def update_music_data(self):
analyzer = Analyzer()
music_list = self.banshee.get_tracks()
# delete previously analyzed songs no longer existing in Banshee
for mp3 in self.music_shelve:
if mp3 not in music_list:
del self.music_shelve[mp3]
self.music_shelve.sync()
song_count = len(music_list)
progress = Progress("Analyzing Songs", song_count)
# calculate and save features of new songs
for mp3 in music_list:
if mp3 not in self.music_shelve:
features = analyzer.compute_features(mp3)
if analyzer.valid_features(features):
self.music_shelve[mp3] = features
self.music_shelve.sync()
progress.display()
# convert music data to array
self.music_data = np.array(self.music_shelve.values())
def train(self, data):
# Some initial logistics
samples, dims = data.shape
# Check shape
assert(dims == self.dims)
# Set parameters
rate_lower = 0.1
rate_upper = 0.5
spread_lower = 0.01
if self.new:
# Large spread for fresh weights
spread_upper = self.edge_length / 3.0
else:
# Small spread for trained weights
spread_upper = spread_lower * 1.05
shuffled = range(samples)
np.random.shuffle(shuffled)
# Create progress object
progress = Progress("Training MusicCube", samples)
for ix in range(samples):
# Pick a random vector
sample = data[shuffled[ix], :]
# Figure out who's the closest weight vector
# and calculate distances between weights and the sample
winner = get_winner(sample, self.nodes, self.dims,
self.weights, self.distances)
# Calculate the new learning rate and new learning spread
self.progress = float(ix) / float(samples)
self.rate = self.scale(rate_upper, rate_lower)
self.spread = self.scale(spread_upper, spread_lower)
# Update those weights
update_weights(sample, winner,
self.nodes, self.dims,
self.rate, self.spread,
self.weights, self.indices)
# Display progress
progress.display()
def update_banshee(self):
self.counter = {}
positions = {}
paths = self.get_paths()
song_count = len(paths)
progress = Progress("Updating Banshee", song_count)
for song in paths:
position = self.get_position(song)
positions[song] = position
# count song positions for plotting
if position not in self.counter:
self.counter[position] = 1
else:
self.counter[position] += 1
progress.display()
# update song positions in Banshee
self.banshee.update_tracks(positions)
