def gpu(data):
data_size = int(np.log2(len(data))) # 2**10 = 1024
last_index = int(2**(data_size - 1))
bands_indexes = [[i, i + 1]
for i in range(last_index)] # maximum index is 2**(10-1)
audio_levels = AudioLevels(data_size, len(bands_indexes))
new_data = [float(i) for i in data]
data = np.array(new_data, dtype=np.float32)
levels, _, _ = audio_levels.compute(data, bands_indexes)
filterInvalidNumbers(levels)
return levels
class FFT(object):
def __init__(self,
chunk_size,
sample_rate,
num_bins,
min_frequency,
max_frequency,
custom_channel_mapping,
custom_channel_frequencies,
input_channels=2):
"""
:param chunk_size: chunk size of audio data
:type chunk_size: int
:param sample_rate: audio file sample rate
:type sample_rate: int
:param num_bins: length of gpio to process
:type num_bins: int
:param input_channels: number of audio input channels to process for (default=2)
:type input_channels: int
:param min_frequency: lowest frequency for which a channel will be activated
:type min_frequency: float
:param max_frequency: max frequency for which a channel will be activated.
:type max_frequency: float
:param custom_channel_mapping: custom map of channels to different frequencies
:type custom_channel_mapping: list | int
:param custom_channel_frequencies: custom list of frequencies that should be
utilized for each channel
:type custom_channel_frequencies: list | int
"""
self.chunk_size = chunk_size
self.sample_rate = sample_rate
self.num_bins = num_bins
self.input_channels = input_channels
self.window = hanning(0)
self.min_frequency = min_frequency
self.max_frequency = max_frequency
self.custom_channel_mapping = custom_channel_mapping
self.custom_channel_frequencies = custom_channel_frequencies
self.frequency_limits = self.calculate_channel_frequency()
self.config = ConfigParser.RawConfigParser(allow_no_value=True)
self.config_filename = ""
self.audio_levels = AudioLevels(math.log(chunk_size / 2, 2), num_bins)
fl = array(self.frequency_limits)
self.piff = ((fl * self.chunk_size) / self.sample_rate).astype(int)
for a in range(len(self.piff)):
if self.piff[a][0] == self.piff[a][1]:
self.piff[a][1] += 1
self.piff = self.piff.tolist()
def calculate_levels(self, data):
"""Calculate frequency response for each channel defined in frequency_limits
:param data: decoder.frames(), audio data for fft calculations
:type data: decoder.frames
:return:
:rtype: numpy.array
"""
# create a numpy array, taking just the left channel if stereo
data_stereo = frombuffer(data, dtype="int16")
if self.input_channels == 2:
# data has 2 bytes per channel
# pull out the even values, just using left channel
data = array(data_stereo[::2])
elif self.input_channels == 1:
data = data_stereo
# if you take an FFT of a chunk of audio, the edges will look like
# super high frequency cutoffs. Applying a window tapers the edges
# of each end of the chunk down to zero.
if len(data) != len(self.window):
self.window = hanning(len(data)).astype(float32)
data = data * self.window
# if all zeros in data then there is no need to do the fft
if all(data == 0.0):
return zeros(self.num_bins, dtype="float32")
# Apply FFT - real data
# Calculate the power spectrum
cache_matrix = array(self.audio_levels.compute(data, self.piff)[0])
cache_matrix[isinf(cache_matrix)] = 0.0
return cache_matrix
def calculate_channel_frequency(self):
"""Calculate frequency values
Calculate frequency values for each channel,
taking into account custom settings.
