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from knowledge import *
from utils import expr
import random
random.seed("aima-python")
party = [
{'Pizza': 'Yes', 'Soda': 'No', 'GOAL': True},
{'Pizza': 'Yes', 'Soda': 'Yes', 'GOAL': True},
{'Pizza': 'No', 'Soda': 'No', 'GOAL': False}
]
animals_umbrellas = [
{'Species': 'Cat', 'Rain': 'Yes', 'Coat': 'No', 'GOAL': True},
{'Species': 'Cat', 'Rain': 'Yes', 'Coat': 'Yes', 'GOAL': True},
{'Species': 'Dog', 'Rain': 'Yes', 'Coat': 'Yes', 'GOAL': True},
{'Species': 'Dog', 'Rain': 'Yes', 'Coat': 'No', 'GOAL': False},
{'Species': 'Dog', 'Rain': 'No', 'Coat': 'No', 'GOAL': False},
{'Species': 'Cat', 'Rain': 'No', 'Coat': 'No', 'GOAL': False},
{'Species': 'Cat', 'Rain': 'No', 'Coat': 'Yes', 'GOAL': True}
]
conductance = [
{'Sample': 'S1', 'Mass': 12, 'Temp': 26, 'Material': 'Cu', 'Size': 3, 'GOAL': 0.59},
{'Sample': 'S1', 'Mass': 12, 'Temp': 100, 'Material': 'Cu', 'Size': 3, 'GOAL': 0.57},
{'Sample': 'S2', 'Mass': 24, 'Temp': 26, 'Material': 'Cu', 'Size': 6, 'GOAL': 0.59},
{'Sample': 'S3', 'Mass': 12, 'Temp': 26, 'Material': 'Pb', 'Size': 2, 'GOAL': 0.05},
{'Sample': 'S3', 'Mass': 12, 'Temp': 100, 'Material': 'Pb', 'Size': 2, 'GOAL': 0.04},
{'Sample': 'S4', 'Mass': 18, 'Temp': 100, 'Material': 'Pb', 'Size': 3, 'GOAL': 0.04},
{'Sample': 'S4', 'Mass': 18, 'Temp': 100, 'Material': 'Pb', 'Size': 3, 'GOAL': 0.04},
{'Sample': 'S5', 'Mass': 24, 'Temp': 100, 'Material': 'Pb', 'Size': 4, 'GOAL': 0.04},
{'Sample': 'S6', 'Mass': 36, 'Temp': 26, 'Material': 'Pb', 'Size': 6, 'GOAL': 0.05},
]
def r_example(Alt, Bar, Fri, Hun, Pat, Price, Rain, Res, Type, Est, GOAL):
return {'Alt': Alt, 'Bar': Bar, 'Fri': Fri, 'Hun': Hun, 'Pat': Pat,
'Price': Price, 'Rain': Rain, 'Res': Res, 'Type': Type, 'Est': Est,
'GOAL': GOAL}
restaurant = [
r_example('Yes', 'No', 'No', 'Yes', 'Some', '$$$', 'No', 'Yes', 'French', '0-10', True),
r_example('Yes', 'No', 'No', 'Yes', 'Full', '$', 'No', 'No', 'Thai', '30-60', False),
r_example('No', 'Yes', 'No', 'No', 'Some', '$', 'No', 'No', 'Burger', '0-10', True),
r_example('Yes', 'No', 'Yes', 'Yes', 'Full', '$', 'Yes', 'No', 'Thai', '10-30', True),
r_example('Yes', 'No', 'Yes', 'No', 'Full', '$$$', 'No', 'Yes', 'French', '>60', False),
r_example('No', 'Yes', 'No', 'Yes', 'Some', '$$', 'Yes', 'Yes', 'Italian', '0-10', True),
r_example('No', 'Yes', 'No', 'No', 'None', '$', 'Yes', 'No', 'Burger', '0-10', False),
r_example('No', 'No', 'No', 'Yes', 'Some', '$$', 'Yes', 'Yes', 'Thai', '0-10', True),
r_example('No', 'Yes', 'Yes', 'No', 'Full', '$', 'Yes', 'No', 'Burger', '>60', False),
r_example('Yes', 'Yes', 'Yes', 'Yes', 'Full', '$$$', 'No', 'Yes', 'Italian', '10-30', False),
r_example('No', 'No', 'No', 'No', 'None', '$', 'No', 'No', 'Thai', '0-10', False),
r_example('Yes', 'Yes', 'Yes', 'Yes', 'Full', '$', 'No', 'No', 'Burger', '30-60', True)
]
def test_current_best_learning():
examples = restaurant
hypothesis = [{'Alt': 'Yes'}]
h = current_best_learning(examples, hypothesis)
values = [guess_value(e, h) for e in examples]
assert values == [True, False, True, True, False, True, False, True, False, False, False, True]
examples = animals_umbrellas
initial_h = [{'Species': 'Cat'}]
h = current_best_learning(examples, initial_h)
values = [guess_value(e, h) for e in examples]
assert values == [True, True, True, False, False, False, True]
examples = party
initial_h = [{'Pizza': 'Yes'}]
h = current_best_learning(examples, initial_h)
values = [guess_value(e, h) for e in examples]
assert values == [True, True, False]
def test_version_space_learning():
V = version_space_learning(party)
