def get_song_meta(song_filename, chunk_size):
music_file = audio_decoder.open(song_filename)
sample_rate = music_file.getframerate()
num_channels = music_file.getnchannels()
sample_width = music_file.getsampwidth()
frame = music_file.readframes(1)
filename = os.path.basename(song_filename)
dirname = os.path.dirname(song_filename)
config_cache, fft_cache = check_cache_exists(dirname, filename)
# TODO(mdietz): Try to get an id3 tag so we can get album and title
meta = {
"filename": filename,
"path": dirname,
"sample_rate": sample_rate,
"num_channels": num_channels,
"sample_width": sample_width,
"frame_width": sample_width * num_channels,
"config_cache": config_cache,
"fft_cache": fft_cache,
"chunk_size": chunk_size
}
meta.update(fetch_id3_meta(song_filename))
music_file.close()
return meta
def cache_song(song_filename, chunk_size):
music_file = audio_decoder.open(song_filename)
sample_rate = music_file.getframerate()
num_channels = music_file.getnchannels()
logging.info("Sample rate: %s" % sample_rate)
logging.info("Channels: %s" % num_channels)
logging.info("Frame size: %s" % music_file.getsampwidth())
fft_calc = fft.FFT(chunk_size, sample_rate, hc.GPIOLEN, _MIN_FREQUENCY,
_MAX_FREQUENCY, _CUSTOM_CHANNEL_MAPPING,
_CUSTOM_CHANNEL_FREQUENCIES)
# Init cache matrix
cache_matrix = np.empty(shape=[0, hc.GPIOLEN])
cache_filename = os.path.dirname(song_filename) + "/." + os.path.basename(
song_filename) + ".sync"
cache_found = fft_calc.compare_config(cache_filename)
if cache_found:
mean, std, cache_matrix = load_cached_fft(fft_calc, cache_filename)
else:
# The values 12 and 1.5 are good estimates for first time playing back
# (i.e. before we have the actual mean and standard deviations
# calculated for each channel).
mean = [12.0] * hc.GPIOLEN
std = [1.5] * hc.GPIOLEN
total = 0
while True:
data = music_file.readframes(chunk_size)
if not data:
break
total += len(data)
matrix = fft_calc.calculate_levels(data)
# Add the matrix to the end of the cache
cache_matrix = np.vstack([cache_matrix, matrix])
for i in range(0, hc.GPIOLEN):
std[i] = np.std([item for item in cache_matrix[:, i] if item > 0])
mean[i] = np.mean(
[item for item in cache_matrix[:, i] if item > 0])
# Add mean and std to the top of the cache
cache_matrix = np.vstack([mean, cache_matrix])
cache_matrix = np.vstack([std, cache_matrix])
# Save the cache using numpy savetxt
np.savetxt(cache_filename, cache_matrix)
# Save fft config
fft_calc.save_config()
logging.info("Cached sync data written to '." + cache_filename +
"' [" + str(len(cache_matrix)) + " rows]")
logging.info("Cached config data written to '." +
fft_calc.config_filename)
music_file.close()
return mean, std, cache_matrix
def __init__(self, song_filename, chunk_size):
music_file = audio_decoder.open(song_filename)
self._chunk_size = chunk_size
# TODO(mdietz): We can get this from the cache, too
self.sample_rate = music_file.getframerate()
self.num_channels = music_file.getnchannels()
self.sample_width = music_file.getsampwidth()
# Just a vanity metric
chunk_period = float(self._chunk_size) / float(self.sample_rate)
logging.info("Playing: %s" % song_filename)
logging.info("Sample Rate: %d" % self.sample_rate)
logging.info("Number of Channels: %d" % self.num_channels)
logging.info("Chunk size: %d" % self._chunk_size)
logging.info("Chunk period: %f" % chunk_period)
self._stream = music_file
def __init__(self, song_filename, chunk_size):
music_file = audio_decoder.open(song_filename)
self._chunk_size = chunk_size
# TODO(mdietz): We can get this from the cache, too
self.sample_rate = music_file.getframerate()
self.num_channels = music_file.getnchannels()
self.sample_width = music_file.getsampwidth()
# Just a vanity metric
chunk_period = float(self._chunk_size) / float(self.sample_rate)
logging.info("Playing: %s" % song_filename)
logging.info("Sample Rate: %d" % self.sample_rate)
logging.info("Number of Channels: %d" % self.num_channels)
logging.info("Chunk size: %d" % self._chunk_size)
logging.info("Chunk period: %f" % chunk_period)
self._stream = music_file
def cache_song(song_filename, chunk_size):
music_file = audio_decoder.open(song_filename)
sample_rate = music_file.getframerate()
num_channels = music_file.getnchannels()
logging.info("Sample rate: %s" % sample_rate)
logging.info("Channels: %s" % num_channels)
logging.info("Frame size: %s" % music_file.getsampwidth())
fft_calc = fft.FFT(chunk_size,
sample_rate,
hc.GPIOLEN,
_MIN_FREQUENCY,
_MAX_FREQUENCY,
_CUSTOM_CHANNEL_MAPPING,
_CUSTOM_CHANNEL_FREQUENCIES)
# Init cache matrix
cache_matrix = np.empty(shape=[0, hc.GPIOLEN])
cache_filename = os.path.dirname(song_filename) + "/." + os.path.basename(
song_filename) + ".sync"
cache_found = fft_calc.compare_config(cache_filename)
if cache_found:
mean, std, cache_matrix = load_cached_fft(fft_calc, cache_filename)
else:
# The values 12 and 1.5 are good estimates for first time playing back
# (i.e. before we have the actual mean and standard deviations
# calculated for each channel).
mean = [12.0] * hc.GPIOLEN
std = [1.5] * hc.GPIOLEN
total = 0
while True:
data = music_file.readframes(chunk_size)
if not data:
break
total += len(data)
matrix = fft_calc.calculate_levels(data)
# Add the matrix to the end of the cache
cache_matrix = np.vstack([cache_matrix, matrix])
for i in range(0, hc.GPIOLEN):
std[i] = np.std([item for item in cache_matrix[:, i]
if item > 0])
mean[i] = np.mean([item for item in cache_matrix[:, i]
if item > 0])
# Add mean and std to the top of the cache
cache_matrix = np.vstack([mean, cache_matrix])
cache_matrix = np.vstack([std, cache_matrix])
# Save the cache using numpy savetxt
np.savetxt(cache_filename, cache_matrix)
# Save fft config
fft_calc.save_config()
logging.info("Cached sync data written to '." + cache_filename
+ "' [" + str(len(cache_matrix)) + " rows]")
logging.info("Cached config data written to '." +
fft_calc.config_filename)
music_file.close()
return mean, std, cache_matrix
