}Kg0 ~dZddlZddlZddlmZddlmZddlm Z dd gZ ejd d d ejd ejfdZ ejd d dZejd d  ddejdejdedejfdZ ddejdejdedejfdZ dde de dededejf dZejd d  ddejdejdejdedef dZy)zMatching functionsN)ParameterError)valid_intervals) _SequenceLikematch_intervals match_eventsT)nopythoncacheint_aint_bc|d|dg}|d|dkr|j|d|dg}|d|dkr|j|d|dz }|dkrd}|d|dz }|dkDr||z Sy)zJaccard similarity between two intervals Parameters ---------- int_a, int_b : np.ndarrays, shape=(2,) Returns ------- Jaccard similarity between intervals rrg)reverse)r r endsstarts intersectionunions Y/home/alanp/www/video.onchill/myenv/lib/python3.12/site-packages/librosa/util/matching.py __jaccardrs !HeAh D Awa Aha !F ay6!97VAY&La GfQi E qye## cNd}d}|D]}t|||}||kDs||}}|S)z4Find the best Jaccard match from query to candidates)r)query intervals_to candidates best_scorebest_idxidxscores r__match_interval_overlapsr /sAJH%c!23 : #(#J  Orintervals_fromrstrictreturncBtj|dddf}tj|dddf}||df}||df}tj||dddfd}tj||dddfd}tjt |t j } tt |D]} || } || } || } t|d| t|| dz}t |dkDrt| ||| | <N|rttj}tj}|| dkDr| d||| dz z }|| dzt |kr||| dz| dz }||kr||| dz | | <||| dz| | <| S)z.Numba-accelerated interval matching algorithm.Nrrright)sideleftdtype) npargsort searchsortedemptylennumbauint32rangesetr rinf)r!rr" start_index end_index start_sorted end_sorted search_ends search_startsoutputir after_query before_queryr dist_before dist_afters r__match_intervalsr@<s **\!Q$/0K <1-.I Q/Lil+J//,q!t0D7SKOOJq!t0D6RM XXc.) >F 3~& 'q!"!n $Q' \k23c)LM:R6SS  z?Q 1%zRF1I  &&KJQ!##AhM!4Dq4H)II 1~!C $55)+a.1*<=aH Z'%mA&6&:;q ' A(:;q =(> Mrct|dk(st|dk(r tdt|t| t|||S#t$r}td||d}~wwxYw)a Match one set of time intervals to another. This can be useful for tasks such as mapping beat timings to segments. Each element ``[a, b]`` of ``intervals_from`` is matched to the element ``[c, d]`` of ``intervals_to`` which maximizes the Jaccard similarity between the intervals:: max(0, |min(b, d) - max(a, c)|) / |max(d, b) - min(a, c)| In ``strict=True`` mode, if there is no interval with positive intersection with ``[a,b]``, an exception is thrown. In ``strict=False`` mode, any interval ``[a, b]`` that has no intersection with any element of ``intervals_to`` is instead matched to the interval ``[c, d]`` which minimizes:: min(|b - c|, |a - d|) that is, the disjoint interval [c, d] with a boundary closest to [a, b]. .. note:: An element of ``intervals_to`` may be matched to multiple entries of ``intervals_from``. Parameters ---------- intervals_from : np.ndarray [shape=(n, 2)] The time range for source intervals. The ``i`` th interval spans time ``intervals_from[i, 0]`` to ``intervals_from[i, 1]``. ``intervals_from[0, 0]`` should be 0, ``intervals_from[-1, 1]`` should be the track duration. intervals_to : np.ndarray [shape=(m, 2)] Analogous to ``intervals_from``. strict : bool If ``True``, intervals can only match if they intersect. If ``False``, disjoint intervals can match. Returns ------- interval_mapping : np.ndarray [shape=(n,)] For each interval in ``intervals_from``, the corresponding interval in ``intervals_to``. See Also -------- match_events Raises ------ ParameterError If either array of input intervals is not the correct shape If ``strict=True`` and some element of ``intervals_from`` is disjoint from every element of ``intervals_to``. Examples -------- >>> ints_from = np.array([[3, 5], [1, 4], [4, 5]]) >>> ints_to = np.array([[0, 2], [1, 3], [4, 5], [6, 7]]) >>> librosa.util.match_intervals(ints_from, ints_to) array([2, 1, 2], dtype=uint32) >>> # [3, 5] => [4, 