results = []
for e in party:
guess = False
for h in V:
if guess_value(e, h):
guess = True
break
results.append(guess)
assert results == [True, True, False]
assert [{'Pizza': 'Yes'}] in V
def test_minimal_consistent_det():
assert minimal_consistent_det(party, {'Pizza', 'Soda'}) == {'Pizza'}
assert minimal_consistent_det(party[:2], {'Pizza', 'Soda'}) == set()
assert minimal_consistent_det(animals_umbrellas, {'Species', 'Rain', 'Coat'}) == {'Species', 'Rain', 'Coat'}
assert minimal_consistent_det(conductance, {'Mass', 'Temp', 'Material', 'Size'}) == {'Temp', 'Material'}
assert minimal_consistent_det(conductance, {'Mass', 'Temp', 'Size'}) == {'Mass', 'Temp', 'Size'}
A, B, C, D, E, F, G, H, I, x, y, z = map(expr, 'ABCDEFGHIxyz')
# knowledge base containing family relations
small_family = FOIL_container([expr("Mother(Anne, Peter)"),
expr("Mother(Anne, Zara)"),
expr("Mother(Sarah, Beatrice)"),
expr("Mother(Sarah, Eugenie)"),
expr("Father(Mark, Peter)"),
expr("Father(Mark, Zara)"),
expr("Father(Andrew, Beatrice)"),
expr("Father(Andrew, Eugenie)"),
expr("Father(Philip, Anne)"),
expr("Father(Philip, Andrew)"),
expr("Mother(Elizabeth, Anne)"),
expr("Mother(Elizabeth, Andrew)"),
expr("Male(Philip)"),
expr("Male(Mark)"),
expr("Male(Andrew)"),
expr("Male(Peter)"),
expr("Female(Elizabeth)"),
expr("Female(Anne)"),
expr("Female(Sarah)"),
expr("Female(Zara)"),
expr("Female(Beatrice)"),
expr("Female(Eugenie)"),
])
smaller_family = FOIL_container([expr("Mother(Anne, Peter)"),
expr("Father(Mark, Peter)"),
expr("Father(Philip, Anne)"),
expr("Mother(Elizabeth, Anne)"),
expr("Male(Philip)"),
expr("Male(Mark)"),
expr("Male(Peter)"),
expr("Female(Elizabeth)"),
expr("Female(Anne)")
])
# target relation
target = expr('Parent(x, y)')
#positive examples of target
examples_pos = [{x: expr('Elizabeth'), y: expr('Anne')},
{x: expr('Elizabeth'), y: expr('Andrew')},
{x: expr('Philip'), y: expr('Anne')},
{x: expr('Philip'), y: expr('Andrew')},
{x: expr('Anne'), y: expr('Peter')},
{x: expr('Anne'), y: expr('Zara')},
{x: expr('Mark'), y: expr('Peter')},
{x: expr('Mark'), y: expr('Zara')},
{x: expr('Andrew'), y: expr('Beatrice')},
{x: expr('Andrew'), y: expr('Eugenie')},
{x: expr('Sarah'), y: expr('Beatrice')},
{x: expr('Sarah'), y: expr('Eugenie')}]
# negative examples of target
examples_neg = [{x: expr('Anne'), y: expr('Eugenie')},
{x: expr('Beatrice'), y: expr('Eugenie')},
{x: expr('Mark'), y: expr('Elizabeth')},
{x: expr('Beatrice'), y: expr('Philip')}]
def test_tell():
"""
adds in the knowledge base a sentence
"""
smaller_family.tell(expr("Male(George)"))
smaller_family.tell(expr("Female(Mum)"))
assert smaller_family.ask(expr("Male(George)")) == {}
assert smaller_family.ask(expr("Female(Mum)"))=={}
assert not smaller_family.ask(expr("Female(George)"))
assert not smaller_family.ask(expr("Male(Mum)"))
def test_extend_example():
"""
Create the extended examples of the given clause.
(The extended examples are a set of examples created by extending example
with each possible constant value for each new variable in literal.)
"""
assert len(list(small_family.extend_example({x: expr('Andrew')}, expr('Father(x, y)')))) == 2
assert len(list(small_family.extend_example({x: expr('Andrew')}, expr('Mother(x, y)')))) == 0
assert len(list(small_family.extend_example({x: expr('Andrew')}, expr('Female(y)')))) == 6
def test_new_literals():
assert len(list(small_family.new_literals([expr('p'), []]))) == 8
assert len(list(small_family.new_literals([expr('p & q'), []]))) == 20
def test_new_clause():
"""
Finds the best clause to add in the set of clauses.
