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#Code automatically generated with fuzzylite 6.0.
library(ggplot2);
engine.name = "Laundry"
engine.fll = "Engine: Laundry
InputVariable: Load
enabled: true
range: 0.000 6.000
lock-range: false
term: small Discrete 0.000 1.000 1.000 1.000 2.000 0.800 5.000 0.000
term: normal Discrete 3.000 0.000 4.000 1.000 6.000 0.000
InputVariable: Dirt
enabled: true
range: 0.000 6.000
lock-range: false
term: low Discrete 0.000 1.000 2.000 0.800 5.000 0.000
term: high Discrete 1.000 0.000 2.000 0.200 4.000 0.800 6.000 1.000
OutputVariable: Detergent
enabled: true
range: 0.000 80.000
lock-range: false
aggregation: Maximum
defuzzifier: MeanOfMaximum 500
default: nan
lock-previous: false
term: less_than_usual Discrete 10.000 0.000 40.000 1.000 50.000 0.000
term: usual Discrete 40.000 0.000 50.000 1.000 60.000 1.000 80.000 0.000
term: more_than_usual Discrete 50.000 0.000 80.000 1.000
OutputVariable: Cycle
enabled: true
range: 0.000 20.000
lock-range: false
aggregation: Maximum
defuzzifier: MeanOfMaximum 500
default: nan
lock-previous: false
term: short Discrete 0.000 1.000 10.000 1.000 20.000 0.000
term: long Discrete 10.000 0.000 20.000 1.000
RuleBlock:
enabled: true
conjunction: Minimum
disjunction: Maximum
implication: Minimum
activation: General
rule: if Load is small and Dirt is not high then Detergent is less_than_usual
rule: if Load is small and Dirt is high then Detergent is usual
rule: if Load is normal and Dirt is low then Detergent is less_than_usual
rule: if Load is normal and Dirt is high then Detergent is more_than_usual
rule: if Detergent is usual or Detergent is less_than_usual then Cycle is short
rule: if Detergent is more_than_usual then Cycle is long"
engine.fldFile = "Laundry.fld"
if (require(data.table)) {
engine.df = data.table::fread(engine.fldFile, sep="auto", header="auto")
} else {
engine.df = read.table(engine.fldFile, header=TRUE)
}
engine.plot.i1i2_o1 = ggplot(engine.df, aes(Load, Dirt)) +
geom_tile(aes(fill=Detergent)) +
scale_fill_gradient(low="yellow", high="red") +
stat_contour(aes(x=Load, y=Dirt, z=Detergent), color="black") +
ggtitle("(Load, Dirt) = Detergent")
engine.plot.i2i1_o1 = ggplot(engine.df, aes(Dirt, Load)) +
geom_tile(aes(fill=Detergent)) +
scale_fill_gradient(low="yellow", high="red") +
stat_contour(aes(x=Dirt, y=Load, z=Detergent), color="black") +
ggtitle("(Dirt, Load) = Detergent")
engine.plot.i1i2_o2 = ggplot(engine.df, aes(Load, Dirt)) +
geom_tile(aes(fill=Cycle)) +
scale_fill_gradient(low="yellow", high="red") +
stat_contour(aes(x=Load, y=Dirt, z=Cycle), color="black") +
ggtitle("(Load, Dirt) = Cycle")
engine.plot.i2i1_o2 = ggplot(engine.df, aes(Dirt, Load)) +
geom_tile(aes(fill=Cycle)) +
scale_fill_gradient(low="yellow", high="red") +
stat_contour(aes(x=Dirt, y=Load, z=Cycle), color="black") +
ggtitle("(Dirt, Load) = Cycle")
if (require(gridExtra)) {
engine.plots = arrangeGrob(engine.plot.i1i2_o1, engine.plot.i2i1_o1, engine.plot.i1i2_o2, engine.plot.i2i1_o2, ncol=2, top=engine.name)
ggsave(paste0(engine.name, ".pdf"), engine.plots)
if (require(grid)) {
grid.newpage()
grid.draw(engine.plots)
}
}
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