# -*- coding: utf-8 -*- # ------------------------------------------------------------------------------ # Name: reduction.py # Purpose: Tools for creating a score reduction. # # Authors: Christopher Ariza # Michael Scott Asato Cuthbert # # Copyright: Copyright © 2011-2013 Michael Scott Asato Cuthbert # License: BSD, see license.txt # ------------------------------------------------------------------------------ ''' Tools for generation reduction displays, showing a score and or a chord reduction, and one or more reductive representation lines. Used by graph.PlotHorizontalBarWeighted() ''' from __future__ import annotations import copy import re import typing as t import unittest from music21 import exceptions21 from music21 import chord from music21 import common from music21.common.types import DocOrder from music21 import environment from music21 import expressions from music21 import instrument from music21 import note from music21 import pitch from music21 import prebase from music21 import stream environLocal = environment.Environment('analysis.reduction') # ------------------------------------------------------------------------------ class ReductiveEventException(exceptions21.Music21Exception): pass # as lyric, or as parameter # # ::/p:g#/o:5/nh:f/ns:n/l:1/g:ursatz/v:1 class ReductiveNote(prebase.ProtoM21Object): ''' The extraction of an event from a score and specification of where and how it should be presented in a reductive score. A specification string, as well as Note, must be provided for parsing. A specification must be created when access the Measure that the source note is found in. Storing the measure and index position provides significant performance optimization, as we do no have to search every note when generated the reduction. The `measureIndex` is the index of measure where this is found, not the measure number. The `measureOffset` is the position in the measure specified by the index. ''' _delimitValue = ':' # store the delimiter string, must start with 2 _delimitArg = '/' # map the abbreviation to the data key _parameterKeys = { 'p': 'pitch', 'o': 'octave', 'nf': 'noteheadFill', 'sd': 'stemDirection', 'g': 'group', 'v': 'voice', 'ta': 'textAbove', # text annotation 'tb': 'textBelow', # text annotation } _defaultParameters = { 'pitch': None, # use notes, or if a chord take highest 'octave': None, # use notes 'noteheadFill': None, # use notes 'stemDirection': 'noStem', 'group': None, 'voice': None, } def __init__(self, specification, inputNote, measureIndex, measureOffset): self._specification = specification self._note = None # store a reference to the note this is attached to self._parameters = {} # do parsing if possible self._isParsed = False self._parseSpecification(self._specification) self._note = inputNote # keep a reference self.measureIndex = measureIndex self.measureOffset = measureOffset def _reprInternal(self): msg = [] for key in self._parameterKeys: attr = self._parameterKeys[key] if attr in self._parameters: # only show those defined if self._parameters[attr]: msg.append(key) msg.append(':') msg.append(self._parameters[attr]) if self._note is not None: msg.append(' of ') msg.append(repr(self._note)) return ''.join(msg) def __getitem__(self, key): return self._parameters[key] def _parseSpecification(self, spec: str): # start with the defaults self._parameters = copy.deepcopy(self._defaultParameters) spec = spec.strip() # spec = spec.replace(' ', '') if not spec.startswith(self._delimitValue + self._delimitValue): return # nothing to parse args = spec.split(self._delimitArg) for a in args[1:]: # skip the first arg, as it is just delimiter # if no delimit arg, it cannot be parsed if self._delimitValue not in a: continue candidateKey, value = a.split(self._delimitValue) candidateKey = candidateKey.strip() value = value.strip() if candidateKey.lower() in self._parameterKeys: attr = self._parameterKeys[candidateKey] self._parameters[attr] = value self._isParsed = True def isParsed(self) -> bool: return self._isParsed def getNoteAndTextExpression(self): ''' Produce a new note, a deep copy of the supplied note and with the specified modifications. ''' n = None if self._note.isChord: # need to permit specification by pitch if 'pitch' in self._parameters: p = pitch.Pitch(self._parameters['pitch']) for sub in self._note: # iterate over components if p.name.lower() == sub.pitch.name.lower(): # copy the component n = copy.deepcopy(sub) else: # get first, or get entire chord? # n = copy.deepcopy(self._note.pitches[0]) n = copy.deepcopy(self._note.pitches[0]) else: n = copy.deepcopy(self._note) # always clear certain parameters if n is None: pitchParameter = self._parameters['pitch'] raise ReductiveEventException( f'Could not find pitch, {pitchParameter!r} in self._note: {self._note!r}') n.lyrics = [] n.tie = None