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Redesign key quantity extraction/insertion pipeline #205

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2b3d775
Create first draft of key quantities template csv; start drafting pip…
sbreitbart-NOAA Mar 5, 2026
816b4cf
Finished draft of key quantities pipeline for landings plot
sbreitbart-NOAA Mar 12, 2026
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1 change: 1 addition & 0 deletions DESCRIPTION
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Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,7 @@ Imports:
naniar,
prodlim,
quarto,
rlang,
scales,
stats,
stringr,
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24 changes: 23 additions & 1 deletion R/plot_landings.R
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Expand Up @@ -99,10 +99,32 @@ plot_landings <- function(

### Make RDA ----
if (make_rda) {

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@Schiano-NOAA Schiano-NOAA Mar 16, 2026

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Is this chunk going to be unique to all plots? Like we won't be able to generalize this and make it more concise?

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@Schiano-NOAA Schiano-NOAA Mar 16, 2026

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Line 102-108

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@sbreitbart-NOAA sbreitbart-NOAA Mar 16, 2026

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Lines 102-108 are where key quantities are calculated for this plot (and I'd expect this is where each plot/table's KQs will be calculated too). The next couple of functions are where the generalization happens: in the exporting of the KQs into a csv, and the insertion of the KQs into the alt text/captions csv.

# Obtain relevant key quantities for captions/alt text
landings.end.year <- max(prepared_data$year)
landings.max <- max(prepared_data$estimate)
landings.min <- min(prepared_data$estimate)
landings.start.year <- min(prepared_data$year)
landings.units <- unit_label

# calculate & export key quantities
export_kqs(landings.end.year,
landings.max,
landings.min,
landings.start.year,
landings.units)

# Add key quantities to captions/alt text
insert_kqs(landings.end.year,
landings.max,
landings.min,
landings.start.year,
landings.units)

create_rda(
object = plt,
# get name of function and remove "plot_" from it
topic_label = gsub("plot_", "", as.character(sys.call()[[1]])),
topic_label = gsub("plot_", "", as.character(sys.call()[[1]])),
fig_or_table = "figure",
dat = dat,
dir = figures_dir,
Expand Down
219 changes: 118 additions & 101 deletions R/utils_rda.R
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Expand Up @@ -2,6 +2,123 @@
# RDA utility functions
# @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@

# TODO: update new fxns to work with a specified 'dir' instead of default 'getwd()'?

# Fill in key quantities in template
fill_in_kqs <- function(df, ...) {

arg_names <- sapply(substitute(list(...))[-1], deparse)
arg_values <- list(...)

lookup_df <- tibble::tibble(
key_quantity = arg_names,
value_new = purrr::map_chr(arg_values, as.character)
)

# TODO: Add message when certain values aren't overwritten (already present)
df <- df |>
dplyr::mutate(across(everything(), as.character)) |>
dplyr::left_join(lookup_df, by = "key_quantity") |>
dplyr::mutate(value = dplyr::if_else(
(is.na(value) | value == "" & !is.na(value_new)),
value_new,
value)) |>
dplyr::select(-value_new)
}

# Calculate and export key quantities
## kqs (e.g., landings.end.year) are the ellipsis args
export_kqs <- function(...) {

# Open new or existing key quantities csv
if (file.exists(fs::path(getwd(), "key_quantities.csv"))) {
cli::cli_alert_info("Key quantities text file (key_quantities.csv) exists. Newly calculated key quantities will be added to it.", wrap = TRUE)
kqs <- utils::read.csv(file.path(getwd(), "key_quantities.csv"))
} else {
kqs <- utils::read.csv(
system.file("resources", "key_quantity_template.csv", package = "stockplotr")
)
}

# kqs (e.g., landings.end.year) are the ellipsis args
kqs_filled <- fill_in_kqs(kqs,
...)

utils::write.csv(
x = kqs_filled,
file = fs::path(getwd(), "key_quantities.csv"),
row.names = FALSE
)

}

# Add key quantities to captions/alt text csv
## kqs (e.g., landings.end.year) are the ellipsis args
insert_kqs <- function(...) {
if (file.exists(fs::path(getwd(), "captions_alt_text.csv"))) {
cli::cli_alert_info("Captions/alternative text file (captions_alt_text.csv) exists. Newly calculated key quantities will be added to it.", wrap = TRUE)
caps_alttext <- utils::read.csv(fs::path(getwd(), "captions_alt_text.csv"))
} else {
caps_alttext <- utils::read.csv(
system.file("resources", "captions_alt_text_template.csv", package = "stockplotr")
)
}

create_patterns <- function(...) {
# Capture the names from the dots without evaluating them yet
arg_names <- sapply(rlang::enexprs(...), as.character)

# Get the actual values
vals <- list(...)

# Combine them into a named character vector
stats::setNames(as.character(vals), arg_names)
}

# insert new kqs into alt text/caps csv, where applicable
patterns_replacements <- create_patterns(...) |>
# If a value = NA, then make it "NA" to avoid errors
tidyr::replace_na("NA")

# replace values in caption column
caps_alttext$caption <- stringr::str_replace_all(
caps_alttext$caption,
patterns_replacements
)

# replace values in alt text column
caps_alttext$alt_text <- stringr::str_replace_all(
caps_alttext$alt_text,
patterns_replacements
)

# export df with updated captions and alt text to csv
utils::write.csv(
x = caps_alttext,
file = fs::path(getwd(), "captions_alt_text.csv"),
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@Schiano-NOAA Schiano-NOAA Mar 16, 2026

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I think this assumes that this file is in the wd. We either need to document that or allow it to be changed

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@sbreitbart-NOAA sbreitbart-NOAA Mar 16, 2026

