gadget3 (version 0.14-0)

array_utils: Gadget3 array-handling utilities

Description

Tools to make munging array reports easier

Usage

g3_array_agg(
        ar,
        margins = NULL,
        agg = c(
            "sum",
            "length_mean", "length_sd",
            "predator_length_mean", "predator_length_sd" ),
        opt_time_split = !("time" %in% margins || "time" %in% ...names()),
        opt_length_midlen = FALSE,
        ... )
g3_array_combine(
        arrays,
        agg = sum,
        init_val = 0 )
g3_array_plot(
        ar,
        legend = "topright" )

Value

An array, filtered by ... and aggregated by margins.

If ar was a list, a list of filtered/aggregated arrays

Arguments

ar

Input array, e.g. dstart_fish__num from a model report, or list of arrays

arrays

List of input arrays, can be a nested list as generated by cons in g3_quota_assess

margins

dimension names to include in the final array, e.g. c("age", "year") to generate a report by-year & age. If NULL, no aggregation is done

agg

Function or character. Function to use when aggregating, or name of one of the built-in functions

init_val

The initial value to use when combining arrays

opt_time_split

Boolean, should we split up "time" into separate "year" & "step" dimensions?

opt_length_midlen

Boolean, should we convert "length"

legend

Location of legend, passed to legend's x parameter

...

Filters to apply to any dimension, including "year" / "step" if opt_time_split is TRUE. e.g. length = 40, age = 5, step = 1

Details

g3_array_agg allows you to both filter & aggregate an array at the same time.

Specifying a filter in ... is simplfied in comparison to a regular R subset:

1. You can give the dimensions in any order

2. Values are always interpreted, age = 3 will be interpreted as "age3", not the third age.

For particular dimensions we have extra helpers:

age

Numeric ages e.g. age = 5 are converted to "age5", as generated by gadget3

length

Numeric lengths will pick a value within groups, e.g. with lengths "10:20", "20:30", length = 15 will pick the smaller lengthgroup

g3_array_combine generates the union of 2 disjoint arrays, so you can combine aggregated output from an immature and mature stock for example.

g3_array_plot will plot the contents of an array, for arrays with 2 dimensions or less.

Examples

# Generate an array to test with
dn <- list(
    length = c("50:60", "60:70", "70:Inf"),
    age = paste0("age", 0:5),
    time = paste0(rep(1990:1996, each = 2), c("-01", "-02")) )
ar <- array(
    seq_len(prod(sapply(dn, length))),
    dim = sapply(dn, length),
    dimnames = dn)
ar[,,"1994-02", drop = FALSE]
g3_array_plot(ar[,,"1994-02"])
g3_array_plot(ar["50:60","age3",])

# Generate by-year report for ages 2..4
g3_array_agg(ar, c('age', 'year'), age = 2:4)

# ...for only step 1
g3_array_agg(ar, c('age', 'year'), age = 2:4, step = 1)

# Report on smallest length group, for each timestep
g3_array_agg(ar, c('length', 'time'), length = 55)
# Use midlen as the dimension name
g3_array_agg(ar, c('length', 'time'), length = 55, opt_length_midlen = TRUE)

# Combine 2 arrays with disjoint age ranges into one list
g3_array_combine(list(
    g3_array_agg(ar, c('age', 'year'), age = 2:4),
    g3_array_agg(ar / 1000, c('age', 'year'), age = 3:5) ))

# We can aggregate lists of arrays, applying the same options for each
list(a = ar, b = ar * 10) |> g3_array_agg(c('year', 'age'), length = 55)

# We can aggregate then combine
list(a = ar, b = ar * 10) |>
     g3_array_agg(c('year', 'age'), length = 55) |> g3_array_combine()