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TheAlgorithms-Python/networking_flow/minimum_cut.py at master · windNight/TheAlgorithms-Python · GitHub
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networking_flow
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minimum_cut.py
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TheAlgorithms-Python
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networking_flow
/
minimum_cut.py
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# Minimum cut on Ford_Fulkerson algorithm.
test_graph
=
[
[
0
,
16
,
13
,
0
,
0
,
0
],
[
0
,
0
,
10
,
12
,
0
,
0
],
[
0
,
4
,
0
,
0
,
14
,
0
],
[
0
,
0
,
9
,
0
,
0
,
20
],
[
0
,
0
,
0
,
7
,
0
,
4
],
[
0
,
0
,
0
,
0
,
0
,
0
],
]
def
BFS
(
graph
,
s
,
t
,
parent
):
# Return True if there is node that has not iterated.
visited
=
[
False
]
*
len
(
graph
)
queue
=
[
s
]
visited
[
s
]
=
True
while
queue
:
u
=
queue
.
pop
(
0
)
for
ind
in
range
(
len
(
graph
[
u
])):
if
visited
[
ind
]
is
False
and
graph
[
u
][
ind
]
>
0
:
queue
.
append
(
ind
)
visited
[
ind
]
=
True
parent
[
ind
]
=
u
return
True
if
visited
[
t
]
else
False
def
mincut
(
graph
,
source
,
sink
):
"""This array is filled by BFS and to store path
>>> mincut(test_graph, source=0, sink=5)
[(1, 3), (4, 3), (4, 5)]
"""
parent
=
[
-
1
]
*
(
len
(
graph
))
max_flow
=
0
res
=
[]
temp
=
[
i
[:]
for
i
in
graph
]
# Record original cut, copy.
while
BFS
(
graph
,
source
,
sink
,
parent
):
path_flow
=
float
(
"Inf"
)
s
=
sink
while
s
!=
source
:
# Find the minimum value in select path
path_flow
=
min
(
path_flow
,
graph
[
parent
[
s
]][
s
])
s
=
parent
[
s
]
max_flow
+=
path_flow
v
=
sink
while
v
!=
source
:
u
=
parent
[
v
]
graph
[
u
][
v
]
-=
path_flow
graph
[
v
][
u
]
+=
path_flow
v
=
parent
[
v
]
for
i
in
range
(
len
(
graph
)):
for
j
in
range
(
len
(
graph
[
0
])):
if
graph
[
i
][
j
]
==
0
and
temp
[
i
][
j
]
>
0
:
res
.
append
((
i
,
j
))
return
res
if
__name__
==
"__main__"
:
print
(
mincut
(
test_graph
,
source
=
0
,
sink
=
5
))
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