5] (ints_to[2]) >>> # [1, 4] => [1, 3] (ints_to[1]) >>> # [4, 5] => [4, 5] (ints_to[2]) The reverse matching of the above is not possible in ``strict`` mode because ``[6, 7]`` is disjoint from all intervals in ``ints_from``. With ``strict=False``, we get the following: >>> librosa.util.match_intervals(ints_to, ints_from, strict=False) array([1, 1, 2, 2], dtype=uint32) >>> # [0, 2] => [1, 4] (ints_from[1]) >>> # [1, 3] => [1, 4] (ints_from[1]) >>> # [4, 5] => [4, 5] (ints_from[2]) >>> # [6, 7] => [4, 5] (ints_from[2]) rz'Attempting to match empty interval list)r"z&Unable to match intervals with strict=N)r.rrr@)r!rr"excs rrrrsyd >a3|#4#9FGGN#L!Y fMM YEfXNOUXXYs A A*A%%A* events_from events_tor'r%ct|dk(st|dk(r td|s6|s4tjtj||s td|s"t |t |kr td|s"t |t |kDr tdtj|tj}t|||||S)aMatch one set of events to another. This is useful for tasks such as matching beats to the nearest detected onsets, or frame-aligned events to the nearest zero-crossing. .. note:: A target event may be matched to multiple source events. Examples -------- >>> # Sources are multiples of 7 >>> s_from = np.arange(0, 100, 7) >>> s_from array([ 0, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84, 91, 98]) >>> # Targets are multiples of 10 >>> s_to = np.arange(0, 100, 10) >>> s_to array([ 0, 10, 20, 30, 40, 50, 60, 70, 80, 90]) >>> # Find the matching >>> idx = librosa.util.match_events(s_from, s_to) >>> idx array([0, 1, 1, 2, 3, 3, 4, 5, 6, 6, 7, 8, 8, 9, 9]) >>> # Print each source value to its matching target >>> zip(s_from, s_to[idx]) [(0, 0), (7, 10), (14, 10), (21, 20), (28, 30), (35, 30), (42, 40), (49, 50), (56, 60), (63, 60), (70, 70), (77, 80), (84, 80), (91, 90), (98, 90)] Parameters ---------- events_from : ndarray [shape=(n,)] Array of events (eg, times, sample or frame indices) to match from. events_to : ndarray [shape=(m,)] Array of events (eg, times, sample or frame indices) to match against. left : bool right : bool If ``False``, then matched events cannot be to the left (or right) of source events. Returns ------- event_mapping : np.ndarray [shape=(n,)] For each event in ``events_from``, the corresponding event index in ``events_to``:: event_mapping[i] == arg min |events_from[i] - events_to[:]| See Also -------- match_intervals Raises ------ ParameterError If either array of input events is not the correct shape rz$Attempting to match empty event listzWCannot match events with left=right=False and events_from is not contained in events_tozICannot match events with left=False and max(events_to) < max(events_from)zJCannot match events with right=False and min(events_to) > min(events_from)r() r.rr*allin1dmaxmin empty_likeint32__match_events_helper)rCrDr'r%r:s rr r s~ ;1I! 3CDD E266"''+y*I#J    c)ns;'77 4   s9~K(88 4  ]];bhh 7F !iu MMrr:ctj|}||}tj|}||}tj||} t| D]\} } d} d} d}t | }d}d}d}| | } || }| t |k(r| dz} |r | dkDr| dz }d} |r| t |dz kr| dz}d} t || |z }|r| rt |||z }|r| rt |||z }| r$|s|| |kDs| s||ks ||kr||kr |||| <| r||kr |||| <|| || <tj |}|||<|S)NFrrrT)r*r+r, enumerater.absrJ)r:rCrDr'r%from_idx sorted_fromto_idx sorted_tomatching_indicesind middle_ind left_flag right_flagleft_ind right_ind left_diff right_diffmid_diffsorted_from_num solutionss rrLrL4szz+&Hh'K ZZ "F&!Iy+>%%56Z  ()   %c* %c* Y ' !OJ JN!A~HI Z#i.1"44"QIJy,>? IIh//ABI ZYy1OCDJ :&89x#7J&9x+? *F3KZ(2 +F3K!,F3Ka7f f%I Ih r)T)TT)__doc__numpyr*r/ exceptionsrutilsr_typingr__all__jitndarrayrr boolr@rr rLrrrjs &"# n - D%RZZ &> D% &  D%IM2JJ2.0jj2BF2ZZ2&2lJN]YJJ]Y.0jj]YBF]YZZ]YF _N_N_N _N  _N ZZ _ND D%  H JJHHzzH  H  H&Hr