Commit
·
a89d907
1
Parent(s):
b034509
Update for bytes
Browse files
dist.py
CHANGED
@@ -1,23 +1,89 @@
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"""
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Args:
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-
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wildcard_offsets_str1 (iterable, optional): Indices in str1 that are wildcards. Defaults to None.
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wildcard_offsets_str2 (iterable, optional): Indices in str2 that are wildcards. Defaults to None.
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verbose (bool, optional): If True, prints the DP matrix and explains the process.
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Returns:
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list: If verbose=True, also returns a list of operations performed.
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"""
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# Initialize empty sets if None
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-
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m, n = len(
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# Create a matrix of size (m+1) x (n+1)
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dp = [[0] * (n + 1) for _ in range(m + 1)]
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@@ -33,14 +99,14 @@ def levenshtein_with_wildcard(str1, str2, wildcard_offsets_str1=None, wildcard_o
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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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# Check if either position is a wildcard
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# If either position is a wildcard, treat it as a match (cost = 0)
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if
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dp[i][j] = dp[i - 1][j - 1] # No cost for wildcard matches
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else:
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cost = 0 if
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dp[i][j] = min(
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dp[i - 1][j] + 1, # deletion
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dp[i][j - 1] + 1, # insertion
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@@ -48,26 +114,26 @@ def levenshtein_with_wildcard(str1, str2, wildcard_offsets_str1=None, wildcard_o
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)
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if verbose:
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operations = explain_match(
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return dp[m][n], operations
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return dp[m][n]
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def explain_match(
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"""
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Traces the optimal alignment path and explains each step of the matching process.
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Args:
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dp (list): The dynamic programming matrix.
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Returns:
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list: A list of explanation strings for each operation performed.
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"""
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m, n = len(
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operations = []
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# Find the optimal path
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@@ -108,68 +174,87 @@ def explain_match(str1, str2, dp, wildcard_offsets_str1, wildcard_offsets_str2):
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if curr_i > prev_i and curr_j > prev_j:
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char1_idx = curr_i-1
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char2_idx = curr_j-1
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char1 =
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char2 =
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elif char1 == char2:
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operations.append(f"Match:
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else:
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operations.append(f"Substitution: Replace
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# Horizontal move (insertion)
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elif curr_i == prev_i and curr_j > prev_j:
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char_idx = curr_j-1
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-
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# Vertical move (deletion)
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elif curr_i > prev_i and curr_j == prev_j:
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char_idx = curr_i-1
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return operations
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def
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def print_match_summary(
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"""
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Prints a summary of the match between two
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Args:
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"""
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#
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distance, operations = levenshtein_with_wildcard(
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)
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#
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str1_visual += bytes([char])
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print(f"Comparing '{str1_visual}' and '{str2_visual}'")
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print(f"Wildcards in str1: {sorted(wildcard_offsets_str1)}")
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print(f"Wildcards in str2: {sorted(wildcard_offsets_str2)}")
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print(f"Edit distance: {distance}")
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print("\nMatch process:")
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@@ -178,15 +263,27 @@ def print_match_summary(str1, str2, wildcard_offsets_str1=None, wildcard_offsets
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# Visual representation of the alignment
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i, j = 0, 0
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match_indicators = ""
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for op in operations:
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if "Match:" in op or "Substitution:" in op or "Wildcard match:" in op or "Double wildcard:" in op:
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# Determine match indicator
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if "Wildcard match:" in op or "Double wildcard:" in op:
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@@ -199,25 +296,36 @@ def print_match_summary(str1, str2, wildcard_offsets_str1=None, wildcard_offsets
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i += 1
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j += 1
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elif "Insertion:" in op:
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match_indicators += " "
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j += 1
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elif "Deletion:" in op:
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match_indicators += " "
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i += 1
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print("\nAlignment:")
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print(match_indicators)
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print(
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print("\nLegend:")
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print("| = exact match, * = wildcard match, X = substitution, - = gap (insertion/deletion)
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# Summary of wildcard matches
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wildcard_matches = [op for op in operations if "Wildcard match:" in op or "Double wildcard:" in op]
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# Example usage
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if __name__ == "__main__":
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# Example 1: "hello" vs "hello" with no wildcards
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print_match_summary("hello", "hello")
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print_match_summary("hello", "hallo")
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# Example 3: "hello" with 3rd position (index 2) as wildcard vs "hallo" - expect distance of 0
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print_match_summary("hello", "hallo",
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# Example
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print_match_summary("hello", "
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# Example
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print_match_summary("hello", "
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# Example
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print_match_summary("
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#!/usr/bin/env python3
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"""
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Levenshtein distance calculation with wildcard support for both strings and bytes.
