angr/analyses/bindiff.py
def _normalized_levenshtein_distance(s1, s2, acceptable_differences):
    """
    This function calculates the levenshtein distance but allows for elements in the lists to be different by any number
    in the set acceptable_differences.

    :param s1:                      A list.
    :param s2:                      Another list.
    :param acceptable_differences:  A set of numbers. If (s2[i]-s1[i]) is in the set then they are considered equal.
    :returns:
    """
    if len(s1) > len(s2):
        s1, s2 = s2, s1
        acceptable_differences = set(-i for i in acceptable_differences)
    distances = range(len(s1) + 1)
    for index2, num2 in enumerate(s2):
        new_distances = [index2 + 1]
        for index1, num1 in enumerate(s1):
            if num2 - num1 in acceptable_differences:
                new_distances.append(distances[index1])
            else:
                new_distances.append(1 + min((distances[index1],
                                             distances[index1+1],
                                             new_distances[-1])))
        distances = new_distances
    return distances[-1]

    This function calculates the levenshtein distance but allows for elements in the lists to be different by any number
    in the set acceptable_differences.

    :param s1:                      A list.
    :param s2:                      Another list.
    :param acceptable_differences:  A set of numbers. If (s2[i]-s1[i]) is in the set then they are considered equal.
    :returns:
    
This function calculates the levenshtein distance but allows for elements in the lists to be different by any number
in the set acceptable_differences.
This function calculates the levenshtein distance but allows for elements in the lists to be different by any number in the set acceptable_differences .
def _normalized_levenshtein_distance(s1, s2, acceptable_differences):
    if len(s1) > len(s2):
        s1, s2 = s2, s1
        acceptable_differences = set(-i for i in acceptable_differences)
    distances = range(len(s1) + 1)
    for index2, num2 in enumerate(s2):
        new_distances = [index2 + 1]
        for index1, num1 in enumerate(s1):
            if num2 - num1 in acceptable_differences:
                new_distances.append(distances[index1])
            else:
                new_distances.append(1 + min((distances[index1],
                                             distances[index1+1],
                                             new_distances[-1])))
        distances = new_distances
    return distances[-1]
def _normalized_levenshtein_distance ( s1 , s2 , acceptable_differences ) : if len ( s1 ) > len ( s2 ) : s1 , s2 = s2 , s1 acceptable_differences = set ( - i for i in acceptable_differences ) distances = range ( len ( s1 ) + 1 ) for index2 , num2 in enumerate ( s2 ) : new_distances = [ index2 + 1 ] for index1 , num1 in enumerate ( s1 ) : if num2 - num1 in acceptable_differences : new_distances . append ( distances [ index1 ] ) else : new_distances . append ( 1 + min ( ( distances [ index1 ] , distances [ index1 + 1 ] , new_distances [ - 1 ] ) ) ) distances = new_distances return distances [ - 1 ]
This function calculates the levenshtein distance but allows for elements in the lists to be different by any number
in the set acceptable_differences.
This function calculates the levenshtein distance but allows for elements in the lists to be different by any number in the set acceptable_differences .
"""
    This function calculates the levenshtein distance but allows for elements in the lists to be different by any number
    in the set acceptable_differences.

    :param s1:                      A list.
    :param s2:                      Another list.
    :param acceptable_differences:  A set of numbers. If (s2[i]-s1[i]) is in the set then they are considered equal.
    :returns:
    """
None
s1
None
s2
None
acceptable_differences
A set of numbers. If (s2[i]-s1[i]) is in the set then they are considered equal.
A set of numbers . If ( s2 [ i ] - s1 [ i ] ) is in the set then they are considered equal .