:return: frequency values for each channel
:rtype: list
"""
# How many channels do we need to calculate the frequency for
if self.custom_channel_mapping != 0 and len(self.custom_channel_mapping) == self.num_bins:
logging.debug("Custom Channel Mapping is being used: %s",
str(self.custom_channel_mapping))
channel_length = max(self.custom_channel_mapping)
else:
logging.debug("Normal Channel Mapping is being used.")
channel_length = self.num_bins
logging.debug("Calculating frequencies for %d channels.", channel_length)
octaves = (log(self.max_frequency / self.min_frequency)) / log(2)
logging.debug("octaves in selected frequency range ... %s", octaves)
octaves_per_channel = octaves / channel_length
frequency_limits = []
frequency_store = []
frequency_limits.append(self.min_frequency)
if self.custom_channel_frequencies != 0 and (
len(self.custom_channel_frequencies) >= channel_length + 1):
logging.debug("Custom channel frequencies are being used")
frequency_limits = self.custom_channel_frequencies
else:
logging.debug("Custom channel frequencies are not being used")
for pin in range(1, self.num_bins + 1):
frequency_limits.append(frequency_limits[-1]
* 10 ** (3 / (10 * (1 / octaves_per_channel))))
for pin in range(0, channel_length):
frequency_store.append((frequency_limits[pin], frequency_limits[pin + 1]))
logging.debug("channel %d is %6.2f to %6.2f ", pin, frequency_limits[pin],
frequency_limits[pin + 1])
# we have the frequencies now lets map them if custom mapping is defined
if self.custom_channel_mapping != 0 and len(self.custom_channel_mapping) == self.num_bins:
frequency_map = []
for pin in range(0, self.num_bins):
mapped_channel = self.custom_channel_mapping[pin] - 1
mapped_frequency_set = frequency_store[mapped_channel]
mapped_frequency_set_low = mapped_frequency_set[0]
mapped_frequency_set_high = mapped_frequency_set[1]
logging.debug("mapped channel: " + str(mapped_channel) + " will hold LOW: "
+ str(mapped_frequency_set_low) + " HIGH: "
+ str(mapped_frequency_set_high))
frequency_map.append(mapped_frequency_set)
return frequency_map
else:
return frequency_store
def compare_config(self, cache_filename):
"""
Compare the current configuration used to generate fft to a saved
copy of the data that was used to generate the fft data for an
existing cache file
:param cache_filename: path and name of cache file
:type cache_filename: str
"""
self.config_filename = cache_filename.replace(".sync", ".cfg")
if not os.path.isfile(self.config_filename):
logging.warn("No cached config data found")
return False
else:
has_config = True
with open(self.config_filename) as f:
self.config.readfp(f)
fft_cache = dict()
fft_current = dict()
try:
fft_cache["chunk_size"] = self.config.getint("fft", "chunk_size")
fft_cache["sample_rate"] = self.config.getint("fft", "sample_rate")
fft_cache["num_bins"] = self.config.getint("fft", "num_bins")
fft_cache["min_frequency"] = self.config.getfloat("fft", "min_frequency")
fft_cache["max_frequency"] = self.config.getfloat("fft", "max_frequency")
temp = [int(channel) for channel in
self.config.get("fft", "custom_channel_mapping").split(',')]
if len(temp) == 1:
fft_cache["custom_channel_mapping"] = temp[0]
else:
fft_cache["custom_channel_mapping"] = temp
temp = [int(channel) for channel in
self.config.get("fft", "custom_channel_frequencies").split(',')]
if len(temp) == 1:
fft_cache["custom_channel_frequencies"] = temp[0]
else:
fft_cache["custom_channel_frequencies"] = temp
fft_cache["input_channels"] = self.config.getint("fft", "input_channels")
except ConfigParser.Error:
has_config = False
fft_current["chunk_size"] = self.chunk_size
fft_current["sample_rate"] = self.sample_rate
fft_current["num_bins"] = self.num_bins
fft_current["min_frequency"] = self.min_frequency
fft_current["max_frequency"] = self.max_frequency
