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k-highest-ranked-items-within-a-price-range.py
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k-highest-ranked-items-within-a-price-range.py
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# Time: O(m * n + klogk)
# Space: O(m * n)
import random
# bfs, quick select
class Solution(object):
def highestRankedKItems(self, grid, pricing, start, k):
"""
:type grid: List[List[int]]
:type pricing: List[int]
:type start: List[int]
:type k: int
:rtype: List[List[int]]
"""
directions = [(0, 1), (1, 0), (0, -1), (-1, 0)]
def nth_element(nums, n, left=0, compare=lambda a, b: a < b):
def tri_partition(nums, left, right, target, compare):
mid = left
while mid <= right:
if nums[mid] == target:
mid += 1
elif compare(nums[mid], target):
nums[left], nums[mid] = nums[mid], nums[left]
left += 1
mid += 1
else:
nums[mid], nums[right] = nums[right], nums[mid]
right -= 1
return left, right
right = len(nums)-1
while left <= right:
pivot_idx = random.randint(left, right)
pivot_left, pivot_right = tri_partition(nums, left, right, nums[pivot_idx], compare)
if pivot_left <= n <= pivot_right:
return
elif pivot_left > n:
right = pivot_left-1
else: # pivot_right < n.
left = pivot_right+1
def get_val(x):
return (lookup[x[0]][x[1]], grid[x[0]][x[1]], x[0], x[1])
result = []
q = [start]
lookup = [[-1]*len(grid[0]) for _ in xrange(len(grid))]
d = lookup[start[0]][start[1]] = 0
while q:
if len(result) >= k:
if len(result) > k:
nth_element(result, k-1, compare=lambda a, b: get_val(a) < get_val(b))
result = result[:k]
break
new_q = []
for r, c in q:
if pricing[0] <= grid[r][c] <= pricing[1]:
result.append([r, c])
for dr, dc in directions:
nr, nc = r+dr, c+dc
if not (0 <= nr < len(grid) and 0 <= nc < len(grid[0]) and grid[nr][nc] and lookup[nr][nc] == -1):
continue
lookup[nr][nc] = d+1
new_q.append((nr, nc))
q = new_q
d += 1
result.sort(key=lambda x: get_val(x))
return result