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This module provides functions to calculate Levenshtein (edit) distance between
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two sequences (strings or bytes) with support for wildcard positions.
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"""
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def ensure_same_type(seq1, seq2):
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"""
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Ensure both sequences are the same type (both str or both bytes).
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Args:
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seq1: First sequence (str or bytes)
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seq2: Second sequence (str or bytes)
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Returns:
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Tuple of (seq1, seq2) with consistent types
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"""
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if isinstance(seq1, str) and isinstance(seq2, bytes):
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seq2 = seq2.decode('utf-8', errors='replace')
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elif isinstance(seq1, bytes) and isinstance(seq2, str):
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seq2 = seq2.encode('utf-8', errors='replace')
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return seq1, seq2
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def to_bytes(s):
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"""
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Convert a sequence to bytes if it's a string, otherwise return as is.
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Args:
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s: The sequence to convert (str or bytes)
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Returns:
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bytes: The input converted to bytes if it was a string
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"""
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return s.encode('utf-8', errors='replace') if isinstance(s, str) else s
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def to_str(s):
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"""
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Convert a sequence to string if it's bytes, otherwise return as is.
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Args:
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s: The sequence to convert (str or bytes)
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Returns:
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str: The input converted to string if it was bytes
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"""
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return s.decode('utf-8', errors='replace') if isinstance(s, bytes) else s
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def get_element_repr(element):
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"""
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Get a human-readable representation of a sequence element.
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Args:
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element: A single element from a sequence (byte or character)
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Returns:
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str: A printable representation of the element
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"""
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if isinstance(element, int): # For bytes objects
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if 32 <= element <= 126: # Printable ASCII
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return repr(chr(element))
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return f"0x{element:02x}"
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return repr(element) # For str objects
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def levenshtein_with_wildcard(seq1, seq2, wildcard_offsets_seq1=None, wildcard_offsets_seq2=None, verbose=False):
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"""
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Calculate the Levenshtein distance between two sequences with support for wildcards.
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Works with both strings and bytes.
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Args:
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seq1: First sequence (str or bytes)
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seq2: Second sequence (str or bytes)
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wildcard_offsets_seq1 (iterable, optional): Indices in seq1 that are wildcards. Defaults to None.
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wildcard_offsets_seq2 (iterable, optional): Indices in seq2 that are wildcards. Defaults to None.
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verbose (bool, optional): If True, returns additional information about operations. Defaults to False.
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Returns:
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int: The Levenshtein distance between the two sequences.
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list: If verbose=True, also returns a list of operations performed.
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"""
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# Initialize empty sets if None
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wildcard_offsets_seq1 = set(wildcard_offsets_seq1 or [])
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wildcard_offsets_seq2 = set(wildcard_offsets_seq2 or [])
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m, n = len(seq1), len(seq2)
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# Create a matrix of size (m+1) x (n+1)
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dp = [[0] * (n + 1) for _ in range(m + 1)]
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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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# Check if either position is a wildcard
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is_seq1_wildcard = (i - 1) in wildcard_offsets_seq1
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is_seq2_wildcard = (j - 1) in wildcard_offsets_seq2
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# If either position is a wildcard, treat it as a match (cost = 0)
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if is_seq1_wildcard or is_seq2_wildcard:
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dp[i][j] = dp[i - 1][j - 1] # No cost for wildcard matches
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else:
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cost = 0 if seq1[i - 1] == seq2[j - 1] else 1
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dp[i][j] = min(
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dp[i - 1][j] + 1, # deletion
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dp[i][j - 1] + 1, # insertion
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)
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if verbose:
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operations = explain_match(seq1, seq2, dp, wildcard_offsets_seq1, wildcard_offsets_seq2)
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return dp[m][n], operations
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return dp[m][n]
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def explain_match(seq1, seq2, dp, wildcard_offsets_seq1, wildcard_offsets_seq2):
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"""
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Traces the optimal alignment path and explains each step of the matching process.
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Args:
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seq1: First sequence (str or bytes)
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seq2: Second sequence (str or bytes)
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dp (list): The dynamic programming matrix.
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wildcard_offsets_seq1 (set): Indices in seq1 that are wildcards.
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wildcard_offsets_seq2 (set): Indices in seq2 that are wildcards.
