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smadani2
nulling-python
Commits
7ffb19ce
Commit
7ffb19ce
authored
5 years ago
by
Sepehr Madani
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Rename fitness to pattern & fix empty bucket bug
parent
3ee2e665
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1 changed file
algorithms/genetic_algorithm.py
+20
-13
20 additions, 13 deletions
algorithms/genetic_algorithm.py
with
20 additions
and
13 deletions
algorithms/genetic_algorithm.py
+
20
−
13
View file @
7ffb19ce
from
random
import
randrange
,
random
,
choice
,
sample
from
random
import
randrange
,
random
,
choice
,
sample
from
cmath
import
exp
,
phase
from
cmath
import
exp
,
phase
from
copy
import
deepcopy
from
copy
import
deepcopy
from
math
import
log10
,
pi
from
math
import
log10
,
pi
,
nan
from
typing
import
List
from
typing
import
List
from
time
import
time_ns
from
time
import
time_ns
...
@@ -13,12 +13,15 @@ from .base_algorithm import BaseAlgorithm
...
@@ -13,12 +13,15 @@ from .base_algorithm import BaseAlgorithm
class
Chromosome
:
class
Chromosome
:
def
__init__
(
self
,
n
,
bit_count
):
def
__init__
(
self
,
n
,
bit_count
):
self
.
gene
=
[
Chromosome
.
new_gene
(
bit_count
)
for
_
in
range
(
n
)]
self
.
gene
=
[
Chromosome
.
new_gene
(
bit_count
)
for
_
in
range
(
n
)]
self
.
fitness
=
float
(
"
nan
"
)
self
.
pattern
=
nan
self
.
needs_update
=
True
self
.
needs_update
=
True
def
__hash__
(
self
):
return
hash
(
tuple
(
self
.
gene
))
def
get_score
(
self
):
def
get_score
(
self
):
"""
Evaluates a score based on chromosome
'
s
fitness
"""
"""
Evaluates a score based on chromosome
'
s
pattern
"""
return
-
20
*
log10
(
abs
(
self
.
fitness
))
return
-
20
*
log10
(
abs
(
self
.
pattern
))
@staticmethod
@staticmethod
def
new_gene
(
bit_count
):
def
new_gene
(
bit_count
):
...
@@ -96,21 +99,25 @@ class GeneticAlgorithm(BaseAlgorithm):
...
@@ -96,21 +99,25 @@ class GeneticAlgorithm(BaseAlgorithm):
self
.
crossover
(
p1
,
p2
,
child
,
child
+
1
)
self
.
crossover
(
p1
,
p2
,
child
,
child
+
1
)
else
:
else
:
bucket_idx
=
randrange
(
self
.
bucket_count
)
bucket_idx
=
randrange
(
self
.
bucket_count
)
while
len
(
self
.
buckets
[
bucket_idx
])
==
0
:
bucket_idx
=
(
bucket_idx
+
1
)
%
self
.
bucket_count
bucket_opp
=
(
bucket_idx
+
self
.
bucket_count
//
2
)
%
self
.
bucket_count
p1
=
choice
(
self
.
buckets
[
bucket_idx
])
p1
=
choice
(
self
.
buckets
[
bucket_idx
])
p2
=
min
(
p2
=
min
(
self
.
buckets
[
(
bucket_
idx
+
self
.
bucket_count
//
2
)
%
self
.
bucket_count
],
self
.
buckets
[
bucket_
opp
],
key
=
lambda
x
:
abs
(
x
.
fitness
+
p1
.
fitness
)
key
=
lambda
x
:
abs
(
x
.
pattern
+
p1
.
pattern
)
)
)
if
len
(
self
.
buckets
[
bucket_opp
])
>
0
else
choice
(
self
.
chromosomes
)
self
.
crossover_bucket
(
p1
,
p2
,
child
,
child
+
1
)
self
.
crossover_bucket
(
p1
,
p2
,
child
,
child
+
1
)
def
organize_sample
(
self
):
def
organize_sample
(
self
):
"""
Reorganizes the sample by updating
fitness
for all chromosomes and sorting them by their scores.
"""
Reorganizes the sample by updating
pattern
for all chromosomes and sorting them by their scores.
Optionally, if use_buckets is True, allocates each chromosome to its respective bucket.
"""
Optionally, if use_buckets is True, allocates each chromosome to its respective bucket.
"""
# Update
fitness
# Update
pattern
for
chromosome
in
self
.
chromosomes
:
for
chromosome
in
self
.
chromosomes
:
if
chromosome
.
needs_update
:
if
chromosome
.
needs_update
:
chromosome
.
fitness
=
min
(
chromosome
.
pattern
=
min
(
compute_pattern
(
compute_pattern
(
N
=
self
.
N
,
N
=
self
.
N
,
k
=
self
.
k
,
k
=
self
.
k
,
...
@@ -121,14 +128,14 @@ class GeneticAlgorithm(BaseAlgorithm):
...
@@ -121,14 +128,14 @@ class GeneticAlgorithm(BaseAlgorithm):
)
)
chromosome
.
needs_update
=
False
chromosome
.
needs_update
=
False
# Sort sample by
fitness
# Sort sample by
chromosome score
self
.
chromosomes
.
sort
(
key
=
lambda
x
:
x
.
get_score
(),
reverse
=
True
)
self
.
chromosomes
.
sort
(
key
=
lambda
x
:
x
.
get_score
(),
reverse
=
True
)
# Allocate chromosomes to their respective buckets
# Allocate chromosomes to their respective buckets
if
self
.
buckets
is
not
None
:
if
self
.
buckets
is
not
None
:
self
.
initialize_buckets
()
self
.
initialize_buckets
()
for
chromosome
in
self
.
chromosomes
:
for
chromosome
in
self
.
chromosomes
:
bucket_idx
=
int
(((
phase
(
chromosome
.
fitness
)
+
pi
)
/
(
2
*
pi
))
*
self
.
bucket_count
)
%
self
.
bucket_count
bucket_idx
=
int
(((
phase
(
chromosome
.
pattern
)
+
pi
)
/
(
2
*
pi
))
*
self
.
bucket_count
)
%
self
.
bucket_count
self
.
buckets
[
bucket_idx
].
append
(
chromosome
)
self
.
buckets
[
bucket_idx
].
append
(
chromosome
)
def
mutate_sample
(
self
):
def
mutate_sample
(
self
):
...
@@ -176,7 +183,7 @@ class GeneticAlgorithm(BaseAlgorithm):
...
@@ -176,7 +183,7 @@ class GeneticAlgorithm(BaseAlgorithm):
)
)
def
crossover_bucket
(
self
,
p1
,
p2
,
c1
,
c2
):
def
crossover_bucket
(
self
,
p1
,
p2
,
c1
,
c2
):
"""
Creates two children from parents
'
genes using AM-GM
"""
"""
Creates two children from parents
'
genes using
the
AM-GM
approximation
"""
for
ii
in
range
(
self
.
N
):
for
ii
in
range
(
self
.
N
):
g1
=
p1
.
gene
[
ii
]
g1
=
p1
.
gene
[
ii
]
...
...
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