record_grooming_rule: record_grooming_rule

In Craig44/stockassessmenthelper: Package to help plot stock assessment models and functionality

record_grooming_rule

Description

record_grooming_rule

Usage

record_grooming_rule(
  df,
  index,
  catch.col,
  record = NULL,
  rule,
  year.col = NULL,
  attribute = "catch",
  keep_NA = T
)

Arguments

df	the df we are manipulating
index	a conditional index length(index) == nrow(df). TRUE means it stays, FALSE means it is being excluded from
catch.col	column label for the catch variable
record	a data.frame to append the summaries to.
rule	the label for the grooming rule (string)
year.col	column label for the year variable. Can be ommited, if supplied the Data.frame will break down catch and number of events removed from each grooming rule by year.
attribute	if by year specify the attribute to record catch absoulte catch events number of events relative_catch is the percent change in catch from applying the rule relative_events is the percent change in number of events from applying the rule cumulative_catch track the catch left in the data set after each grooming rule cumulative_events track the events left in the data set after each grooming rule
keep_NA	if index has NA's and this is true then they stay in the data

Details

a utility function to record the effect of grooming rules on data sets. It will note remove the index from the dataset. TODO: As well as recording the effect of a groomong rule on catch and number of records summarise spatail distribution.

Value

the record data frame with new entries for the grooming rule

Examples

## Not run: 
## example of plotting this output
## plot records
melt_total = melt(total_grooming_record, id.vars = "rule")
melt_total$rule = factor(melt_total$rule, ordered = T, levels = total_grooming_record$rule)
ggplot(melt_total %>% filter(variable %in%  c("events", "catch")), 
      aes(y = value /1000, x = rule, group = 1)) +
 geom_line(size = 2, linetype = "dotted") +
 geom_point(size = 4, aes(col = rule)) + 
 theme(axis.text.x = element_blank()) +
 ylab("") +
 ylim(0,1600) +
 facet_wrap(~variable) +
 xlab("")

## End(Not run)

Craig44/stockassessmenthelper documentation built on April 14, 2023, 10:57 a.m.