
  ply_validity = NA,
  timestep_days = NA,
  ...
)

Arguments

data_ply: a data.frame containing all relevant, validated modeling data for a single ply of data. (1 ply ~= 1 date, although the day length has been specified by day_start and day_end and may not be exactly 24 hours)
data_daily_ply: NULL or a data.frame containing inputs with a daily timestep.
day_start: start time (inclusive) of a day's data in number of hours from the midnight that begins the date. For example, day_start=-1.5 indicates that data describing 2006-06-26 begin at 2006-06-25 22:30, or at the first observation time that occurs after that time if day_start doesn't fall exactly on an observation time.
day_end: end time (exclusive) of a day's data in number of hours from the midnight that begins the date. For example, day_end=30 indicates that data describing 2006-06-26 end at the last observation time that occurs before 2006-06-27 06:00.
ply_date: the modal date of this ply of data and data_daily, and the date by which this ply should be referred topresent.
ply_validity: the output of mm_is_valid_day as applied to this data_ply for those tests specified in day_tests. Those tests will have been run before this function is called. The result is TRUE if the ply is entirely valid, or a character vector containing one or more error messages if any tests failed.
timestep_days: numeric length of the mean timestep for this day, if requested by setting timestep_days to TRUE or a numeric value in the call to mm_model_by_ply
...: other args that were passed untouched from the function calling mm_model_by_ply, through mm_model_by_ply, and finally to this function.

Examples

mm_model_by_ply_prototype()
#> # A tibble: 1 × 9
#>   data_ply_start data_ply_end data_ply_nrow data_daily_ply_date day_start
#>   <lgl>          <lgl>                <dbl> <chr>               <lgl>    
#> 1 NA             NA                       0 ""                  NA       
#> # ℹ 4 more variables: day_end <lgl>, ply_date <lgl>, ply_validity <chr>,
#> #   timestep_days <lgl>
mm_model_by_ply_prototype(extra_arg=7:12)
#> # A tibble: 1 × 10
#>   data_ply_start data_ply_end data_ply_nrow data_daily_ply_date day_start
#>   <lgl>          <lgl>                <dbl> <chr>               <lgl>    
#> 1 NA             NA                       0 ""                  NA       
#> # ℹ 5 more variables: day_end <lgl>, ply_date <lgl>, ply_validity <chr>,
#> #   timestep_days <lgl>, extra_arg <int>