B ‰°b¶ã@sdZGdd„dƒZdS)zDApproximate calculation of appropriate thresholds for motif finding.c@sVeZdZdZddd„Zddd„Zd d „Zd d „Zd d„Zdd„Z ddd„Z dd„Z dS)ÚScoreDistributionaClass representing approximate score distribution for a given motif. Utilizes a dynamic programming approach to calculate the distribution of scores with a predefined precision. Provides a number of methods for calculating thresholds for motif occurrences. NéècCsú|dkrFtd| ¡ƒ|_td| ¡ƒ|j|_||j|_| ¡|_n:td|jƒ|_td|jƒ|j|_||j|_| |¡|_|j|jd|_ dg|j|_ d|j |  |j¡ <dg|j|_ d|j |  |j¡ <|dkrx.t | ¡| ¡ƒD]\}}| |||j¡qôWnäxât|jƒD]Ô}dg|j}dg|j} |dd…|f}x˜| ¡D]Œ\} } || } td|| |fƒ| }|  | ¡} xXt|jƒD]J}|| || ¡|j ||7<| | || ¡|j || 7<qWqTW||_ | |_ qWdS)zInitialize the class.Ngégð?é)ÚminÚ min_scoreÚmaxZ max_scoreZintervalÚlengthÚn_pointsÚicZmeanÚstepÚ mo_densityÚ _index_diffÚ bg_densityÚzipZlog_oddsZpwmÚmodifyÚ backgroundÚrangeÚitemsÚpowÚ_add)ÚselfZmotifZ precisionZpssmrÚloZmoZpositionÚmo_newÚbg_newZletterZscoreZbgÚdÚi©rú4lib/python3.7/site-packages/Bio/motifs/thresholds.pyÚ__init__s<        ".zScoreDistribution.__init__çcCst||d|j|jƒS)Ngà?)Úintr )rÚxÚyrrrr 4szScoreDistribution._index_diffcCstdt|jd||ƒƒS)Nér)rrr )rrÚjrrrr7szScoreDistribution._addc Cs¨dg|j}dg|j}x~| ¡D]r\}}| |¡}x^t|jƒD]P} || | |¡|j| ||7<|| | |¡|j| ||7<q@Wq"W||_||_dS)z%Modify motifs and background density.gN)r rr rrr r) rZscoresZmo_probsZbg_probsrrÚkÚvrrrrrr:s   &.zScoreDistribution.modifycCs>|j}d}x"||kr,|d8}||j|7}q W|j||jS)zVApproximate the log-odds threshold which makes the type I error (false positive rate).gr)r rrr )rÚfprrÚprobrrrÚ threshold_fprFs  zScoreDistribution.threshold_fprcCs<d}d}x"||kr*|d7}||j|7}q W|j||jS)zWApproximate the log-odds threshold which makes the type II error (false negative rate).éÿÿÿÿgr)r rr )rÚfnrrr(rrrÚ threshold_fnrOs  zScoreDistribution.threshold_fnrçð?FcCsp|j}d}d}x4|||krB|d8}||j|7}||j|8}qW|r\|j||j|fS|j||jSdS)zMApproximate log-odds threshold making FNR equal to FPR times rate_proportion.ggð?rN)r rr rr )rZrate_proportionZ return_raterr'r+rrrÚthreshold_balancedXsz$ScoreDistribution.threshold_balancedcCs|jd|j dS)a"Threshold selection mimicking the behaviour of patser (Hertz, Stormo 1999) software. It selects such a threshold that the log(fpr)=-ic(M) note: the actual patser software uses natural logarithms instead of log_2, so the numbers are not directly comparable. r)r')r)r )rrrrÚthreshold_patserfsz"ScoreDistribution.threshold_patser)NrNN)r)r-F) Ú__name__Ú __module__Ú __qualname__Ú__doc__rr rrr)r,r.r/rrrrr s #    rN)r3rrrrrÚs