Create data of input rate information for a single input with some checks on the validity of the information provided by the user. This can be used to assign rates to experiment plots using assign_rates().
Usage
prep_rate(
plot_info,
gc_rate,
unit,
rates = NULL,
min_rate = NA,
max_rate = NA,
num_rates = 5,
design_type = NA,
rank_seq_ws = NULL,
rank_seq_as = NULL,
rate_jump_threshold = NA
)
Arguments
- plot_info
(data.frame) plot information created by make_input_plot_data
- gc_rate
(numeric) Input rate the grower would have chosen if not running an experiment. This rate is assigned to the non-experiment part of the field. This rate also becomes one of the trial input rates unless you specify the trial rates directly using rates argument
- unit
(string) unit of input
- rates
(numeric vector) Default is NULL. Sequence of trial rates in the ascending order.
- min_rate
(numeric) minimum input rate. Ignored if rates are specified.
- max_rate
(numeric) maximum input rate. Ignored if rates are specified
- num_rates
(numeric) Default is 5. It has to be an even number if design_type is "ejca". Ignored if rates are specified.
- design_type
(string) type of trial design. available options are Latin Square ("ls"), Strip ("str"), Randomized Strip ("rstr"), Randomized Block ("rb"), Sparse ("sparse"), and Extra Jump-conscious Alternate "ejca". See the article on trial design for more details.
- rank_seq_ws
(integer) vector of integers indicating the order of the ranking of the rates, which will be repeated "within" a strip.
- rank_seq_as
(integer) vector of integers indicating the order of the ranking of the rates, which will be repeated "across" strip for their first plots.
- rate_jump_threshold
(integer) highest jump in rate rank acceptable
Examples
plot_info <-
prep_plot(
input_name = "seed",
unit_system = "imperial",
machine_width = 60,
section_num = 24,
harvester_width = 30,
plot_width = 30
)
#>
prep_rate(
plot_info,
gc_rate = 30000,
unit = "seeds",
rates = c(20000, 25000, 30000, 35000, 40000)
)
#> You did not specify design_type. It is assumed to be of type ls.
#> # A tibble: 1 × 12
#> input_name design_type gc_rate unit tgt_rate_original tgt_rate_equiv min_rate
#> <chr> <lgl> <dbl> <chr> <list> <list> <lgl>
#> 1 seed NA 30000 seeds <dbl [5]> <dbl [5]> NA
#> # ℹ 5 more variables: max_rate <lgl>, num_rates <int>, rank_seq_ws <list>,
#> # rank_seq_as <list>, rate_jump_threshold <lgl>