Coerce an aggregation structure into a tabular form

Coerce a price index aggregation structure into an aggregation matrix, or a data frame.

Usage

# S3 method for class 'piar_aggregation_structure'
as.matrix(x, ..., sparse = FALSE)

# S3 method for class 'piar_aggregation_structure'
as.data.frame(
  x,
  row.names = NULL,
  optional = FALSE,
  ...,
  stringsAsFactors = FALSE
)

Arguments

x

A price index aggregation structure, as made by aggregation_structure().

...

Not currently used.

sparse

Should the result be a sparse matrix from Matrix? This is faster for large aggregation structures. The default returns an ordinary dense matrix.

row.names, stringsAsFactors

See as.data.frame().

optional

Not currently used.

Value

as.matrix() represents an aggregation structure as a matrix, such that multiplying with a (column) vector of elemental indexes gives the aggregated index.

as.data.frame() takes an aggregation structure and returns a data frame that could have generated it, with columns level1, level2, ..., ea, and weight.

See also

as_aggregation_structure() for coercing into an aggregation structure.

treemap::treemap() and data.tree::as.Node() for visualizing an aggregation structure.

Other aggregation structure methods: cut.piar_aggregation_structure(), levels.piar_aggregation_structure(), update.piar_aggregation_structure(), weights.piar_aggregation_structure()

Examples

# A simple aggregation structure
#            1
#      |-----+-----|
#      11          12
#  |---+---|       |
#  111     112     121
#  (1)     (3)     (4)

aggregation_weights <- data.frame(
  level1 = c("1", "1", "1"),
  level2 = c("11", "11", "12"),
  ea     = c("111", "112", "121"),
  weight = c(1, 3, 4)
)

pias <- as_aggregation_structure(aggregation_weights)

as.matrix(pias)
#>      111   112 121
#> 1  0.125 0.375 0.5
#> 11 0.250 0.750 0.0
#> 12 0.000 0.000 1.0

all.equal(as.data.frame(pias), aggregation_weights)
#> [1] TRUE

if (FALSE) { # \dontrun{
# Visualize as a treemap.
treemap::treemap(
  aggregation_weights,
  index = names(aggregation_weights)[-4],
  vSize = "weight",
  title = "aggregation structure"   
)

# Or turn into a more genereal tree object and plot.
aggregation_weights$pathString <- do.call(
  \(...) paste(..., sep = "/"),
  aggregation_weights[-4]
)
plot(data.tree::as.Node(aggregation_weights))
} # }