def test_harmonic_synthesis_ifft(self):
pd = SMSPeakDetection()
pd.hop_size = hop_size
frames = pd.find_peaks(self.audio)
pt = SMSPartialTracking()
pt.max_partials = max_partials
frames = pt.find_partials(frames)
synth = SMSSynthesis()
synth.hop_size = hop_size
synth.max_partials = max_partials
synth.det_synthesis_type = SMSSynthesis.SMS_DET_IFFT
synth_audio = synth.synth(frames)
assert len(synth_audio) == len(self.audio)
sms_audio, sampling_rate = simpl.read_wav(
libsms_harmonic_synthesis_ifft_path
)
assert len(synth_audio) == len(sms_audio)
for i in range(len(synth_audio)):
assert_almost_equals(synth_audio[i], sms_audio[i], float_precision)
def test_size_next_read(self):
audio, sampling_rate = simpl.read_wav(audio_path)
pd = SMSPeakDetection()
pd.hop_size = hop_size
pd.max_peaks = max_peaks
sizes = self.test_data['size_next_read']
frames = pd.find_peaks(audio[0:num_samples])
for i, frame in enumerate(frames):
assert sizes[i] == frame.size, (sizes[i], frame.size)
def test_residual_synthesis(self):
res = SMSResidual()
res.hop_size = hop_size
simpl_residual = res.synth(self.audio)
sms_residual, sampling_rate = simpl.read_wav(
libsms_residual_synthesis_path
)
assert len(simpl_residual) == len(sms_residual)
for i in range(len(simpl_residual)):
assert_almost_equals(simpl_residual[i], sms_residual[i],
float_precision)
def test_peak_detection(self):
audio, sampling_rate = simpl.read_wav(audio_path)
pd = SMSPeakDetection()
pd.hop_size = hop_size
pd.max_peaks = max_peaks
frames = pd.find_peaks(audio[0:num_samples])
sms_frames = self.test_data['peak_detection']
sms_frames = [f for f in sms_frames if f['status'] != 0]
# assert len(sms_frames) == len(frames)
for frame in frames:
assert len(frame.peaks) <= max_peaks, len(frame.peaks)
max_amp = max([p.amplitude for p in frame.peaks])
assert max_amp
import sys
import numpy as np
import scipy.io.wavfile as wav
import simpl
usage = 'Usage: python {0} '.format(__file__) + \
'<input wav file> <time scale factor> <output wav file>'
if len(sys.argv) != 4:
print usage
sys.exit(1)
audio, sampling_rate = simpl.read_wav(sys.argv[1])
time_scale_factor = float(sys.argv[2])
output_file = sys.argv[3]
pd = simpl.LorisPeakDetection()
peaks = pd.find_peaks(audio)
pt = simpl.SMSPartialTracking()
partials = pt.find_partials(peaks)
synth = simpl.SndObjSynthesis()
audio_out = np.array([])
step_size = 1.0 / time_scale_factor
current_frame = 0
while current_frame < len(partials):
i = int(current_frame)
frame = synth.synth_frame(partials[i])
audio_out = np.hstack((audio_out, frame))
current_frame += step_size
def setup_class(cls):
cls.audio = simpl.read_wav(audio_path)[0]
cls.audio = cls.audio[len(cls.audio) / 2:
(len(cls.audio) / 2) + num_samples]
def setup_class(cls):
cls.audio = simpl.read_wav(audio_path)[0]
cls.test_data = _load_libsms_test_data()
def setup_class(cls):
cls.audio = simpl.read_wav(audio_path)[0]
cls.audio = cls.audio[0:num_samples]
def setup_class(cls):
cls.audio = simpl.read_wav(audio_path)[0]
import pysms
import sndobj
import simpl
float_precision = 5
frame_size = 512
hop_size = 512
max_peaks = 10
max_partials = 10
num_frames = 30
num_samples = num_frames * hop_size
audio_path = os.path.join(
os.path.dirname(__file__), 'audio/flute.wav'
)
audio, sampling_rate = simpl.read_wav(audio_path)
def _pysms_analysis_params(sampling_rate):
analysis_params = pysms.SMS_AnalParams()
pysms.sms_initAnalParams(analysis_params)
analysis_params.iSamplingRate = sampling_rate
analysis_params.iFrameRate = sampling_rate / hop_size
analysis_params.iWindowType = pysms.SMS_WIN_HAMMING
analysis_params.fHighestFreq = 20000
analysis_params.iFormat = pysms.SMS_FORMAT_IHP
analysis_params.nTracks = max_peaks
analysis_params.peakParams.iMaxPeaks = max_peaks
analysis_params.nGuides = max_peaks
analysis_params.iMaxDelayFrames = 4
analysis_params.analDelay = 0
import sys
import simpl
import matplotlib.pyplot as plt
usage = 'Usage: python {0} <wav file>'.format(__file__)
if len(sys.argv) != 2:
print usage
sys.exit(1)
audio = simpl.read_wav(sys.argv[1])[0]
# take just a few frames
audio = audio[len(audio) / 2:(len(audio) / 2) + 4096]
# peak detection using the SndObj library
pd = simpl.SndObjPeakDetection()
pd.max_peaks = 20
frames = pd.find_peaks(audio)
# plot peaks using matplotlib
simpl.plot.plot_peaks(frames)
plt.show()