n.expressions = [] n.articulations = [] n.duration.dots = 0 # set to zero if n.pitch.accidental is not None: n.pitch.accidental.displayStatus = True te = None if 'octave' in self._parameters: if self._parameters['octave']: n.pitch.octave = self._parameters['octave'] if 'stemDirection' in self._parameters: n.stemDirection = self._parameters['stemDirection'] if 'noteheadFill' in self._parameters: nhf = self._parameters['noteheadFill'] if nhf: if nhf == 'yes': nhf = True elif nhf == 'no': nhf = False n.noteheadFill = nhf # environLocal.printDebug(['set notehead fill:', n.noteheadFill]) if 'textBelow' in self._parameters: n.addLyric(self._parameters['textBelow']) if 'textAbove' in self._parameters: te = expressions.TextExpression(self._parameters['textAbove']) return n, te # ------------------------------------------------------------------------------ class ScoreReductionException(exceptions21.Music21Exception): pass class ScoreReduction: ''' An object to reduce a score. ''' def __init__(self, **keywords): # store a list of one or more reductions self._reductiveNotes = {} self._reductiveVoices = [] self._reductiveGroups = [] # store the source score self._score = None self._chordReduction = None # store a chordal reduction of available def _setScore(self, value): if not isinstance(value, stream.Stream): raise ScoreReductionException('cannot set a non Stream') if value.hasPartLikeStreams: # make a local copy self._score = copy.deepcopy(value) else: # assume a single stream, place in a Score s = stream.Score() s.insert(0, copy.deepcopy(value)) self._score = s self._score.setDerivationMethod('ScoreReduction', recurse=True) def _getScore(self): return self._score score = property(_getScore, _setScore, doc=''' Get or set the Score. Setting the score set a deepcopy of the score; the score set here will not be altered. >>> s = corpus.parse('bwv66.6') >>> sr = analysis.reduction.ScoreReduction() >>> sr.score = s ''') def _setChordReduction(self, value): if not isinstance(value, stream.Stream): raise ScoreReductionException('cannot set a non Stream') if value.hasPartLikeStreams(): # make a local copy self._chordReduction = copy.deepcopy(value) else: # assume a single stream, place in a Score s = stream.Score() s.insert(0, copy.deepcopy(value)) self._chordReduction = s def _getChordReduction(self): return self._chordReduction chordReduction = property(_getChordReduction, _setChordReduction, doc=''' Get or set a Chord reduction as a Stream or Score. Setting the this values set a deepcopy of the reduction; the reduction set here will not be altered. ''') def _extractReductionEvents(self, score, removeAfterParsing=True): ''' Remove and store all reductive events Store in a dictionary where obj id is obj key ''' if score is None: return # iterate overall notes, check all lyrics for p in score.parts: for i, m in enumerate(p.getElementsByClass(stream.Measure)): for n in m.recurse().notes: infoDict = {'part': p, 'measure': m, 'measureIndex': i} self._extractNoteReductiveEvent(n, infoDict, removeAfterParsing) def _extractNoteReductiveEvent(self, n, infoDict=None, removeAfterParsing=True): if infoDict is None: infoDict = {'part': None, 'measure': None, 'measureIndex': 0 } m = infoDict['measure'] if not n.lyrics: return removalIndices = [] if n in m: offset = n.getOffsetBySite(m) else: # it is in a Voice offset = 0.0 for v in m.voices: if n in v: offset = n.getOffsetBySite(v) # a list of Lyric objects for k, l in enumerate(n.lyrics): # store measure index rn = ReductiveNote(l.text, n, infoDict['measureIndex'], offset) if rn.isParsed(): # environLocal.printDebug(['parsing reductive note', rn]) # use id, lyric text as hash key = str(id(n)) + l.text self._reductiveNotes[key] = rn removalIndices.append(k) if removeAfterParsing: for q in removalIndices: # replace position in list with empty lyric n.lyrics[q] = note.Lyric('') def _parseReductiveNotes(self): self._reductiveNotes = {} self._extractReductionEvents(self._chordReduction) self._extractReductionEvents(self._score) for unused_key, rn in self._reductiveNotes.items(): if rn['group'] not in self._reductiveGroups: self._reductiveGroups.append(rn['group']) if rn['voice'] not in self._reductiveVoices: self._reductiveVoices.append(rn['voice']) # if we have None and a group, then we should just use that one # group; same with voices if (len(self._reductiveGroups) == 2 and None in self._reductiveGroups): self._reductiveGroups.remove(None) # for now, sort all # environLocal.printDebug(['self._reductiveGroups', self._reductiveGroups]) if (len(self._reductiveVoices) == 2 and None in self._reductiveVoices): self._reductiveVoices.remove(None) def _createReduction(self): self._parseReductiveNotes() s = stream.Score() # need to scan all tags oneGroup = False if len(self._reductiveGroups) == 1: # if 1, can be None or a group name: oneGroup = True oneVoice = False if len(self._reductiveVoices) == 1: # if 1, can be None or a group name: oneVoice = True if self._score: mTemplate = self._score.parts.first().template(retainVoices=False) else: mTemplate = self._chordReduction.parts.first().template(retainVoices=False) # for each defined reductive group for gName in self._reductiveGroups: # create reductive parts # need to break by necessary parts, voices; for now, assume one g = copy.deepcopy(mTemplate) g.id = gName inst = instrument.Instrument() inst.partName = gName g.insert(0, inst) gMeasures = g.getElementsByClass(stream.Measure) # for m in gMeasures._elements: # print(gName, m) # m.clef = clef.TrebleClef() # TODO: insert into note or chord for unused_key, rn in self._reductiveNotes.items(): if oneGroup or rn['group'] == gName: # environLocal.printDebug([ # '_createReduction(): found reductive note, rn', rn, 'group', gName]) gMeasure = gMeasures[rn.measureIndex] if not gMeasure.voices: # common setup routines # if no voices, start by removing rests gMeasure.removeByClass('Rest') for vId in self._reductiveVoices: v = stream.Voice() v.id = vId gMeasure.insert(0, v) if oneVoice: n, te = rn.getNoteAndTextExpression() gMeasure.voices[0].insertIntoNoteOrChord( rn.measureOffset, n) # place the text expression in the Measure, not Voice if te: gMeasure.insert(rn.measureOffset, te) else: v = gMeasure.getElementById(rn['voice']) if v is None: # just take the first v = gMeasure.voices[0] n, te = rn.getNoteAndTextExpression() v.insertIntoNoteOrChord(rn.measureOffset, n) if te: gMeasure.insert(rn.measureOffset, te) # after gathering all parts, fill with rests for i, m in enumerate(g.getElementsByClass(stream.Measure)): # only make rests if there are notes in the measure for v in m.voices: if v.recurse().notes: v.makeRests(fillGaps=True, inPlace=True) m.flattenUnnecessaryVoices(inPlace=True) # hide all rests in all containers for r in m[note.Rest]: r.style.hideObjectOnPrint = True # m.show('t') # add to score s.insert(0, g) # g.show('t') if self._chordReduction: for p in self._chordReduction.parts: s.insert(0, p) srcParts = [] # for bracket if self._score: for p in self._score.parts: s.insert(0, p) srcParts.append(p) # store to brace return s def reduce(self): ''' Given a score, populate this Score reduction ''' # if not set here or before if self.score is None and self.chordReduction is None: raise ScoreReductionException('no score defined to reduce') return self._createReduction() # ------------------------------------------------------------------------------ class PartReductionException(exceptions21.Music21Exception): pass # ------------------------------------------------------------------------------ class PartReduction: ''' A part reduction reduces a Score into one or more parts. Parts are combined based on a part group dictionary. Each resulting part is then segmented by an object. This object is assigned as floating-point value. This reduction is designed to work with the GraphHorizontalBarWeighted and related Plot subclasses. If the `fillByMeasure` parameter is True, and if measures are available, each part will segment by Measure divisions, and look for the target activity only once per Measure. If more than one target is found in the Measure, values will be averaged. If `fillByMeasure` is False, the part will be segmented by each Note. The `segmentByTarget` parameter is True, segments, which may be Notes or Measures, will be divided if necessary to show changes that occur over the duration of the segment by a target object. If the `normalizeByPart` parameter is True, each part will be normalized within the range only of that part. If False, all parts will be normalized by the max of all parts. The default is True. If the `normalize` parameter is False, no normalization will take place. The default is True. ''' def __init__(self, srcScore=None, *, partGroups: list[dict[str, t.Any]]|None = None, fillByMeasure: bool = True, segmentByTarget: bool = True, normalize: bool = True, normalizeByPart: bool = False, **keywords): if srcScore is None: return if not isinstance(srcScore, stream.Score): raise PartReductionException('provided Stream must be Score') self._score = srcScore # an ordered list of dictionaries for # part id, part color, and a list of Part objs # TODO: typed dict self._partBundles: list[dict[str, t.Any]] = [] # a dictionary of part id to a list of events self._eventSpans: dict[str|int, list[t.Any]] = {} # define how parts are grouped # a list of dictionaries, with keys for name, color, and a match list self._partGroups = partGroups self._fillByMeasure = fillByMeasure # We re-partition if the spans change self._segmentByTarget = segmentByTarget self._normalizeByPart = normalizeByPart # norm by all parts is default self._normalizeToggle = normalize # check that there