"""
clause = small_family.new_clause([examples_pos, examples_neg], target)[0][1]
assert len(clause) == 1 and ( clause[0].op in ['Male', 'Female', 'Father', 'Mother' ] )
def test_choose_literal():
"""
Choose the best literal based on the information gain
"""
literals = [expr('Father(x, y)'), expr('Father(x, y)'), expr('Mother(x, y)'), expr('Mother(x, y)')]
examples_pos = [{x: expr('Philip')}, {x: expr('Mark')}, {x: expr('Peter')}]
examples_neg = [{x: expr('Elizabeth')}, {x: expr('Sarah')}]
assert small_family.choose_literal(literals, [examples_pos, examples_neg]) == expr('Father(x, y)')
literals = [expr('Father(x, y)'), expr('Father(y, x)'), expr('Male(x)')]
examples_pos = [{x: expr('Philip')}, {x: expr('Mark')}, {x: expr('Andrew')}]
examples_neg = [{x: expr('Elizabeth')}, {x: expr('Sarah')}]
assert small_family.choose_literal(literals, [examples_pos, examples_neg]) == expr('Father(x,y)')
def test_gain():
"""
Calculates the utility of each literal, based on the information gained.
"""
gain_father = small_family.gain( expr('Father(x,y)'), [examples_pos, examples_neg] )
gain_male = small_family.gain(expr('Male(x)'), [examples_pos, examples_neg] )
assert round(gain_father, 2) == 2.49
assert round(gain_male, 2) == 1.16
def test_update_examples():
"""Add to the kb those examples what are represented in extended_examples
List of omitted examples is returned.
"""
extended_examples = [{x: expr("Mark") , y: expr("Peter")},
{x: expr("Philip"), y: expr("Anne")} ]
uncovered = smaller_family.update_examples(target, examples_pos, extended_examples)
assert {x: expr("Elizabeth"), y: expr("Anne") } in uncovered
assert {x: expr("Anne"), y: expr("Peter")} in uncovered
assert {x: expr("Philip"), y: expr("Anne") } not in uncovered
assert {x: expr("Mark"), y: expr("Peter")} not in uncovered
def test_foil():
"""
Test the FOIL algorithm, when target is Parent(x,y)
"""
clauses = small_family.foil([examples_pos, examples_neg], target)
assert len(clauses) == 2 and \
((clauses[0][1][0] == expr('Father(x, y)') and clauses[1][1][0] == expr('Mother(x, y)')) or \
(clauses[1][1][0] == expr('Father(x, y)') and clauses[0][1][0] == expr('Mother(x, y)')))
target_g = expr('Grandparent(x, y)')
examples_pos_g = [{x: expr('Elizabeth'), y: expr('Peter')},
{x: expr('Elizabeth'), y: expr('Zara')},
{x: expr('Elizabeth'), y: expr('Beatrice')},
{x: expr('Elizabeth'), y: expr('Eugenie')},
{x: expr('Philip'), y: expr('Peter')},
{x: expr('Philip'), y: expr('Zara')},
{x: expr('Philip'), y: expr('Beatrice')},
{x: expr('Philip'), y: expr('Eugenie')}]
examples_neg_g = [{x: expr('Anne'), y: expr('Eugenie')},
{x: expr('Beatrice'), y: expr('Eugenie')},
{x: expr('Elizabeth'), y: expr('Andrew')},
{x: expr('Elizabeth'), y: expr('Anne')},
{x: expr('Elizabeth'), y: expr('Mark')},
{x: expr('Elizabeth'), y: expr('Sarah')},
{x: expr('Philip'), y: expr('Anne')},
{x: expr('Philip'), y: expr('Andrew')},
{x: expr('Anne'), y: expr('Peter')},
{x: expr('Anne'), y: expr('Zara')},
{x: expr('Mark'), y: expr('Peter')},
{x: expr('Mark'), y: expr('Zara')},
{x: expr('Andrew'), y: expr('Beatrice')},
{x: expr('Andrew'), y: expr('Eugenie')},
{x: expr('Sarah'), y: expr('Beatrice')},
{x: expr('Mark'), y: expr('Elizabeth')},
{x: expr('Beatrice'), y: expr('Philip')},
{x: expr('Peter'), y: expr('Andrew')},
{x: expr('Zara'), y: expr('Mark')},
{x: expr('Peter'), y: expr('Anne')},
{x: expr('Zara'), y: expr('Eugenie')}]
clauses = small_family.foil([examples_pos_g, examples_neg_g], target_g)
assert len(clauses[0]) == 2
assert clauses[0][1][0].op == 'Parent'
assert clauses[0][1][0].args[0] == x
assert clauses[0][1][1].op == 'Parent'
assert clauses[0][1][1].args[1] == y
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