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import
pytest
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
if
__name__
==
"__main__"
:
pytest
.
main
()
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