,j+SrSSKrSSKrSSKJrJrJrJrJrJ r SSK r SSK J r SSKJr SSKJr SSKJr "S S \ R&R(R*5r\S :XaSSKr\R2"5 gg) zi ######## Features ######## See :class:`pyannote.core.SlidingWindowFeature` for the complete reference. N)TupleOptionalUnionIteratorListText) Alignment)Segment) SlidingWindow)Timelinec \rSrSrSrS S\R S\S\\ 4Sjjr Sr \ S 5r \ S 5rS rS rS rS\S\R 4SjrSrS\\\R 44SjrSrS!S\\S\\\\R \4\R 44SjjrS"S\\\4S\S\\ S\S\\R S44 Sjjr!Sr"\R \#RH4r%S\R 4Sjr&Sr'S#Sjr(Sr)g)$SlidingWindowFeature1zPeriodic feature vectors Parameters ---------- data : (n_frames, n_features) numpy array sliding_window : SlidingWindow labels : list, optional Textual description of each dimension. Ndatasliding_windowlabelsc6X lXlX0lSUlgN)rrr_SlidingWindowFeature__i)selfrrrs ڣC:\Users\johnn\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\LocalCache\local-packages\Python313\site-packages\pyannote/core/feature.py__init__SlidingWindowFeature.__init__<s.<  c4URRS$)zNumber of feature vectorsrrshapers r__len__SlidingWindowFeature.__len__Dsyyq!!rcLURRS[U55$)Nr)rrange_to_segmentlenr s rextentSlidingWindowFeature.extentHs""33As4yAArc4URRS$)zDimension of feature vectorsr rr s r dimensionSlidingWindowFeature.dimensionLsyyq!!rcj[R"S[5 URRS$)Nz(This is deprecated in favor of `__len__`r)warningswarnDeprecationWarningrrr s r getNumberSlidingWindowFeature.getNumberQs% @BTUyyq!!rcP[R"S[5 UR$)Nz3This is deprecated in favor of `dimension` property)r,r-r.r)r s r getDimension!SlidingWindowFeature.getDimensionUs  ACU ~~rcP[R"S[5 UR$)Nz0This is deprecated in favor of `extent` property)r,r-r.r&r s r getExtentSlidingWindowFeature.getExtent[s  >@R {{rireturnc URU$)zGet ith feature vectorr)rr7s r __getitem__ SlidingWindowFeature.__getitem__asyy|rcSUlU$r)rr s r__iter__SlidingWindowFeature.__iter__es rcU=RS- slURURURUR4$![an[ 5eSnAff=f)Nr )rrr IndexError StopIteration)res r__next__SlidingWindowFeature.__next__isS A  "&&txx0$))DHH2EE E "/ ! "s1A A" AA"c"UR5$N)rDr s rnextSlidingWindowFeature.nextps}}rwindowc## URRSn[U5H=nU(a"URUURU4v M,URUv M? g7f)zFeature vector iterator Parameters ---------- window : bool, optional When True, yield both feature vector and corresponding window. Default is to only yield feature vector rN)rrranger)rrJ n_samplesr7s r iterfeatures!SlidingWindowFeature.iterfeaturesssWIIOOA& y!AiilD$7$7$:::iil" "sA'A)focusmodefixed return_datac U(d"[U[5(d Sn[U5eU(dUb Sn[U5eURR XUSS9nUR R Sn[UR R 5S- n/SSpn UHcupU [U S5[U S5- - n U [X5[X5- - n U S:dX:aMHU [U S5[X5//- n Me U (a>[R"U V V s/sHupUR X2SS24PM sn n 5nO2SUR R SS-n[R"U5nUbn[R"[R"UR SU 4S U--5U[R"UR US- U 4S U--5/5nU(aU$[URU SSRURR URR"S 9n[%UUUR&S 9$s sn n f) aExtract frames Parameters ---------- focus : Segment or Timeline mode : {'loose', 'strict', 'center'}, optional In 'strict' mode, only frames fully included in 'focus' support are returned. In 'loose' mode, any