def idwt1(cA, cD, wname):
[lpd1, hpd1, lpr1, hpr1] = filter.filtcoef(wname)
len_lpfilt = int(len(lpr1))
len_hpfilt = int(len(hpr1))
len_avg = int(len_lpfilt / 2 + len_hpfilt / 2)
N = 2 * len(cD)
U = 2
cA_up = sample.upsamp(cA, U)
cA_up = misc.per_ext(cA_up, int(len_avg / 2))
X_lp = np.real(convol.convfft(cA_up, lpr1))
cD_up = sample.upsamp(cD, U)
cD_up = misc.per_ext(cD_up, int(len_avg / 2))
X_hp = np.real(convol.convfft(cD_up, hpr1))
X_lp = X_lp[0 : N + len_avg - 1]
X_lp = X_lp[len_avg - 1 :]
X_hp = X_hp[0 : N + len_avg - 1]
X_hp = X_hp[len_avg - 1 :]
X = X_lp + X_hp
return X
def idwt1(cA,cD,wname):
[lpd1,hpd1,lpr1,hpr1]=filter.filtcoef(wname)
len_lpfilt=int(len(lpr1))
len_hpfilt=int(len(hpr1))
len_avg=int(len_lpfilt/2 + len_hpfilt/2)
N= 2 * len(cD)
U=2
cA_up=sample.upsamp(cA,U)
cA_up=misc.per_ext(cA_up,int(len_avg/2))
X_lp=np.real(convol.convfft(cA_up,lpr1))
cD_up=sample.upsamp(cD,U)
cD_up=misc.per_ext(cD_up,int(len_avg/2))
X_hp=np.real(convol.convfft(cD_up,hpr1))
X_lp=X_lp[0:N+len_avg-1]
X_lp=X_lp[len_avg-1:]
X_hp=X_hp[0:N+len_avg-1]
X_hp=X_hp[len_avg-1:]
X=X_lp+X_hp
return X
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 swt(sig, J, nm):
swtop = np.array([])
N = int(len(sig))
length = N
[lpd, hpd, lpr, hpr] = filter.filtcoef(nm)
for iter in range(J):
if iter > 0:
M = int(2 ** iter)
low_pass = sample.upsamp(lpd, M)
high_pass = sample.upsamp(hpd, M)
else:
low_pass = lpd
high_pass = hpd
len_filt = int(len(low_pass))
sig = misc.per_ext(sig, int(len_filt / 2))
cA = np.real(convol.convfft(sig, low_pass))
cD = np.real(convol.convfft(sig, high_pass))
cA = cA[len_filt:]
cA = cA[0:N]
cD = cD[len_filt:]
cD = cD[0:N]
sig = cA
if iter == J - 1:
swtop = np.append(cD, swtop)
swtop = np.append(cA, swtop)
else:
swtop = np.append(cD, swtop)
return swtop, length
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 swt(sig,J,nm):
swtop=np.array([])
N=int(len(sig))
length=N
[lpd,hpd,lpr,hpr]=filter.filtcoef(nm)
for iter in range(J):
if iter > 0:
M=int(2**iter)
low_pass=sample.upsamp(lpd,M)
high_pass=sample.upsamp(hpd,M)
else:
low_pass=lpd
high_pass=hpd
len_filt=int(len(low_pass))
sig=misc.per_ext(sig,int(len_filt/2))
cA=np.real(convol.convfft(sig,low_pass))
cD=np.real(convol.convfft(sig,high_pass))
cA=cA[len_filt:]
cA=cA[0:N]
cD=cD[len_filt:]
cD=cD[0:N]
sig=cA
if iter==J-1:
swtop=np.append(cD,swtop)
swtop=np.append(cA,swtop)
else:
swtop=np.append(cD,swtop)
return swtop,length
def iswt(swtop,J,nm):
N=int(len(swtop)/(J+1))
[lpd,hpd,lpr,hpr]=filter.filtcoef(nm)
low_pass=lpr
high_pass=hpr
lf=int(len(low_pass))
for iter in range(J):
iswt_output=np.zeros(N)
if iter==0:
