trim: Trim FLR objects using named dimensions

In FLCore: Core package of FLR, fisheries modelling in R.

Description

Subsetting of FLR objects can be carried out using the dimension names by using trim. A number of dimension names and selected dimensions are passed to the method and those are used to subset the input object.

Exceptions are made for those classes where certain slots might differ in one or more dimensions. If trim is applied on an FLQuant object of length 1 in its first dimension and with dimension name equal to 'all', values to trim on specified for that dimension will be ignored. For example, FLStock objects contain slots with length=1 on their first dimension. Specifying values to trim along over the first dimension will have no effect on those slots (catch, landings, discards, and stock). Calculations might need to be carried out to recalculate those slots if their quant-structured counterparts are modified along the first dimension.

Generic function

trim(x)

Methods

signature(x=FLQuant) :

Trims along the specified dimensions.

signature(x=FLComp) :

Trims along the specified dimensions.

signature(x=FLStock) :

Trims along the specified dimensions, but ignores the quant (first) dimension for those slots where it is always of length=1.

signature(x=FLCohort) :

Trims along the specified dimensions.

signature(x=FLIndex) :

Trims along the specified dimensions, but ignores the quant (first) dimension for thoe slots where it is of length=1.

Author(s)

The FLR Team

See Also

FLQuant, FLStock, FLCohort, FLIndex

Examples

data(ple4)

# This is equivalent to window(catch(ple4), start=1990, end=1995)
trim(catch(ple4), year=1990:1995)

trim(catch.n(ple4), year=1990:1995, age=1:2)

# Now on an FLStock
summary(trim(ple4), year=1990:1995)

# If 'age' is trimmed in ple4, catch, landings and discards need to be recalculated
shpl4 <- trim(ple4, age=1:4)
landings(shpl4) <- computeLandings(shpl4)
discards(shpl4) <- computeDiscards(shpl4)
catch(shpl4) <- computeCatch(shpl4)

summary(shpl4)

FLCore documentation built on May 2, 2019, 5:46 p.m.