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city_lights.py
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city_lights.py
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# Copyright (c) 2019 kamyu. All rights reserved.
#
# Facebook Hacker Cup 2018 Final Round - City Lights
# https://www.facebook.com/hackercup/problem/162710881087828/
#
# Time: O(S^2 * W^2), there is no built-in rbtree in python, so we can use skip list alternatively,
# which implementation is much simpler than rbtree
# and has the same complexity on average
# Space: O(S * W * min(S, W))
#
# based on official solution:
# dp[i][h][b] = # of combinations in i's subtree requiring b buildings, with height h still required
# dp_accu[i][h][b] = sum of dp[i][0..(h-1)][b]
from collections import defaultdict
from bisect import bisect_left
from random import randint, seed
# Template:
# https://github.com/kamyu104/LeetCode-Solutions/blob/master/Python/design-skiplist.py
class SkipNode(object):
def __init__(self, level=0, val=None):
self.val = val
self.nexts = [None]*level
self.prevs = [None]*level
class SkipList(object):
P_NUMERATOR, P_DENOMINATOR = 1, 2 # P = 1/4 in redis implementation
MAX_LEVEL = 32 # enough for 2^32 elements
def __init__(self, end=float("inf"), can_duplicated=False):
seed(0)
self.__head = SkipNode()
self.__len = 0
self.__can_duplicated = can_duplicated
self.add(end)
def lower_bound(self, target):
return self.__lower_bound(target, self.__find_prev_nodes(target))
def find(self, target):
return self.__find(target, self.__find_prev_nodes(target))
def add(self, val):
if not self.__can_duplicated and self.find(val):
return False
node = SkipNode(self.__random_level(), val)
if len(self.__head.nexts) < len(node.nexts):
self.__head.nexts.extend([None]*(len(node.nexts)-len(self.__head.nexts)))
prevs = self.__find_prev_nodes(val)
for i in xrange(len(node.nexts)):
node.nexts[i] = prevs[i].nexts[i]
if prevs[i].nexts[i]:
prevs[i].nexts[i].prevs[i] = node
prevs[i].nexts[i] = node
node.prevs[i] = prevs[i]
self.__len += 1
return True
def remove(self, val):
prevs = self.__find_prev_nodes(val)
curr = self.__find(val, prevs)
if not curr:
return False
self.__len -= 1
for i in reversed(xrange(len(curr.nexts))):
prevs[i].nexts[i] = curr.nexts[i]
if curr.nexts[i]:
curr.nexts[i].prevs[i] = prevs[i]
if not self.__head.nexts[i]:
self.__head.nexts.pop()
return True
def __lower_bound(self, val, prevs):
if prevs:
candidate = prevs[0].nexts[0]
if candidate:
return candidate
return None
def __find(self, val, prevs):
candidate = self.__lower_bound(val, prevs)
if candidate and candidate.val == val:
return candidate
return None
def __find_prev_nodes(self, val):
prevs = [None]*len(self.__head.nexts)
curr = self.__head
for i in reversed(xrange(len(self.__head.nexts))):
while curr.nexts[i] and curr.nexts[i].val < val:
curr = curr.nexts[i]
prevs[i] = curr
return prevs
def __random_level(self):
level = 1
while randint(1, SkipList.P_DENOMINATOR) <= SkipList.P_NUMERATOR and \
level < SkipList.MAX_LEVEL:
level += 1
return level
def __len__(self):
return self.__len-1 # excluding end node
def __str__(self):
result = []
for i in reversed(xrange(len(self.__head.nexts))):
result.append([])
curr = self.__head.nexts[i]
while curr:
result[-1].append(str(curr.val))
curr = curr.nexts[i]
return "\n".join(map(lambda x: "->".join(x), result))
def add(a, b):
return (a+b)%MOD
def multiply(a, b):
return (a*b)%MOD
def compute_accu(i, dp, dp_accu):
for h in xrange(len(dp[i])): # O(W) times
for b in xrange(len(dp[i][h])): # O(min(S, W)) times
dp_accu[i][h+1][b] = add(dp_accu[i][h][b], dp[i][h][b])
