3 ­d5ã @sXdZy ddlZWnek r$YnXddd„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 éNÚ1FcCs®t|ƒt|ƒkrtdƒ‚|t|ƒkr,tdƒ‚d}xhtt|ƒ|dƒD]P}t||||…j|ƒ||||…j|ƒƒ}|rˆ||7}qF|td|ƒ7}qFW|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 lengthsrégð?)ÚlenÚ ValueErrorÚrangeÚabsÚcountÚmin)Zseg1Zseg2ÚkÚboundaryZweightedÚwdÚiZndiff©rú9/tmp/pip-build-v9q4h5k9/nltk/nltk/metrics/segmentation.pyÚ windowdiff1s 0 rcCsFtj||fƒ}|tj|ƒ|ddd…f<|tj|ƒ|dd…df<|S)Nr)ÚnpÚemptyZarange)ZnrowsZncolsÚins_costÚdel_costÚmatrrrÚ _init_matbsrc Cs®x¨t|ƒD]œ\}}x’t|ƒD]†\}} |t|| ƒ|||f} || krV|||f} n2|| krt||||df} n|||d|f} t| | ƒ||d|df<qWq WdS)Nr)Ú enumeraterr ) rZrowvZcolvrrÚshift_cost_coeffr ZrowiÚjZcoljZ shift_costZtcostrrrÚ_ghd_auxisrç@çð?c s°‡fdd„t|ƒDƒ}‡fdd„t|ƒDƒ}t|ƒ}t|ƒ} |dkrP| dkrPdS|dkrh| dkrh||S|dkr€| dkr€| |St| d|d||ƒ} t| |||||ƒ| d S) 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 csg|]\}}|ˆkr|‘qSrr)Ú.0r Úval)r rrú §szghd..csg|]\}}|ˆkr|‘qSrr)rr r)r rrr¨srgréÿÿÿÿr )r r )rrrr) ÚrefÚhyprrrr Zref_idxZhyp_idxZ nref_boundZ nhyp_boundrr)r rÚghdys.r#cCs |dkr&ttt|ƒ|j|ƒdƒƒ}d}x`tt|ƒ|dƒD]H}||||…j|ƒdk}||||…j|ƒdk}||kr@|d7}q@W|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 Ng@rrgð?)ÚintÚroundrrr)r!r"r r Úerrr ÚrÚhrrrÚpk¼s r))rF)rrrr)Nr) Ú__doc__ZnumpyrÚ ImportErrorrrrr#r)rrrrÚ)s  1 C