Shortcut to a lapply equivalent to apply a function to a list of scanList: a sLlist object Written analogously to lapply()

Source: R/scanList_tools.R

Shortcut to a lapply equivalent to apply a function to a list of scanList: a sLlist object Written analogously to lapply()

sLlapply(sLlist, FUN, ...)

Arguments

sLlist

a sLlist object, a list of scanList objects (see perform_exp())
FUN

function, to be applied to each scanList objects in sLlist
...

extra argument to be passed, notably named arguments used by FUN (see lapply())

Value

a sLlist object, a list of scanList objects on which the function FUN has been applied (see perform_exp())

Examples

set.seed(42)
n <- 5L
samp.effort <- 100L

# Adjacency matrix import
## random directed adjacency matrix
Adj <- sample(1:samp.effort,n * n) |>
  matrix(nrow = 5,dimnames = list(letters[1:n],letters[1:n]))
Adj[lower.tri(Adj,diag = TRUE)] <- 0L
Adj

#>   a   b  c  d  e
#> a 0 100 37 27 58
#> b 0   0 20 36 42
#> c 0   0  0  5 93
#> d 0   0  0  0 30
#> e 0   0  0  0  0

# Designing the experiments:
## setting a constant probability of not observing edges
group.scan <- design_sampling(method = "group",sampling = 0.8)

## setting an even focal sampling
focal.scan <- design_sampling(method = "focal",sampling = "even")

sL <- simunet(Adj = Adj,samp.effort = samp.effort,mode = "upper",n.scans = 120L)

sL |> perform_exp(group.scan,focal.scan) |> sLlapply(attrs,a = "edge.Prob")

#> [[1]]
#> 
#> Edge presence probability matrix                           
#> a . 0.992 0.391 0.253 0.633
#> b . .     0.217 0.406 0.423
#> c . .     .     0.076 0.921
#> d . .     .     .     0.257
#> e . .     .     .     .    
#> 
#>  alpha.prior = 0.5 - beta.prior = 0.5
#> [[2]]
#> 
#> Edge presence probability matrix                           
#> a . 0.992 0.391 0.253 0.633
#> b . .     0.217 0.406 0.423
#> c . .     .     0.076 0.921
#> d . .     .     .     0.257
#> e . .     .     .     .    
#> 
#>  alpha.prior = 0.5 - beta.prior = 0.5
#> attr(,"class")
#> [1] "sLlist"