RidZGddZy)zDApproximate calculation of appropriate thresholds for motif finding.cFeZdZdZd dZd dZdZdZdZdZ d d Z d Z y)ScoreDistributionaClass 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. Nc|utd|j|_td|j|jz |_||j z|_|j|_nmtd|j|_td|j|jz |_||j z|_|j||_|j|j dz z |_ dg|j z|_ d|j|j|j <dg|j z|_ d|j|j|j <|Nt|j|jD]"\}}|j!|||j"$yt%|j D]}dg|j z}dg|j z} |dd|f}|j'D]\} } || } t)d|| |f| z}|j| } t%|j D]\}||j+|| xx|j||zz cc<| |j+|| xx|j|| zz cc<^||_ | |_ y)zInitialize the class.N?)min min_scoremax max_scoreintervallengthn_pointsicmeanstep mo_density _index_diff bg_densityziplog_oddspwmmodify backgroundrangeitemspow_add)selfmotif precisionpssmrlomopositionmo_newbg_newletterscorebgdis M/home/agent/.friday_env/lib/python3.12/site-packages/Bio/motifs/thresholds.py__init__zScoreDistribution.__init__su < eoo&78DNU__%67$..HDM% 4DMhhjDG dhh/DNTXX.?DM% 3DMii +DGMMT]]Q%67 %$--/=@))$..99:%$--/=@))$..99: <enn. < 6B BE$4$45 6"$++. )..!X+&%'XXZKMFE#F+BQVX%5 67"rCs r-threshold_balancedz$ScoreDistribution.threshold_balancedXs MMO#c) FA 4??1% %C 4??1% %CO#c) >>A M136 6>>A M1 1r/cB|jd|j zS)a"Threshold selection mimicking the behaviour of patser (Hertz, Stormo 1999) software. It selects such a threshold that the log(fpr)=-ic(M) note: the actual patser software uses natural logarithms instead of log_2, so the numbers are not directly comparable. r)r>)r@r)rs r-threshold_patserz"ScoreDistribution.threshold_patserfs"!!a$''k!22r/)NiNN)r)rF) __name__ __module__ __qualname____doc__r.rrrr@rDrHrJr/r-rr s0!)F;5 !.. 23r/rN)rNrrOr/r-rPs Kd3d3r/