DUfd ddlZddlZddlZddlZejdejfdZdZ dZ dZ dZ dZ dd Zdd Zd Zdd ZdZddZddZddZdejejjffdZ ddZ ddZddZdZdS)Nz(\d+)cZtd||DS)Nc\g|])}||rt|n|*S)isdigitint.0xs Q/var/www/html/software/conda/lib/python3.11/site-packages/bioframe/core/arrops.py znatsort_key.. s4PPP1aPAIIKK.#a&&&QPPP)tuplesplit)s _NS_REGEXs r natsort_keyrs+ PP 8J8JPPP Q QQr c.t|tS)N)key)sortedr)iterables r natsortedr s ( , , ,,r ctj|}t|stjgtSt t d|D}tj|dddS)Ndtypec34K|]}t|VdSN)rrs r zargnatsort..s(55!{1~~555555r )npasarraylenarrayrrziplexsort)r"colss r argnatsortr&so Ju  E u::'x#&&&& 55u5556 7 7D :d44R4j ! !!r cltj||kd}|d|ddz}}||fS)zDFind the first and the last occurence + 1 of the value in the array.rr)rwhere)arrval block_idxslohis r _find_block_spanr/s;#*%%a(J ]JrNQ.B r6Mr cxtj|j|jzf|j}||ddd<||ddd<|S)a\ Interweave two arrays. Parameters ---------- a, b : numpy.ndarray Arrays to interweave, must have the same length/ Returns ------- out : numpy.ndarray Array of interweaved values from a and b. Notes ----- From https://stackoverflow.com/questions/5347065/interweaving-two-numpy-arrays rrNr()remptysizer)abouts r interweaver7 sH$ (AFQVO%QW 5 5 5CC1IC1I Jr ctj|t||ddd}d|||k<|S)a# Calculate sums of slices of an array. Parameters ---------- arr : numpy.ndarray starts : numpy.ndarray Starts for each slice ends : numpy.ndarray Stops for each slice Returns ------- sums : numpy.ndarray Sums of the slices. Nr1r)raddreduceatr7)r*startsendssumss r sum_slicesr>8sA" 6??3 64 8 8 9 9##A# >DD4 Kr c|du|dukrtd|||z }tj|r"tjt ||}tj||}tj|tj||z |z }||z}|S)a Create concatenated ranges of integers for multiple start/length. Parameters ---------- starts : numpy.ndarray Starts for each range stops : numpy.ndarray Stops for each range lengths : numpy.ndarray Lengths for each range. Either stops or lengths must be provided. Returns ------- concat_ranges : numpy.ndarray Concatenated ranges. Notes ----- See the following illustrative example: starts = np.array([1, 3, 4, 6]) stops = np.array([1, 5, 7, 6]) print arange_multi(starts, lengths) >>> [3 4 4 5 6] From: https://codereview.stackexchange.com/questions/83018/vectorized-numpy-version-of-arange-with-multiple-start-stop Nz)Either stops or lengths must be provided!) ValueErrorrisscalarfullr!repeatarangesumcumsum)r;stopslengths cat_start cat_counter cat_ranges r arange_multirLNs@  7d?++DEEE&. {6-UV,, &'**I)GKKMM**RY7"G..K K'I r Fc|j|jcxkr|jcxkr |jksntd|r ||k||kzS||k||kzS)aE Take pairs of intervals and test if each pair has an overlap. Parameters ---------- starts1, ends1, starts2, ends2 : numpy.ndarray Interval coordinates. All four arrays must have the same size. Warning: if provided as pandas.Series, indices will be ignored. closed : bool If True then treat intervals as closed and accept single-point overlaps. Returns ------- have_overlap : numpy.ndarray A boolean array where the i-th element says if the i-th interval in set 1 overlaps the i-th interval in set 2. z.All four input arrays must have the same size.)r3r@)starts1ends1starts2ends2closeds r _check_overlaprSsx( LEJ D D D D', D D D D%* D D D DIJJJ 55 W%566%GeO44r cntj||tj||z }d||dk<|S)aT Take pairs of intervals and return the length of an overlap in each pair. Parameters ---------- starts1, ends1, starts2, ends2 : numpy.ndarray Interval coordinates. All four arrays must have the same size. Warning: if provided as pandas.Series, indices will be ignored. Returns ------- overlap_size : numpy.ndarray An array where the i-th element contains the length of an overlap between the i-th interval in set 1 and the i-th interval in set 2. 