Basic example

A basic example showing how to use afscISS for a production run.

library(afscISS)
#> Loading required package: data.table
#> 
#> Attaching package: 'data.table'
#> The following object is masked from 'package:base':
#> 
#>     %notin%

# 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 case

Plot 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: 580 × 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 0.00805       0 0.0316 
#>  2  1990       301502     4     4     23 0.00403       0 0.0169 
#>  3  1990       301502     4     4     24 0.00201       0 0.00871
#>  4  1990       301502     4     4     25 0.00604       0 0.0254 
#>  5  1990       301502     4     4     27 0.00645       0 0.0222 
#>  6  1990       301502     4     4     28 0.00604       0 0.0227 
#>  7  1990       301502     4     4     29 0.00655       0 0.0244 
#>  8  1990       301502     4     4     31 0.00101       0 0.00491
#>  9  1990       301502     4     4     32 0.00686       0 0.0234 
#> 10  1990       301502     4     4     33 0.000789      0 0.00369
#> # ℹ 570 more rows

Examine 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: 544 × 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 0.00260 0        0.0177 
#>  2  1990       301502     4     4     7 0.00117 0        0.00387
#>  3  1990       301502     4     4     8 0.00106 0        0.00566
#>  4  1990       301502     4     4     9 0.00809 0.000894 0.0266 
#>  5  1990       301502     4     4    10 0.108   0.0102   0.311  
#>  6  1990       301502     4     4    11 0.131   0.00948  0.317  
#>  7  1990       301502     4     4    12 0.112   0        0.307  
#>  8  1990       301502     4     4    13 0.152   0.0111   0.366  
#>  9  1990       301502     4     4    14 0.200   0.0471   0.421  
#> 10  1990       301502     4     4    15 0.1000  0.00839  0.281  
#> # ℹ 534 more rows