def update_features(self, n_bins = 3):
latest_data_window = self.stream_reader.data_buffer.get_most_recent(self.FFT_window_size)
self.fft = getFFT(latest_data_window, self.rate, self.FFT_window_size, log_scale = self.log_features)
#Equalize pink noise spectrum falloff:
self.fft = self.fft * self.power_normalization_coefficients
self.num_ffts += 1
self.fft_fps = self.num_ffts / (time.time() - self.stream_reader.stream_start_time)
if self.smoothing_length_ms > 0:
self.feature_buffer.append_data(self.fft)
buffered_features = self.feature_buffer.get_most_recent(len(self.smoothing_kernel))
if len(buffered_features) == len(self.smoothing_kernel):
buffered_features = self.smoothing_kernel * buffered_features
self.fft = np.mean(buffered_features, axis=0)
self.strongest_frequency = self.fftx[np.argmax(self.fft)]
#ToDo: replace this for-loop with pure numpy code
for bin_index in range(self.n_frequency_bins):
self.frequency_bin_energies[bin_index] = np.mean(self.fft[self.fftx_indices_per_bin[bin_index]])
#Beat detection ToDo:
#https://www.parallelcube.com/2018/03/30/beat-detection-algorithm/
#https://github.com/shunfu/python-beat-detector
#https://pypi.org/project/vamp/
return
def update_features(self, n_bins=3):
latest_data_window = self.stream_reader.data_buffer.get_most_recent(
self.FFT_window_size)
self.fft = getFFT(latest_data_window,
self.rate,
self.FFT_window_size,
log_scale=self.log_features)
#Equalize pink noise spectrum falloff:
self.fft = self.fft * self.power_normalization_coefficients
self.num_ffts += 1
self.fft_fps = self.num_ffts / (time.time() -
self.stream_reader.stream_start_time)
if self.smoothing_length_ms > 0:
self.feature_buffer.append_data(self.fft)
buffered_features = self.feature_buffer.get_most_recent(
len(self.smoothing_kernel))
if len(buffered_features) == len(self.smoothing_kernel):
buffered_features = self.smoothing_kernel * buffered_features
self.fft = np.mean(buffered_features, axis=0)
self.strongest_frequency = self.fftx[np.argmax(self.fft)]
for bin_index in range(self.n_frequency_bins):
self.frequency_bin_energies[bin_index] = np.mean(
self.fft[self.fftx_indices_per_bin[bin_index]])
return
def stream_readchunk(self):
"""Reads some audio and re-launches itself"""
try:
self.data = numpy.fromstring(self.stream.read(self.chunk),
dtype=numpy.int16)
self.fftx, self.fft = getFFT(self.data, self.rate)
except Exception as E:
print("💩 Something bad happen. Terminating...")
print(E)
self.keepRecording = False
if self.keepRecording:
self.stream_thread_new()
else:
self.stream.close()
# self.pa.terminate()
print("🛑 Stream STOPPED")
self.chunksRead += 1
