def calc_NMF(self):
if (
self.spectrogram == []
or self.length != int(self.length_t.text())
or self.offset != int(self.offset_t.text())
or self.wsize != int(self.stftw_t.text())
or self.step != int(self.stfts_t.text())
):
self.length = int(self.length_t.text())
self.offset = int(self.offset_t.text())
self.wsize = int(self.stftw_t.text())
self.step = int(self.stfts_t.text())
global stft_wsize
stft_wsize = self.wsize
# global stft_step = self.step
self.spectrogram = stft(SD.data[self.offset : self.length + 1], self.wsize, self.step)
global Ymean
Ymean = np.mean(np.abs(self.spectrogram))
self.K = int(self.K_t.text())
self.envs = int(self.envs_t.text())
self.iter = int(self.iter_t.text())
self.mfw = MusicFactorWindow(self.K)
Y = np.abs(self.spectrogram)
phase = np.angle(self.spectrogram)
# H, U = music_factorize.nmf_euc(Y, self.K, self.iter)
H, U, fai, F = music_factorize.comp_nmf(Y, self.K, self.iter)
# H,U,G,O = music_factorize.m_fact_euc(Y, self.K, self.envs, self.iter, H, U)
self.mfw.disp_musicfactor(H, U, phase, fai, F)
self.mfw.show()
self.mfw.reconst_music()
def make_spectrogram(self):
if (SD.orig_spectrogram == [] or SD.length != int(self.length_t.text()) or SD.offset != int(self.offset_t.text()) or SD.stft_wsize != int(self.stftw_t.text()) or SD.stft_step != int(self.stfts_t.text())):
SD.length = int(self.length_t.text())
SD.offset = int(self.offset_t.text())
SD.stft_wsize = int(self.stftw_t.text())
SD.stft_step = int(self.stfts_t.text())
SD.orig_spectrogram = stft(SD.orig_data[SD.offset:SD.length + 1], SD.stft_wsize, SD.stft_step)
SD.Ymean = np.mean(np.abs(SD.orig_spectrogram))
def make_spectrogram(self):
wsize
# global stft_step = self.step
Org_spectrogram = stft(SD.data[self.offset:self.length + 1], self.wsize, self.step)
global Ymean
Ymean = np.mean(np.abs(self.spectrogram))
self.spw.disp_spectrogram(self.spectrogram)
self.spw.show()
def lsee_mstftm(self, X):
V = X * self.phase
eps = np.finfo(float).eps
for i in range(10):
v_aud = istft(V * np.exp((0 + 1j)), stft_wsize, stft_step)
V = stft(v_aud, stft_wsize, stft_step)
while V.shape[1] < X.shape[1]:
V = np.c_[V, [eps for i in range(V.shape[0])]]
while X.shape[1] < V.shape[1]:
X = np.c_[V, [eps for i in range(X.shape[0])]]
V = X * V / np.abs(V)
return V
def make_spectrogram(self):
if (
self.spectrogram == []
or self.length != int(self.length_t.text())
or self.offset != int(self.offset_t.text())
or self.wsize != int(self.stftw_t.text())
or self.step != int(self.stfts_t.text())
):
self.length = int(self.length_t.text())
self.offset = int(self.offset_t.text())
self.wsize = int(self.stftw_t.text())
self.step = int(self.stfts_t.text())
global stft_wsize
stft_wsize = self.wsize
# global stft_step = self.step
self.spectrogram = stft(SD.data[self.offset : self.length + 1], self.wsize, self.step)
global Ymean
Ymean = np.mean(np.abs(self.spectrogram))
self.spw.disp_spectrogram(self.spectrogram)
self.spw.show()
if (not os.path.exists(filepath)) or (not os.path.isdir(filepath)):
os.mkdir(filepath)
wsize = 2048
step = 1024
input_fname = sys.argv[1]
# input_fname = QtGui.QFileDialog.getOpenFileName(self, 'Open file')
wf = wave.open(input_fname, "rb")
printWaveInfo(wf)
paras = wf.getparams()
buffer = wf.readframes(wf.getnframes())
mdata = np.frombuffer(buffer, dtype="int16")
Org_spectr = stft(mdata, wsize, step)
phase = np.angle(Org_spectr)
print("median1")
Ht = medianfilter(abs(Org_spectr),0,l)
recon1 = istft( Ht * np.exp(0 + 1j) * phase, wsize, step)
save_as_wave(filepath+"/"+fname+"median1.wav",paras,recon1)
print("median2")
Hf = medianfilter(abs(Org_spectr),1,l)
recon2 = istft( Hf * np.exp(0 + 1j) * phase, wsize, step)
save_as_wave(filepath+"/"+fname+"median2.wav",paras,recon2)
print("wener")
