fsr (version 1.0.0)

spa_set_classification: Setting a new classification for fuzzy topological relationships

Description

This functions configures a new set of linguistic values and their corresponding membership functions to be used by fuzzy topological relationships.

Usage

spa_set_classification(classes, mfs)

Arguments

classes

A character vector containing linguistic values that characterizes different situations of fuzzy topological relationships.

mfs

A vector containing membership functions generated by the function genmf of the FuzzyR package. Their domain have to be in [0, 1].

Value

No return values, called for side effects.

Details

This function replaces the default linguistic values employed by fuzzy topological relationships. Each membership function i of the parameter mfs represents the class i of the parameter classes. The length of these parameters have to be same.

References

Carniel, A. C.; Schneider, M. Spatial Plateau Algebra: An Executable Type System for Fuzzy Spatial Data Types. In Proceedings of the 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2018), pp. 1-8, 2018.

Examples

# NOT RUN {
library(tibble)
library(sf)
library(FuzzyR)

set.seed(456)

# some random points to create pgeometry objects by using the function spa_creator
tbl = tibble(x = runif(10, min= 0, max = 30), 
             y = runif(10, min = 0, max = 30), 
             z = runif(10, min = 0, max = 50))

#getting the convex hull on the points to clipping the construction of plateau region objects
pts <- st_as_sf(tbl, coords = c(1, 2))
ch <- st_convex_hull(do.call(c, st_geometry(pts)))

pregions <- spa_creator(tbl, base_poly = ch, fuzz_policy = "fcp", k = 2)

# Showing the default list of classes
spa_overlap(pregions$pgeometry[[1]], pregions$pgeometry[[2]], ret = "list")

# Changing the default classification

classes <- c("small", "medium", "large")
small <- genmf("trapmf", c(0, 0.3, 0.4, 0.6))
medium <- genmf("trapmf", c(0.4, 0.6, 0.8, 1))
large <- genmf("trapmf", c(0.6, 0.8, 1, 1))

spa_set_classification(classes, c(small, medium, large))

spa_overlap(pregions$pgeometry[[1]], pregions$pgeometry[[2]], ret = "list")

# }