rh SrSSKJr SSKJr SSKJrJr SSKr SSK r SSK J r SSK J r SSK Jr SS K Jr SS K Jr SS K Jr SS K Jr SS K Jr \ R((aSSK Jr \ R,"S5r"SS\ R05r"SS5r"SS\5r"SS\5r\r"SS\5r"SS\5r"SS\5r "SS\5r!\\\\ \!/r""S S!\5r#"S"S#\5r$S)S$jr%S*S%jr&"S&S'\ RN5r(\%\\#\$\\\\ \\!/ r)\*S(:XaSSK r \ RV"\(5 gg)+a Modular analysis procedures for use alone or applied with :class:`music21.analysis.windowed.WindowedAnalysis` class. All procedures should inherit from :class:`music21.analysis.discrete.DiscreteAnalysis`, or provide a similar interface. The :class:`music21.analysis.discrete.KrumhanslSchmuckler` (for algorithmic key detection) and :class:`music21.analysis.discrete.Ambitus` (for pitch range analysis) provide examples. ) annotations) OrderedDict)IterableSequenceN) environment) exceptions21)harmony)interval)note)key) percussion)pitchstreamzanalysis.discretec\rSrSrSrg)DiscreteAnalysisException3N)__name__ __module__ __qualname____firstlineno____static_attributes__rS/home/james-whalen/.local/lib/python3.13/site-packages/music21/analysis/discrete.pyrr3srrc\rSrSr%SrSr/rS\S'SSjrSSjr SS jr S r S r S r S rSSSjjrSrSrSrSrSrg)DiscreteAnalysis7a Parent class for analytical methods. Each analytical method returns a discrete numerical (or other) results as well as a color. Colors can be used in mapping output. Analytical methods may make use of a `referenceStream` to configure the processor on initialization. z list[str] identifiersNc,Xl/Ul/UlgN)_referenceStreamsolutionsFoundalternativeSolutions)selfreferenceStreams r__init__DiscreteAnalysis.__init__Es / !%'!rc~[US5[US5[US54nSUSSUSSUSS3$)z Utility conversion method >>> da = analysis.discrete.DiscreteAnalysis() >>> ffffff = (255, 255, 255) >>> da._rgbToHex(ffffff) '#ffffff' r#02x)round)r&rgbs r _rgbToHexDiscreteAnalysis._rgbToHexRsOCFmU3q6]E#a&M93q6#,s1vcl3q6#,77rc ^^TRS5m[T5m[UU4Sj[STTS-555$)z Utility conversion method for six-digit hex values to RGB lists. >>> da = analysis.discrete.DiscreteAnalysis() >>> da._hexToRgb('#ffffff') [255, 255, 255] >>> da._hexToRgb('#ff8000') [255, 128, 0] >>> da._hexToRgb('#000000') [0, 0, 0] r-c3L># UHn[TXTS--S5v M g7f)N)int).0ilvvalues r -DiscreteAnalysis._hexToRgb..ls*Q;PaCaB!G ,b11;Ps!$rr5)lstriplenlistrange)r&r;r:s `@r _hexToRgbDiscreteAnalysis._hexToRgb^s: S! ZQ5Ba;PQQQrc*US:aSnU$US:aSnU$)z Utility conversion method -- limits all numbers to between 0 and 255. >>> da = analysis.discrete.DiscreteAnalysis() >>> da._rgbLimit(70) 70 >>> da._rgbLimit(300) 255 >>> da._rgbLimit(-30) 0 rr)r&r;s r _rgbLimitDiscreteAnalysis._rgbLimitns* 19E S[E rc/Ulg)z Clear all stored solutions N)r$r&s rclearSolutionsFound$DiscreteAnalysis.clearSolutionsFounds !rcd/nURHup#X1;dM URU5 M U$)z] Based on solutions found so far with this processor, return the colors that have been used. r$append)r&postunused_solutioncolors r getColorsUsedDiscreteAnalysis.getColorsUseds5 &*&9&9 "O  E"': rcd/nURHup#X!;dM URU5 M U$)z` Based on solutions found so far with this processor, return the solutions that have been used. rM)r&rOsolution unused_colors rgetSolutionsUsed!DiscreteAnalysis.getSolutionsUseds5 &*&9&9 "H# H%': rc/$)z A list of pairs showing all discrete results and the assigned color. Data should be organized to be passed to :class:`music21.graph.GraphColorGridLegend`. If `compress` is True, the legend will only show values for solutions that have been encountered. r)r&compresss rsolutionLegendDiscreteAnalysis.solutionLegends  rcg)K Return a string describing the solution values. Used in Legend formation. NrrIs rsolutionUnitString#DiscreteAnalysis.solutionUnitStringsrcg)z