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Returns:
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list: A list of explanation strings for each operation performed.
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"""
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m, n = len(seq1), len(seq2)
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operations = []
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# Find the optimal path
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if curr_i > prev_i and curr_j > prev_j:
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char1_idx = curr_i-1
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char2_idx = curr_j-1
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char1 = seq1[char1_idx]
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char2 = seq2[char2_idx]
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is_seq1_wildcard = char1_idx in wildcard_offsets_seq1
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is_seq2_wildcard = char2_idx in wildcard_offsets_seq2
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char1_repr = get_element_repr(char1)
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char2_repr = get_element_repr(char2)
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if is_seq1_wildcard and is_seq2_wildcard:
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operations.append(f"Double wildcard: Position {char1_idx} in seq1 and position {char2_idx} in seq2 are both wildcards")
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elif is_seq1_wildcard:
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operations.append(f"Wildcard match: Position {char1_idx} in seq1 is a wildcard, matches {char2_repr} at position {char2_idx} in seq2")
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elif is_seq2_wildcard:
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operations.append(f"Wildcard match: Position {char2_idx} in seq2 is a wildcard, matches {char1_repr} at position {char1_idx} in seq1")
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elif char1 == char2:
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operations.append(f"Match: {char1_repr} at position {char1_idx} matches {char2_repr} at position {char2_idx}")
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else:
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operations.append(f"Substitution: Replace {char1_repr} at position {char1_idx} with {char2_repr} at position {char2_idx}")
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# Horizontal move (insertion)
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elif curr_i == prev_i and curr_j > prev_j:
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char_idx = curr_j-1
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char_repr = get_element_repr(seq2[char_idx])
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operations.append(f"Insertion: Insert {char_repr} at position {char_idx} in seq2")
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# Vertical move (deletion)
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elif curr_i > prev_i and curr_j == prev_j:
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char_idx = curr_i-1
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char_repr = get_element_repr(seq1[char_idx])
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operations.append(f"Deletion: Delete {char_repr} at position {char_idx} in seq1")
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return operations
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+
def create_gap_element(sequence):
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"""
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Create a gap element compatible with the sequence type.
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Args:
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sequence: The sequence (str or bytes) to create a gap for
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Returns:
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The appropriate gap element for the sequence type
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"""
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if isinstance(sequence, bytes):
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return b'-'
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else:
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return '-'
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def print_match_summary(seq1, seq2, wildcard_offsets_seq1=None, wildcard_offsets_seq2=None):
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"""
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Prints a summary of the match between two sequences, highlighting wildcards by their offsets.
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Works with both strings and bytes.
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Args:
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seq1: First sequence (str or bytes)
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seq2: Second sequence (str or bytes)
