Index a table by a MultiFactor and apply arbitrary code to it

weave_apply can run arbitrary code specified by FUN across any number of row-based subsets of table .data. Mimics lapply.

Arguments

.x

a MultiFactor object.

.path

either a formula or a `character vector“ of length 2 with the names of the desired combination of feature types.

.data

A table. A data.frame, matrix, other object with rows and columns.

.fun

A function, passed to lapply.

...

Additional arguments passed to lapply call.

.index

Character scalar Where in .x can the target feature names be found. (Default: "row.names")

Value

a Named list of desired output.

See also

weave() lapply() LinkMap() MultiFactor()

Examples

# Prepare data
x <- trade_posts()

# Generate small example feature table 'df'.
n <- nlevels(x)[["clothing"]]
df <- replicate(10, rbinom(n, rbinom(n, 100, runif(n)), runif(n)))

#' # Ensure rownames correspond to the second (RHS) variable in the formula.
df <- as.data.frame(df, row.names = levels(x)$clothing)

# Apply arbitrary code to x based on group membership
weave_apply(
    x,
    .path = fruit ~ clothing,
    .data = df,
    .fun = function(x) colSums(x)
)
#> $apples
#>  V1  V2  V3  V4  V5  V6  V7  V8  V9 V10 
#> 133  81  40  64  98  36 150  83  51 101 
#> 
#> $pears
#>  V1  V2  V3  V4  V5  V6  V7  V8  V9 V10 
#> 174 117  52  90  43  32 100  39  42 139 
#> 
#> $cherries
#>  V1  V2  V3  V4  V5  V6  V7  V8  V9 V10 
#> 174 117  52  90  43  32 100  39  42 139 
#> 
#> $melons
#>  V1  V2  V3  V4  V5  V6  V7  V8  V9 V10 
#>  92  81  39  57  30  28  87  39  29  85 
#> 
#> $grapes
#>  V1  V2  V3  V4  V5  V6  V7  V8  V9 V10 
#> 215 117  53  97 111  40 163  83  64 155 
#>