Given an analysis specific result, return the appropriate color. Must be able to handle None in the case that there is no result. Nrr&rUs rsolutionToColor DiscreteAnalysis.solutionToColor rcg)z Given a Stream, apply the analysis to all components of this Stream. Expected return is a solution (method-specific) and a color value. Nr)r&sStreams rprocessDiscreteAnalysis.processrercg)zF For a given Stream, apply the analysis and return the best solution. Nr)r& subStreams r getSolutionDiscreteAnalysis.getSolutions r)r#r%r$r")r0zSequence[float | int]returnstr)r;rornz list[int]FrZboolrnz4list[list[str | list[tuple[int | str, str | None]]]])rrrr__doc__namer __annotations__r(r1rBrFrJrRrWr[r_rcrhrlrrrrrr7sU DK ' 8R $!       rrc^\rSrSr%SrSrSrSS/rSrS\ S 'S r S\ S 'SU4S jjr S r SSjr SS SjjrSrSSjrS!SjrS"SjrS#S$SjjrSrSrSrSSjrS#SjrSrSrSrU=r$)%KeyWeightKeyAnalysisz8 Base class for all key-weight key analysis subclasses. FzKeyWeightKeyAnalysis Base Classz key.baseClasszkeyscape.baseClass)CC#C-D-DE-EFF#G-GA-AB-Bztuple[str, ...]keysValidMajor)ryrzr}D#r~rrrrG#rrA#rrkeysValidMinorc>[TU]US9 UbURU5UlOSUl0Ul0UlUR 5 gN)r')superr(_getSharpFlatCountsharpFlatCountmajorKeyColorsminorKeyColors_fillColorDictionariesr&r' __class__s rr(KeyWeightKeyAnalysis.__init__sP 9  &"&"9"9/"JD "&D    ##%rc*SSSSSSSS.nURUR4URUR44GHTup#UGHGn[R "U5nUR nURX5n[[U55HnURXgS -5Xg'M X0R:Xa3[[U55HnURXgS - 5Xg'M [UR5S :acS nURS S :Xa XSU-S.n O"URS S:Xa SU-SU-US.n O0n U HnURXgX-5Xg'M URU5X$R'GMJ GMW g)z >>> p = analysis.discrete.KrumhanslSchmuckler() This automatically calls _fillColorDictionaries >>> len(p.majorKeyColors) 15 >>> p.majorKeyColors['C'] '#ff816b' z#CD4F39z#DAA520z#BCEE68z#96CDCDz#6495EDz#8968CDz#FF83FA)ryr}rrrrr2dr+-)rr+r,r-N) rrrrrPitchsteprBrAr?rFrtr1) r&stepLibdstvalidvalidKeyrrgbStepr9 magnitudeshiftLibs rr+KeyWeightKeyAnalysis._fillColorDictionariess" !//1D1DE //1D1DEGJC! ;;x0}}..7s7|,A!% R!@GJ-///"3w<0%)^^GJ4D%E 1x}}%) "I}}Q'3.'02 >#R!q)S0')I~"y.Y#W#%%%)^^GJ4L%M &&*^^G%<MM"9"GrcSnSnURHTnURcMURRS:aUS- nM3URRS:dMOUS- nMV X24$)z Determine count of sharps and flats in a Stream >>> s = corpus.parse('bach/bwv66.6') >>> p = analysis.discrete.KrumhanslSchmuckler() >>> p._getSharpFlatCount(s.flatten()) (87, 0) rrr+)pitches accidentalalter)r&rk flatCount sharpCountps rr'KeyWeightKeyAnalysis._getSharpFlatCount1si  ""A||'<<%%)OI\\''!+!OJ # $$rcfUR5nUS:Xa/SQ$US:Xa/SQ$[SU35ez Returns the key weights. To provide different key weights, subclass and override this method. The defaults here are KrumhanslSchmuckler. >>> a = analysis.discrete.KrumhanslSchmuckler() >>> len(a.getWeights('major')) 12 >>> len(a.getWeights('minor')) 12 major) gffffff@gףp= @gףp= @gp= ף@gQ@g\(\@g)\(@g(\@gQ@gHzG @gRQ@g ףp= @minor) gRQ@gq= ףp@g)\( @gQ@g@g= ףp= @gRQ@g@gףp= @gQ@gQ @g\(\ @$Weights must be major or minor, not lowerrr& weightTypes r getWeightsKeyWeightKeyAnalysis.getWeightsFsC %%'  [ [ 7 "[ [+.RS]R^,_` `rcS/S-nUR(dgURH8nURnURHnX%R==U- ss'M M: U$)aF Given a flat Stream, return a pitch class distribution. The value of each pitch class is scaled by its duration in quarter lengths. >>> a = analysis.discrete.KrumhanslSchmuckler() >>> s = stream.Stream() >>> n1 = note.Note('c') >>> n1.quarterLength = 3 >>> n2 = note.Note('f#') >>> n2.quarterLength = 2 >>> s.append(n1) >>> s.append(n2) >>> a._getPitchClassDistribution(s) [3.0, 0, 0, 0, 0, 0, 2.0, 0, 0, 0, 0, 0] >>> c1 = chord.Chord(['d', 'e', 'b-']) >>> c1.quarterLength = 1.5 >>> s.append(c1) >>> a._getPitchClassDistribution(s) [3.0, 0, 1.5, 0, 1.5, 0, 2.0, 0, 0, 0, 1.5, 0] r N)notes quarterLengthr pitchClass)r& streamObjpcDistnlengthrs r_getPitchClassDistribution/KeyWeightKeyAnalysis._getPitchClassDistributionYsW,rA__FYY||$.