fft_current["custom_channel_mapping"] = self.custom_channel_mapping
fft_current["custom_channel_frequencies"] = self.custom_channel_frequencies
fft_current["input_channels"] = self.input_channels
if fft_cache != fft_current:
has_config = False
logging.warn("Cached config data does not match")
if has_config:
self.audio_levels = None
return has_config
def save_config(self):
"""Save the current configuration used to generate the fft data"""
if self.config.has_section("fft"):
self.config.remove_section("fft")
self.config.add_section("fft")
self.config.set('fft', '# DO NOT EDIT THIS SECTION')
self.config.set('fft', '# EDITING THIS SECTION WILL CAUSE YOUR SYNC FILE TO BE INVALID')
self.config.set('fft', 'chunk_size', str(self.chunk_size))
self.config.set('fft', 'sample_rate', str(self.sample_rate))
self.config.set('fft', 'num_bins', str(self.num_bins))
self.config.set('fft', 'min_frequency', str(self.min_frequency))
self.config.set('fft', 'max_frequency', str(self.max_frequency))
if isinstance(self.custom_channel_mapping, list):
self.config.set('fft', 'custom_channel_mapping', str(self.custom_channel_mapping)[1:-1])
else:
self.config.set('fft', 'custom_channel_mapping', str(self.custom_channel_mapping))
if isinstance(self.custom_channel_frequencies, list):
self.config.set('fft', 'custom_channel_frequencies',
str(self.custom_channel_frequencies)[1:-1])
else:
self.config.set('fft', 'custom_channel_frequencies',
str(self.custom_channel_frequencies))
self.config.set('fft', 'input_channels', str(self.input_channels))
with open(self.config_filename, "w") as f:
self.config.write(f)
class FFT(object):
def __init__(self,
chunk_size,
sample_rate,
num_bins,
min_frequency,
max_frequency,
custom_channel_mapping,
custom_channel_frequencies,
input_channels=2):
"""
:param chunk_size: chunk size of audio data
:type chunk_size: int
:param sample_rate: audio file sample rate
:type sample_rate: int
:param num_bins: length of gpio to process
:type num_bins: int
:param input_channels: number of audio input channels to process for (default=2)
:type input_channels: int
:param min_frequency: lowest frequency for which a channel will be activated
:type min_frequency: float
:param max_frequency: max frequency for which a channel will be activated.
:type max_frequency: float
:param custom_channel_mapping: custom map of channels to different frequencies
:type custom_channel_mapping: list | int
:param custom_channel_frequencies: custom list of frequencies that should be
utilized for each channel
:type custom_channel_frequencies: list | int
"""
self.chunk_size = chunk_size
self.sample_rate = sample_rate
self.num_bins = num_bins
self.input_channels = input_channels
self.window = hanning(0)
self.min_frequency = min_frequency
self.max_frequency = max_frequency
self.custom_channel_mapping = custom_channel_mapping
self.custom_channel_frequencies = custom_channel_frequencies
self.frequency_limits = self.calculate_channel_frequency()
self.config = ConfigParser.RawConfigParser(allow_no_value=True)
self.config_filename = ""
self.audio_levels = AudioLevels(math.log(chunk_size / 2, 2), num_bins)
fl = array(self.frequency_limits)
self.piff = ((fl * self.chunk_size) / self.sample_rate).astype(int)
for a in range(len(self.piff)):
if self.piff[a][0] == self.piff[a][1]:
self.piff[a][1] += 1
self.piff = self.piff.tolist()
def calculate_levels(self, data):
"""Calculate frequency response for each channel defined in frequency_limits
:param data: decoder.frames(), audio data for fft calculations
:type data: decoder.frames
:return:
:rtype: numpy.array
"""
# create a numpy array, taking just the left channel if stereo
data_stereo = frombuffer(data, dtype="int16")
if self.input_channels == 2:
# data has 2 bytes per channel
# pull out the even values, just using left channel
data = array(data_stereo[::2])
elif self.input_channels == 1:
