# Reads MPD or MCMC estimates and data from iSCAM file structure into an operating model

Source:`R/iSCAM2OM.R`

`iSCAM2OM.Rd`

Functions for importing an iSCAM assessment. From a fitted model, `iSCAM2OM`

populates the various slots of an operating model and `iSCAM2Data`

generates a Data object.
These functions rely on several functions written by Chris Grandin (DFO PBS).

## Usage

```
iSCAM2OM(
iSCAMdir,
nsim = 48,
proyears = 50,
mcmc = FALSE,
spawn_time_frac = 0,
Name = "iSCAM model",
Source = "No source provided",
length_timestep = 1,
nyr_par_mu = 2,
Author = "No author provided",
report = FALSE,
silent = FALSE
)
iSCAM2Data(
iSCAMdir,
Name = "iSCAM assessment",
Source = "No source provided",
length_timestep = 1,
Author = "No author provided"
)
```

## Arguments

- iSCAMdir
A folder with iSCAM input and output files in it. Alternatively, a list returned by load.iscam.files.

- nsim
The number of simulations to take for parameters with uncertainty (for OM@cpars custom parameters)

- proyears
The number of MSE projection years

- mcmc
Logical, whether to use mcmc samples to create custom parameters cpars. Alternatively, a list returned by read.mcmc. Set the seed for the function to sub-sample the mcmc samples.

- spawn_time_frac
Numeric between 0-1 indicating when spawning occurs within the time step

- Name
The name of the operating model

- Source
Reference to assessment documentation e.g. a url

- length_timestep
How long is a model time step in years (e.g. a quarterly model is 0.25, a monthly model 1/12) (currently only uses annual time step)

- nyr_par_mu
integer, the number of recent years to estimate vulnerability over for future projections

Who did the assessment

- report
logical should a numbers at age reconstruction plot be produced?

- silent
logical should progress reporting be printed to the console?

## Biological parameters

The function calls `model <- load.iscam.files(iSCAMdir)`

and grabs the following matrices:

`model$mpd$d3_weight_mat`

- fecundity (product of weight and maturity at age)`model$mpd$ma`

- maturity at age

## MPD historical reconstruction

The function calls `model <- load.iscam.files(iSCAMdir)`

and then grabs the following matrices:

`model$mpd$N`

- abundance at age`model$mpd$F`

- fishing mortality at age`model$mpd$M`

- natural mortality at age

If a delay-difference model is recognized, then the following is used instead:

`model$mpd$F_dd`

- fishing mortality at age`model$mpd$M_dd`

- natural mortality at age

Abundance at age is reconstructed using `model$mpd$rt`

(recruitment) and projected with `F_dd`

and
`M_dd`

to match `model$mpd$numbers`

.

## MCMC historical reconstruction

If `mcmc = TRUE`

the function calls `mcmc_model <- read.mcmc(iSCAMdir)`

, and grabs `nsim`

sub-samples of the MCMC output
through the following arrays:

`mcmc_model$params`

and`mcmc_model$ft`

- fishing mortality at age from the fleet selectivity parameters and apical F's`mcmc_model$m`

- year-specific natural mortality at age`mcmc_model$params$rinit`

and`mcmc_model$rt`

- recruitment and abundance

## Start age

While the iSCAM start age can be greater than zero, abundance at age is back-calculated to age zero with M, maturity, growth = 0. In this way, the stock-recruit dynamics from iSCAM are preserved.

These arrays are then passed to Assess2OM to generate the operating model.

## Reference points

iSCAM calculates the stock-recruit relationship and subsequently a single set of MSY and unfished reference points using R0, steepness, and unfished spawners per recruit from the mean M, fecundity, and growth (mean with respect to time).

R0 and h are recalculated for the operating model by obtaining the stock-recruit alpha and beta from the
iSCAM parameters and the mean unfished spawners per recruit in the first `ageM`

(age of 50% maturity) years.