are measures for p in self._score.parts: if not p.hasMeasures(): self._fillByMeasure = False # environLocal.printDebug(['overriding fillByMeasure as no measures are defined']) break def _createPartBundles(self): ''' Fill the _partBundles list with dictionaries, each dictionary defining a name (part id or supplied), a color, and list of Parts that match. ''' self._partBundles = [] if self._partGroups: for d in self._partGroups: # a list of dictionaries name, pColor, matches = d['name'], d['color'], d['match'] sub = [] for p in self._score.parts: # environLocal.printDebug(['_createPartBundles: part.id', p.id]) # if matches is None, use group name if matches is None: matches = [name] pId = str(p.id).lower() for m in matches: # strings or instruments if (isinstance(m, str) and pId.find(m.lower()) >= 0): sub.append(p) break elif re.match(m.lower(), pId): sub.append(p) # TODO: match if m is Instrument class if not sub: continue data = { 'pGroupId': name, 'color': pColor, 'parts': sub, } self._partBundles.append(data) else: # manually creates for p in self._score.parts: # store one or more Parts associated with an id data = {'pGroupId': p.id, 'color': '#666666', 'parts': [p]} self._partBundles.append(data) # create flat representation of all parts in a bundle for partBundle in self._partBundles: if len(partBundle['parts']) == 1: partBundle['parts.flat'] = partBundle['parts'][0].flatten() else: # align all parts and flatten # this takes a flat presentation of all parts s = stream.Stream() for p in partBundle['parts']: s.insert(0, p) partBundle['parts.flat'] = s.flatten() def _createEventSpans(self): # for each part group id key, store a list of events self._eventSpans = {} for partBundle in self._partBundles: pGroupId = partBundle['pGroupId'] pColor = partBundle['color'] parts = partBundle['parts'] # print(pGroupId) dataEvents = [] # combine multiple streams into a single eStart = None eEnd = None eLast = None # segmenting by measure if that measure contains notes. # Note that measures are not elided of activity is contiguous if self._fillByMeasure: partMeasures = [] for p in parts: partMeasures.append(p.getElementsByClass(stream.Measure).stream()) # environLocal.printDebug(['partMeasures', partMeasures]) # assuming that all parts have same the number of measures # iterate over each measure # iLast = len(partMeasures[0]) - 1 for i in range(len(partMeasures[0])): active = False # check for activity in any part in the part group for p in partMeasures: # iter of parts containing measures # print(p, i, p[i], len(p[i].flatten().notes)) if p[i].iter().notes: active = True break # environLocal.printDebug([i, 'active', active]) if not active: continue # get offset, or start, of this measure e = partMeasures[0][i] eStart = e.getOffsetBySite(partMeasures[0]) # use duration, not barDuration.quarterLength # as want filled duration? eEnd = (eStart + e.barDuration.quarterLength) ds = {'eStart': eStart, 'span': eEnd - eStart, 'weight': None, 'color': pColor, } dataEvents.append(ds) # if eStart is None and active: # eStart = partMeasures[0][i].getOffsetBySite( # partMeasures[0]) # elif (eStart is not None and not active) or i >= iLast: # if eStart is None: # nothing to do; just the last # continue # # if this is the last measure, and it is active # if (i >= iLast and active): # eLast = partMeasures[0][i] # # use duration, not barDuration.quarterLength # # as want filled duration? # eEnd = (eLast.getOffsetBySite( # partMeasures[0]) + # eLast.barDuration.quarterLength) # ds = {'eStart':eStart, 'span':eEnd-eStart, # 'weight':None, 'color':pColor} # dataEvents.append(ds) # eStart = None # eLast = partMeasures[0][i] # fill by alternative approach, based on activity of notes # creates region for each contiguous span of notes # this is useful as it will handle overlaps and similar arrangements # TODO: this needs further testing else: # this takes a flat presentation of all parts, and then # finds any gaps in consecutive notes eSrc = partBundle['parts.flat'] # a li=st, not a stream # a None in the resulting list designates a rest noteSrc = eSrc.findConsecutiveNotes() for i, e in enumerate(noteSrc): # environLocal.printDebug(['i, e', i, e]) # if this event is a rest, e is None if e is None: if eStart is None: # the first event is a rest continue else: eEnd = eLast.getOffsetBySite(eSrc) + eLast.quarterLength # create a temporary weight ds = {'eStart': eStart, 'span': eEnd - eStart, 'weight': None, 'color': pColor, } dataEvents.append(ds) eStart = None elif i >= len(noteSrc) - 1: # this is the last if eStart is None: # the last event was a rest # this the start is the start of this event eStart = e.getOffsetBySite(eSrc) eEnd = e.getOffsetBySite(eSrc) + e.quarterLength # create a temporary weight ds = {'eStart': eStart, 'span': eEnd - eStart, 'weight': None, 