An individual management procedure (MP) is run for a number of years, on an operating model, observation error model, control and arguments.
mp(
om,
oem = NULL,
iem = NULL,
ctrl,
args,
scenario = "NA",
tracking = "missing",
logfile = tempfile(),
verbose = TRUE,
parallel = TRUE
)The operating model (OM), an object of class FLom or FLombf.
The observation error model (OEM), an object of class FLoem.
The implementation error model (IEM), an object of class FLiem.
A control structure for the MP run, an object of class mpCtrl.
MSE arguments, list. Only 'iy', the intermediate (starting) year, is required.
Name of the scenario tested in this run, character.
Extra elements (rows) to add to the standard tracking FLQuant in its first dimensions, character.
Should output be verbose or not, logical.
An object of class FLmse.
# dataset contains both OM (FLom) and OEM (FLoem)
data(sol274)
#> Warning: namespace ‘DBI’ is not available and has been replaced
#> by .GlobalEnv when processing object ‘om’
# choose sa and hcr
control <- mpCtrl(list(
est = mseCtrl(method=perfect.sa),
hcr = mseCtrl(method=catchSSB.hcr,
args=list(MSY=14000))))
tes <- mp(om, oem=oem, ctrl=control, args=list(iy=2017))
#> 2017 -
#> Warning: longer object length is not a multiple of shorter object length
#> Call to oem method failed, check inputs
#> <simpleError in (function (stk, deviances, observations, args, tracking) { y0 <- ac(args$y0) dy <- ac(args$dy) dyrs <- ac(seq(args$dy - args$frq + 1, args$dy)) if (!all(names(deviances) == c("stk", "idx"))) stop("deviances(oem) must have elements 'stk' and 'idx'.") if (!all(names(observations) == c("stk", "idx"))) stop("observations(oem) must have elements 'stk' and 'idx'.") simp <- (dim(observations$stk)[c(3, 4, 5)] == 1) + (dim(stk)[c(3, 4, 5)] == 1) < 2 if (any(simp)) stk <- simplify(stk, c("unit", "season", "area")[simp], harvest = FALSE) stk <- window(stk, start = y0, end = dy, extend = FALSE) if (!is.null(deviances$stk)) { for (i in names(deviances$stk)) { slot(stk, i)[, dyrs] <- do.call(i, list(object = stk))[, dyrs] * deviances$stk[[i]][, dyrs] + 0.001 } landings(stk)[, dyrs] <- computeLandings(stk[, dyrs]) discards(stk)[, dyrs] <- computeDiscards(stk[, dyrs]) catch(stk)[, dyrs] <- computeCatch(stk[, dyrs]) observations$stk[, dyrs] <- stk[, dyrs] } idx <- observations$idx upi <- unlist(lapply(idx, function(x) unname(range(x, "maxyear")) > args$dy)) if (is.null(deviances$idx) | length(deviances$idx) == 0) { deviances$idx <- lapply(observations$idx, function(x) index.q(x) %=% 1) } idx[upi] <- Map(function(x, y) { res <- survey(stk[, dyrs], x[, dyrs], sel = sel.pattern(x)[, dyrs], index.q = index.q(x)[, dyrs] * y[, dyrs]) index(res)[index(res) == 0] <- c(min(index(res)[index(res) > 0]/2)) index(x)[, dyrs] <- index(res) return(window(x, end = dy)) }, x = idx[upi], y = deviances$idx[upi]) for (i in seq(idx[upi])) observations$idx[upi][[i]][, dyrs] <- idx[upi][[i]][, dyrs] list(stk = stk, idx = idx, observations = observations, tracking = tracking)})(deviances = list(stk = list(catch.n = new("FLQuant", .Data = structure(c(1.14961555357345, 1.15159686412954, 0.988995796484863, 1.01144041980525, 1.17446100392486, 0.814581855443871, 0.824061196001491, 1.01559779425034, 1.08727280439922, 0.911860692454371, 1.05149802445468, 1.01240966849453, 1.06680794883527, 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