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Mapper for aggregation

Source: R/mappers.R
bm_aggregate.Rd

Constructs a mapper that aggregates elements of the input state, so it can be used e.g. for weighted summation or integration over blocks of values.

Usage

bm_aggregate(rescale = FALSE, n_block = NULL, type = NULL)

bru_mapper_aggregate(...)

Arguments

rescale

logical; For bm_aggregate and bm_logsumexp, specifies if the blockwise sums should be normalised by the blockwise weight sums or not:

  • FALSE: (default) Straight weighted sum, no rescaling.

  • TRUE: Divide by the sum of the weight values within each block. This is useful for integration averages, when the given weights are plain integration weights. If the weights are NULL or all ones, this is the same as dividing by the number of entries in each block.

n_block

Predetermined number of output blocks. If NULL, overrides the maximum block index in the inputs. The priority order is input$n_block, the mapper definition n_block, then max(input$block).

type

character; if non-NULL, overrides the rescale argument, and constructs an aggregation mapper of the given type instead. Supported values are "sum", "average", "logsumexp", and "logaverageexp".

...

Arguments passed on to bm_aggregate()

See also

bru_mapper, bru_mapper_generics

Other mappers: bm_collect(), bm_const(), bm_factor(), bm_fm_mesh_1d, bm_fmesher(), bm_harmonics(), bm_index(), bm_linear(), bm_logsumexp(), bm_marginal(), bm_matrix(), bm_mesh_B(), bm_multi(), bm_pipe(), bm_repeat(), bm_scale(), bm_shift(), bm_sum(), bm_taylor(), bru_get_mapper(), bru_mapper()

Other specific bm_aggregate method implementations: ibm_eval(), ibm_jacobian(), ibm_n(), ibm_n_output(), ibm_values()

Examples

m <- bm_aggregate()
ibm_eval2(m, list(block = c(1, 2, 1, 2), weights = 1:4), 11:14)
#> $offset
#> [1] 50 80
#> 
#> $jacobian
#> 2 x 4 sparse Matrix of class "dgCMatrix"
#>             
#> [1,] 1 . 3 .
#> [2,] . 2 . 4
#> 
ibm_eval2(m, list(block = c(1, 2, 1, 2), weights = 1:4, n_block = 3), 11:14)
#> $offset
#> [1] 50 80  0
#> 
#> $jacobian
#> 3 x 4 sparse Matrix of class "dgCMatrix"
#>             
#> [1,] 1 . 3 .
#> [2,] . 2 . 4
#> [3,] . . . .
#>