$!  rcUcgS/S-nURU5n[[U55H7n[[U55HnX5==XFU- S-X-- ss'M M9 U$)zTakes in a pitch class distribution as a list and convolutes it over Sapp's given distribution for finding key, returning the result. Nrr)rrAr?)r&pcDistributionrrU toneWeightsr9js r_convoluteDistribution+KeyWeightKeyAnalysis._convoluteDistribution{ss  !38ooj1 s8}%A3~./ UbL 9N.sJ4ILRF<4Is)sorted enumeratereverserr)r& keyResults differences likelyKeysaunused_correlationrs r_getLikelyKeys#KeyWeightKeyAnalysis._getLikelyKeyssd  #$#( JIj4IJ J '( " #kk"o{?JN'(rcUcgS/S-nS/S-nS/S-nS/S-nURU5n[U5[U5- n [U5[U5- n [[U55Hn [[U55Hyn X[XU - S-U - X,U - --X['XkXU - S-U - S--Xk'X{X,U - S--X{'XkS:XdX{S:XaSXK'M][ X[XkX{-S-- 5XK'M{ M U$)zc Takes in a list of numerical probable key results and returns the difference of the top two keys. Ngrr,r?)rsumr?rAfloat) r&rrrrUtop bottomRight bottomLeftrprofileAveragehistogramAverager9rs r_getDifference#KeyWeightKeyAnalysis._getDifferences\  !$ ebjebj URZ ooj1 [)C ,<<~.^1DDs8}%A3{+,Q" ->&),<<$>?"-Q" ->14E"F  * "%(88Q2?!@ >Q&*-1*<"%HK"';>JM3QVY2Y(Z"[HK-&rc/SQn/nU(acUR5nUR5n/nUH:nUH1nUScM XgSR:XdMURU5 M8 M< OUn/nSn SHn U S:Xa URn OU S:Xa UR n U /n /n UV s/sHn [ R"U 5PM sn HynURX/5nSnU(aX;aS nURU ;aS nU(aS nS nO"URnU S:XaUR5nU RUU45 M{ U RU 5 URU 5 M U$s sn f![a SnNf=f) z Returns a list of lists of possible results for the creation of a legend. >>> p = analysis.discrete.KrumhanslSchmuckler() >>> post = p.solutionLegend() )r{ryrzr|r}rr~rrrrrrrrrrrrNr)MajorMinorrrFT#ffffffr) rRrWrtrNrrrrrcKeyErrorr)r&rZ _keySortOrder colorsUsed solutionsUsedkeySortOrderFilteredkeyElsoldataryLabelrowpairsrkeyPitchrQmaskkeyStrs rr[#KeyWeightKeyAnalysis.solutionLegends  ++-J 113M$& &(C1v~ A +,33E: )'$1 !#)F ++7"++=CHC46E5IJ5IU[[^5IJ! 00(1CDE.#==-D%EF&]]F(!' fe_-/K0 JJu  KK E)F 5K ! E!s* E2E77 FFcg)r^KeysrrIs rr_'KeyWeightKeyAnalysis.solutionUnitString srcUSnUcgUSR5nUS:XaURUR$URUR$)z Given a two-element tuple of (tonicPitch, modality) return the proper color >>> p = analysis.discrete.KrumhanslSchmuckler() >>> solution = (pitch.Pitch('C'), 'major') >>> p.solutionToColor(solution) '#ff816b' rrr+r)rrrtr)r&rU solutionKeymodalitys rrc$KeyWeightKeyAnalysis.solutionToColors^qk  A;$$& w &&{'7'78 8&&{'7'78 8rcURU5nURUS5nURUUS5nURX45nURUS5nURUUS5nURXg5nXX4$)Nrr)rrrr) r&rgrkeyResultsMajordifferenceMajorlikelyKeysMajorkeyResultsMinordifferenceMinorlikelyKeysMinors r _likelyKeys KeyWeightKeyAnalysis._likelyKeys's88A55ngN--o.>> ks = analysis.discrete.KrumhanslSchmuckler() >>> s = converter.parse('tinynotation: 4/4 b-4 e- f g-') >>> ks._bestKeyEnharmonic(pitch.Pitch('e#'), 'minor', s) >>> ks._bestKeyEnharmonic(pitch.Pitch('f-'), 'major', s) NFrTrinPlace)rtrr getEnharmonic)r&pitchObjmodergflipEnharmonics r_bestKeyEnharmonic'KeyWeightKeyAnalysis._bestKeyEnharmonic7sl    7?}}D$7$77!% W_}}D$7$77!%   " "4 " 0rcUR5RR[R5nUR U5up4UbUVVs/sH upVXeS4PM nnnO/nUbUUVVs/sH upVXeS4PM snn- nU(d [ S5eUR5 UR5 USupenURXXU5nXXU4n URU 5n U(aE/Ul USSH5upenURXXU5nURRXXU45 M7 URRX45 X4$s snnfs snnf)a Takes in a Stream or sub-Stream and performs analysis on all contents of the Stream. The :class:`~music21.analysis.windowed.WindowedAnalysis` windowing system can be used to get many results by calling this method. Returns two values, a solution data list and a color string. The data list contains a key (as a string), a mode (as a string), and a correlation value (degree of certainty) Nrrz.failed to get likely keys for Stream componentrr+)flatten notesAndRestsgetElementsNotOfClassr Unpitchedrrsortrrrcr%rNr$) r&rgstoreAlternativesrrr coefficientsortListrrUrQs rrhKeyWeightKeyAnalysis.processhs//#11GGW,0+;+;G+D(  &,;=,;(%1,; =HH  & -<>-<)!