intersecting frames are returned. In 'center' mode, first and last frames are chosen to be the ones whose centers are the closest to 'focus' start and end times. Defaults to 'loose'. fixed : float, optional Overrides `Segment` 'focus' duration and ensures that the number of returned frames is fixed (which might otherwise not be the case because of rounding errors). return_data : bool, optional Return a numpy array (default). For `Segment` 'focus', setting it to False will return a `SlidingWindowFeature` instance. Returns ------- data : `numpy.ndarray` or `SlidingWindowFeature` Frame features. See also -------- SlidingWindow.crop zG"focus" must be a "Segment" instance when "return_data"is set to False.Nz9"fixed" cannot be set when "return_data" is set to False.T)rQrR return_rangesrr )r)r )startdurationstepr) isinstancer ValueErrorrcroprrr%minmaxnpvstackemptytiler rVrWrXrr)rrPrQrRrSmsgrangesrM n_dimensionsclipped_ranges repeat_first repeat_lastrVendrrrs rr\SlidingWindowFeature.crops@Jj&@&@# S/ !%"3MCS/ !$$)) E*  IIOOA& 499??+a/ 571k JE CQK#eQ-7 7L 3s.U1FF FKQw%,CqM3s3F#G"HH! 99W*%dii 1 5WXD499??12..E88E?D  99GGDIIaLI& MM,33$..:Q:Q3R S*D!!rcUR$rGr:r s r __array__SlidingWindowFeature.__array__s yyrc^URSS5nX5-H.n[UTR[4-5(aM([s $ [ SU55nU(a[ SU55US'[ X5"U0UD6n[U5[ La[ U4SjU55$US:Xag[T5"UTRTRS9$)Noutc3h# UH(n[U[5(a UROUv M* g7frGrZrr.0xs r 7SlidingWindowFeature.__array_ufunc__..s) JPQj$899AFFq @&02c3h# UH(n[U[5(a UROUv M* g7frGr}r~s rrrs)"NQ*Q(<==1Dcrc3n># UH*n[T5"UTRTRS9v M, g7f)rYN)typerr)rrrs rrrs,PT1T 1d11$++FPTs25atrY) getrZ_HANDLED_TYPESrNotImplementedtuplegetattrrrr)rufuncmethodinputskwargsrzrrs` r__array_ufunc__$SlidingWindowFeature.__array_ufunc__sjj#A a!4!48L7N!NOO%%  JP   !"NQ"F5Mu%v88 : PT t^:dD$7$7 L Lrc URRnURRnURRn[ U5nUSU--[ R "U5U--nURRnURRnURRn [ U5n USU --[ R "U 5U--n [ R"URRV s/sH/n [ R"XU 5SS2[ R4PM1 sn 5n [XRURS9$s sn f)zAlign features by linear temporal interpolation Parameters ---------- to : SlidingWindowFeature Features to align with. Returns ------- aligned : SlidingWindowFeature Aligned features g?NrY)rrVrXrWr%r_arangehstackrTinterpnewaxisrr)rto old_startold_step old_duration old_samplesold_t new_startnew_step new_duration new_samplesnew_told_datanew_datas ralignSlidingWindowFeature.align#s)''-- &&++**33 $i C,..;1G(1RR%%++ $$))((11 "g C,..;1G(1RR99!%   +H %1!RZZ-@ +   $H.?.? TT  s6E")__irrrrG)F)looseNT)rrr8r)*rs __module__ __qualname____firstlineno____doc__r_ndarrayr rrrr!propertyr&r)r/r2r5intr;r>rr rDrHrboolrrrNr r floatr\rtnumbersNumberrrwrr__static_attributes__r{rrrr1sUYJJ0=GKDz"BB"""  SRZZ"% 34"(-#tn# %bjj'12BJJ>? @#,"!% kNWh&'kNkN kN  kN rzz11 2 kNZ "jj'..1N2::M@ Urr__main__)rrr,typingrrrrrrnumpyr_pyannote.core.utils.typesr segmentr r timeliner libmixinsNDArrayOperatorsMixinrrsdoctesttestmodr{rrrsb<??/"RU266==>>RUj z OOr