glmp: Define the GLMP

In rLDCP: Text Generation from Data

Description

Granular Linguistic Model of Phenomena (GLMP) is a network of cp and pm objects. that allows the designer to model computationally her/his own perceptions. The input data are introduced into the model through 1PMs which interpret the input data and create CPs. Then, 2PMs take several CPs as input and generate 2CPs. Of course, following the same scheme, is possible to add additional upper levels.

The glmp constructor receive as arguments the list of pms and the method with the computational model.

Usage

glmp(pms, method)

Arguments

pms	is the list of pm objects included in the glmp.
method	is the function with the glmp computational model. The method must have two arguments: the list of pm objects defined in the glmp and the input data: my_glmp_method <- function(pm,input)

Value

The generated glmp = list(pm, method)

Examples

## Not run: glmp_method <- function(pm,input){

  pm$pm_depth   <- pm_infer(pm$pm_depth, input[1])
  pm$pm_height  <- pm_infer(pm$pm_height,input[2])
  pm$pm_width   <- pm_infer(pm$pm_width, input[3])

  pm$pm_frame  <- pm_infer(pm$pm_frame, list( pm$pm_depth$y,
                                           pm$pm_height$y,
                                           pm$pm_width$y)
  )
  pm
}

my_glmp <- glmp(list(pm_depth  = pm_depth,
                     pm_height = pm_height,
                     pm_width  = pm_width,
                     pm_frame  = pm_frame),
                glmp_method)
                
## End(Not run)

rLDCP documentation built on May 2, 2019, 2:30 a.m.