Skip to contents

Mapper for adding multiple mappers

Source: R/mapper_sum.R
bm_sum.Rd

Defines a mapper that adds the effects of each submapper. The ibm_n() method returns the sum of ibm_n(mappers[[k]]), and ibm_values() returns seq_len(ibm_n(mapper)).

Usage

bm_sum(mappers, single_input = FALSE)

bru_mapper_sum(...)

# S3 method for class 'bm_sum'
ibm_n(mapper, inla_f = FALSE, multi = FALSE, ...)

# S3 method for class 'bm_sum'
ibm_n_output(mapper, input, state = NULL, ...)

# S3 method for class 'bm_sum'
ibm_values(mapper, inla_f = FALSE, multi = FALSE, ...)

# S3 method for class 'bm_sum'
ibm_is_linear(mapper, multi = FALSE, ...)

# S3 method for class 'bm_sum'
ibm_jacobian(
  mapper,
  input,
  state = NULL,
  inla_f = FALSE,
  multi = FALSE,
  ...,
  sub_lin = NULL
)

# S3 method for class 'bm_sum'
ibm_eval(mapper, input, state, multi = FALSE, ..., sub_lin = NULL)

# S3 method for class 'bm_sum'
ibm_linear(mapper, input, state, ...)

# S3 method for class 'bm_sum'
ibm_invalid_output(mapper, input, state, multi = FALSE, ...)

# S3 method for class 'bm_sum'
x[i, drop = TRUE]

# S3 method for class 'bru_mapper_sum'
x[i, drop = TRUE]

# S3 method for class 'bm_sum'
ibm_names(mapper)

# S3 method for class 'bm_sum'
ibm_names(mapper) <- value

# S3 method for class 'bru_mapper_sum'
ibm_names(mapper) <- value

Arguments

mappers

A list of bru_mapper objects.

single_input

logical. If TRUE, the input is passed to all sub-mappers. Otherwise, the input should be a list, data.frame, or matrix. If the mappers list has named entries, the input can reference their corresponding sub-mapper using its name.

...

Arguments passed on to other methods

mapper

A mapper S3 object, inheriting from bru_mapper.

inla_f

logical; when TRUE for ibm_n() and ibm_values(), the result must be compatible with the INLA::f(...) and corresponding INLA::inla.stack(...) constructions. For ibm_{eval,jacobian,linear}, the input interpretation may be different. Implementations do not normally need to do anything different, except for mappers of the type needed for hidden multicomponent models such as "bym2", which can be handled by bm_collect.

multi

logical; If TRUE (or positive), recurse one level into sub-mappers

input

Data input for the mapper.

state

A vector of latent state values for the mapping, of length ibm_n(mapper, inla_f = FALSE)

sub_lin

Internal, optional pre-computed sub-mapper information

x

object from which to extract element(s)

i

indices specifying element(s) to extract

drop

logical; For [.bm_sum, whether to extract an individual mapper when i identifies a single element. If FALSE, a list of sub-mappers is returned (suitable e.g. for creating a new bm_sum object). Default: TRUE

value

a character vector of the same length as the number of sub-mappers in the mapper

Value

A bm_sum object.

  • [-indexing a bm_sum extracts a subset bm_sum object (for drop FALSE) or an individual sub-mapper (for drop TRUE, and i identifies a single element)

  • The names() method for bm_sum returns the names from the sub-mappers list

Methods (by generic)

  • ibm_jacobian(bm_sum): Accepts a list with named entries, or a list with unnamed but ordered elements. The names must match the sub-mappers, see ibm_names.bm_sum(). Each list element should take a format accepted by the corresponding sub-mapper. In case each element is a vector, the input can be given as a data.frame with named columns, a matrix with named columns, or a matrix with unnamed but ordered columns.

  • ibm_invalid_output(bm_sum): Accepts a list with named entries, or a list with unnamed but ordered elements. The names must match the sub-mappers, see ibm_names.bm_sum(). Each list element should take a format accepted by the corresponding sub-mapper. In case each element is a vector, the input can be given as a data.frame with named columns, a matrix with named columns, or a matrix with unnamed but ordered columns.

See also

bru_mapper, bru_mapper_generics

Other mappers: bm_aggregate(), bm_collect(), bm_const(), bm_factor(), 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_taylor(), bru_get_mapper(), bru_mapper(), bru_mapper.fm_mesh_1d(), bru_mapper.fm_mesh_2d(), bru_mapper_generics

Examples

(m <- bm_sum(list(a = bm_index(3), b = bm_index(2))))
#> sum(a = index, b = index)
ibm_n(m)
#> [1] 5
ibm_values(m)
#> [1] 1 2 3 4 5
ibm_jacobian(m, list(a = 1:3, b = c(1, 1, 2)))
#> 3 x 5 sparse Matrix of class "dgCMatrix"
#>               
#> [1,] 1 . . 1 .
#> [2,] . 1 . 1 .
#> [3,] . . 1 . 1
ibm_eval(
  m,
  list(a = 1:3, b = c(1, 1, 2)),
  seq_len(ibm_n(m))
)
#> [1] 5 6 8