fl.Triangle("right", 0.333000000, 0.666000000,
1.000000000)
])
]
engine.output_variables = [
fl.OutputVariable(name="steer",
description="direction to steer the vehicle to",
enabled=True,
minimum=0.000000000,
maximum=1.000000000,
lock_range=False,
aggregation=fl.Maximum(),
defuzzifier=fl.Centroid(100),
lock_previous=False,
terms=[
fl.Gaussian("left", 0.333000000, 0.143534483),
fl.Gaussian("right", 0.666500000, 0.143750000)
])
]
engine.rule_blocks = [
fl.RuleBlock(name="steer_away",
description="steer away from obstacles",
enabled=True,
conjunction=None,
disjunction=None,
implication=fl.Minimum(),
activation=fl.General(),
rules=[
fl.Rule.create("if obstacle is left then steer is right",
engine),
fl.Rule.create("if obstacle is right then steer is left",
fl.Trapezoid("Bad", 0.000, 1.000, 3.000, 7.000),
fl.Trapezoid("Good", 3.000, 7.000, 10.000, 11.000)
])
]
engine.output_variables = [
fl.OutputVariable(name="Tip",
description="",
enabled=True,
minimum=0.000,
maximum=30.000,
lock_range=False,
aggregation=fl.AlgebraicSum(),
defuzzifier=fl.Centroid(200),
lock_previous=False,
terms=[
fl.Gaussian("AboutTenPercent", 10.000, 2.000),
fl.Gaussian("AboutFifteenPercent", 15.000, 2.000),
fl.Gaussian("AboutTwentyPercent", 20.000, 2.000)
]),
fl.OutputVariable(name="CheckPlusTip",
description="",
enabled=True,
minimum=1.000,
maximum=1.300,
lock_range=False,
aggregation=fl.AlgebraicSum(),
defuzzifier=fl.Centroid(200),
lock_previous=False,
terms=[
fl.Gaussian("PlusAboutTenPercent", 1.100, 0.020),
fl.Gaussian("PlusAboutFifteenPercent", 1.150, 0.020),
minimum=0.000,
maximum=6.500,
lock_range=False,
terms=[
fl.Sigmoid("A", 0.500, -20.000),
fl.ZShape("B", 0.000, 1.000),
fl.Ramp("C", 1.000, 0.000),
fl.Triangle("D", 0.500, 1.000, 1.500),
fl.Trapezoid("E", 1.000, 1.250, 1.750, 2.000),
fl.Concave("F", 0.850, 0.250),
fl.Rectangle("G", 1.750, 2.250),
fl.Discrete("H", [
2.000, 0.000, 2.250, 1.000, 2.500, 0.500, 2.750,
1.000, 3.000, 0.000
]),
fl.Gaussian("I", 3.000, 0.200),
fl.Cosine("J", 3.250, 0.650),
fl.GaussianProduct("K", 3.500, 0.100, 3.300, 0.300),
fl.Spike("L", 3.640, 1.040),
fl.Bell("M", 4.000, 0.250, 3.000),
fl.PiShape("N", 4.000, 4.500, 4.500, 5.000),
fl.Concave("O", 5.650, 6.250),
fl.SigmoidDifference("P", 4.750, 10.000, 30.000,
5.250),
fl.SigmoidProduct("Q", 5.250, 20.000, -10.000, 5.750),
fl.Ramp("R", 5.500, 6.500),
fl.SShape("S", 5.500, 6.500),
fl.Sigmoid("T", 6.000, 20.000)
])
]
engine.output_variables = [
import fuzzylite as fl
engine = fl.Engine(name="sugeno1", description="")
engine.input_variables = [
fl.InputVariable(name="input",
description="",
enabled=True,
minimum=-5.000,
maximum=5.000,
lock_range=False,
terms=[
fl.Gaussian("low", -5.000, 4.000),
fl.Gaussian("high", 5.000, 4.000)
])
]
engine.output_variables = [
fl.OutputVariable(name="output",
description="",
enabled=True,
minimum=0.000,
maximum=1.000,
lock_range=False,
aggregation=None,
defuzzifier=fl.WeightedAverage("TakagiSugeno"),
lock_previous=False,
terms=[
fl.Linear("line1", [-1.000, -1.000], engine),
fl.Linear("line2", [1.000, -1.000], engine)
])
]
engine.rule_blocks = [
import fuzzylite as fl
engine = fl.Engine(name="tanksg", description="")
engine.input_variables = [
