def crossVal(args):
fileList = [file for file in glob.glob(os.path.join(args.directory, '*.xml'))]
if args.folds != None:
numFolds = int(args.folds)
numFiles = len(fileList)
foldIndices = generateFoldIndices(numFolds,numFiles - 1)
for i in foldIndices[0]:
for f in foldIndices[1:-1]:
for j in f:
if i == j:
return
resultsFile = 'Results_' +args.type + '.txt'
results = open(resultsFile, 'w')
for testFold in range(numFolds):
trainingSet = []
for index, fold in enumerate(foldIndices):
if index != testFold:
for i in fold:
trainingSet.append(fileList[i])
testSet = [fileList[j] for j in foldIndices[testFold]]
solutionTreeDict, allProductions = music_grammar.getAllProductions(args.directory, args.type, trainingSet, args.type, args.verbose)
foldFile = 'fold' + str(testFold) + '_' + args.type + '_trainingProductions.txt'
f = open(foldFile, 'w')
for prod in allProductions:
f.write(prod + '\n')
foldTestFile = 'fold' + str(testFold) + '_' + args.type + '_testSetFilenames.txt'
f2 = open(foldTestFile, 'w')
for filename in testSet:
f2.write(filename + '\n')
S = Nonterminal('S')
smallTrees = music_grammar.collectProductions(allProductions, args.verbose)
trainedGrammar = induce_pcfg(S, smallTrees)
print(trainedGrammar)
print('length of the trainingset is: ' + str(len(trainingSet)))
print('length of the testset is: ' + str(len(testSet)))
print("starting to get solutions for the test set ")
testProductions = []
solutionTreeDictForTestSet, testProductions = music_grammar.getAllProductions(args.directory, args.type, testSet, args.type, args.verbose)
foldTestSolutionsFile = 'fold' + str(testFold) + '_' + args.type + '_testSolutions.txt'
f3 = open(foldTestSolutionsFile, 'w')
#for key, value in solutionTreeDictForTestSet.items():
# f3.write(key + '\n' + str(value) + '\n')
json.dump(solutionTreeDictForTestSet,f3)
print("parsing the test set")
totalCorrect, totalCorrectNonN, totalProductions, totalLeaves, parseTreeStrings = music_grammar.parseAllTestXmls(testSet, trainedGrammar, solutionTreeDictForTestSet, args.verbose, False)#"./MusicXml/Test"
#print the parses
foldParsesFile = 'fold' + str(testFold) + '_' + args.type + '_parsedTestSet.txt'
f4 = open(foldParsesFile, 'w')
#for filename, parse in parseTreeStrings.items():
#f4.write(filename + '\n' + parse + '\n')
json.dump(parseTreeStrings, f4)
percentageCorrect = -1
percentageCorrectNonN = -1
percentageLeaves = -1
if totalProductions > 0:
percentageCorrect = totalCorrect / totalProductions
percentageCorrectNonN = totalCorrectNonN / totalProductions
percentageLeaves = totalLeaves / totalProductions
results.write("Fold number " + str(testFold) + " results:\ntotalCorrect: " + str(totalCorrect) + "\npercentageCorrect: " + str(percentageCorrect) + "\ntotalCorrectNonN: " + str(totalCorrectNonN) + "\npercentageCorrectNonN: " + str(percentageCorrectNonN) + "\ntotalProductions: " + str(totalProductions) + "\ntotalLeaves: " + str(totalLeaves) + "\npercentageLeavess: " + str(percentageLeaves) + "\n")
def main():
parser = argparse.ArgumentParser()
parser.add_argument("directory", help="Directory that contains melody files")
parser.add_argument("solutions", help="Directory that contains the solution files")
parser.add_argument("-g", "--grammar", help="The file that specifies a saved grammar, this grammar will be used instead of training a new one")
parser.add_argument("-f", "--folds", help="number of folds desired")