'color': pColor, } dataEvents.append(ds) eStart = None else: if eStart is None: eStart = e.getOffsetBySite(eSrc) eLast = e # environLocal.printDebug(['dataEvents', dataEvents]) self._eventSpans[pGroupId] = dataEvents def _getValueForSpan( self, target='Dynamic', splitSpans=True, targetToWeight=None ): ''' For each span, determine the measured parameter value. This is translated as the height of the bar graph. If `splitSpans` is True, a span will be split of the target changes over the span. Otherwise, Spans will be averaged. This is the `segmentByTarget` parameter. The `targetToWeight` parameter is a function that takes a list or Stream of objects (of the class specified by `target`) and returns a single floating-point value. ''' # this temporary function only works with dynamics def _dynamicToWeight(targets): # permit a stream if hasattr(targets, 'isStream') and targets.isStream: pass elif not common.isIterable(targets): targets = [targets] summation = 0 for e in targets: # a Stream summation += e.volumeScalar # for dynamics return summation / len(target) # supply function to convert one or more targets to number if targetToWeight is None: targetToWeight = _dynamicToWeight if not splitSpans: # this is segmentByTarget for partBundle in self._partBundles: flatRef = partBundle['parts.flat'] for ds in self._eventSpans[partBundle['pGroupId']]: # for each event span, find the targeted object offsetStart = ds['eStart'] offsetEnd = offsetStart + ds['span'] match = flatRef.getElementsByOffset( offsetStart, offsetEnd, includeEndBoundary=False, mustFinishInSpan=False, mustBeginInSpan=True ).getElementsByClass(target).stream() if not match: w = None else: w = targetToWeight(match) # environLocal.printDebug(['segment weight', w]) ds['weight'] = w else: for partBundle in self._partBundles: finalBundle = [] flatRef = partBundle['parts.flat'] # get each span for ds in self._eventSpans[partBundle['pGroupId']]: offsetStart = ds['eStart'] offsetEnd = offsetStart + ds['span'] # get all targets within the contiguous region # e.g., Dynamics objects match = flatRef.getElementsByOffset(offsetStart, offsetEnd, includeEndBoundary=True, mustFinishInSpan=False, mustBeginInSpan=True).getElementsByClass(target).stream() # environLocal.printDebug(['matched elements', target, match]) # extend duration of all found dynamics match.extendDuration(target, inPlace=True) # match.show('t') dsFirst = copy.deepcopy(ds) if not match: # weight is not known finalBundle.append(dsFirst) continue # create new spans for each target in this segment for i, tar in enumerate(match): targetStart = tar.getOffsetBySite(flatRef) # can use extended duration targetSpan = tar.duration.quarterLength # if dur of target is greater tn this span # end at this span if targetStart + targetSpan > offsetEnd: targetSpan = offsetEnd - targetStart # if we have the last matched target, it will # have zero duration, as there is no following # thus, span needs to be distance to end of regions if targetSpan <= 0.001: targetSpan = offsetEnd - targetStart # environLocal.printDebug([t, 'targetSpan', targetSpan, # 'offsetEnd', offsetEnd, "ds['span']", ds['span']]) if i == 0 and ds['eStart'] == targetStart: # the target start at the same position # as the start of this existing span # dsFirst['eStart'] = targetStart dsFirst['span'] = targetSpan dsFirst['weight'] = targetToWeight(tar) finalBundle.append(dsFirst) elif t == 0 and ds['eStart'] != targetStart: # add two, one for the empty region, one for target # adjust span of first; weight is not known # (hangs over from last) dsFirst['span'] = targetStart - offsetStart finalBundle.append(dsFirst) dsNext = copy.deepcopy(ds) dsNext['eStart'] = targetStart dsNext['span'] = targetSpan dsNext['weight'] = targetToWeight(tar) finalBundle.append(dsNext) else: # for all other cases, create segment for each dsNext = copy.deepcopy(ds) dsNext['eStart'] = targetStart dsNext['span'] = targetSpan dsNext['weight'] = targetToWeight(tar) finalBundle.append(dsNext) # after iterating all ds spans, reassign self._eventSpans[partBundle['pGroupId']] = finalBundle def _extendSpans(self): ''' Extend the value of a target parameter to the next boundary. An undefined boundary will wave as its weight None. ''' # environLocal.printDebug(['_extendSpans: pre']) # for partBundle in self._partBundles: # for i, ds in enumerate(self._eventSpans[partBundle['pGroupId']]): # print(ds) minValue = 0.01 # for error conditions for partBundle in self._partBundles: lastWeight = None for i, ds in enumerate(self._eventSpans[partBundle['pGroupId']]): if i == 0: # cannot extend first if ds['weight'] is None: # this is an error in the rep ds['weight'] = minValue # environLocal.printDebug([ # 'cannot extend a weight: no previous weight defined']) else: lastWeight = ds['weight'] else: # not first if ds['weight']: lastWeight = ds['weight'] elif