def main(file, bit_depth):
f = wave.open(file, 'rb')
signal = f.readframes(-1)
data = np.fromstring(signal, bit_depth)
rate = f.getframerate()
channels = f.getnchannels()
show = True
if channels == 1:
_len = len(data)
x = np.linspace(0, rate, _len)
# print('Length d:', len(data))
# print('Length x:', len(x))
yf = fft(data)
# print('Length:', len(yf))
yf = np.abs(yf)
half_y = yf[:int(_len / 2)]
half_x = x[:int(_len / 2)]
csvobj = fs.get_csv_writer('data_fft.csv', 'f', 'a')
fft_writer = csvobj.writer
[fft_writer.writerow([f, a]) for f, a in zip(half_x, half_y)]
# plt.semilogx(half_x, half_y)
elif channels == 2:
_len = len(data) / channels
x = np.linspace(0, rate, num=_len)
# left channel
ldata = data[::2]
# right channel
rdata = data[1::2]
half_x = x[:int(_len / 2)]
half_y = ldata[:int(_len / 2)]
# plt.semilogx(x[:int(_len/2)], ldata[:int(_len/2)])
# plt.plot(x[:int(_len/2)], rdata[:int(_len/2)])
else:
show = False
if show:
plt.semilogx(half_x, half_y)
plt.title('FFT plot: %s' % file)
plt.show()
def process_raw(count, raw, params, fname):
data = np.fromstring(raw, bit_depth)
data_length = len(data)
max_freq_range = data_length if data_length > params.framerate else params.framerate
x = np.linspace(0, params.framerate, data_length)
y = np.abs(fft(data))
csvobj = fs.get_csv_writer(
'processed/data_fft_%s_%s.csv' % (fname, pad(count)), 'f', 'a')
writer = csvobj.writer
half = int(data_length / 2)
[writer.writerow([f, a]) for f, a in zip(x[:half], y[:half])]
csvobj.fd.close()
wav_file = 'processed/audio_%s_%s.wav' % (fname, pad(count))
write_wav(wav_file, raw)
def main(bit_depth='Int16'):
files = os.listdir('processed')
s = 'audio_'
for file in files:
base_name, ext = os.path.splitext(file)
actual_file_path = os.path.join('processed', file)
if ext == '.wav':
f = wave.open(actual_file_path, 'rb')
params = f.getparams()
rate = params.framerate
if params.nchannels == 1:
raw = f.readframes(-1)
data = np.fromstring(raw, bit_depth)
x = np.linspace(0, rate, len(data))
y = np.abs(fft(data))
csv_file_name = 'processed/data_fft_%s.csv' % base_name[len(s
):]
o = fs.get_csv_writer(csv_file_name, 'f', 'a')
writer = o.writer
half = int(len(data) / 2)
[writer.writerow((f, a)) for f, a in zip(x[:half], y[:half])]
o.fd.close()
print('Saved: ', csv_file_name)
def write_data_to_csv(file, data): x, y = data o = fs.get_csv_writer(file, 'f', 'a') w = o.writer [ w.writerow(rec) for rec in zip(x, y)] o.fd.close()
def main(file, bit_depth):
f = wave.open(file, 'rb')
signal = f.readframes(-1)
data = np.fromstring(signal, bit_depth)
_len = len(data)
rate = f.getframerate()
channels = f.getnchannels()
compute = True
if channels == 1:
x = np.linspace(0, rate, _len)
yf = fft(data)
yf = np.abs(yf)
half_y = yf[:int(_len / 2)]
half_x = x[:int(_len / 2)]
elif channels == 2:
x = np.linspace(0, rate, _len / channels)
# considering only left data
l_data = data[::2]
assert (len(l_data) == _len / channels)
yf = np.abs(fft(l_data))
assert len(x) == len(yf)
half_x = x[:int(_len / channels / 2)]
half_y = yf[:int(_len / channels / 2)]
else:
compute = False
print('nothing done')
if compute:
csv_obj = fs.get_csv_writer('samples/data_fft.csv', 'f', 'a')
fft_writer = csv_obj.writer
[fft_writer.writerow([f, a]) for f, a in zip(half_x, half_y)]
file_base = path.basename(file)
file_without_ext, ext = path.splitext(file_base)
unique_file_csv = 'samples/data_fft_%s%s' % (file_without_ext, EXT_CSV)
csv_obj.fd.close()
fs.copy('samples/data_fft.csv', unique_file_csv)
print('Saved fft:', unique_file_csv)
max_y = max(half_y)
csv_obj = fs.get_csv_writer('samples/fundamental_frequencies.csv', 'f',
'a', 'na')
writer = csv_obj.writer
fft_set = [(f, a, a / max_y) for f, a, in zip(half_x, half_y)]
result = [(f, a, na) for f, a, na in fft_set if f < 20000 and na > 0.5]
for row in result:
writer.writerow(row)
freq_unique_file = 'samples/fundamental_frequencies_%s%s' % (
file_without_ext, EXT_CSV)
csv_obj.fd.close()
fs.copy('samples/fundamental_frequencies.csv', freq_unique_file)
print('Saved fundamentals:', freq_unique_file)
def write_data_to_csv(file, data, *headers):
o = fs.get_csv_writer(file, *headers)
w = o.writer
[w.writerow(a) for a in data]
o.fd.close()