parser.add_argument("-o", "--outfile", help="The file that the grammar will be saved in")
parser.add_argument("-t", "--type", help="The type of solutions file we're using, either 'PR' or 'TS' for Prolongational Reduction or Time-span Tree, respectively")
parser.add_argument("-v", "--verbose", help="increase output verbosity")
args = parser.parse_args()
print(args)
if args.verbose == None or args.verbose == 'False':
args.verbose = False
elif args.verbose == 'True':
args.verbose = True
#If the grammar is specified, then the "directory" folder will be used as a test set
#If the grammar is not specified, it will use 20% of the files in "directory" as a test set, and the rest as a training set to create the grammar
#If folds are specified, then it will split the files in "directory" into numFolds groups, applying training and testing, and then adding up the percentages overall
allProductions = []
stats = True
if args.grammar != None and args.grammar != '':
if not os.path.isfile(args.grammar):
return
f = open(args.grammar, 'r')
for line in f.readlines():
allProductions.append(line)
S = Nonterminal('S')
smallTrees = music_grammar.collectProductions(allProductions, args.verbose)
trainedGrammar = induce_pcfg(S, smallTrees)
print(trainedGrammar)
np_productions = trainedGrammar.productions(Nonterminal('4'))
dict = {}
for pr in np_productions: dict[pr.rhs()] = pr.prob()
np_probDist = DictionaryProbDist(dict)
#Used this code for generating specific figures:
exampleTree = Tree.fromstring('(S (N (N (5 5)) (N (m4 -4))) (N (6 6)))')
#exampleTree.draw()
exampleTreeToCompare = Tree.fromstring('(S (N (5 5)) (N (N (m4 -4)) (N (6 6))))')
#exampleTreeToCompare.draw()
validate_tree.compareTreesBottomUp(exampleTree, exampleTreeToCompare)
#exampleTreeToCompare.draw()
for i in range(100):
rightHand = np_probDist.generate()
print(rightHand)
print(len(rightHand))
generatedTree = pcfg_generate.generate(trainedGrammar)
print('resulting tree: ')
generatedTreeObj = Tree.fromstring(generatedTree)
print(generatedTreeObj)
print(str(generatedTreeObj.leaves()))
print('\n\n')
embellishedTree = pcfg_generate.expandAllLeaves(trainedGrammar, generatedTreeObj)
print(embellishedTree)
print(str(Tree.fromstring(str(embellishedTree)).leaves()))
fileToTest = "./MusicXml/72_Preludes 1 La fille aux cheveux de lin.xml"
musicXmlTest = converter.parse(fileToTest)
curPitchList = music_grammar.getPitchListFromFile(fileToTest)
intervalList = music_grammar.getIntervalStringsFromPitchList(curPitchList)
with open(music_grammar.musicGrammarFilename, 'r') as f:
musicGrammarString = f.read()
musicGrammar = CFG.fromstring(musicGrammarString)
parser = ChartParser(musicGrammar, trace=2)
#parses = parser.parse(intervalList)
print(intervalList)
print('num intervals is: ' + str(len(intervalList)))
#numTrees = sum(1 for _ in parses)
#print('numTrees is: ' + str(numTrees))
#return
#this is for the musical examples
trainedParser = ViterbiParser(trainedGrammar)
parses = trainedParser.parse_all(intervalList)
bestParse = parses[0]
#bestParse.draw()
treeType = bestParse.convert(ParentedTree)
parse_depth = 0
depth = score_from_tree.get_total_depth_of_tree_obj(bestParse, parse_depth)
print('depth is : ' + str(depth))
print('builtin height is : ' + str(bestParse.height()))
print(bestParse)
bestParse.draw()
#score_from_tree.get_tree_obj_to_negative_depth(bestParse, 2, parse_depth)
#prunedBestParse, removedLeaves, leafIndex= score_from_tree.remove_embellishment_rules_from_tree_below_depth(bestParse, {}, depth - 2, 0, 0)