&'2-<> >H+,\] ]  ({   # #AW 5[)$$X. (*D %(0 $ ++AW=))00!;1GH)5 ""H#45A= >s E2EcP[R"USUSS9nUSUlU$)zW Convert a solution into an appropriate object representation, returning a Key object. rr+)tonicrr,)r KeycorrelationCoefficient)r&rUks r_solutionToObject&KeyWeightKeyAnalysis._solutionToObjects- GG(1+HQK 8#+A; rc URUR5SS9up#URU5nURc/UlURH-nURR URU55 M/ U$)a8 Return a music21 Key object defining the results of the analysis. Do not call process before calling this method, as this method calls process. Note that all alternative solutions are returned as Key objects and stored on a list found at Key.alternateInterpretations. >>> s = corpus.parse('bach/bwv66.6') >>> p = analysis.discrete.KrumhanslSchmuckler() >>> p.getSolution(s) # this seems correct >>> s = corpus.parse('bach/bwv57.8') >>> p = analysis.discrete.KrumhanslSchmuckler(s) >>> p.getSolution(s) T)r)rhrr!alternateInterpretationsr%rN)r&rgrUrVr rs rrl KeyWeightKeyAnalysis.getSolutions{("&goo.?SW!X  " "8 , % % -)+A &,,C & & - -d.D.DS.I J-r)r%rrrr")rnztuple[int, int]r)rnz list[float])rnzlist[t.Any] | None)rnzNone | list[float]rprq)rrrrrs_DOC_ALL_INHERITEDrtr rrurr(rrrrrrrr[r_rcrrrhr!rlr __classcell__rs@rrwrws -D"$89K 'NO'NO &8=t%*a&D $!FL\ 9(0 /bDLrrwcJ^\rSrSrSrSrSr/SQrS U4SjjrS Sjr Sr U=r $) KrumhanslSchmuckleria Implementation of Krumhansl-Schmuckler/Kessler weightings for Krumhansl-Schmuckler key determination algorithm. Values from https://extras.humdrum.org/man/keycor/, which describes these weightings as "Strong tendency to identify the dominant key as the tonic." * Changed in v6.3: it used to be that these were different from the Kessler profiles, but that was likely a typo. Thus, KrumhanslKessler and KrumhanslSchmuckler are synonyms of each other. Fz)Krumhansl Schmuckler/Kessler Key Analysis)z key.krumhanslzkey.schmucklerzkey.krumhansl-schmucklerzkey.krumhanslschmuckler krumhansl schmucklerzkrumhansl-schmucklerkrumhanslschmucklerz key.kesslerzkey.krumhansl-kesslerzkey.krumhanslkesslerkesslerzkrumhansl-kesslerkrumhanslkesslerc >[TU]US9 grrr(rs rr(KrumhanslSchmuckler.__init__ 9rcfUR5nUS:Xa/SQ$US:Xa/SQ$[SU35errrs rrKrumhanslSchmuckler.getWeightssG %%'  & & 7 "[ [+.RS]R^,_` `rrr"r& rrrrrsr'rtr r(rrr(r)s@rr+r+s-  6DK:aarr+cJ^\rSrSrSrSrSr/SQrS U4SjjrS Sjr Sr U=r $) AardenEsseni as Implementation of Aarden-Essen weightings for Krumhansl-Schmuckler key determination algorithm. Values from https://extras.humdrum.org/man/keycor/, which describes these weightings as "Weak tendency to identify the subdominant key as the tonic." (N.B. -- we are not sure exactly where the minor weightings come from, and recommend only using these weights for major). FzAarden Essen Key Analysis) z key.aardenz key.essenzkey.aarden-essenzkey.aardenessenaardenessenz aarden-essen aardenessenr keyscapec >[TU]US9 grr2rs rr(AardenEssen.__init__r4rcfUR5nUS:Xa/SQ$US:Xa/SQ$[SU35e)z Returns the key weights. >>> a = analysis.discrete.AardenEssen() >>> len(a.getWeights('major')) 12 >>> len(a.getWeights('minor')) 12 r) g2w-!1@IΣ?g|?5^-@gv?g( 3@g&†&@gIΣ?gZd;6@rAg:KTO @gF?gY4 @r) gC2@g,=)?g $(~,@g h"0@[tz?g=U,@rBgǺ2@g2C@g~5?g7T7@g䠄?rrrs rrAardenEssen.getWeightssQ %%'  0 07 "K K,.RS]R^,_` `rrr"r&r7r)s@rr9r9 s- &DK:aarr9cJ^\rSrSrSrSrSr/SQrS U4SjjrS Sjr Sr U=r $) SimpleWeightsi5a( Implementation of simple weights by Craig Sapp for Krumhansl-Schmuckler key determination algorithm. Values from https://extras.humdrum.org/man/keycor/, which describes these weightings as "Performs most consistently with large regions of music, becomes noisier with smaller regions of music." FzSimple Weight Key Analysis)z key.simplez key.weightzkey.simple-weightzkey.simpleweightsimpleweightz simple-weight simpleweightc >[TU]US9 grr2rs rr(SimpleWeights.