def city_lights_helper(i, children, building_height, window_heights, dp, dp_accu):
dp[i][0][0] = 1
for c in children[i]: # O(2) times
city_lights_helper(c, children, building_height, window_heights, dp, dp_accu)
compute_accu(i, dp, dp_accu), compute_accu(c, dp, dp_accu)
tmp = [[0 for _ in xrange(len(dp[i][h]))] for h in xrange(len(dp[i]))]
for h in xrange(len(dp[i])): # O(W) times
for b in xrange(len(dp[i][h])): # O(min(S, W)) times
for b2 in xrange(len(dp[i][h])-b): # O(min(S, W)) times
# new_dp[i][h][b+b2] = dp[i][h][b]*dp[c][h][b2] + dp[i][h][b]*dp[c][0..(h-1)][b2] + dp[i][0..(h-1)][b]*dp[c][h][b2]
tmp[h][b+b2] = add(tmp[h][b+b2], dp[i][h][b]*dp_accu[c][h+1][b2] + dp_accu[i][h][b]*dp[c][h][b2])
dp[i][:] = tmp
window_heights[i].sort()
tmp = [[0 for _ in xrange(len(dp[i][h]))] for h in xrange(len(dp[i]))]
power = 1
for j in xrange(len(window_heights[i])+1): # O(W) times
h2 = window_heights[i][j-1] if j-1 >= 0 else 0
for h in xrange(len(dp[i])): # O(W) times
for b in xrange(len(dp[i][h])): # O(min(S, W)) times
tmp[max(h, h2)][b] = add(tmp[max(h, h2)][b], power*dp[i][h][b]) # count # of combinations
if j-1 >= 0:
power = multiply(power, 2)
dp[i][:] = tmp
for h in xrange(building_height[i], len(dp[i])): # O(W) times
for b in xrange(len(dp[i][h])-1): # O(min(S, W)) times
dp[i][0][b+1] = add(dp[i][0][b+1], dp[i][h][b]) # make this node as a new building with height h
dp[i][h][b] = 0 # no need to keep tracking count on any not-yet-satisfied path
def city_lights():
W, S = map(int, raw_input().strip().split())
W_P, S_P = [None]*W, [None]*S
w_y_set = set([0])
for i in xrange(W):
W_P[i]= map(int, raw_input().strip().split())
w_y_set.add(W_P[i][Y])
for i in xrange(S):
S_P[i]= map(int, raw_input().strip().split())
sorted_w_y, height_to_idx = sorted(w_y_set), {} # Time: O(WlogW), coordinate compression of y of W
for i, y in enumerate(sorted_w_y):
height_to_idx[y] = i
S_P.sort(key=lambda x: x[Y]) # Time: O(SlogS)
children = defaultdict(list)
ordered_set, building_height, lookup = SkipList(((float("inf"), float("inf")), float("inf"))), [bisect_left(sorted_w_y, 1)], {}
ordered_set.add(((float("-inf"), float("inf")), 0))
for x, y in S_P: # Time: O(SlogS + SlogW), split intervals by x of star in non-decreasing order of y to build up binary tree
(a, b), c = ordered_set.lower_bound(((x, float("inf")), float("inf"))).prevs[0].val
if not a <= x <= b:
continue
if a < x:
children[c].append(len(building_height))
ordered_set.add(((a, x-1), len(building_height)))
building_height.append(bisect_left(sorted_w_y, y))
if b > x:
children[c].append(len(building_height))
ordered_set.add(((x+1, b), len(building_height)))
building_height.append(bisect_left(sorted_w_y, y))
ordered_set.remove(((a, b), c))
lookup[x] = c
window_heights = defaultdict(list)
for x, y in W_P: # Time: O(WlogS), group windows by tree nodes
c = lookup[x] if x in lookup else ordered_set.lower_bound(((x, float("inf")), float("inf"))).prevs[0].val[1]
window_heights[c].append(height_to_idx[y])
dp = [[[0 for _ in xrange(min(len(building_height), len(W_P))+1)] for _ in xrange(len(w_y_set))] for _ in xrange(len(building_height))]
dp_accu = [[[0 for _ in xrange(min(len(building_height), len(W_P))+1)] for _ in xrange(len(w_y_set)+1)] for _ in xrange(len(building_height))]
city_lights_helper(0, children, building_height, window_heights, dp, dp_accu) # Time: O(S^2*W^2)
result = 0
for i in xrange(1, len(dp[0][0])): # Time: O(min(S, W)), compute expected number
result = add(result, i*dp[0][0][i])
return result
MOD = 10**9+7
X, Y = range(2)
for case in xrange(input()):
print 'Case #%d: %s' % (case+1, city_lights())