fl.InputVariable(name="level",
description="",
enabled=True,
minimum=-1.000,
maximum=1.000,
lock_range=False,
terms=[
fl.Gaussian("high", -1.000, 0.300),
fl.Gaussian("okay", 0.004, 0.300),
fl.Gaussian("low", 1.000, 0.300)
]),
fl.InputVariable(name="rate",
description="",
enabled=True,
minimum=-0.100,
maximum=0.100,
lock_range=False,
terms=[
fl.Gaussian("negative", -0.100, 0.030),
fl.Gaussian("none", 0.000, 0.030),
fl.Gaussian("positive", 0.100, 0.030)
])
]
engine.output_variables = [
fl.OutputVariable(name="valve",
description="",
enabled=True,
import fuzzylite as fl
engine = fl.Engine(name="tipper1", description="")
engine.input_variables = [
fl.InputVariable(name="service",
description="",
enabled=True,
minimum=0.000,
maximum=10.000,
lock_range=False,
terms=[
fl.Gaussian("poor", 0.000, 1.500),
fl.Gaussian("good", 5.000, 1.500),
fl.Gaussian("excellent", 10.000, 1.500)
])
]
engine.output_variables = [
fl.OutputVariable(name="tip",
description="",
enabled=True,
minimum=0.000,
maximum=30.000,
lock_range=False,
aggregation=fl.Maximum(),
defuzzifier=fl.Centroid(200),
lock_previous=False,
terms=[
fl.Triangle("cheap", 0.000, 5.000, 10.000),
fl.Triangle("average", 10.000, 15.000, 20.000),
fl.Triangle("generous", 20.000, 25.000, 30.000)
])
import fuzzylite as fl
engine = fl.Engine(name="tippersg", description="")
engine.input_variables = [
fl.InputVariable(name="service",
description="",
enabled=True,
minimum=0.000,
maximum=10.000,
lock_range=False,
terms=[
fl.Gaussian("poor", 0.000, 1.500),
fl.Gaussian("average", 5.000, 1.500),
fl.Gaussian("good", 10.000, 1.500)
]),
fl.InputVariable(name="food",
description="",
enabled=True,
minimum=0.000,
maximum=10.000,
lock_range=False,
terms=[
fl.Trapezoid("rancid", -5.000, 0.000, 1.000, 3.000),
fl.Trapezoid("delicious", 7.000, 9.000, 10.000,
15.000)
])
]
engine.output_variables = [
fl.OutputVariable(name="tip",
description="",
enabled=True,
fl.ZShape("Low", 2.000, 8.000),
fl.SShape("High", 2.000, 8.000)
])
]
engine.output_variables = [
fl.OutputVariable(name="PercentageInStocks",
description="",
enabled=True,
minimum=0.000,
maximum=100.000,
lock_range=False,
aggregation=fl.EinsteinSum(),
defuzzifier=fl.Centroid(200),
lock_previous=False,
terms=[
fl.Gaussian("AboutFifteen", 15.000, 10.000),
fl.Gaussian("AboutFifty", 50.000, 10.000),
fl.Gaussian("AboutEightyFive", 85.000, 10.000)
])
]
engine.rule_blocks = [
fl.RuleBlock(
name="",
description="",
enabled=True,
conjunction=fl.EinsteinProduct(),
disjunction=fl.EinsteinSum(),
implication=fl.EinsteinProduct(),
activation=fl.General(),
rules=[
fl.Rule.create(
maximum=3.000,
lock_range=False),
fl.InputVariable(name="in4",
description="",
enabled=True,
minimum=-3.000,
maximum=3.000,
lock_range=False),
fl.InputVariable(name="in5",
description="",
enabled=True,
minimum=0.500,
maximum=1.500,
lock_range=False,
terms=[
fl.Gaussian("small", 0.500, 0.200),
fl.Gaussian("medium", 1.000, 0.200),
fl.Gaussian("large", 1.500, 0.200)
])
]
engine.output_variables = [
fl.OutputVariable(
name="out",
description="",
enabled=True,
minimum=-10.000,
maximum=10.000,
lock_range=False,
aggregation=None,
defuzzifier=fl.WeightedAverage("TakagiSugeno"),
lock_previous=False,