data = data_stereo
# if you take an FFT of a chunk of audio, the edges will look like
# super high frequency cutoffs. Applying a window tapers the edges
# of each end of the chunk down to zero.
if len(data) != len(self.window):
self.window = hanning(len(data)).astype(float32)
data = data * self.window
# if all zeros in data then there is no need to do the fft
if all(data == 0.0):
return zeros(self.num_bins, dtype="float32")
# Apply FFT - real data
# Calculate the power spectrum
cache_matrix = array(self.audio_levels.compute(data, self.piff)[0])
cache_matrix[isinf(cache_matrix)] = 0.0
return cache_matrix
def calculate_channel_frequency(self):
"""Calculate frequency values
Calculate frequency values for each channel,
taking into account custom settings.
:return: frequency values for each channel
:rtype: list
"""
# How many channels do we need to calculate the frequency for
if self.custom_channel_mapping != 0 and len(
self.custom_channel_mapping) == self.num_bins:
logging.debug("Custom Channel Mapping is being used: %s",
str(self.custom_channel_mapping))
channel_length = max(self.custom_channel_mapping)
else:
logging.debug("Normal Channel Mapping is being used.")
channel_length = self.num_bins
logging.debug("Calculating frequencies for %d channels.",
channel_length)
octaves = (log(self.max_frequency / self.min_frequency)) / log(2)
logging.debug("octaves in selected frequency range ... %s", octaves)
octaves_per_channel = octaves / channel_length
frequency_limits = []
frequency_store = []
frequency_limits.append(self.min_frequency)
if self.custom_channel_frequencies != 0 and (len(
self.custom_channel_frequencies) >= channel_length + 1):
logging.debug("Custom channel frequencies are being used")
frequency_limits = self.custom_channel_frequencies
else:
logging.debug("Custom channel frequencies are not being used")
for pin in range(1, self.num_bins + 1):
frequency_limits.append(frequency_limits[-1] *
10**(3 / (10 *
(1 / octaves_per_channel))))
for pin in range(0, channel_length):
frequency_store.append(
(frequency_limits[pin], frequency_limits[pin + 1]))
logging.debug("channel %d is %6.2f to %6.2f ", pin,
frequency_limits[pin], frequency_limits[pin + 1])
# we have the frequencies now lets map them if custom mapping is defined
if self.custom_channel_mapping != 0 and len(
self.custom_channel_mapping) == self.num_bins:
frequency_map = []
for pin in range(0, self.num_bins):
mapped_channel = self.custom_channel_mapping[pin] - 1
mapped_frequency_set = frequency_store[mapped_channel]
mapped_frequency_set_low = mapped_frequency_set[0]
mapped_frequency_set_high = mapped_frequency_set[1]
logging.debug("mapped channel: " + str(mapped_channel) +
" will hold LOW: " +
str(mapped_frequency_set_low) + " HIGH: " +
str(mapped_frequency_set_high))
frequency_map.append(mapped_frequency_set)
return frequency_map
else:
return frequency_store
def compare_config(self, cache_filename):
"""
Compare the current configuration used to generate fft to a saved
copy of the data that was used to generate the fft data for an
existing cache file
:param cache_filename: path and name of cache file
:type cache_filename: str
"""
self.config_filename = cache_filename.replace(".sync", ".cfg")
if not os.path.isfile(self.config_filename):
logging.warn("No cached config data found")
return False
else:
has_config = True
with open(self.config_filename) as f:
self.config.readfp(f)
fft_cache = dict()
