def gimme_loop_handler(cls, addr, tags, data, source):
# time in seconds; key between 0 (for C) and 11 (for B)
pd_looper_id, required_tempo, required_key = data[0], data[1], data[2]
# If the track hasn't been registered yet, we do that
pd_looper_infos = cls.pd_loopers.setdefault(pd_looper_id, {
'current_loop_id': None,
'track_ids': [],
'tempo': None,
})
current_loop_id = pd_looper_infos['current_loop_id']
# Picking the new loop in the pool
with cls.pool_lock:
# prefilter available loops (those whose track haven't been picked already)
available_loops = cls.pool.values()
forbidden_tracks = cls.forbidden_tracks(pd_looper_id)
available_loops = filter(lambda l: l['track_id'] not in forbidden_tracks, available_loops)
# Select the most suitable next loop according to the current loop.
if current_loop_id is not None:
def sort_key(l):
timbre_dist = loop_distance(cls.old_loops[current_loop_id], l)
tempo_dist = abs(1 - l['tempo'] / float(required_tempo)) * 40
return timbre_dist + tempo_dist
loop_infos = sorted(available_loops, key=lambda l: sort_key)[0]
else:
loop_infos = available_loops[0]
# Remove the loop from the pool, reserving the loop's track for this looper
cls.pool.pop(loop_infos['loop_id'])
pd_looper_infos['track_ids'].append(loop_infos['track_id'])
pd_looper_infos['current_loop_id'] = loop_infos['loop_id']
# Adding the picked looped to `old_loops`, so that we remember it
# but it cannot be used again.
with cls.old_loops_lock:
cls.old_loops[loop_infos['loop_id']] = loop_infos
if current_loop_id is not None: cls.old_loops.pop(current_loop_id)
# Preparing the loop
logger.info('sending new loop %s to looper %s, left : %s' % (loop_infos['path'], pd_looper_id, len(cls.pool)))
loop = Sound.from_file(loop_infos['path'])
required_length = loop.length * float(required_tempo) / loop_infos['tempo']
beat_length = 60.0 / required_tempo
required_length = round(required_length / beat_length) * beat_length
loop = loop.time_stretch(required_length).fade(in_dur=0.002, out_dur=0.002)
loop.to_file(loop_infos['path'])
# Sending loop, and fill-up the pool if necessary.
send_msg('/new_loop', pd_looper_id, loop_infos['path'], int(round(loop.length * 1000)), loop_infos['loop_id'])
if len(LoopScraper.pool) < LoopScraper.pool_min_size: LoopScraper.wake_up_scrapers()
def scrape(self):
id_counter = 0
track_id, filename, sound_length = get_sound()
# Check if the sound is long enough, and if yes we extract some loops from it.
# TODO: make this less restrictive to waste a bit less
if sound_length > 2 * self.sample_length:
offset = 0
upper_limit = sound_length - 2 * self.sample_length
while (offset + 2 * self.sample_length < upper_limit):
# Calculate a random offset where the loop will start
offset = random.randint(offset, int(min(offset + sound_length * 0.2, upper_limit)))
# Extracting a loop and saving it to 'loop<n>.wav'
sample = Sound.from_file(filename, start=offset, end=offset+self.sample_length)
loops = sample.extract_loops()
for loop in loops:
if id_counter > 10:
offset = upper_limit
break
id_counter += 1
loop_id = '%s_%s' % (track_id, id_counter)
loop_path = self._get_free_path()
logger.info('loop extracted to %s' % loop_path)
loop.to_file(loop_path)
#key, key_confidence, length = loop.echonest.key, loop.echonest.key_confidence, loop.length
with self.pool_lock:
self.pool[loop_id] = dict(loop.loop_infos, **{
'path': loop_path,
'length': loop.length,
'loop_id': loop_id,
'track_id': track_id,
'timbre_start': loop.loop_infos['timbre_start'],
'timbre_end': loop.loop_infos['timbre_end']
#'key': (key, key_confidence)
})
# Increment values for next loop
offset += self.sample_length
# Delete the sounds to save memory
# We also have to collect manually because of a "bug" in pandas:
# https://github.com/pydata/pandas/issues/2659
if 'loop' in locals(): del loop
del sample
gc.collect()
def scrape(self):
track_id, pad_path, pad_length = get_sound()
new_pad_path = self._get_free_path()
pad_id = '%s' % (track_id)
sound = Sound.from_file(pad_path, end=min(30, pad_length))
sound = sound.remove_beats()
sound.to_file(new_pad_path)
logger.info('pad extracted to %s' % new_pad_path)
'''pad.to_file(pad_path)
# Delete the sound to save memory
# We also have to collect manually because of a "bug" in pandas:
# https://github.com/pydata/pandas/issues/2659
del pad
gc.collect()'''
with self.pool_lock:
self.pool[pad_id] = {
'path': new_pad_path,
'pad_id': pad_id
}
