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LeetCode-Solutions/Python/best-meeting-point.py at master · dbgee/LeetCode-Solutions · GitHub
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Python
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best-meeting-point.py
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46 lines (38 loc) · 1.61 KB
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LeetCode-Solutions
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Python
/
best-meeting-point.py
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# Time: O(m * n)
# Space: O(m + n)
from
random
import
randint
class
Solution
(
object
):
def
minTotalDistance
(
self
,
grid
):
"""
:type grid: List[List[int]]
:rtype: int
"""
x
=
[
i
for
i
,
row
in
enumerate
(
grid
)
for
v
in
row
if
v
==
1
]
y
=
[
j
for
row
in
grid
for
j
,
v
in
enumerate
(
row
)
if
v
==
1
]
mid_x
=
self
.
findKthLargest
(
x
,
len
(
x
)
/
2
+
1
)
mid_y
=
self
.
findKthLargest
(
y
,
len
(
y
)
/
2
+
1
)
return
sum
([
abs
(
mid_x
-
i
)
+
abs
(
mid_y
-
j
)
for
i
,
row
in
enumerate
(
grid
)
for
j
,
v
in
enumerate
(
row
)
if
v
==
1
])
def
findKthLargest
(
self
,
nums
,
k
):
left
,
right
=
0
,
len
(
nums
)
-
1
while
left
<=
right
:
pivot_idx
=
randint
(
left
,
right
)
new_pivot_idx
=
self
.
PartitionAroundPivot
(
left
,
right
,
pivot_idx
,
nums
)
if
new_pivot_idx
==
k
-
1
:
return
nums
[
new_pivot_idx
]
elif
new_pivot_idx
>
k
-
1
:
right
=
new_pivot_idx
-
1
else
:
# new_pivot_idx < k - 1.
left
=
new_pivot_idx
+
1
def
PartitionAroundPivot
(
self
,
left
,
right
,
pivot_idx
,
nums
):
pivot_value
=
nums
[
pivot_idx
]
new_pivot_idx
=
left
nums
[
pivot_idx
],
nums
[
right
]
=
nums
[
right
],
nums
[
pivot_idx
]
for
i
in
xrange
(
left
,
right
):
if
nums
[
i
]
>
pivot_value
:
nums
[
i
],
nums
[
new_pivot_idx
]
=
nums
[
new_pivot_idx
],
nums
[
i
]
new_pivot_idx
+=
1
nums
[
right
],
nums
[
new_pivot_idx
]
=
nums
[
new_pivot_idx
],
nums
[
right
]
return
new_pivot_idx
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