def test_bior2(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
ST = pyyawt.dwtmode("status","nodisp")
wnames = ['bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8']
for N in np.arange(len(wnames)):
wname = wnames[N]
[Lo_D,Hi_D,Lo_R,Hi_R] = pyyawt.wfilters(wname)
[c,l] = pyyawt.wavedec(s1,3,wname)
s0 = pyyawt.waverec(c,l,wname)
[cA1,cD1] = pyyawt.dwt(s1,wname)
[cA2,cD2] = pyyawt.dwt(cA1,wname)
[cA3,cD3] = pyyawt.dwt(cA2,wname)
ca2 = pyyawt.idwt(cA3,cD3,wname,np.size(cA2))
ca1 = pyyawt.idwt(ca2,cD2,wname,np.size(cA1))
a0 = pyyawt.idwt(ca1,cD1,wname,np.size(s1))
np.testing.assert_almost_equal(a0, s0)
Lo_D = np.random.randn(np.size(Lo_D))
Hi_D = np.random.randn(np.size(Lo_D))
ca2 = pyyawt.idwt(cA3,cD3,Lo_R,Hi_R,np.size(cA2))
ca1 = pyyawt.idwt(ca2,cD2,Lo_R,Hi_R,np.size(cA1))
a0 = pyyawt.idwt(ca1,cD1,Lo_R,Hi_R,np.size(s1))
s0 = pyyawt.waverec(c,l,Lo_R,Hi_R)
np.testing.assert_almost_equal(a0, s0)
def rsHRF_iterative_wiener_deconv(y, h, Iterations=1000):
N = y.shape[0]
nh = max(h.shape)
h = np.append(h, np.zeros((N - nh, 1)))
H = np.fft.fft(h, axis=0)
Y = np.fft.fft(y, axis=0)
[c, l] = pyyawt.wavedec(abs(y), 1, 'db2')
sigma = pyyawt.wnoisest(c, l, 1)
Phh = np.square(abs(H))
sqrdtempnorm = ((((np.linalg.norm(y - np.mean(y), 2)**2) - (N - 1) *
(sigma**2))) / (np.linalg.norm(h, 1))**2)
Nf = (sigma**2) * N
tempreg = Nf / sqrdtempnorm
Pxx0 = np.square(
abs(np.multiply(Y, (np.divide(np.conj(H), (Phh + N * tempreg))))))
Pxx = Pxx0
for i in range(0, Iterations):
M = np.divide(np.multiply(np.multiply(np.conjugate(H), Pxx), Y),
np.add(np.multiply(np.square(abs(H)), Pxx), Nf))
PxxY = np.divide(np.multiply(Pxx, Nf),
np.add(np.multiply(np.square(abs(H)), Pxx), Nf))
Pxx = np.add(PxxY, np.square(abs(M)))
WienerFilterEst = np.divide(
np.multiply(np.conj(H), Pxx),
np.add(np.multiply(np.square(abs(H)), Pxx), Nf))
return np.real(np.fft.ifft(np.multiply(WienerFilterEst, Y)))
def test_bior2(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
ST = pyyawt.dwtmode("status", "nodisp")
wnames = [
'bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8'
]
for N in np.arange(len(wnames)):
wname = wnames[N]
[Lo_D, Hi_D, Lo_R, Hi_R] = pyyawt.wfilters(wname)
[c, l] = pyyawt.wavedec(s1, 3, wname)
s0 = pyyawt.waverec(c, l, wname)
[cA1, cD1] = pyyawt.dwt(s1, wname)
[cA2, cD2] = pyyawt.dwt(cA1, wname)
[cA3, cD3] = pyyawt.dwt(cA2, wname)
ca2 = pyyawt.idwt(cA3, cD3, wname, np.size(cA2))
ca1 = pyyawt.idwt(ca2, cD2, wname, np.size(cA1))
a0 = pyyawt.idwt(ca1, cD1, wname, np.size(s1))
np.testing.assert_almost_equal(a0, s0)
Lo_D = np.random.randn(np.size(Lo_D))
Hi_D = np.random.randn(np.size(Lo_D))
ca2 = pyyawt.idwt(cA3, cD3, Lo_R, Hi_R, np.size(cA2))
ca1 = pyyawt.idwt(ca2, cD2, Lo_R, Hi_R, np.size(cA1))
a0 = pyyawt.idwt(ca1, cD1, Lo_R, Hi_R, np.size(s1))
s0 = pyyawt.waverec(c, l, Lo_R, Hi_R)
np.testing.assert_almost_equal(a0, s0)
def test_bior(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
wnames = [
'bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8'
]
for N in np.arange(len(wnames)):
wname = wnames[N]
[cA1, cD1] = pyyawt.dwt(s1, wname)
[cA2, cD2] = pyyawt.dwt(cA1, wname)
[cA3, cD3] = pyyawt.dwt(cA2, wname)