prunedBestParse, removedLeaves, leafIndex, maxSubtreeDepth = score_from_tree.remove_embellishment_rules_from_tree_negative_depth(bestParse, {}, 3, 0, 0)
print(prunedBestParse)
#for s in parentedBestParse.subtrees(lambda t: t.height() > parse_depth - 3):
#treepos = parentedBestParse.treeposition(s)
#parentedBestParse.remove(treepos)
prunedBestParse.draw()
score_from_tree.get_melody_from_parse_tree(bestParse, removedLeaves, musicXmlTest)
PR_fileToTest = "./MusicXml/PR/PR-39_Andante C dur.xml"
ET = ElementTree()
ET.parse(PR_fileToTest)
root = ET.getroot()
rootName = args.type.lower()
topXml = root.find(rootName)
depth = 0
depth = score_from_tree.get_total_depth_of_tree(topXml, depth, rootName)
print('depth is ' + str(depth))
musicXmlTest.show()
for d in reversed(range(0, depth - 1)):
pitch_refs = score_from_tree.gather_note_refs_of_depth(topXml, [], rootName, d, 0)
pitch_refs.sort(key=music_grammar.pitchRefToNum)
melody_of_depth = score_from_tree.pitch_refs_to_notes(pitch_refs, musicXmlTest)
melody_of_depth.show()
print (pitch_refs)
#examples with 3-child nodes
#, './MusicXml/MSC-166.xml', './MusicXml/MSC-103.xml', './MusicXml/37_Sonate fur Klavier Nr.48 C dur Op.30-1 Mov.1.xml', './MusicXml/MSC-211.xml'
#wrong buti like it , './MusicXml/MSC-238.xml'
#like: ./MusicXml/MSC-141.xml fold 2,
#filesToTest = ['./MusicXml/MSC-238.xml', './MusicXml/39_Andante C dur.xml']#fold 1
#filesToTest = ['./MusicXml/MSC-224.xml', './MusicXml/MSC-141.xml']# fold 2
#filesToTest = ["./MusicXml/03_Bagatelle 'Fur Elise' WoO.59.xml"]#fold 3
#filesToTest = ['./MusicXml/MSC-111.xml'] #['./MusicXml/MSC-108.xml', './MusicXml/01_Waltz in E flat Grande Valse Brillante Op.18.xml', './MusicXml/MSC-231.xml', './MusicXml/37_Sonate fur Klavier Nr.48 C dur Op.30-1 Mov.1.xml', './MusicXml/59_Schwanengesang No.1 Op.72-4 D.957-4 Standchen.xml']#fold4
#filesToTest = ['./MusicXml/MSC-111.xml', './MusicXml/MSC-108.xml', './MusicXml/01_Waltz in E flat Grande Valse Brillante Op.18.xml', './MusicXml/MSC-231.xml', './MusicXml/59_Schwanengesang No.1 Op.72-4 D.957-4 Standchen.xml']
#PR
#filesToTest = ['./MusicXml/80_Symphonie Nr.40 g moll KV.550 1.Satz.xml', './MusicXml/31_Sinfonie Nr.9 d moll Op.125 4.Satz An die Freude.xml']# fold 0 PR
#filesToTest = ['./MusicXml/34_Water Music in D major HWV 349 No.11 Alla Hornpipe.xml', './MusicXml/02_Moments Musicaux.xml']#fold 0 20%
#filesToTest = ['./MusicXml/84_Toccata und Fuge d moll BWV565.xml'] #fold 1
#filesToTest = ['./MusicXml/33_Swan Lake Op.20 No.9 Finale.xml', './MusicXml/40_Alpengluhen Op.193.xml']# fold 3 Pr
#filesToTest = ['./MusicXml/57_Waves of the Danube.xml']#, './MusicXml/60_Ma Vlast Moldau.xml']# fold 3 PR < 20%
filesToTest = ['./MusicXml/02_Moments Musicaux.xml']#fold 4 ts
totalCorrect, totalCorrectNonN, totalProductions, totalLeaves, parseTreeStrings = music_grammar.parseAllTestXmls(filesToTest, trainedGrammar, solutionTreeDictForTestSet, args.verbose, False)
solutionTreeDictForTestSet, testProductions = music_grammar.getAllProductions(args.directory, args.type, filesToTest, args.type, args.verbose)
parseFilename = "fold4_" + args.type + "_parsedTestSet.txt"
parseFile = open(parseFilename, 'r')
parses = json.load(parseFile)
for filename, solutionTree in parseTreeStrings.items():
if "_afterComparison" in filename:
continue
treeSolution = solutionTreeDictForTestSet[filename]
