新增一个计算字符串编辑距离的复杂函数
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@@ -51,3 +51,64 @@ def word_segmentation(
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return jieba.dt.cut(str(sentence), cut_all=cut_all, HMM=HMM, use_paddle=use_paddle)
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except ImportError:
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raise ValueError("jieba is not install")
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def GetEditorDistanceAndOperations(s1:str, s2:str) -> Tuple[int, List[Tuple[str, int, int, str]]]:
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"""
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计算两个字符串的编辑距离和操作序列
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操作格式: (操作类型, 开始位置, 结束位置, 内容)
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位置基于源字符串s1
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"""
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m, n = len(s1), len(s2)
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# 使用简单的LCS算法来找到最长公共子序列
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# 然后基于LCS生成操作序列
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lcs = [[0] * (n + 1) for _ in range(m + 1)]
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# 构建LCS表
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for i in range(1, m + 1):
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for j in range(1, n + 1):
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if s1[i - 1] == s2[j - 1]:
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lcs[i][j] = lcs[i - 1][j - 1] + 1
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else:
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lcs[i][j] = max(lcs[i - 1][j], lcs[i][j - 1])
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# 基于LCS生成操作序列
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operations = []
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i, j = m, n
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while i > 0 or j > 0:
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if i > 0 and j > 0 and s1[i - 1] == s2[j - 1]:
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# 字符匹配,不需要操作
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i -= 1
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j -= 1
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elif j > 0 and (i == 0 or lcs[i][j - 1] >= lcs[i - 1][j]):
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# 需要插入s2[j-1]
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# 找到插入位置(在s1中的位置)
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insert_pos = i
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operations.insert(0, ("add", insert_pos, insert_pos, s2[j - 1]))
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j -= 1
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else:
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# 需要删除s1[i-1]
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operations.insert(0, ("delete", i - 1, i, s1[i - 1]))
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i -= 1
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# 合并连续的操作
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merged_operations = []
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for op in operations:
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if merged_operations and merged_operations[-1][0] == op[0]:
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last_op = merged_operations[-1]
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if op[0] == "add" and last_op[2] == op[1]:
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# 合并连续的添加操作
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merged_operations[-1] = (op[0], last_op[1], op[2], last_op[3] + op[3])
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elif op[0] == "delete" and last_op[2] == op[1]:
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# 合并连续的删除操作
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merged_operations[-1] = (op[0], last_op[1], op[2], last_op[3] + op[3])
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else:
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merged_operations.append(op)
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else:
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merged_operations.append(op)
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# 计算编辑距离
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edit_distance = m + n - 2 * lcs[m][n]
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return edit_distance, merged_operations
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