__init__Dr4rcfUR5nUS:Xa/SQ$US:Xa/SQ$[SU35e)z Returns the key weights. >>> a = analysis.discrete.SimpleWeights() >>> len(a.getWeights('major')) 12 >>> len(a.getWeights('minor')) 12 r) r,rr+rr+r+rr,rr+rr+r) r,rr+r+rr+rr,r+rrrrrrs rrSimpleWeights.getWeightsGsC %%'  7 7 7 "; ;+.RS]R^,_` `rrr"r&r7r)s@rrErE5s- 'DK:aarrEcJ^\rSrSrSrSrSr/SQrS U4SjjrS Sjr Sr U=r $) BellmanBudgei[z Implementation of Bellman-Budge weightings for Krumhansl-Schmuckler key determination algorithm. Values from https://extras.humdrum.org/man/keycor/, which describes these weightings as "No particular tendencies for confusions with neighboring keys." FzBellman Budge Key Analysis)z key.bellmanz key.budgezkey.bellman-budgezkey.bellmanbudgebellmanbudgez bellman-budge bellmanbudgec >[TU]US9 grr2rs rr(BellmanBudge.__init__hr4rcfUR5nUS:Xa/SQ$US:Xa/SQ$[SU35e)z Returns the key weights. >>> a = analysis.discrete.BellmanBudge() >>> len(a.getWeights('major')) 12 >>> len(a.getWeights('minor')) 12 >>> a.getWeights('major') [16.8..., 0.8..., 12.9..., 1.4..., ...] r) g0@gQ?gfffff)@g(\?g{G*@g\('@g?gHzG4@g?gGz @gףp= ?gp= #%@r) g)\(2@gGz?g{G)@gGz*@gQ?gL&@gGz?gR5@g(\@g{Gz?gq= ףp?gQk$@rrrs rrBellmanBudge.getWeightsksC %%'  a a 7 "a a+.RS]R^,_` `rrr"r&r7r)s@rrNrN[s-  'DK:aarrNcJ^\rSrSrSrSrSr/SQrS U4SjjrS Sjr Sr U=r $) TemperleyKostkaPayneia/ Implementation of Temperley-Kostka-Payne weightings for Krumhansl-Schmuckler key determination algorithm. Values from https://extras.humdrum.org/man/keycor/, which describes these weightings as "Strong tendency to identify the relative major as the tonic in minor keys. Well-balanced for major keys." Fz#Temperley Kostka Payne Key Analysis) z key.temperleyz key.kostkaz key.paynezkey.temperley-kostka-paynezkey.temperleykostkapayne temperleykostkapayneztemperley-kostka-paynetemperleykostkapaynec >[TU]US9 grr2rs rr(TemperleyKostkaPayne.__init__r4rcfUR5nUS:Xa/SQ$US:Xa/SQ$[SU35e)z Returns the key weights. >>> a = analysis.discrete.TemperleyKostkaPayne() >>> len(a.getWeights('major')) 12 >>> len(a.getWeights('minor')) 12 r) gV-?gQ?gZd;?gˡE?gq= ףp?q= ףp?g~jt?gzG?g9v?gCl?gv/?g?r) gbX9?g/$?gtV?g-?gJ +?r_gzG?gCl?gB`"?gx&?g/$?gQ?rrrs rrTemperleyKostkaPayne.getWeightssM %%'  > > 7 "> >,.RS]R^,_` `rrr"r&r7r)s@rrWrWs- 0DK :aarrWc^\rSrSrSrSrSrSS/rSSU4SjjjrSSjr SS jr SSS jjr S r SS jr S rSrSrU=r$)Ambitusiz A basic analysis method for measuring register. >>> ambitusAnalysis = analysis.discrete.Ambitus() >>> ambitusAnalysis.identifiers[0] 'ambitus' FzAmbitus Analysisambitusspancz>[TU]US9 SUlSUl[ 5UlUR 5 gr)rr( minPitchObj maxPitchObjr_pitchSpanColors_generateColorsrs rr(Ambitus.__init__s; 9.2-17B} rcSnUcuURbeURUR5nUcgUuUlUl[ URR URR - 5nOSnOUnXB- nUS:XaSnSnSn[ X$S-5HFn[SU- U- U-5U-n URU S-U S-U 45URU'US- nMH g) a& Provide uniformly distributed colors across the entire range. >>> ambitusAnalysis = analysis.discrete.Ambitus() >>> ambitusAnalysis._generateColors() >>> for i, j in ambitusAnalysis._pitchSpanColors.items(): ... if i > 3: break ... print(i, j) 0 #130f19 1 #14101b 2 #16111d 3 #16121e rNr+go@g?g333333?) r# getPitchSpanrfrgr7psrAr/r1rh) r& numColorsminPitchpitchSpanReturnmaxPitch valueRanger antiBlackr9vals rriAmbitus._generateColorss  $$0"&"3"3D4I4I"J"*5D2 $"2t//22T5E5E5H5HHI H( ?J xA.A%)+z9TABYNC'+~~d cCiRU6V'WD ! !! $ AID /rcXRLa:UR(a)UR(aURUR4$UR5RnU(dg/n/nUH~nSn[ U[ R5(a+[ U[R5(d URnX6Vs/sHowRPM sn- nURU5 M U(dgUR[U55nUR[U55n XHn XIn XRLa XlXlX4$s snf)a For a given subStream, return a tuple consisting of the two pitches with the minimum and maximum pitch space value. This public method may be used by other classes. It ignores ChordSymbol objects. Demonstration: >>> s = corpus.parse('bach/bwv66.6') >>> p = analysis.discrete.Ambitus() >>> pitchMin, pitchMax = p.getPitchSpan(s.parts[0].getElementsByClass(stream.Measure)[3]) >>> pitchMin.ps, pitchMax.ps (66.0, 71.0) >>> p.getPitchSpan(s.parts[0].getElementsByClass(stream.Measure)[6]) (, ) >>> s = stream.Stream() >>> c = chord.Chord(['a2', 'b4', 'c8']) >>> s.append(c) >>> p.getPitchSpan(s) (, ) Returns None if the stream contains no pitches. >>> s = stream.Stream(note.Rest()) >>> p.getPitchSpan(s) is None True OMIT_FROM_DOCS And with only ChordSymbols: >>> s.insert(4, harmony.ChordSymbol('C6')) >>> p.getPitchSpan(s) is None True Nr)r#rfrgrecurser isinstancer GeneralNoter ChordSymbolrroextendindexminmax) r&rk justNotespsFound pitchesFoundrrr minPitchIndex maxPitchIndexrfrgs rrnAmbitus.getPitchSpans&L -- -$2B2BtGWGW##T%5%55 5%%'--  "*, A-/G!T--..z!WEXEX7Y7Y)) g.gg. .G    (  c'l3  c'l3 "1 "1 -- -* * ''!/sEc6/nU(aUR5n/n0n[[URR 555H0nU(aURUU;aMURUXE'M2 [ UR 55nUR 5 US[U5S-nU[U5S-SnXx4HIn S/n /n U HnXEn U RX\45 M U RU 5 URU 5 MK U$)a Return legend data. >>> s = corpus.parse('bach/bwv66.6') >>> soprano = s.parts[0] >>> p = analysis.discrete.Ambitus(soprano) # provide ref stream >>> p.solutionLegend() [['', [(0, '#130f19'), (1, '#211a2c'), (2, '#2f263f'), (3, '#3e3253'), (4, '#4c3d66'), (5, '#5b4979')]], ['', [(6, '#69548c'), (7, '#775f9f'), (8, '#866bb2'), (9, '#9476c5'), (10, '#a382d9'), (11, '#b18eec'), (12, '#bf99ff')]]] >>> len(p.solutionLegend()) 2 >>> [len(x) for x in p.solutionLegend()] [2, 2] >>> [len(y) for y in [x for x in p.solutionLegend()]] [2, 2] >>> s = corpus.parse('bach/bwv66.6') >>> p = analysis.discrete.Ambitus() >>> p.solutionLegend(compress=True) # empty if nothing processed [['', []], ['', []]] >>> x = p.process(s.parts[0]) >>> [len(y) for y in [x for x in p.solutionLegend(compress=True)]] [2, 2] >>> x = p.process(s.parts[1]) >>> [len(y) for y in [x for x in p.solutionLegend(compress=True)]] [2, 2] Nr,r)rRrAr?rhkeysr@rrN) r&rZrrcolorsr9r keysTopRow keysBottomRowkeyGrouprrrQs rr[Ambitus.solutionLegend>sN ++-J!#s40055789A((+:=--a0FI :FKKM" +CIN, c$i1n./ $3H=?DC46E  aZ( JJu  KK 4 rcg)r^z Half-StepsrrIs rr_Ambitus.solutionUnitStringsrcHUcURS5$URU$)z >>> p = analysis.discrete.Ambitus() >>> s = stream.Stream() >>> c = chord.Chord(['a2', 'b4', 'c8']) >>> s.append(c) >>> minPitch, maxPitch = p.getPitchSpan(s) >>> p.solutionToColor(maxPitch.ps - minPitch.ps).startswith('#') True )rErErE)r1rhrbs rrcAmbitus.solutionToColors*  >>/2 2$$X..rcURU5nUbJ[R"USUSS9nURUSRUSR- 5nOSnSnUR R X445 X44$)z Given a Stream, return a solution (as an interval) and a color string. >>> p = analysis.discrete.Ambitus() >>> s = stream.Stream() >>> c = chord.Chord(['a2', 'b4', 'c8']) >>> s.append(c) >>> p.process(s) (, '#665288') Nrr+) noteStartnoteEndr)rnr Intervalrcror$rN)r&rgrOrUrQs rrhAmbitus.processs  )  ((47DGLH((ad1gjj)@AEHE ""H#45rc,URU5up#U$)z Procedure to only return an Interval object. >>> s = corpus.parse('bach/bwv66.6') >>> p = analysis.discrete.Ambitus() >>> p.getSolution(s) )rhr&rgrUrVs rrlAmbitus.getSolutions"&g!6r)rhrgrfr")r'zstream.Stream | None)rnz&tuple[pitch.Pitch, pitch.Pitch] | Nonerprq)rUz int | Nonernro)rrrrrsr'rtr r(rirnr[r_rcrhrlrr(r)s@rrbrbsV Df%K'VF(PEN /".  