create_normerr_map: Create a mapping for absolute energy-independent...

In gschnabel/nucdataBaynet: Bayesian networks for nuclear data evaluation

Create a mapping for absolute energy-independent normalization errors

Description

Creates a map to distribute the absolute normalization errors given at the source indices to the experimental data at the target indices.

Usage

create_normerr_map()

Details

The following fields are required in the parameter list to initialize the mapping:

mapname	Name of the mapping
maptype	Must be "normerr_map"
src_idx	Vector of source indices
tar_idx	Vector of target indices
src_feat	Vector with the names of the normalization errors at the source indices. This vector must not contain duplicated strings.
tar_feat	Vector with the names of the normalization error associated with the variables at the target indices.

Value

Returns a list of functions to operate with the mapping, see create_maptype_map.

Note

This mapping may be used in a product mapping to define relative normalization errors, see create_product_mapping

See Also

Other mappings: create_compound_map(), create_convolution_with_xtrafo_map(), create_derivative2nd_map(), create_derivative_map(), create_linearinterpol_map(), create_linearinterpol_with_xtrafo_map(), create_linearmap_map(), create_maptype_map(), create_map(), create_nonlinear_map(), create_product_map()

Examples

params <- list(
  mapname = "mymap",
  maptype = "normerr_map",
  src_idx = 1:3,
  tar_idx = 4:9,
  src_feat = c("expnorm1", "expnorm2", "expnorm3"),
  tar_feat = c(rep("expnorm1", 2), rep("expnorm2", 3),
               rep("expnorm3", 1))
)
mymap <- create_normerr_map()
mymap$setup(params)
x <- c(1, 5, 7, rep(0, 6))
mymap$propagate(x)
mymap$jacobian(x)

gschnabel/nucdataBaynet documentation built on Feb. 3, 2023, 4:13 a.m.