fft_current = dict()
try:
fft_cache["chunk_size"] = self.config.getint("fft", "chunk_size")
fft_cache["sample_rate"] = self.config.getint("fft", "sample_rate")
fft_cache["num_bins"] = self.config.getint("fft", "num_bins")
fft_cache["min_frequency"] = self.config.getfloat(
"fft", "min_frequency")
fft_cache["max_frequency"] = self.config.getfloat(
"fft", "max_frequency")
temp = [
int(channel) for channel in self.config.get(
"fft", "custom_channel_mapping").split(',')
]
if len(temp) == 1:
fft_cache["custom_channel_mapping"] = temp[0]
else:
fft_cache["custom_channel_mapping"] = temp
temp = [
int(channel) for channel in self.config.get(
"fft", "custom_channel_frequencies").split(',')
]
if len(temp) == 1:
fft_cache["custom_channel_frequencies"] = temp[0]
else:
fft_cache["custom_channel_frequencies"] = temp
fft_cache["input_channels"] = self.config.getint(
"fft", "input_channels")
except ConfigParser.Error:
has_config = False
fft_current["chunk_size"] = self.chunk_size
fft_current["sample_rate"] = self.sample_rate
fft_current["num_bins"] = self.num_bins
fft_current["min_frequency"] = self.min_frequency
fft_current["max_frequency"] = self.max_frequency
fft_current["custom_channel_mapping"] = self.custom_channel_mapping
fft_current[
"custom_channel_frequencies"] = self.custom_channel_frequencies
fft_current["input_channels"] = self.input_channels
if fft_cache != fft_current:
has_config = False
logging.warn("Cached config data does not match")
if has_config:
self.audio_levels = None
return has_config
def save_config(self):
"""Save the current configuration used to generate the fft data"""
if self.config.has_section("fft"):
self.config.remove_section("fft")
self.config.add_section("fft")
self.config.set('fft', '# DO NOT EDIT THIS SECTION')
self.config.set(
'fft',
'# EDITING THIS SECTION WILL CAUSE YOUR SYNC FILE TO BE INVALID')
self.config.set('fft', 'chunk_size', str(self.chunk_size))
self.config.set('fft', 'sample_rate', str(self.sample_rate))
self.config.set('fft', 'num_bins', str(self.num_bins))
self.config.set('fft', 'min_frequency', str(self.min_frequency))
self.config.set('fft', 'max_frequency', str(self.max_frequency))
if isinstance(self.custom_channel_mapping, list):
self.config.set('fft', 'custom_channel_mapping',
str(self.custom_channel_mapping)[1:-1])
else:
self.config.set('fft', 'custom_channel_mapping',
str(self.custom_channel_mapping))
if isinstance(self.custom_channel_frequencies, list):
self.config.set('fft', 'custom_channel_frequencies',
str(self.custom_channel_frequencies)[1:-1])
else:
self.config.set('fft', 'custom_channel_frequencies',
str(self.custom_channel_frequencies))
self.config.set('fft', 'input_channels', str(self.input_channels))
with open(self.config_filename, "w") as f:
self.config.write(f)
class FFT(object):
def __init__(self,
chunk_size,
sample_rate,
num_bins,
min_frequency,
max_frequency,
custom_channel_mapping,
custom_channel_frequencies,
input_channels=2):
"""
:param chunk_size: chunk size of audio data
:type chunk_size: int
:param sample_rate: audio file sample rate
:type sample_rate: int
:param num_bins: length of gpio to process
:type num_bins: int
:param input_channels: number of audio input channels to process for (default=2)
:type input_channels: int
:param min_frequency: lowest frequency for which a channel will be activated
:type min_frequency: float
:param max_frequency: max frequency for which a channel will be activated.