rrbc`^\rSrSrSrSrSrSS/rS U4SjjrSr SS jr SS jr S r S r U=r$)MelodicIntervalDiversityizN An analysis method to determine the diversity of intervals used in a Stream. FzInterval Diversityzinterval.diversity intervalsc >[TU]US9 grr2rs rr(!MelodicIntervalDiversity.__init__r4rcg)Nrrrbs rrc(MelodicIntervalDiversity.solutionToColorsrcSSKJn Uc0nUR5(a%[UR UR 55nOU/nUGH&nUR 5RSS9R [R5R5n[U5HupU [U5S- ::aXS-n OSn U cM&[R"X5n U(aU RRS:XaM_U(a*U RRS:aU R!5n U R"U;aU S/X)R"'MX)R"S==S- ss'M GM) U$)z Find all unique melodic intervals in this Stream. If `found` is provided as a dictionary, this dictionary will be used to store Intervals, and counts of Intervals already found will be incremented. rrNFr r,r+)music21rhasPartLikeStreamsr@getElementsByClassStreamr stripTiesr Noterr?r r chromatic semitonesr directedName) r&rgfoundignoreDirection ignoreUnisonrprocListr noteStreamr9rnNexts rcountMelodicIntervals.MelodicIntervalDiversity.countMelodicIntervalss? # =E  % % ' 'G66v}}EFHyHA..u.=PPQUQZQZ[bbdJ!*-J!++&1u-E E$ ))!3A#;;00A5$&;;0014 ! A~~U212Ann-nn-a0A50). > rcnURX5n[U5UR[U554$)z8 Find how many unique intervals are used in this Stream )rr?rc)r&rgruniqueIntervalss rrh MelodicIntervalDiversity.processs444WN?#T%9%9#o:N%OOOrcHURUR55up#U$)z- Solution is the number of unique intervals. )rhrrs rrl$MelodicIntervalDiversity.getSolutions!"&goo.?!@rrr")NTT)T)rrrrrsr'rtr r(rcrrhrlrr(r)s@rrrs? D'5K:4lPrrc zUS:XaSn[U5nUbU"5nURU5$[SU35e)a Public interface to discrete analysis methods to be applied to a Stream given as an argument. Methods return process-specific data format. See subclasses for details. Analysis methods can be specified as arguments or by use of a `method` keyword argument. If `method` is the class name, that class is returned. Otherwise, the :attr:`~music21.analysis.discrete.DiscreteAnalysis.identifiers` list of all :class:`~music21.analysis.discrete.DiscreteAnalysis` subclass objects will be searched for matches. The first match that is found is returned. :class:`~music21.analysis.discrete.Ambitus` :class:`~music21.analysis.discrete.KrumhanslSchmuckler` >>> s = corpus.parse('bach/bwv66.6') >>> analysis.discrete.analyzeStream(s, 'Krumhansl') >>> analysis.discrete.analyzeStream(s, 'ambitus') >>> analysis.discrete.analyzeStream(s, 'key') >>> analysis.discrete.analyzeStream(s, 'span') Note that the same results can be obtained by calling "analyze" directly on the stream object: >>> s.analyze('key') >>> s.analyze('span') rArdzno such analysis method: )analysisClassFromMethodNamerlr)rmethodkeywordsanalysisClassNameobjs r analyzeStreamrsRJ5PQW5X$!y)) $&?x$H IIrc[[[[[[ /nSnUHQnUR 5URR 5;d UR 5UR;dMOUn O Uc&UH nURH nX:XdM Un M M" Uc+UH%nURH nX;dM Un O UcM$ U$ U$)a Returns an analysis class given a method name, or None if none can be found Searches first the class name, then the .identifiers array for each class, then a subset of any identifier. >>> acfmn = analysis.discrete.analysisClassFromMethodName >>> acfmn('aarden') >>> acfmn('span') This one is fundamentally important: >>> acfmn('key') >>> print(repr(acfmn('unknown-format'))) None N) rbr+r9rErNrWrrrtr )ranalysisClassesmatch analysisClassidStrs rrrPs,  5O*.E( LLNm44::< <<<>]%7%77!E  ) },M&22?)E 3- },M&22?)E 3   L- Lrc>\rSrSrSrSrSrSrSrSr Sr S r g ) Testic2SSKJn U"U[55 g)Nr) testCopyAll)music21.test.commonTestrglobals)r&rs rtestCopyAndDeepcopyTest.testCopyAndDeepcopys7D')$rc$SSKJn [5nURS5nURS5nURS5nUR UR 55 UR UR 55upgUR5 UR5 Xg-nUR