percentageCorrect = -1
print(filename)
treeSolutionObj = Tree.fromstring(treeSolution)
treeSolutionObj.draw()
parseTreeNoProbabilities = removeProbability(str(parseTreeStrings[filename]))
parseTreeObj = Tree.fromstring(parseTreeNoProbabilities)
parseTreeObj.draw()
parseAfterCompNoProbabilities = removeProbability(str(parseTreeStrings[filename+'_afterComparison']))
parseAfterCompObj = Tree.fromstring(parseAfterCompNoProbabilities)
parseAfterCompObj.draw()
percentageCorrectNonN = -1
percentageLeaves = -1
if totalProductions > 0:
percentageCorrect = totalCorrect / totalProductions
percentageCorrectNonN = totalCorrectNonN / totalProductions
percentageLeaves = totalLeaves / totalProductions
print("results:\ntotalCorrect: " + str(totalCorrect) + "\npercentageCorrect: " + str(percentageCorrect) + "\ntotalCorrectNonN: " + str(totalCorrectNonN) + "\npercentageCorrectNonN: " + str(percentageCorrectNonN) + "\ntotalProductions: " + str(totalProductions) + "\ntotalLeaves: " + str(totalLeaves) + "\npercentageLeavess: " + str(percentageLeaves) + "\n")
#finish this case
return
if stats == True:
totalCorrect = 0
totalCorrectNonN = 0
totalProductions = 0
totalLeaves = 0
#./MusicXml/MSC-103.xml, ./MusicXml/24_Orphee aux Enfers Overture.xml, ./MusicXml/MSC-211.xml, ./MusicXml/39_Andante C dur.xml,./MusicXml/01_Waltz in E flat Grande Valse Brillante Op.18.xml
#small ones
#./MusicXml/MSC-224.xml
#pretty good one: ['./MusicXml/57_Waves of the Danube.xml', './MusicXml/MSC-107.xml','./MusicXml/59_Schwanengesang No.1 Op.72-4 D.957-4 Standchen.xml', './MusicXml/MSC-231.xml']
goodOnesTS = ['./MusicXml/57_Waves of the Danube.xml', './MusicXml/MSC-107.xml','./MusicXml/59_Schwanengesang No.1 Op.72-4 D.957-4 Standchen.xml', './MusicXml/MSC-231.xml']
goodOnesPR = ['./MusicXml/02_Moments Musicaux.xml',"./MusicXml/95_12 Variationen uber ein franzosisches Lied 'Ah,vous dirai-je, maman' C dur K.265 K6.300e.xml"]
#music_grammar.getAllProductionsHarmonicGrammar(args.directory, args.type, [goodOnesPR[0]], args.type, "MINOR", args.verbose)
#if stats == True:
# return
num_skip = 0
for fold in range(int(args.folds)):
bestSolutionFiles = []
worstSolutionFile = ""
bestPercentage = .25
worstPercentage = .2
#get parses from file
parseFilename = "fold" + str(fold) + "_" + args.type + "_parsedTestSet.txt"
parseFile = open(parseFilename, 'r')
parses = json.load(parseFile)
#get solutions from file
solutionsFilename = "fold" + str(fold) + "_" + args.type + "_testSolutions.txt"
solutionsFile = open(solutionsFilename, 'r')
solutions = json.load(solutionsFile)
foldLeaves = 0
foldProductions = 0
foldCorrect = 0
foldCorrectNonN = 0
for filename, solutionTree in solutions.items():
if parses[filename] != None and parses[filename] != '':
solutionTreeObj = Tree.fromstring(solutionTree)
parseStr = parses[filename]
probabilisticPart = re.findall('(\(p=[^()]*\))', parseStr)
indexOfProbPart = parseStr.index(probabilisticPart[0])
parseTreeObj = Tree.fromstring(parseStr[:indexOfProbPart])
#here's where we look at example reductions in musical scores
curMusicXml = converter.parse(filename)
if len(curMusicXml.flat.notes) >= 15 and len(curMusicXml.flat.notes) < 20 or filename == './MusicXml/03_Bagatelle \'Fur Elise\' WoO.59.xml':
print(filename)
if filename != './MusicXml/03_Bagatelle \'Fur Elise\' WoO.59.xml':
continue
#if args.type == 'PR':
solutionFilename = args.type + "-" + basename(filename)