:type max_frequency: float
:param custom_channel_mapping: custom map of channels to different frequencies
:type custom_channel_mapping: list | int
:param custom_channel_frequencies: custom list of frequencies that should be
utilized for each channel
:type custom_channel_frequencies: list | int
"""
self.chunk_size = chunk_size
self.sample_rate = sample_rate
self.num_bins = num_bins
self.input_channels = input_channels
self.window = hanning(0)
self.min_frequency = min_frequency
self.max_frequency = max_frequency
self.custom_channel_mapping = custom_channel_mapping
self.custom_channel_frequencies = custom_channel_frequencies
self.frequency_limits = self.calculate_channel_frequency()
self.config_filename = ""
self.audio_levels = AudioLevels(math.log(chunk_size / 2, 2), num_bins)
fl = array(self.frequency_limits)
self.piff = ((fl * self.chunk_size) / self.sample_rate).astype(int)
for a in range(len(self.piff)):
if self.piff[a][0] == self.piff[a][1]:
self.piff[a][1] += 1
self.piff = self.piff.tolist()
def calculate_levels(self, data):
"""Calculate frequency response for each channel defined in frequency_limits
:param data: decoder.frames(), audio data for fft calculations
:type data: decoder.frames
:return:
:rtype: numpy.array
"""
# create a numpy array, taking just the left channel if stereo
data_stereo = frombuffer(data, dtype="int16")
if self.input_channels == 2:
# data has 2 bytes per channel
# pull out the even values, just using left channel
data = array(data_stereo[::2])
elif self.input_channels == 1:
data = data_stereo
# if you take an FFT of a chunk of audio, the edges will look like
# super high frequency cutoffs. Applying a window tapers the edges
# of each end of the chunk down to zero.
if len(data) != len(self.window):
self.window = hanning(len(data)).astype(float32)
data = data * self.window
# if all zeros in data then there is no need to do the fft
if all(data == 0.0):
return zeros(self.num_bins, dtype="float32")
# Apply FFT - real data
# Calculate the power spectrum
cache_matrix = array(self.audio_levels.compute(data, self.piff)[0])
cache_matrix[isinf(cache_matrix)] = 0.0
return cache_matrix
def calculate_channel_frequency(self):
"""Calculate frequency values
Calculate frequency values for each channel,
taking into account custom settings.
:return: frequency values for each channel
:rtype: list
"""
# How many channels do we need to calculate the frequency for
if self.custom_channel_mapping != 0 and len(self.custom_channel_mapping) == self.num_bins:
logging.debug("Custom Channel Mapping is being used: %s",
str(self.custom_channel_mapping))
channel_length = max(self.custom_channel_mapping)
else:
logging.debug("Normal Channel Mapping is being used.")
channel_length = self.num_bins
logging.debug("Calculating frequencies for %d channels.", channel_length)
octaves = (log(self.max_frequency / self.min_frequency)) / log(2)
logging.debug("octaves in selected frequency range ... %s", octaves)
octaves_per_channel = octaves / channel_length
frequency_limits = []
frequency_store = []
frequency_limits.append(self.min_frequency)
if self.custom_channel_frequencies != 0 and (
len(self.custom_channel_frequencies) >= channel_length + 1):
logging.debug("Custom channel frequencies are being used")
frequency_limits = self.custom_channel_frequencies
else:
logging.debug("Custom channel frequencies are not being used")
for pin in range(1, self.num_bins + 1):
frequency_limits.append(frequency_limits[-1]
* 10 ** (3 / (10 * (1 / octaves_per_channel))))
for pin in range(0, channel_length):
frequency_store.append((frequency_limits[pin], frequency_limits[pin + 1]))
logging.debug("channel %d is %6.2f to %6.2f ", pin, frequency_limits[pin],
frequency_limits[pin + 1])
# we have the frequencies now lets map them if custom mapping is defined
if self.custom_channel_mapping != 0 and len(self.custom_channel_mapping) == self.num_bins:
frequency_map = []
for pin in range(0, self.num_bins):
mapped_channel = self.custom_channel_mapping[pin] - 1
mapped_frequency_set = frequency_store[mapped_channel]
mapped_frequency_set_low = mapped_frequency_set[0]
mapped_frequency_set_high = mapped_frequency_set[1]
logging.debug("mapped channel: " + str(mapped_channel) + " will hold LOW: "
+ str(mapped_frequency_set_low) + " HIGH: "
+ str(mapped_frequency_set_high))
frequency_map.append(mapped_frequency_set)
return frequency_map
else:
return frequency_store