def generate_notes(self, ngrams, initial, count, key):
output = []
current = deque(initial, maxlen=self.learner.NGRAM_LEN)
# Add in the key as a filter for next note
# Find its index first in a list of keys
frequency_list = self.FREQUENCY_LIST * 2
# filter_key gives back a list of indexes, look these up in the keys
key_filter = utils.filter_by_key_major(key)
key_filter = [frequency_list[i] for i in key_filter]
print key_filter
while len(output) < count:
# Check if current is a rare ending only note
if tuple(current) not in ngrams:
self.NOT_FOUND_NOTE += 1
num = random.randint(0, len(ngrams) - 1)
current = deque(ngrams.keys()[num],
maxlen=self.learner.NGRAM_LEN)
if not output:
# This is the initial one, so we add
# the "random" choice into it to start off.
output += filter(lambda x: x in key_filter, current)
else:
self.FOUND_NOTE += 1
next = utils.get_result_from_distribution(
ngrams[tuple(current)], filt=key_filter)
# Account for the key here, unless it is a rest.
if next != "REST":
note = self.FREQUENCY_LIST[
self.FREQUENCY_LIST.index(next) + key]
if note in key_filter:
output.append(note)
else:
self.NOT_IN_KEY += 1
else:
output.append(next)
current.append(next)
return output
def generate_rhythms(self, ngrams, initial, bpm, time):
output = []
current = deque(initial, maxlen=self.learner.NGRAM_LEN)
while sum(output) < (float(time) / 60 * bpm):
# Check if current is a rare ending only rhythm
if tuple(current) not in ngrams:
self.NOT_FOUND_RHYTHM += 1
num = random.randint(0, len(ngrams) - 1)
current = deque(ngrams.keys()[num],
maxlen=self.learner.NGRAM_LEN)
if not output:
# This is the initial one, so we add
# the "random" choice into it to start off.
output += current
else:
self.FOUND_RHYTHM += 1
next = utils.get_result_from_distribution(
ngrams[tuple(current)])
output.append(next)
current.append(next)
return output