solutionFilepath = args.directory + '/' + args.type + '/' + solutionFilename
#else:
# solutionFilename = args.type + "-" + basename(filename)[4:]
# solutionFilepath = args.directory + '/' + args.type + '/' + solutionFilename[:-4] + '_1' + solutionFilename[-4:]
ET = ElementTree()
ET.parse(solutionFilepath)
root = ET.getroot()
rootName = args.type.lower()
topXml = root.find(rootName)
#topXml.show()
if num_skip > 0:
num_skip -= 1
continue
parseTreeObj.draw()
#score_from_tree.print_reductions_for_parse_tree(parseTreeObj, curMusicXml)
depth = 0
depth = score_from_tree.get_total_depth_of_tree(topXml, depth, rootName)
print('depth is ' + str(depth))
curMusicXml.show()
for d in reversed(range(0, depth - 1)):
pitch_refs = score_from_tree.gather_note_refs_of_depth(topXml, [], rootName, d, 0)
pitch_refs.sort(key=music_grammar.pitchRefToNum)
melody_of_depth = score_from_tree.pitch_refs_to_notes(pitch_refs, curMusicXml)
melody_of_depth.show()
print (pitch_refs)
continue
parseTreeObjAfterComparison = copy.deepcopy(parseTreeObj)
numProductions = len(solutionTreeObj.productions())
foldProductions += numProductions
bottomCorrect, bottomCorrectNonN = validate_tree.compareTreesBottomUp(solutionTreeObj, parseTreeObjAfterComparison)
if bottomCorrect / numProductions > worstPercentage:# and bottomCorrect / numProductions < bestPercentage:
bestSolutionFiles.append(filename)
if filename in goodOnesPR and False:
print(filename)
print(parseTreeObj.leaves())
solutionTreeObj.draw()
parseTreeObj.draw()
parseTreeObjAfterComparison.draw()
#bestPercentage = bottomCorrect / numProductions
#if bottomCorrect / numProductions < worstPercentage:
# worstSolutionFile = filename
# worstPercentage = bottomCorrect / numProductions
foldLeaves = len(solutionTreeObj.leaves())
foldCorrect += bottomCorrect
foldCorrectNonN += bottomCorrectNonN
totalProductions += foldProductions
totalLeaves += foldLeaves
totalCorrect += foldCorrect
totalCorrectNonN += foldCorrectNonN
foldPercentageCorrect = -1
foldPercentageCorrectNonN = -1
foldPercentageLeaves = -1
if foldProductions > 0:
foldPercentageCorrect = foldCorrect / foldProductions
foldPercentageCorrectNonN = foldCorrectNonN / foldProductions
foldPercentageLeaves = foldLeaves / foldProductions
print("Fold number " + str(fold) + " results:\nfoldCorrect: " + str(foldCorrect) + "\nfoldPercentageCorrect: " + str(foldPercentageCorrect) + "\nfoldCorrectNonN: " + str(foldCorrectNonN) + "\nfoldPercentageCorrectNonN: " + str(foldPercentageCorrectNonN) + "\nfoldProductions: " + str(foldProductions) + "\nfoldLeaves: " + str(foldLeaves) + "\nfoldPercentageLeaves: " + str(foldPercentageLeaves))
print("Best: " + str(bestSolutionFiles) + ', ' + str(bestPercentage))
print("Worst: " + worstSolutionFile + ', ' + str(worstPercentage)+ "\n")
percentageCorrect = -1
percentageCorrectNonN = -1
percentageLeaves = -1
if totalProductions > 0:
percentageCorrect = totalCorrect / totalProductions
percentageCorrectNonN = totalCorrectNonN / totalProductions
percentageLeaves = totalLeaves / totalProductions
print("results:\ntotalCorrect: " + str(totalCorrect) + "\npercentageCorrect: " + str(percentageCorrect) + "\ntotalCorrectNonN: " + str(totalCorrectNonN) + "\npercentageCorrectNonN: " + str(percentageCorrectNonN) + "\ntotalProductions: " + str(totalProductions) + "\ntotalLeaves: " + str(totalLeaves) + "\npercentageLeavess: " + str(percentageLeaves) + "\n")
#finish this case
return
#cross-validate
crossVal(args)