0 if the intervals overlap by a single point, -1 if they do not overlap. rr)rminimummaximum)rNrOrPrQ overlap_sizes r _size_overlaprXs;$:eU++bj'.J.JJL%'L!" r c||||fD]6}t|tjrtjdt 7t j|}t j|}t j|}t j|}t|}t|}t j ||g} t j ||g} t j t j d|dz t j d|dzg} t j | | g} | | | | | | } } } t j d||z} t j | | |rdnd}|| dzk}| |||}} t j t j| | || z dz | t| dz|gj}||dddf|dddfzdk}|d|dddfdzdz |dddf<|dddfdz |dddf<|r0|t j |dddf|dddfg}|S) ak Take two sets of intervals and return the indices of pairs of overlapping intervals. Parameters ---------- starts1, ends1, starts2, ends2 : numpy.ndarray Interval coordinates. Warning: if provided as pandas.Series, indices will be ignored. closed : bool If True, then treat intervals as closed and report single-point overlaps. Returns ------- overlap_ids : numpy.ndarray An Nx2 array containing the indices of pairs of overlapping intervals. The 1st column contains ids from the 1st set, the 2nd column has ids from the 2nd set. MOne of the inputs is provided as pandas.Series and its index will be ignored.r(rrightleftNr)axis) isinstancepdSerieswarningswarn SyntaxWarningrr r! concatenaterDr$ searchsortedvstackrCrLTsort)rNrOrPrQrRrhvecn1n2r;r<idsorder match_starts match_ends match_mask overlap_idss r _overlap_intervals_legacyrrs,/ c29 % %  M#    j!!G Ju  Ej!!G Ju  E WB WB ^Wg. / /F >5%. ) )D .29QQ///1b1f1E1EF G GC Jf~ & &Eu tE{CJ#DF9QR((L&/LwwfMMJlQ..J+J7J9O*L) Ic,'l)BQ)F G G  \A-z:: ;   k!!!Q$/+aaad2CCqHIK"$AAAqD)R014K1#AAAqD)A-K1 V!"*k!!!Q$.?QQQPQTAR-S"T"TU r cZ|}|||kxxdz cc<||gS)aj Convert points to len1 segments for internal use in overlap(). This enables desired overlap behavior for points and preserves behavior for semi-open intervals of len>=1. Parameters ---------- starts, ends : numpy.ndarray Returns ------- pseudo_ends : numpy.ndarray An array of pseudo-ends for overlapping intervals. r()copy)r;r< pseudo_endss r _convert_points_to_len1_segmentsrv s<))++K1$ K  r c t||||fD]6}t|tjrtjdt 7t j|}t j|}t||\}}t j|}t j|}t||\}}t|}t|}t j d|} t j d|} t j ||g} t j ||g} || || | | } }}|| || | | } }}t j ||d} t j |||rdnd}t j ||d}t j |||rdnd}|| k}||k}| |||}} ||||}}t j t j| ||| z dddf| t| |dddfg| t||dddft j| |||z dddfgg}|r0|t j |dddf|dddfg}|S)aj Take two sets of intervals and return the indices of pairs of overlapping intervals. Parameters ---------- starts1, ends1, starts2, ends2 : numpy.ndarray Interval coordinates. Warning: if provided as pandas.Series, indices will be ignored. closed : bool If True, then treat intervals as closed and report single-point overlaps. Returns ------- overlap_ids : numpy.ndarray An Nx2 array containing the indices of pairs of overlapping intervals. The 1st column contains ids from the 1st set, the 2nd column has ids from the 2nd set. rZrr\r[Nr()r^r_r`rarbrcrr rvr!rDr$reblockrCrL)rNrOrPrQrRrhrirjrkids1ids2order1order2match_2in1_startsmatch_2in1_endsmatch_1in2_startsmatch_1in2_endsmatch_2in1_maskmatch_1in2_maskrqs r overlap_intervalsrs*/ c29 % %  M#    j!!G Ju  E5guEENGUj!!G Ju  E5guEENGU WB WB 9Q  D 9Q  DZ( ) )F Z( ) )F"6?E&M4+BA F F9RYr]],?BW,WXX&'<>QRRi/      Q9'' ?!