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Diffstat (limited to 'min_cost_convert_string1.py')
-rw-r--r-- | min_cost_convert_string1.py | 102 |
1 files changed, 102 insertions, 0 deletions
diff --git a/min_cost_convert_string1.py b/min_cost_convert_string1.py new file mode 100644 index 0000000..cb9c4fc --- /dev/null +++ b/min_cost_convert_string1.py @@ -0,0 +1,102 @@ +# 2976. Minimum Cost to Convert String I +from collections import defaultdict +import heapq + +""" +you are given two 0 indexed strings 'source' and 'target', both of length 'n' +and consisting of lowercase english letters. you are also given two 0 indexed +character arrays 'original' and 'changed', and an integer array 'cost' where +'cost[i]' represents the cost of changing the character 'original[i]' to the +character 'changed[i]' you start with the string 'source'. in one operation, +you can pick a character 'x' from te string and change it to the character +'y' at a cost of 'z' if there exists any index 'j' such that 'cost[j] == z, +original[j] == x, changed[j] == y'. return the minimum cost to conver the +string 'source' to the string 'target'. +""" + + +class Solution(object): + def minimumCost(self, source, target, original, changed, cost): + """ + :type source: str + :type target: str + :type original: List[str] + :type changed: List[str] + :type cost: List[int] + :rtype: int + """ + + def build(original, changed, costs): + graph = defaultdict(lambda: defaultdict(lambda: float("inf"))) + for ori, ch, cost in zip(original, changed, costs): + graph[ori][ch] = min(graph[ori][ch], cost) + return graph + + def dijkstra(graph, start_node, target_node): + if start_node not in graph: + return float("inf") + + visited_nodes = set() + min_heap = [(0, start_node)] + + while min_heap: + cost_to_current, current_node = heapq.heappop(min_heap) + if current_node == target_node: + return cost_to_current + if current_node in visited_nodes: + continue + visited_nodes.add(current_node) + for neighbor_node in graph[current_node]: + if neighbor_node not in visited_nodes: + heapq.heappush( + min_heap, + ( + cost_to_current + graph[current_node][neighbor_node], + neighbor_node, + ), + ) + return float("inf") + + graph = build(original, changed, cost) + total_cost = 0 + memo = {} + + for s, t in zip(source, target): + if s != t: + if (s, t) in memo: + cost = memo[(s, t)] + else: + cost = dijkstra(graph, s, t) + memo[(s, t)] = cost + if cost == float("inf"): + return -1 + total_cost += cost + + return total_cost + + +if __name__ == "__main__": + obj = Solution() + print( + obj.minimumCost( + source="abcd", + target="acbe", + original=["a", "b", "c", "c", "e", "d"], + changed=["b", "c", "b", "e", "b", "e"], + cost=[2, 5, 5, 1, 2, 20], + ) + ) + print( + obj.minimumCost( + source="aaaa", + target="bbbb", + original=["a", "c"], + changed=["c", "b"], + cost=[1, 2], + ) + ) + print( + obj.minimumCost( + source="abcd", target="abce", original=["a"], changed=["e"], cost=[10000] + ) + ) |