def __init__(self, data, fs, n_fft=512, win_len=512, hop_len=512):
chop_fraction = data.size % win_len
if chop_fraction != 0:
data = data[:-chop_fraction]
self.data = data
self.fs = fs
self.envelope = AudioProcessing.get_envelope(self.data,
frame_size=win_len)
self.envelope[self.envelope < 0] = 0
self.n_fft = n_fft
self.win_len = win_len
self.hop_len = hop_len
self.stft = AudioProcessing.get_stft(self.data, n_fft, win_len,
hop_len)
self.stft = np.absolute(self.stft)
self.smooth_spectrogram()
n_drop = int(np.ceil(500 / (float(self.fs) / self.n_fft)))
self.stft = self.stft[n_drop:, :]
self._remove_spectrogram_noise()
self._calculate_background_noise()
self._get_temporal_entropy()
self._get_segments_above_noise()
self._get_spectral_entropy()
def _get_segments_above_noise(self):
threshold = self.background_noise + 3
envelope = AudioProcessing.get_envelope(abs(self.data),
frame_size=1024)
non_zero = envelope[np.nonzero(envelope)]
data_log = 20 * np.log10(non_zero)
# print(data_log.shape)
# kernel = 1/256.0*np.ones(156)
#
# data_log = np.convolve(data_log,kernel)
# print(data_log.shape)
ind = np.where(data_log > threshold)
check_array = np.zeros(self.envelope.size)
check_array[ind] = 1
diff = np.diff(check_array)
ones = np.where(diff == 1)[0]
minus_ones = np.where(diff == -1)[0]
if ones.size == 0:
ones = np.array([0])
if minus_ones.size == 0:
minus_ones = np.array([check_array.size - 1])
if ones[0] >= minus_ones[0]:
ones = np.append(0, ones)
if ones[-1] >= minus_ones[-1]:
minus_ones = np.append(minus_ones, [check_array.size - 1])
segments = []
# considering segments which are greater than 100 ms
min_seg_length = 0.1 * self.fs
for i in range(ones.size):
seg_duration = (minus_ones[i] - ones[i])
if seg_duration > min_seg_length:
segments.append(
(ones[i], minus_ones[i], minus_ones[i] - ones[i]))
if 0:
# plotting check array
segment_array = np.zeros(self.data.size)
for segment in segments:
segment_array[segment[0]:segment[1]] = 1
import matplotlib.pyplot as plt
plt.plot(self.data)
plt.plot(segment_array)
plt.show()
self.segments = segments