lastWeight: # its None, use last ds['weight'] = lastWeight # do not have a list; mist set to min elif ds['weight'] is None and lastWeight is None: ds['weight'] = minValue # environLocal.printDebug([ # 'cannot extend a weight: no previous weight defined']) # environLocal.printDebug(['_extendSpans: post']) # for partBundle in self._partBundles: # for i, ds in enumerate(self._eventSpans[partBundle['pGroupId']]): # print(ds) def _normalize(self, byPart=False): ''' Normalize, either within each Part, or for all parts ''' partMaxRef = {} for partBundle in self._partBundles: partMax = 0 for ds in self._eventSpans[partBundle['pGroupId']]: if ds['weight'] > partMax: partMax = ds['weight'] partMaxRef[partBundle['pGroupId']] = partMax try: maxOfMax = max(partMaxRef.values()) except ValueError: # empty part? maxOfMax = 0 for partBundle in self._partBundles: for ds in self._eventSpans[partBundle['pGroupId']]: # weight is now fraction of the max for that part if byPart: bestMax = partMaxRef[partBundle['pGroupId']] else: bestMax = maxOfMax if bestMax != 0: ds['weight'] = (ds['weight'] / bestMax) else: ds['weight'] = 1 # error? def process(self): ''' Core processing routines. ''' self._createPartBundles() self._createEventSpans() self._getValueForSpan(splitSpans=self._segmentByTarget) self._extendSpans() if self._normalizeToggle: self._normalize(byPart=self._normalizeByPart) def getGraphHorizontalBarWeightedData(self): ''' Get all data organized into bar span specifications. ''' # data = [ # ('Violins', [(3, 5, 1, '#fff000'), (1, 12, 0.2, '#3ff203', 0.1, 1)] ), # ('Celli', [(2, 7, 0.2, '#0ff302'), (10, 3, 0.6, '#ff0000', 1)] ), # ] data = [] # iterate over part bundles to get order for partBundle in self._partBundles: # print(partBundle) dataList = [] groupSpans = partBundle['pGroupId'] for ds in self._eventSpans[groupSpans]: # data format here is set by the graphing routine dataList.append([ds['eStart'], ds['span'], ds['weight'], ds['color']]) data.append((partBundle['pGroupId'], dataList)) return data # ------------------------------------------------------------------------------ class Test(unittest.TestCase): def testCopyAndDeepcopy(self): from music21.test.commonTest import testCopyAll testCopyAll(self, globals()) def testExtractionA(self): from music21 import analysis from music21 import corpus s = corpus.parse('bwv66.6') # s.show() s.parts[0].flatten().notes[3].addLyric('test') s.parts[0].flatten().notes[4].addLyric('::/o:6/tb:here') s.parts[3].flatten().notes[2].addLyric('::/o:5/tb:fromBass') s.parts[1].flatten().notes[7].addLyric('::/o:4/nf:no/g:Ursatz/ta:3 3 200') sr = analysis.reduction.ScoreReduction() sr.score = s post = sr.reduce() # post.show() # post.parts[0].show('t') self.assertEqual(len(post.parts[0].flatten().notes), 3) # post.parts[0].show('t') three_measures = post.parts.first()[stream.Measure][:3] new_stream = stream.Stream() for m in three_measures: new_stream.append(m) flat_stream = new_stream.flatten() match = [(repr(e), e.offset, e.duration.quarterLength) for e in flat_stream.notesAndRests] self.maxDiff = None self.assertEqual(match, [('', 0.0, 1.0), ('', 1.0, 1.0), ('', 2.0, 1.0), ('', 3.0, 1.0), ('', 4.0, 1.0), ('', 5.0, 1.0)]) # test that lyric is found self.assertEqual(post.parts[0].flatten().notes[0].lyric, 'fromBass') def testExtractionB(self): from music21 import analysis from music21 import corpus s = corpus.parse('bwv66.6') s.parts[0].flatten().notes[4].addLyric('::/o:6/v:1/tb:s/g:Ursatz') s.parts[3].flatten().notes[2].addLyric('::/o:5/v:2/tb:b') s.parts[2].flatten().notes[3].addLyric('::/o:4/v:2/tb:t') s.parts[1].flatten().notes[2].addLyric('::/o:4/v:2/tb:a') sr = analysis.reduction.ScoreReduction() extract = s.measures(0, 10) # extract.show() sr.score = extract # sr.score = s post = sr.reduce() # post.show() self.assertEqual(len(post.parts), 5) match = post.parts[0].flatten().notes self.assertEqual(len(match), 3) # post.show() # def testExtractionC(self): # from music21 import analysis # from music21 import corpus # # http://solomonsmusic.net/schenker.htm # # shows extracting an Ursatz line # # # BACH pre;ide !, WTC # # src = corpus.parse('bwv846') # import warnings # with warnings.catch_warnings(): # catch deprecation warning # warnings.simplefilter('ignore', category=exceptions21.Music21DeprecationWarning) # chords = src.flatten().makeChords(minimumWindowSize=4, # make chords is gone # makeRests=False) # for c in chords.flatten().notes: # c.quarterLength = 4 # for m in chords.getElementsByClass(stream.Measure): # m.clef = clef.bestClef(m, recurse=True) # # chords.measure(1).notes[0].addLyric('::/p:e/o:5/nf:no/ta:3/g:Ursatz') # chords.measure(1).notes[0].addLyric('::/p:c/o:4/nf:no/tb:I') # # chords.measure(24).notes[0].addLyric('::/p:d/o:5/nf:no/ta:2') # chords.measure(24).notes[0].addLyric('::/p:g/o:3/nf:no/tb:V') # # chords.measure(30).notes[0].addLyric('::/p:f/o:4/tb:7') # # chords.measure(34).notes[0].addLyric('::/p:c/o:5/nf:no/v:1/ta:1') # chords.measure(34).notes[0].addLyric('::/p:g/o:4/nf:no/v:2') # chords.measure(34).notes[0].addLyric('::/p:c/o:4/nf:no/v:1/tb:I') # # sr = analysis.reduction.ScoreReduction() # sr.chordReduction = chords # # sr.score = src # unused_post = sr.reduce() # # unused_post.show() def testExtractionD(self): # this shows a score, extracting a single pitch from music21 import analysis from music21 import corpus src = corpus.parse('schoenberg/opus19', 6) for n in src.flatten().notes: if isinstance(n, note.Note): if n.pitch.name == 'F#': n.addLyric('::/p:f#/o:4') # if n.pitch.name == 'C': # n.addLyric('::/p:c/o:4/g:C') elif isinstance(n, chord.Chord): if 'F#' in [p.name for p in n.pitches]: n.addLyric('::/p:f#/o:4') # if 'C' in [p.name for p in n.pitches]: # n.addLyric('::/p:c/o:4/g:C') sr = analysis.reduction.ScoreReduction() sr.score = src unused_post = sr.reduce() # post.show() def testExtractionD2(self): # this shows a score, extracting a single pitch from music21 import analysis from music21 import corpus src = corpus.parse('schoenberg/opus19', 6) for n in src.flatten().notes: if isinstance(n, note.Note): if n.pitch.name == 'F#': n.addLyric('::/p:f#/o:4/g:F#') if n.pitch.name == 'C': n.addLyric('::/p:c/o:4/g:C') elif isinstance(n, chord.Chord): if 'F#' in [p.name for p in n.pitches]: n.addLyric('::/p:f#/o:4/g:F#') if 'C' in [p.name for p in n.pitches]: n.addLyric('::/p:c/o:4/g:C') sr = analysis.reduction.ScoreReduction() sr.score = src unused_post = sr.reduce() # post.show() def testExtractionE(self): from music21 import analysis from music21 import corpus src = corpus.parse('corelli/opus3no1/1grave') # chords = src.chordify() sr = analysis.reduction.ScoreReduction() # sr.chordReduction = chords sr.score = src unused_post = sr.reduce() # post.show() def testPartReductionA(self): from music21 import analysis from music21 import corpus s = corpus.parse('bwv66.6') partGroups = [ { 'name': 'High Voices', 'color': '#ff0088', 'match': ['soprano', 'alto'] }, { 'name': 'Low Voices', 'color': '#8800ff', 'match': ['tenor', 'bass'] }, ] pr = analysis.reduction.PartReduction(s, partGroups=partGroups) pr.process() for sub in pr._partGroups: self.assertEqual(len(sub['match']), 2) def _matchWeightedData(self, match, target): ''' Utility function to compare known data but not compare floating point weights. ''' for partId, b in enumerate(target): a = match[partId] self.assertEqual(a[0], b[0]) for i, dataMatch in enumerate(a[1]): # second item has data dataTarget = b[1][i] # start self.assertAlmostEqual(dataMatch[0], dataTarget[0]) # span self.assertAlmostEqual(dataMatch[1], dataTarget[1]) # weight self.assertAlmostEqual( dataMatch[2], dataTarget[2], msg=(f'for partId {partId}, entry {i}: ' + f'should be {dataMatch[2]} <-> was {dataTarget[2]}') ) def testPartReductionB(self, show=False): ''' Artificially create test cases. ''' from music21 import analysis from music21 import dynamics from music21 import graph durDynPairsA = [(1, 'mf'), (3, 'f'), (2, 'p'), (4, 'ff'), (2, 'mf')] durDynPairsB = [(1, 'mf'), (3, 'f'), (2, 'p'), (4, 'ff'), (2, 'mf')] s = stream.Score() pCount = 0 for pairs in [durDynPairsA, durDynPairsB]: p = stream.Part() p.id = pCount pos = 0 for ql, dyn in pairs: p.insert(pos, note.Note(quarterLength=ql)) p.insert(pos, dynamics.Dynamic(dyn)) pos += ql # p.makeMeasures(inPlace=True) s.insert(0, p) pCount += 1 if show is True: s.show() pr = analysis.reduction.PartReduction(s, normalize=False) pr.process() match = pr.getGraphHorizontalBarWeightedData() target = [(0, [[0.0, 1.0, 0.07857142857142858, '#666666'], [1.0, 3.0, 0.09999999999999999, '#666666'], [4.0, 2.0, 0.05, '#666666'], [6.0, 4.0, 0.12142857142857143, '#666666'], [10.0, 2.0, 0.07857142857142858, '#666666']]), (1, [[0.0, 1.0, 0.07857142857142858, '#666666'], [1.0, 3.0, 0.09999999999999999, '#666666'], [4.0, 2.0, 0.05, '#666666'], [6.0, 4.0, 0.12142857142857143, '#666666'], [10.0, 2.0, 0.07857142857142858, '#666666']])] self._matchWeightedData(match, target) if show is True: p = graph.plot.Dolan(s, title='Dynamics') p.run() def testPartReductionC(self): ''' Artificially create test cases. ''' from music21 import analysis from music21 import dynamics s = stream.Score() p1 = stream.Part() p1.id = 0 p2 = stream.Part() p2.id = 1 for ql in [1, 2, 1, 4]: p1.append(note.Note(quarterLength=ql)) p2.append(note.Note(quarterLength=ql)) for pos, dyn in [(0, 'p'), (2, 'fff'), (6, 'ppp')]: p1.insert(pos, dynamics.Dynamic(dyn)) for pos, dyn in [(0, 'p'), (1, 'fff'), (2, 'ppp')]: p2.insert(pos, dynamics.Dynamic(dyn)) s.insert(0, p1) s.insert(0, p2) # s.show() pr = analysis.reduction.PartReduction(s, normalize=False) pr.process() match = pr.getGraphHorizontalBarWeightedData() target = [(0, [[0.0, 2.0, 0.05, '#666666'], [2.0, 4.0, 0.1285714285714286, '#666666'], [6.0, 2.0, 0.0214285714286, '#666666']]), (1, [[0.0, 1.0, 0.05, '#666666'], [1.0, 1.0, 0.1285714285714286, '#666666'], [2.0, 6.0, 0.0214285714286, '#666666']])] self._matchWeightedData(match, target) def testPartReductionD(self): ''' Artificially create test cases. Here, uses rests. ''' from music21 import analysis from music21 import dynamics s = stream.Score() p1 = stream.Part() p1.id = 0 p2 = stream.Part() p2.id = 1 for ql in [None, 2, False, 2, False, 2]: if ql: p1.append(note.Note(quarterLength=ql)) p2.append(note.Note(quarterLength=ql)) else: p1.append(note.Rest(quarterLength=2)) p2.append(note.Rest(quarterLength=2)) for pos, dyn in [(0, 'p'), (2, 'fff'), (6, 'ppp')]: p1.insert(pos, dynamics.Dynamic(dyn)) for pos, dyn in [(0, 'mf'), (2, 'f'), (6, 'mf')]: p2.insert(pos, dynamics.Dynamic(dyn)) s.insert(0, p1) s.insert(0, p2) # s.show() pr = analysis.reduction.PartReduction(s) pr.process() match = pr.getGraphHorizontalBarWeightedData() # print(match) target = [(0, [[2.0, 2.0, 1.0, '#666666'], [6.0, 2.0, 1 / 6, '#666666'], [10.0, 2.0, 1 / 6, '#666666']]), (1, [[2.0, 2.0, 7 / 9, '#666666'], [6.0, 2.0, 0.6111111111111112, '#666666'], [10.0, 2.0, 0.6111111111111112, '#666666']])] self._matchWeightedData(match, target) # p = graph.PlotDolan(s, title='Dynamics') # p.process() def testPartReductionE(self): ''' Artificially create test cases. ''' from music21 import analysis from music21 import dynamics s = stream.Score() p1 = stream.Part() p1.id = 0 p2 = stream.Part() p2.id = 1 for ql in [2, 2, False, 2, False, 2]: if ql: p1.append(note.Note(quarterLength=ql)) p2.append(note.Note(quarterLength=ql)) else: p1.append(note.Rest(quarterLength=2)) p2.append(note.Rest(quarterLength=2)) for pos, dyn in [(0, 'p'), (2, 'fff'), (6, 'ppp')]: p1.insert(pos, dynamics.Dynamic(dyn)) for pos, dyn in [(0, 'mf'), (2, 'f'), (6, 'mf')]: p2.insert(pos, dynamics.Dynamic(dyn)) p1.makeMeasures(inPlace=True) p2.makeMeasures(inPlace=True) s.insert(0, p1) s.insert(0, p2) # s.show() pr = analysis.reduction.PartReduction(s, fillByMeasure=True, segmentByTarget=False, normalize=False) pr.process() target = pr.getGraphHorizontalBarWeightedData() match = [(0, [[0.0, 4.0, 0.178571428571, '#666666'], [4.0, 4.0, 0.0214285714286, '#666666'], [8.0, 4.0, 0.0214285714286, '#666666']]), (1, [[0.0, 4.0, 0.178571428571, '#666666'], [4.0, 4.0, 0.07857142857142858, '#666666'], [8.0, 4.0, 0.07857142857142858, '#666666']])] self._matchWeightedData(match, target) pr = analysis.reduction.PartReduction(s, fillByMeasure=False, segmentByTarget=True, normalize=False) pr.process() target = pr.getGraphHorizontalBarWeightedData() match = [(0, [[0.0, 2.0, 0.05, '#666666'], [2.0, 2.0, 0.1285714285714286, '#666666'], [6.0, 2.0, 0.0214285714286, '#666666'], [10.0, 2.0, 0.0214285714286, '#666666']]), (1, [[0.0, 2.0, 0.07857142857142858, '#666666'], [2.0, 2.0, 0.1, '#666666'], [6.0, 2.0, 0.07857142857142858, '#666666'], [10.0, 2.0, 0.07857142857142858, '#666666']])] # from pprint import pprint as print # print(target) self._matchWeightedData(match, target) pr = analysis.reduction.PartReduction(s, fillByMeasure=False, segmentByTarget=False) pr.process() target = pr.getGraphHorizontalBarWeightedData() # print(target) match = [(0, [[0.0, 4.0, 1.0, '#666666'], [6.0, 2.0, 0.12, '#666666'], [10.0, 2.0, 0.12, '#666666']]), (1, [[0.0, 4.0, 1.0, '#666666'], [6.0, 2.0, 0.44, '#666666'], [10.0, 2.0, 0.44, '#666666']])] self._matchWeightedData(match, target) pr = analysis.reduction.PartReduction(s, fillByMeasure=True, segmentByTarget=True) pr.process() target = pr.getGraphHorizontalBarWeightedData() match = [(0, [[0.0, 2.0, 0.3888888888888, '#666666'], [2.0, 2.0, 1.0, '#666666'], [6.0, 2.0, 0.166666666667, '#666666'], [8.0, 4.0, 0.166666666667, '#666666']]), (1, [[0.0, 2.0, 0.6111111111111112, '#666666'], [2.0, 2.0, 0.7777777777777776, '#666666'], [6.0, 2.0, 0.611111111111111, '#666666'], [8.0, 4.0, 0.611111111111111, '#666666']])] self._matchWeightedData(match, target) # p = graph.PlotDolan(s, title='Dynamics', fillByMeasure=False, # segmentByTarget=True, normalizeByPart=False) # p.process() def xtestPartReductionSchoenberg(self): from music21 import corpus sc = corpus.parse('schoenberg/opus19', 2) pr = PartReduction( sc, fillByMeasure=False, segmentByTarget=True, normalizeByPart=False ) pr.process() unused_target = pr.getGraphHorizontalBarWeightedData() class TestExternal(unittest.TestCase): show = True def testPartReductionB(self): test = Test() test.testPartReductionB(show=self.show) # ------------------------------------------------------------------------------ # define presented order in documentation _DOC_ORDER: DocOrder = [] if __name__ == '__main__': import music21 music21.mainTest(Test) # , runTest='testPartReductionSchoenberg')