View source: R/read_asap3_fit.R
read_asap3_fit | R Documentation |
Gets output from a fit ASAP3 model for plotting with WHAM models.
read_asap3_fit(wd, asap.name, pSPR = 40)
wd |
character, directory where ASAP3 output files are located (ex: 'C:/MY/file/directories/model/'). 5 files are needed: |
asap.name |
character, base name of original .dat file (i.e. without the .dat extension) |
pSPR |
scalar, user-specified percent SPR to use for reference points, expressed as 100*SSBPR(Fspr)/SSBPR(F=0). Default = 40. |
a named list with the following elements:
$years
numeric vector, model years only, e.g. 1972:2020
$years_full
numeric vector, model + proj years, e.g. 1972:2022
. For ASAP this will be the same as $years
.
$selAA
list of length(n_selblocks), first the fleet blocks then indices, i.e. if 4 fleet blocks and 3 indices, selAA[[5]]
is for index 1. Each element is a matrix, years (rows) x ages (cols), selectivity at age
$selblock_pointer_fleets
matrix, n_years x n_fleets, indices of selAA used by each fleet in each year
$selblock_pointer_indices
matrix, n_years x n_indices, indices of selAA used by each index in each year
$MAA
matrix, n_years x n_ages, natural mortality
$log_SSB
matrix, n_years x 2, log-scale spawning stock biomass. 1st col = MLE, 2nd col = SE (from .std file in ADMB).
$log_F
matrix, n_years x 2, log-scale fully-selected F. 1st col = MLE, 2nd col = SE (from .std file in ADMB).
$log_NAA
matrix, n_years x n_ages, numbers at age
$NAA_CV
matrix, n_years x n_ages, CV of numbers at age
$percentSPR
scalar, X% SPR used to calculate reference points, default = 40
$log_Y_FXSPR
matrix, n_years x 2, log-scale yield at FXSPR. 1st col = MLE, 2nd col = SE.
$log_FXSPR
matrix, n_years x 2, log-scale FXSPR. 1st col = MLE, 2nd col = SE.
$log_SSB_FXSPR
matrix, n_years x 2, log-scale SSB at FXSPR, i.e. annual numerator of SPR(FXSPR) * Recruits. 1st col = MLE, 2nd col = SE.
$log_rel_ssb_F_cov
list, length n_years, each element is a 2x2 covariance matrix with SSB / SSB_FXSPR first and F / F_FXSPR second
compare_wham_models
, read_wham_fit
## Not run:
base <- read_asap3_fit(wd=file.path(getwd(),'asap_results'), asap.name='BASE_5C.DAT', pSPR=40)
m1 <- fit_wham(input1)
m2 <- fit_wham(input2)
mods <- list(base=base, m1=m1, m2=m2)
res <- compare_wham_models(mods)
## End(Not run)
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