def dwt1(signal,wname):
[lpd,hpd,lpr,hpr]=filter.filtcoef(wname)
len_lpfilt=int(len(lpd))
len_hpfilt=int(len(hpd))
len_avg=int(len_lpfilt/2 + len_hpfilt/2)
len_sig = int( 2 *(np.ceil(len(signal) * 1.0/2.0)))
D=int(2)
signal=misc.per_ext(signal,int(len_avg/2))
cA_undec=np.real(convol.convfft(signal,lpd))
cA_undec=cA_undec[len_avg-1:]
cA_undec=cA_undec[:len(cA_undec)-len_avg+1]
cA_undec=cA_undec[1:len_sig]
cA=sample.downsamp(cA_undec,D)
cD_undec=np.real(convol.convfft(signal,hpd))
cD_undec=cD_undec[len_avg-1:]
cD_undec=cD_undec[:len(cD_undec)-len_avg+1]
cD_undec=cD_undec[1:len_sig]
cD=sample.downsamp(cD_undec,D)
return cA,cD
def dwt1_sym(signal, wname):
[lpd, hpd, lpr, hpr] = filter.filtcoef(wname)
len_lpfilt = int(len(lpd))
len_hpfilt = int(len(hpd))
lf = len_lpfilt
D = int(2)
signal = misc.symm_ext(signal, int(lf - 1))
cA_undec = np.real(convol.convfft(signal, lpd))
cA_undec = cA_undec[lf:]
cA_undec = cA_undec[: len(cA_undec) - lf + 1]
cA = sample.downsamp(cA_undec, D)
cD_undec = np.real(convol.convfft(signal, hpd))
cD_undec = cD_undec[lf:]
cD_undec = cD_undec[: len(cD_undec) - lf + 1]
cD = sample.downsamp(cD_undec, D)
return cA, cD
def dwt1_sym(signal,wname):
[lpd,hpd,lpr,hpr]=filter.filtcoef(wname)
len_lpfilt=int(len(lpd))
len_hpfilt=int(len(hpd))
lf=len_lpfilt
D=int(2)
signal=misc.symm_ext(signal,int(lf - 1))
cA_undec=np.real(convol.convfft(signal,lpd))
cA_undec=cA_undec[lf:]
cA_undec=cA_undec[:len(cA_undec)-lf+1]
cA=sample.downsamp(cA_undec,D)
cD_undec=np.real(convol.convfft(signal,hpd))
cD_undec=cD_undec[lf:]
cD_undec=cD_undec[:len(cD_undec)-lf+1]
cD=sample.downsamp(cD_undec,D)
return cA,cD
def dwt1(signal, wname):
[lpd, hpd, lpr, hpr] = filter.filtcoef(wname)
len_lpfilt = int(len(lpd))
len_hpfilt = int(len(hpd))
len_avg = int(len_lpfilt / 2 + len_hpfilt / 2)
len_sig = int(2 * (np.ceil(len(signal) * 1.0 / 2.0)))
D = int(2)
signal = misc.per_ext(signal, int(len_avg / 2))
cA_undec = np.real(convol.convfft(signal, lpd))
cA_undec = cA_undec[len_avg - 1 :]
cA_undec = cA_undec[: len(cA_undec) - len_avg + 1]
cA_undec = cA_undec[1:len_sig]
cA = sample.downsamp(cA_undec, D)
cD_undec = np.real(convol.convfft(signal, hpd))
cD_undec = cD_undec[len_avg - 1 :]
cD_undec = cD_undec[: len(cD_undec) - len_avg + 1]
cD_undec = cD_undec[1:len_sig]
cD = sample.downsamp(cD_undec, D)
return cA, cD