UR 55 UR UR 55upU R5 U R5 X-n UR UR 55upU R5 U R5 /n[[U55H*nXunnXunnURUUU-S- 45 M, g)Nr converterz1tinynotation: 4/4 c4 d e f g a b c c#4 d# e# f#z0tinynotation: 4/4 c#4 d# e# f# f g a b- c d e fzQtinynotation: 4/4 c4 d e f g a b c c#4 d# e# f# c#4 d# e# f# f g a b- c d e fg@) rrr+parserhrrrrAr?rN)r&rrs1s2s3likelyKeysMajor1likelyKeysMinor1 allResults1likelyKeysMajor2likelyKeysMinor2 allResults2likelyKeysMajor3likelyKeysMinor3avgr9count1count2s rtestKeyAnalysisKrumhanslTest.testKeyAnalysisKrumhanslsU%  ! __P Q __O P __@A "**,-.]]2::<-H*&9  "**,-.]]2::<-H*&9 ./]]2::<-H*s;'(A#IAv#IAv JJFVOs23 4)rc SSKJn SSKJn UR"5nUR [ R "S55 UR [ R "S55 UR [ R "S55 [5nURU5nUR[US5S5 UR[US 5S 5 UR[U5S 5 UR"5nUR [ R "S 55 UR [ R "S 55 UR [ R "S 55 UR [ R "S 55 [5nURU5nUR[U5S5 UR[US5S5 URUSS9nUR[U5S 5 UR[US5S5 UR[US5S5 [5nURS5nURURS5nUR[U5S5 UR[US5S5 UR[US5S5 UR[US5S5 UR[US5S5 URU5nUR[U5S5 UR[[[U555S 5 UR[US!5S"5 UR[US5S#5 UR[US5S$5 UR[US%5S&5 UR[US5S'5 UR[US5S(5 UR[US 5S)5 g)*Nrr)corpuszg#3a3g4m7z#[, 1]m2z#[, 1]r,c3d3r+M2z#[, 3]F)rzM-2z$[, 1]z#[, 2]zcorelli/opus3no1/1grave P5z#[, 8]P4z#[, 7]m3z#[, 1]z$[, 21] z=['M2', 'M3', 'M6', 'P15', 'P4', 'P5', 'P8', 'd5', 'm2', 'm3']P15z$[, 1]z$[, 16]z$[, 29]M3z$[, 16]z$[, 12]z$[, 79]z$[, 43])rrrrrNr rrr assertEqualror?rpartsrr@)r&rrsmidmidDicts rtestIntervalDiversityTest.testIntervalDiversitysW"" MMO 5!" 4! 4!&(++A. WT]+-RS WT]+-RS Wq) MMO 4! 4! 4! 4!&(++A. Wq) WT]+-RS++Au+E Wq) WU^,.TU WT]+-RS&( LL2 3++AGGAJ7 Wq) WT]+-RS WT]+-RS WT]+-RS WT]+-ST++A. Wr* VDM23X Z WU^,.TU WT]+-ST WT]+-ST WT]+-ST WT]+-ST WT]+-ST WT]+-STrcSSKJn SHmnUR"5nUR[R "U55 UR [URS5R5U5 Mo g)Nrr)rrr Krumhansl) rrrrNr rrroanalyzer)r&rrrs rtestKeyAnalysisSpellingTest.testKeyAnalysisSpellingsR""A A HHTYYq\ "   S;!7!=!=> B#rcXSSKJn SSKJn UR UR 5n[ 5nURU5nURURUR/nUR[US5S5 UR[US5S5 UR[US5SSS 5 [5nURU5nURURUR/nUR[US5S5 UR[US5S 5 [5nURU5nURURUR/nUR[US5S5 UR[US5S 5 [5nURU5nURURUR/nUR[US5S5 UR[US5S 5 [!5nURU5nURURUR/nUR[US5S5 UR[US5S 5 g) Nrr) testFilesrr+rr,z0.81063r)rrmusic21.musicxmlrr edgefield82br+rlrrrrror9rErNrW)r&rrrrr rOs rtestKeyAnalysisDiverseWeights"Test.testKeyAnalysisDiverseWeightss%. OOI22 3  ! MM! !9!9: T!Wt, T!Ww/ T!Wa*I6 M MM! !9!9: T!Wt, T!Ww/ O MM! !9!9: T!Wt, T!Ww/ N MM! !9!9: T!Wt, T!Ww/ " MM! !9!9: T!Wt, T!Ww/rcSSKJn UR"5nUR[R "S5S5 UR[R "S5S5 UR[R "S5S5 UR S 5nUR[U5S 5 URS RS UR55S 5 UR S5nUR[U5S5 URS RSUR55S5 UR"5nUR[R "S5S5 UR[R "S5S5 UR S5nUR[UR5S5 g)Nrrcgrr,r+zC major c38# UHoRv M g7fr"tonicPitchNameWithCaser8kps rr<1Test.testKeyAnalysisLikelyKeys..)!aF`";";F`z7c G a F g e f E- A- B- d D A b b- c# f# C# E g# F# e- Br9zF majorc38# UHoRv M g7fr"r r s rr<r.rrz7C c g f a G d A- B- E- e b- D A f# C# b E c# e- F# B g#zc#r ) rrr repeatAppendr rrrrojoinr$r?)r&rrr rs rtestKeyAnalysisLikelyKeysTest.testKeyAnalysisLikelyKeys sM" MMO tyy~q) tyy~q) tyy~q) II+ , Q+ !aaF`F`!aaR T IIm $ Q+ !aaF`F`!aaR T]]_  #*  $+ JJu  Q778"=rc SSKJn UR"5nUR[R "55 UR[ R"[R "5[R"S5[R"S5/55 URS5nURURS5 g)NrrzE-4zB-4r zE- major) rrrrNr rr PercussionChordrrrrt)r&rrr s rtestKeyAnalysisIgnoresUnpitched$Test.testKeyAnalysisIgnoresUnpitched<s" MMO !" ++ NN  IIe  IIe -   IIe  ,rrN) rrrrrrrrrrrrrrrrrs*%&5R4UlC#0J>8 -rr__main__)rz stream.Streamrro)rrornztype[DiscreteAnalysis] | None),rs __future__r collectionsrcollections.abcrrtypingtunittestrrrr r r r r r TYPE_CHECKINGr Environment environLocalMusic21Exceptionrrrwr+KrumhanslKesslerr9rErNrWkeyWeightKeyAnalysisClassesrbrrrTestCaser _DOC_ORDERrmainTestrrrr+s ##. ??&&':;  = = J J fI+I\+a.+a\')a&)aX#a(#aL$a'$aN&a/&aT 3*M+-A!JJ\S/Sr2J2J 2Jl:~x-8  x-x-w8P"M; !#79  z Tr