A basic example showing how to use afscISS for a
production run.
library(afscISS)
#> Loading required package: data.table
# set some globals
species = c(30150, 30152) # dusky rockfish
region = 'goa'
comp = 'length'
sex_cat = 4 # post expansion
spec_case = 'dr' # dusky rockfish is a special casePlot the length composition ISS.
plot_ISS(species = species,
region = region,
comp = comp,
sex_cat = sex_cat,
spec_case = spec_case)
Get the length composition data frame.
get_comp(species = species,
region = region,
comp = comp,
sex_cat = sex_cat,
spec_case = spec_case)
#> # A tidytable: 557 × 8
#> year species_code sex sex_c length prop q2_5th q97_5th
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1990 301502 4 4 22 0.00808 0 0.0336
#> 2 1990 301502 4 4 23 0.00404 0 0.0163
#> 3 1990 301502 4 4 24 0.00202 0 0.00962
#> 4 1990 301502 4 4 25 0.00606 0 0.0221
#> 5 1990 301502 4 4 27 0.00649 0 0.0256
#> 6 1990 301502 4 4 28 0.00606 0 0.0227
#> 7 1990 301502 4 4 29 0.00657 0 0.0237
#> 8 1990 301502 4 4 31 0.00102 0 0.00472
#> 9 1990 301502 4 4 32 0.00692 0 0.0237
#> 10 1990 301502 4 4 33 0.000736 0 0.00324
#> # ℹ 547 more rowsExamine the same items for age composition data.
plot_ISS(species = species,
region = region,
comp = 'age',
sex_cat = sex_cat,
spec_case = spec_case)
Get the age composition data frame.
get_comp(species = species,
region = region,
comp = 'age',
sex_cat = sex_cat,
spec_case = spec_case)
#> # A tidytable: 511 × 8
#> year species_code sex sex_c age prop q2_5th q97_5th
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1990 301502 4 4 6 0.00263 0 0.0162
#> 2 1990 301502 4 4 7 0.00103 0 0.00433
#> 3 1990 301502 4 4 8 0.00107 0 0.00427
#> 4 1990 301502 4 4 9 0.00813 0.000727 0.0338
#> 5 1990 301502 4 4 10 0.108 0.00337 0.378
#> 6 1990 301502 4 4 11 0.131 0.00460 0.318
#> 7 1990 301502 4 4 12 0.112 0.0130 0.285
#> 8 1990 301502 4 4 13 0.152 0 0.328
#> 9 1990 301502 4 4 14 0.200 0.0414 0.406
#> 10 1990 301502 4 4 15 0.100 0.0107 0.263
#> # ℹ 501 more rows