rm(list=ls())
setwd("C:/Users/Mati/Desktop/Seminarium/Projektowanie rozmytych systemów regółowych w języku R/FRBS")
library(frbs)




varinp.mf <- matrix(c( 5, -1, 0.8493, NA, NA,
                       5, 1, 0.8493, NA, NA,
                       5, -1, 0.8493, NA, NA,
                       5, 1, 0.8493, NA, NA),
                    nrow = 5, byrow = FALSE)
num.fvalinput <- matrix(c(2,2), nrow=1)
x1 <- c("A1","A2")
x2 <- c("B1","B2")
names.varinput <- c(x1, x2)
range.data <- matrix(c(-1.5,1.5, -1.5,1.5), nrow=2)
type.defuz <- "5"
type.tnorm <- "MIN"
type.snorm <- "MAX"
type.implication.func <- "MIN"
name <- "Przykład"
newdata <- matrix(c(-0.6, 0.3), ncol = 2, byrow = TRUE)
colnames.var <- c("x1", "x2")
type.model <- "TSK"
func.tsk <- matrix(c(1,1,1,
                     2,1,0,
                     1,-2,-1,
                     -1,0.5,-2),
                   nrow = 4, byrow = TRUE)

rule <- matrix(c("A1","and","B1","->",
                 "A1","and","B2","->",
                 "A2","and","B1","->",
                 "A2","and","B2","->"),
                 nrow = 4, byrow = TRUE)
object <- frbs.gen(range.data, num.fvalinput, names.varinput,
                   num.fvaloutput, varout.mf=NULL, names.varoutput, rule,
                   varinp.mf, type.model, type.defuz, type.tnorm, type.snorm,
                   func.tsk, colnames.var, type.implication.func, name)
plotMF(object)

object
#res <- predict(object, newdata)$predicted.val