o rZŽh^ã@sVdZzddlZWn eyYnwddd„Zdd„Zd d „Zdd d„Zddd„ZdS)a  Text Segmentation Metrics 1. Windowdiff Pevzner, L., and Hearst, M., A Critique and Improvement of an Evaluation Metric for Text Segmentation, Computational Linguistics 28, 19-36 2. Generalized Hamming Distance Bookstein A., Kulyukin V.A., Raita T. Generalized Hamming Distance Information Retrieval 5, 2002, pp 353-375 Baseline implementation in C++ http://digital.cs.usu.edu/~vkulyukin/vkweb/software/ghd/ghd.html Study describing benefits of Generalized Hamming Distance Versus WindowDiff for evaluating text segmentation tasks Begsten, Y. Quel indice pour mesurer l'efficacite en segmentation de textes ? TALN 2009 3. Pk text segmentation metric Beeferman D., Berger A., Lafferty J. (1999) Statistical Models for Text Segmentation Machine Learning, 34, 177-210 éNÚ1FcCsªt|ƒt|ƒkr tdƒ‚|t|ƒkrtdƒ‚d}tt|ƒ|dƒD](}t||||… |¡||||… |¡ƒ}|rC||7}q"|td|ƒ7}q"|t|ƒ|dS)aW Compute the windowdiff score for a pair of segmentations. A segmentation is any sequence over a vocabulary of two items (e.g. "0", "1"), where the specified boundary value is used to mark the edge of a segmentation. >>> s1 = "000100000010" >>> s2 = "000010000100" >>> s3 = "100000010000" >>> '%.2f' % windowdiff(s1, s1, 3) '0.00' >>> '%.2f' % windowdiff(s1, s2, 3) '0.30' >>> '%.2f' % windowdiff(s2, s3, 3) '0.80' :param seg1: a segmentation :type seg1: str or list :param seg2: a segmentation :type seg2: str or list :param k: window width :type k: int :param boundary: boundary value :type boundary: str or int or bool :param weighted: use the weighted variant of windowdiff :type weighted: boolean :rtype: float z!Segmentations have unequal lengthzCWindow width k should be smaller or equal than segmentation lengthsréçð?)ÚlenÚ ValueErrorÚrangeÚabsÚcountÚmin)Zseg1Zseg2ÚkÚboundaryZweightedÚwdÚiZndiff©rúH/var/www/auris/lib/python3.10/site-packages/nltk/metrics/segmentation.pyÚ windowdiff1s ÿ0 rcCsFt ||f¡}|t |¡|ddd…f<|t |¡|dd…df<|S)Nr)ÚnpÚemptyZarange)ZnrowsZncolsÚins_costÚdel_costÚmatrrrÚ _init_matbsrc Cs¦t|ƒD]L\}}t|ƒD]C\}} |t|| ƒ|||f} || kr)|||f} n|| kr8||||df} n |||d|f} t| | ƒ||d|df<q qdS)Nr)Ú enumeraterr ) rZrowvZcolvrrÚshift_cost_coeffrZrowiÚjZcoljZ shift_costZtcostrrrÚ_ghd_auxisõÿrç@rc s´‡fdd„t|ƒDƒ}‡fdd„t|ƒDƒ}t|ƒ}t|ƒ} |dkr(| dkr(dS|dkr4| dkr4||S|dkr@| dkr@| |St| d|d||ƒ} t| |||||ƒt| dƒS)av Compute the Generalized Hamming Distance for a reference and a hypothetical segmentation, corresponding to the cost related to the transformation of the hypothetical segmentation into the reference segmentation through boundary insertion, deletion and shift operations. A segmentation is any sequence over a vocabulary of two items (e.g. "0", "1"), where the specified boundary value is used to mark the edge of a segmentation. Recommended parameter values are a shift_cost_coeff of 2. Associated with a ins_cost, and del_cost equal to the mean segment length in the reference segmentation. >>> # Same examples as Kulyukin C++ implementation >>> ghd('1100100000', '1100010000', 1.0, 1.0, 0.5) 0.5 >>> ghd('1100100000', '1100000001', 1.0, 1.0, 0.5) 2.0 >>> ghd('011', '110', 1.0, 1.0, 0.5) 1.0 >>> ghd('1', '0', 1.0, 1.0, 0.5) 1.0 >>> ghd('111', '000', 1.0, 1.0, 0.5) 3.0 >>> ghd('000', '111', 1.0, 2.0, 0.5) 6.0 :param ref: the reference segmentation :type ref: str or list :param hyp: the hypothetical segmentation :type hyp: str or list :param ins_cost: insertion cost :type ins_cost: float :param del_cost: deletion cost :type del_cost: float :param shift_cost_coeff: constant used to compute the cost of a shift. ``shift cost = shift_cost_coeff * |i - j|`` where ``i`` and ``j`` are the positions indicating the shift :type shift_cost_coeff: float :param boundary: boundary value :type boundary: str or int or bool :rtype: float cóg|] \}}|ˆkr|‘qSrr©Ú.0rÚval©r rrÚ §ózghd..crrrrr!rrr"¨r#rgr)éÿÿÿÿr$)rrrrÚfloat) ÚrefÚhyprrrr Zref_idxZhyp_idxZ nref_boundZ nhyp_boundrrr!rÚghdys. r(cCsœ|durttt|ƒ| |¡dƒƒ}d}tt|ƒ|dƒD]$}||||… |¡dk}||||… |¡dk}||krC|d7}q|t|ƒ|dS)aù Compute the Pk metric for a pair of segmentations A segmentation is any sequence over a vocabulary of two items (e.g. "0", "1"), where the specified boundary value is used to mark the edge of a segmentation. >>> '%.2f' % pk('0100'*100, '1'*400, 2) '0.50' >>> '%.2f' % pk('0100'*100, '0'*400, 2) '0.50' >>> '%.2f' % pk('0100'*100, '0100'*100, 2) '0.00' :param ref: the reference segmentation :type ref: str or list :param hyp: the segmentation to evaluate :type hyp: str or list :param k: window size, if None, set to half of the average reference segment length :type boundary: str or int or bool :param boundary: boundary value :type boundary: str or int or bool :rtype: float Nrrrr)ÚintÚroundrr r)r&r'r r ÚerrrÚrÚhrrrÚpk¼s€r.)rF)rrrr)Nr) Ú__doc__ÚnumpyrÚ ImportErrorrrrr(r.rrrrÚs   ÿ 1 C