def flat_prior(p=None):
model = train(annotations.corpus())
for key in model:
model[key] = p
if not p:
model[key] = 1/float(len(model.keys()))
return model
def cross_validate(folds=5):
corpus = annotations.corpus()
n = len(corpus)
results = []
for i in range(folds):
print 'Preparing fold {0} out of {1}'.format(i+1, folds)
trainset = []
testset = []
n_test = int(n/float(folds))
for j in range(n_test):
index = int(random.random() * (n-j))
testset += [corpus[index]]
del corpus[index]
trainset = corpus
print 'Training model'
model = train(trainset)
print 'Done. Model: {0}'.format(model)
print 'Evaluating model.'
cross_ent = 0
for (a, parse) in testset:
logP, N = loglikelihood(parse, model)
cross_ent += -logP
cross_ent /= float(n_test)
print 'Done. Average cross-entropy: {0}'.format(cross_ent)
results.append(cross_ent)
corpus = trainset + testset
result = sum(results)/float(len(results))
print 'All done. Resulting cross-entropy: {0}'.format(result)
def corpusAndParser(n=15): from jazzr.models import pcfg, treeconstraints from jazzr.corpus import annotations corpus = annotations.corpus() allowed = treeconstraints.train(corpus) allowed.append(['tie', 'tie', 'on']) model = pcfg.train(corpus) #model = None return annotations.loadAnnotations(), SimpleParser(n=n, model=model, corpus=True, allowed=allowed, tolerance=0.001, maxdepth=5)
def test2():
from jazzr.corpus import annotations
corpus = annotations.corpus('explicitswing')
for song, parse in corpus:
print 'Name: {0}. Length {1}.'.format(song.name, len(song))
try:
test(parse)
except:
print "Failed"
def run():
corpus = acorpus.corpus()
for (a, p) in corpus:
print a.name
newA = convert(a)
normalname = '-'.join(newA.name.split('-')[:-1])
part = newA.name.split('-')[-1:][0]
newA.metadata['name'] = normalname
newA.name = normalname
acorpus.save_annotation('explicitswing', newA, midifile=acorpus.load_midifile('annotations', normalname), part=part)
def __init__(self, collection='explicitswing', n=15, beam=0.8, std=0.1, expected_logratio=0.0, model=None, allowed=None):
if model == None:
corpus = annotations.corpus(collection=collection)
model = pcfg.train(corpus)
self.allowed = treeconstraints.train(corpus)
else:
self.model = model
self.allowed = allowed
# Standard deviation expressed in proportion of beatlength
self.std = std
self.expected_logratio = expected_logratio
super(StochasticParser, self).__init__(beam=beam, model=model, n=n)
from jazzr.corpus import midi, annotations
corpus = annotations.corpus()
names = []
for annotation, tree in corpus:
name = '-'.join(annotation.name.split('-')[0:2])
if not name in names:
names.append(name)
for name in names:
song, version, track, singletrack = midi.parsename(name)
mf = midi.load(song, version, track, singletrack, collection='original')
print mf.name
for track in sorted(mf.keys()):
print '\t{0}'.format(mf[track].name)