Affine Gap¶
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class
py_stringmatching.similarity_measure.affine.
Affine
(gap_start=1, gap_continuation=0.5, sim_func=identity_function)[source]¶ Returns the affine gap score between two strings.
The affine gap measure is an extension of the Needleman-Wunsch measure that handles the longer gaps more gracefully. For more information refer to the string matching chapter in the DI book (“Principles of Data Integration”).
Parameters: - gap_start (float) – Cost for the gap at the start (defaults to 1).
- gap_continuation (float) – Cost for the gap continuation (defaults to 0.5).
- sim_func (function) – Function computing similarity score between two characters, which are represented as strings (defaults to an identity function, which returns 1 if the two characters are the same and returns 0 otherwise).
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gap_start
¶ float
An attribute to store the gap cost at the start.
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gap_continuation
¶ float
An attribute to store the gap continuation cost.
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sim_func
¶ function
An attribute to store the similarity function.
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get_raw_score
(string1, string2)[source]¶ Computes the affine gap score between two strings. This score can be outside the range [0,1].
Parameters: string1,string2 (str) – Input strings. Returns: Affine gap score betwen the two input strings (float). Raises: TypeError
– If the inputs are not strings or if one of the inputs is None.Examples
>>> aff = Affine() >>> aff.get_raw_score('dva', 'deeva') 1.5 >>> aff = Affine(gap_start=2, gap_continuation=0.5) >>> aff.get_raw_score('dva', 'deeve') -0.5 >>> aff = Affine(gap_continuation=0.2, sim_func=lambda s1, s2: (int(1 if s1 == s2 else 0))) >>> aff.get_raw_score('AAAGAATTCA', 'AAATCA') 4.4
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set_gap_continuation
(gap_continuation)[source]¶ Set gap continuation cost.
Parameters: gap_continuation (float) – Cost for the gap continuation.