appx_sig=swtop[0:N]
det_sig=swtop[N:2*N]
else:
det_sig=swtop[(iter+1)*N:(iter+2)*N]
value=int(2**(J-1-iter))
for count in range(value):
appx1=appx_sig[count:N:value]
det1=det_sig[count:N:value]
len1=len(appx1)
appx2=appx1[0:len1:2]
det2=det1[0:len1:2]
U=int(2)
cL0=sample.upsamp(appx2,U)
cH0=sample.upsamp(det2,U)
cL0=misc.per_ext(cL0,int(lf/2))
cH0=misc.per_ext(cH0,int(lf/2))
oup00L=np.real(convol.convfft(cL0,low_pass))
oup00H=np.real(convol.convfft(cH0,high_pass))
oup00L=oup00L[lf-1:]
oup00L=oup00L[0:len1]
oup00H=oup00H[lf-1:]
oup00H=oup00H[0:len1]
oup00=oup00L+oup00H
appx3=appx1[1:len1:2]
det3=det1[1:len1:2]
cL1=sample.upsamp(appx3,U)
cH1=sample.upsamp(det3,U)
cL1=misc.per_ext(cL1,int(lf/2))
cH1=misc.per_ext(cH1,int(lf/2))
oup01L=np.real(convol.convfft(cL1,low_pass))
oup01H=np.real(convol.convfft(cH1,high_pass))
oup01L=oup01L[lf-1:]
oup01L=oup01L[0:len1]
oup01H=oup01H[lf-1:]
oup01H=oup01H[0:len1]
oup01=oup01L+oup01H
oup01=misc.circshift(oup01,-1)
index2=int(0)
for index in xrange(count,N,value):
temp=(oup00[index2]+oup01[index2])*1.0/2.0
iswt_output[index]=temp
index2+=1
appx_sig=iswt_output
return iswt_output
def iswt(swtop, J, nm):
N = int(len(swtop) / (J + 1))
[lpd, hpd, lpr, hpr] = filter.filtcoef(nm)
low_pass = lpr
high_pass = hpr
lf = int(len(low_pass))
for iter in range(J):
iswt_output = np.zeros(N)
if iter == 0:
appx_sig = swtop[0:N]
det_sig = swtop[N : 2 * N]
else:
det_sig = swtop[(iter + 1) * N : (iter + 2) * N]
value = int(2 ** (J - 1 - iter))
for count in range(value):
appx1 = appx_sig[count:N:value]
det1 = det_sig[count:N:value]
len1 = len(appx1)
appx2 = appx1[0:len1:2]
det2 = det1[0:len1:2]
U = int(2)
cL0 = sample.upsamp(appx2, U)
cH0 = sample.upsamp(det2, U)
cL0 = misc.per_ext(cL0, int(lf / 2))
cH0 = misc.per_ext(cH0, int(lf / 2))
oup00L = np.real(convol.convfft(cL0, low_pass))
oup00H = np.real(convol.convfft(cH0, high_pass))
oup00L = oup00L[lf - 1 :]
oup00L = oup00L[0:len1]
oup00H = oup00H[lf - 1 :]
oup00H = oup00H[0:len1]
oup00 = oup00L + oup00H
appx3 = appx1[1:len1:2]
det3 = det1[1:len1:2]
cL1 = sample.upsamp(appx3, U)
cH1 = sample.upsamp(det3, U)
cL1 = misc.per_ext(cL1, int(lf / 2))
cH1 = misc.per_ext(cH1, int(lf / 2))
oup01L = np.real(convol.convfft(cL1, low_pass))
oup01H = np.real(convol.convfft(cH1, high_pass))
oup01L = oup01L[lf - 1 :]
oup01L = oup01L[0:len1]
oup01H = oup01H[lf - 1 :]
oup01H = oup01H[0:len1]
oup01 = oup01L + oup01H
oup01 = misc.circshift(oup01, -1)
index2 = int(0)
for index in xrange(count, N, value):
temp = (oup00[index2] + oup01[index2]) * 1.0 / 2.0
iswt_output[index] = temp
index2 += 1
appx_sig = iswt_output
return iswt_output