def test_term_aggregate_1():
x1 = Antecedent(np.linspace(0, 10, 11), "x1")
x1.automf(3) # term labels: poor, average, good
x2 = Antecedent(np.linspace(0, 10, 11), "x2")
x2.automf(3)
ta = (x1["poor"] & x2["good"])
# print("- ta:", ta)
assert isinstance(ta, TermAggregate)
assert str(ta) == "x1[poor] AND x2[good]"
def test_tipping_problem():
# The full tipping problem uses many of these methods
food = Antecedent(np.linspace(0, 10, 11), 'quality')
service = Antecedent(np.linspace(0, 10, 11), 'service')
tip = Consequent(np.linspace(0, 25, 26), 'tip')
food.automf(3)
service.automf(3)
# Manual membership function definition
tip['bad'] = trimf(tip.universe, [0, 0, 13])
tip['middling'] = trimf(tip.universe, [0, 13, 25])
tip['lots'] = trimf(tip.universe, [13, 25, 25])
# Define fuzzy rules
rule1 = Rule(food['poor'] | service['poor'], tip['bad'])
rule2 = Rule(service['average'], tip['middling'])
rule3 = Rule(service['good'] | food['good'], tip['lots'])
# The control system - defined both possible ways
tipping = ControlSystem([rule1, rule2, rule3])
tipping2 = ControlSystem()
tipping2.addrule(rule2)
tipping2.addrule(rule3)
tipping2.addrule(rule1)
tip_sim = ControlSystemSimulation(tipping)
tip_sim2 = ControlSystemSimulation(tipping2)
# Inputs added both possible ways
inputs = {'quality': 6.5, 'service': 9.8}
for key, value in inputs.items():
tip_sim.input[key] = value
tip_sim2.inputs(inputs)
# Compute the system
tip_sim.compute()
tip_sim2.compute()
assert tip_sim.output == tip_sim2.output
tst.assert_allclose(tip_sim.output['tip'], 19.8578, atol=1e-2, rtol=1e-2)
def test_tipping_problem():
# The full tipping problem uses many of these methods
food = Antecedent(np.linspace(0, 10, 11), 'quality')
service = Antecedent(np.linspace(0, 10, 11), 'service')
tip = Consequent(np.linspace(0, 25, 26), 'tip')
food.automf(3)
service.automf(3)
# Manual membership function definition
tip['bad'] = trimf(tip.universe, [0, 0, 13])
tip['middling'] = trimf(tip.universe, [0, 13, 25])
tip['lots'] = trimf(tip.universe, [13, 25, 25])
# Define fuzzy rules
rule1 = Rule(food['poor'] | service['poor'], tip['bad'])
rule2 = Rule(service['average'], tip['middling'])
rule3 = Rule(service['good'] | food['good'], tip['lots'])
# The control system - defined both possible ways
tipping = ControlSystem([rule1, rule2, rule3])
tipping2 = ControlSystem()
tipping2.addrule(rule2)
tipping2.addrule(rule3)
tipping2.addrule(rule1)
tip_sim = ControlSystemSimulation(tipping)
tip_sim2 = ControlSystemSimulation(tipping2)
# Inputs added both possible ways
inputs = {'quality': 6.5, 'service': 9.8}
for key, value in inputs.items():
tip_sim.input[key] = value
tip_sim2.inputs(inputs)
# Compute the system
tip_sim.compute()
tip_sim2.compute()
assert tip_sim.output == tip_sim2.output
tst.assert_allclose(tip_sim.output['tip'], 19.8578, atol=1e-2, rtol=1e-2)