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wildcard_offsets_seq1 (iterable, optional): Indices in seq1 that are wildcards. Defaults to None.
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wildcard_offsets_seq2 (iterable, optional): Indices in seq2 that are wildcards. Defaults to None.
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Returns:
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tuple: (distance, operations) The edit distance and list of operations
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"""
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# Ensure sequences are of the same type for comparison
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seq1, seq2 = ensure_same_type(seq1, seq2)
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# Initialize empty sets if None
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wildcard_offsets_seq1 = set(wildcard_offsets_seq1 or [])
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wildcard_offsets_seq2 = set(wildcard_offsets_seq2 or [])
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distance, operations = levenshtein_with_wildcard(
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seq1, seq2, wildcard_offsets_seq1, wildcard_offsets_seq2, verbose=True
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)
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# For reporting, convert to a human-readable representation if needed
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+
seq1_repr = repr(seq1)
|
253 |
+
seq2_repr = repr(seq2)
|
|
|
254 |
|
255 |
+
print(f"Comparing {seq1_repr} and {seq2_repr}")
|
256 |
+
print(f"Wildcards in seq1: {sorted(wildcard_offsets_seq1)}")
|
257 |
+
print(f"Wildcards in seq2: {sorted(wildcard_offsets_seq2)}")
|
|
|
|
|
|
|
|
|
258 |
print(f"Edit distance: {distance}")
|
259 |
print("\nMatch process:")
|
260 |
|
|
|
263 |
|
264 |
# Visual representation of the alignment
|
265 |
i, j = 0, 0
|
266 |
+
is_bytes = isinstance(seq1, bytes)
|
267 |
+
|
268 |
+
if is_bytes:
|
269 |
+
aligned_seq1 = bytearray()
|
270 |
+
aligned_seq2 = bytearray()
|
271 |
+
gap = ord('-')
|
272 |
+
else:
|
273 |
+
aligned_seq1 = ""
|
274 |
+
aligned_seq2 = ""
|
275 |
+
gap = '-'
|
276 |
+
|
277 |
match_indicators = ""
|
278 |
|
279 |
for op in operations:
|
280 |
if "Match:" in op or "Substitution:" in op or "Wildcard match:" in op or "Double wildcard:" in op:
|
281 |
+
if is_bytes:
|
282 |
+
aligned_seq1.append(seq1[i])
|
283 |
+
aligned_seq2.append(seq2[j])
|
284 |
+
else:
|
285 |
+
aligned_seq1 += seq1[i]
|
286 |
+
aligned_seq2 += seq2[j]
|
287 |
|
288 |
# Determine match indicator
|
289 |
if "Wildcard match:" in op or "Double wildcard:" in op:
|
|
|
296 |
i += 1
|
297 |
j += 1
|
298 |
elif "Insertion:" in op:
|
299 |
+
if is_bytes:
|
300 |
+
aligned_seq1.append(gap)
|
301 |
+
aligned_seq2.append(seq2[j])
|
302 |
+
else:
|
303 |
+
aligned_seq1 += gap
|
304 |
+
aligned_seq2 += seq2[j]
|
305 |
|
306 |
match_indicators += " "
|
307 |
j += 1
|
308 |
elif "Deletion:" in op:
|
309 |
+
if is_bytes:
|
310 |
+
aligned_seq1.append(seq1[i])
|
311 |
+
aligned_seq2.append(gap)
|
312 |
+
else:
|
313 |
+
aligned_seq1 += seq1[i]
|
314 |
+
aligned_seq2 += gap
|
315 |
+
|
316 |
match_indicators += " "
|
317 |
i += 1
|
318 |
|
319 |
print("\nAlignment:")
|
320 |
+
if is_bytes:
|
321 |
+
aligned_seq1 = bytes(aligned_seq1)
|
322 |
+
aligned_seq2 = bytes(aligned_seq2)
|
323 |
+
|
324 |
+
print(repr(aligned_seq1))
|
325 |
print(match_indicators)
|
326 |
+
print(repr(aligned_seq2))
|
327 |
print("\nLegend:")
|
328 |
+
print("| = exact match, * = wildcard match, X = substitution, - = gap (insertion/deletion)")
|
329 |
|
330 |
# Summary of wildcard matches
|
331 |
wildcard_matches = [op for op in operations if "Wildcard match:" in op or "Double wildcard:" in op]
|
|
|
338 |
|
339 |
# Example usage
|
340 |
if __name__ == "__main__":
|
341 |
+
print("\n--- String Examples ---")
|
342 |
# Example 1: "hello" vs "hello" with no wildcards
|
343 |
print_match_summary("hello", "hello")
|
344 |
|
|
|
346 |
print_match_summary("hello", "hallo")
|
347 |
|
348 |
# Example 3: "hello" with 3rd position (index 2) as wildcard vs "hallo" - expect distance of 0
|
349 |
+
print_match_summary("hello", "hallo", wildcard_offsets_seq1=[2])
|
350 |
+
|
351 |
+
# Example 4: "hello" vs "hillo" with 2nd position (index 1) as wildcard in seq2 - expect distance of 0
|
352 |
+
print_match_summary("hello", "hillo", wildcard_offsets_seq2=[1])
|
353 |
+
|
354 |
+
# Example 5: Multiple wildcards in seq1
|
355 |
+
print_match_summary("hello", "haxyz", wildcard_offsets_seq1=[2, 3, 4])
|
356 |
+
|
357 |
+
print("\n--- Bytes Examples ---")
|
358 |
+
# Example 6: Working with bytes
|
359 |
+
print_match_summary(b"hello", b"hallo")
|
360 |
|
361 |
+
# Example 7: Working with bytes with wildcard
|
362 |
+
print_match_summary(b"hello", b"hallo", wildcard_offsets_seq1=[2])
|
363 |
|
364 |
+
# Example 8: Mixed types (bytes and string)
|
365 |
+
print_match_summary(b"hello", "hallo", wildcard_offsets_seq1=[2])
|
366 |
|
367 |
+
# Example 9: Non-printable bytes example
|
368 |
+
print_match_summary(b"\x01\x02\x03\x04", b"\x01\x05\x03\x04", wildcard_offsets_seq1=[1])
|