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Yes, for sure! I was thinking the same thing. I'll set the wd as the export folder for now but we can make that customizable later

row.names = FALSE
)

# message explaining the extracted and inserted key quantities
replaced_vals <- patterns_replacements |>
as.data.frame() |>
tibble::rownames_to_column() |>
dplyr::rename(
"name" = 1,
"key_quantity" = 2
)

cli::cli_h3("The following key quantities were extracted and inserted into 'captions_alt_text.csv' and 'key_quantities.csv':")
for (i in 1:dim(replaced_vals)[1]) {
cli::cli_li(paste0(
replaced_vals[i, 1],
": ",
replaced_vals[i, 2]
))
}
}


#' Create the rda package for a plot or table
#'
#' @param object Table or plot object
Expand Down Expand Up @@ -46,38 +163,6 @@ create_rda <- function(
unit_label = "mt",
table_df = NULL
) {
# run write_captions.R if its output doesn't exist
if (!file.exists(
fs::path(getwd(), "captions_alt_text.csv")
)
) {
write_captions(
dat = dat,
dir = dir,
year = max(dat$year, na.rm = TRUE) # this is not right I think
)
}

# Remove non-numeric strings from year
year <- dat |>
dplyr::filter(
year %notin% c("Virg", "S/Rcurve", "Init", "selex"),
era == "time"
) |>
dplyr::mutate(year = as.numeric(year))

# add more key quantities included as arguments in this fxn
add_more_key_quants(
dat,
topic = topic_label,
fig_or_table = fig_or_table,
dir = dir,
end_year = max(year$year, na.rm = TRUE),
units = unit_label,
ref_pt = ref_point,
ref_line = ref_line,
scaling = scale_amount
)

# extract this plot's caption and alt text
caps_alttext <- extract_caps_alttext(
Expand All @@ -96,7 +181,7 @@ create_rda <- function(

export_rda(
object = object,
caps_alttext = caps_alttext, # Load in of this is missing I think
caps_alttext = caps_alttext,
figures_tables_dir = dir,
topic_label = topic_label,
fig_or_table = fig_or_table,
Expand Down Expand Up @@ -880,62 +965,6 @@ write_captions <- function(dat, # converted model output object
# F.Ftarg : added with add_more_key_quants


## landings plot

# start year of landings plot
landings.start.year <- dat |>
dplyr::filter(
c(module_name == "t.series" & grepl("landings_observed", label)) | c(module_name == "CATCH" & grepl("ret_bio", label)),
# t.series is associated with a conversion from BAM output and CATCH with SS3 converted output
!is.na(fleet)
) |>
dplyr::slice(which.min(year)) |>
dplyr::select(year) |>
as.numeric()

# end year of landings plot
landings.end.year <- dat |>
dplyr::filter(
c(module_name == "t.series" & grepl("landings_observed", label)) | c(module_name == "CATCH" & grepl("ret_bio", label)),
# t.series is associated with a conversion from BAM output and CATCH with SS3 converted output
!is.na(fleet)
) |>
dplyr::slice(which.max(year)) |>
dplyr::select(year) |>
as.numeric()

# units of landings (plural)
# landings.units : added with add_more_key_quants

# minimum landings
landings.min <- dat |>
dplyr::filter(
c(module_name == "t.series" & grepl("landings_observed", label)) | c(module_name == "CATCH" & grepl("ret_bio", label)),
# t.series is associated with a conversion from BAM output and CATCH with SS3 converted output
!is.na(fleet)
) |>
dplyr::slice(which.min(estimate)) |>
dplyr::select(estimate) |>
as.numeric() |>
round(digits = 2)

# maximum landings
landings.max <- dat |>
dplyr::filter(
c(module_name == "t.series" & grepl("landings_observed", label)) | c(module_name == "CATCH" & grepl("ret_bio", label)),
# t.series is associated with a conversion from BAM output and CATCH with SS3 converted output
!is.na(fleet)
) |>
dplyr::group_by(fleet, year) |>
dplyr::summarise(max_est = max(estimate)) |>
dplyr::filter(!is.na(max_est)) |>
dplyr::group_by(year) |>
dplyr::summarise(max_est_yr = sum(max_est)) |>
dplyr::slice(which.max(max_est_yr)) |>
dplyr::select(max_est_yr) |>
as.numeric() |>
round(digits = 2)

## natural mortality (M)- bam examples have label as natural_mortality
## but other formats don't (in input)
# minimum age of M
Expand Down Expand Up @@ -1492,9 +1521,6 @@ write_captions <- function(dat, # converted model output object
## catch
# catch.fleet <- # fleet

## landings
# landings.tbl.units <- # landings units; remove if units already in table

## discards
# discards.tbl.units <- # discards units

Expand Down Expand Up @@ -1539,12 +1565,6 @@ write_captions <- function(dat, # converted model output object
"F.max" = as.character(F.max),
# 'Ftarg' = as.character(Ftarg),

## landings plot
"landings.start.year" = as.character(landings.start.year),
"landings.end.year" = as.character(landings.end.year),
"landings.min" = as.character(landings.min),
"landings.max" = as.character(landings.max),

## natural mortality (M)
"M.age.min" = as.character(M.age.min),
"M.age.max" = as.character(M.age.max),
Expand Down Expand Up @@ -1687,9 +1707,6 @@ write_captions <- function(dat, # converted model output object
# ## catch
# 'catch.fleet' = as.character(catch.fleet),
#
# ## landings
# 'landings.tbl.units' = as.character(landings.tbl.units),
#
# ## discards
# 'discards.tbl.units' = as.character(discards.tbl.units),
#
Expand Down
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