#G!4!4  !#Wg,>!?!? 9Q++,>? !34!#!O!O!z*@1*DbII9 IbMM/2HH  ''=?STTi 1      Jr c |rtjdt} nM|9|7||}}t||||} | | dddf| dddfk} nt||||} t |} tj| } t || || ||d||rdn|} t || || ||d||rdn|}t || || ||d||rdn|}t || || ||d||rdn|}| | | dddf| dddf<| | |dddf|dddf<| | |dddf|dddf<| | |dddf|dddf<tj| |g}tj||g}||dddf||dddfz dz}||dddf||dddfz dz}tj||| g}tj||tj| j dg}t |dkrtj dtS|,tj |dddf||dddfg}n,tj |dddf|||dddfg}||dd f}|dd df|dddfk}tj tj d |d fd}|dd }|dd}|t|tj|||z  }|S) a For every interval in set 1, return the indices of k closest intervals from set 2. Parameters ---------- starts1, ends1, starts2, ends2 : numpy.ndarray Interval coordinates. Warning: if provided as pandas.Series, indices will be ignored. If start2 and ends2 are None, find closest intervals within the same set. k : int The number of neighbors to report. tie_arr : numpy.ndarray or None Extra data describing intervals in set 2 to break ties when multiple intervals are located at the same distance. Intervals with *lower* tie_arr values will be given priority. ignore_overlaps : bool If True, ignore set 2 intervals that overlap with set 1 intervals. ignore_upstream, ignore_downstream : bool If True, ignore set 2 intervals upstream/downstream of set 1 intervals. direction : numpy.ndarray with dtype bool or None Strand vector to define the upstream/downstream orientation of the intervals. Returns ------- closest_ids : numpy.ndarray An Nx2 array containing the indices of pairs of closest intervals. The 1st column contains ids from the 1st set, the 2nd column has ids from the 2nd set. rrNrr(r\)rrrr[r1rT)rH)rrrrr!rDrrdrfrr2r$r)rrLrU)rNrOrPrQrrignore_overlapsignore_upstreamignore_downstreamrrqnall_idsids_left_upstreamids_right_downstreamids_right_upstreamids_left_downstreamleft_ids right_ids left_dists right_dists closest_ids closest_distsrminterval1_run_border_maskinterval1_run_bordersinterval1_run_startsinterval1_run_endss r closest_intervalsrfsbHhvS111 /  %'GG !+aaad"3{111a47H"HI 'GG  G AillG5  i  %!!A8  i  '!!a6  yj  %!!A7  yj  '!!a&i01B111a41HIaaad!(!34HA4N!OA ' 34G14M N1& z23Eaaad3KLqqq!t~02EFGGH 24HIJJI!!!Q$(5!!!Q$+@@1DJ)AAAqD/*U9QQQT?-CCaGK)Xy+>??KN ["(;+OPQQ A  AAAqD8I J  eRaRi(K!,CRCF 3{122q57I IHRU41JD+P%QRRSTU0"5.qrr2 Jq"47K"KLL   K r c*|jd}| tj|tj}tj||f}tj|d|zf}tj|}||}tj||}||fS)Nrrr)rronesint64rrrF)r;r<weightsrborderscoverage_change borders_ordercoverages r coverage_intervals_rlers QA'!28,,,eFDL!GeGR'\12OJw''Mm$Gy788H H r c|jd}tj||f}tj||z ||z f}tjtj|dtj|zf}tjtjd|dzdtjd|dzzf}tj| ||g}||||}}tjdt}dtj|tj z} t||D]\} } tj | dz } | dkrt| |jdkr&tj|tj |f}tj|dd} | | | <d|| <| dkr d|| | <| S)Nrrr(r1rTF)rrr ones_likerDr$rrrrr#absrE zeros_liker))r;r<rrlens border_types border_ids border_order occupancylevelsborder border_id interval_id new_levels r stack_intervalsr s QAeFDL!G 5v - .D5f--rBL4F4F/FFGLryAE**B1a!e1D1D,DDEJ:ulG<==L!,/L1IZG$'''I "'!28,,, ,F *55 3 3 fY''!+ q==}})/!"444E)R]9-E-E"EF ),,Q/2I"+F; #'Ii q==-2If[) * Mr )NN)F)FF)r)Nr()NNr(NFFFNr)reranumpyrpandasr_compileUrrr&r/r7r>rLrSrXrrrvrrriinformaxrrrrrrr r rs (RZ"$77RRRR---"""0,4444n5555:.PPPPf!!!&ZZZZz"3"3"3"3J?5?5?5?5J xrx!!% &....2@Ahhhh\   RRRRj     r