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81 lines
1.9 KiB
81 lines
1.9 KiB
import math
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with open("input") as file:
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rawWeights = [[int(num) for num in line] for line in file.read().splitlines()]
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Node = tuple[int, int]
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# this is a performance killer -> O(n)
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def popMinNode(openList: dict[Node, int]) -> Node:
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node, _ = min(openList.items(), key=lambda elem: elem[1])
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openList.pop(node)
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return node
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def getNeighbours(node: Node, size):
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x, y = node
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return set(filter(
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lambda n: 0 <= n[0] < size and 0 <= n[1] < size, {
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(x + 1, y),
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(x - 1, y),
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(x, y + 1),
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(x, y - 1)
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}
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))
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# Dijkstra without priority queue -> super slow...
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def findPath(weights):
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size = len(weights)
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target = (size, size)
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openList, closedList = {(0, 0): 0}, set()
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dists = {(x, y): math.inf for x in range(size) for y in range(size)}
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pres = {(x, y): None for x in range(size) for y in range(size)}
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dists[(0, 0)] = 0
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while len(openList) > 0:
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currentNode = popMinNode(openList)
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if currentNode == target:
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# path found
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break
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closedList.add(currentNode)
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for successor in getNeighbours(currentNode, size).difference(closedList):
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x, y = successor
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d = dists[currentNode] + weights[y][x]
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if successor in openList.keys() and d >= dists[successor]:
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continue
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pres[successor] = currentNode
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dists[successor] = d
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openList[successor] = d
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node = (size - 1, size - 1)
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risk = 0
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while node != (0, 0):
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x, y = node
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risk += weights[y][x]
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node = pres[node]
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print(risk)
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def expandWeights(weights):
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size = len(weights)
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parts = [[[val for val in row] for row in weights]]
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for i in range(8):
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part = parts[i]
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added = [[val + 1 if val < 9 else 1 for val in row] for row in part]
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parts.append(added)
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newWeights = []
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for y in range(5):
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row = parts[y]
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for x in range(4):
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addRight = parts[y + x + 1]
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for i in range(size):
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row[i] += addRight[i]
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newWeights.extend(row)
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return newWeights
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findPath(rawWeights)
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findPath(expandWeights(rawWeights))
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