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, wname)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_haar(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
[cA1,cD1] = pyyawt.dwt(s1,'haar')
[cA2,cD2] = pyyawt.dwt(cA1,'haar')
[cA3,cD3] = pyyawt.dwt(cA2,'haar')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,'haar')
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_haar(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
[c,l] = pyyawt.wavedec(s1,3,'haar')
[cA1,cD1] = pyyawt.dwt(s1,'haar')
[cA2,cD2] = pyyawt.dwt(cA1,'haar')
[cA3,cD3] = pyyawt.dwt(cA2,'haar')
ca2 = pyyawt.idwt(cA3,cD3,'haar',np.size(cA2))
ca1 = pyyawt.idwt(ca2,cD2,'haar',np.size(cA1))
a0 = pyyawt.idwt(ca1,cD1,'haar',np.size(s1))
s0 = pyyawt.waverec(c,l,'haar')
np.testing.assert_almost_equal(a0, s0)
def test_haar(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
[c, l] = pyyawt.wavedec(s1, 3, 'haar')
[cA1, cD1] = pyyawt.dwt(s1, 'haar')
[cA2, cD2] = pyyawt.dwt(cA1, 'haar')
[cA3, cD3] = pyyawt.dwt(cA2, 'haar')
ca2 = pyyawt.idwt(cA3, cD3, 'haar', np.size(cA2))
ca1 = pyyawt.idwt(ca2, cD2, 'haar', np.size(cA1))
a0 = pyyawt.idwt(ca1, cD1, 'haar', np.size(s1))
s0 = pyyawt.waverec(c, l, 'haar')
np.testing.assert_almost_equal(a0, s0)
def test_sym(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
for N in np.arange(2,21):
wname = "sym" + str(N)
[cA1,cD1] = pyyawt.dwt(s1,wname)
[cA2,cD2] = pyyawt.dwt(cA1,wname)
[cA3,cD3] = pyyawt.dwt(cA2,wname)
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,wname)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_type2(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
Lo_D = np.random.randn(20)
Hi_D = np.random.randn(20)
[cA1,cD1] = pyyawt.dwt(s1,Lo_D,Hi_D)
[cA2,cD2] = pyyawt.dwt(cA1,Lo_D,Hi_D)
[cA3,cD3] = pyyawt.dwt(cA2,Lo_D,Hi_D)
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_sym(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
for N in np.arange(2,21):
wname = "sym" + str(N)
[c,l] = pyyawt.wavedec(s1,3,wname)
[cA1,cD1] = pyyawt.dwt(s1,wname)
[cA2,cD2] = pyyawt.dwt(cA1,wname)
[cA3,cD3] = pyyawt.dwt(cA2,wname)
ca2 = pyyawt.idwt(cA3,cD3,wname,np.size(cA2))
ca1 = pyyawt.idwt(ca2,cD2,wname,np.size(cA1))
a0 = pyyawt.idwt(ca1,cD1,wname,np.size(s1))
s0 = pyyawt.waverec(c,l,wname)
np.testing.assert_almost_equal(a0, s0)
def test_sym(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
for N in np.arange(2, 21):
wname = "sym" + str(N)
[c, l] = pyyawt.wavedec(s1, 3, wname)
[cA1, cD1] = pyyawt.dwt(s1, wname)
[cA2, cD2] = pyyawt.dwt(cA1, wname)
[cA3, cD3] = pyyawt.dwt(cA2, wname)
ca2 = pyyawt.idwt(cA3, cD3, wname, np.size(cA2))
ca1 = pyyawt.idwt(ca2, cD2, wname, np.size(cA1))
a0 = pyyawt.idwt(ca1, cD1, wname, np.size(s1))
s0 = pyyawt.waverec(c, l, wname)
np.testing.assert_almost_equal(a0, s0)
def test_bior(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
wnames = ['bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8']
for N in np.arange(len(wnames)):
wname = wnames[N]
[cA1,cD1] = pyyawt.dwt(s1,wname)
[cA2,cD2] = pyyawt.dwt(cA1,wname)
[cA3,cD3] = pyyawt.dwt(cA2,wname)
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,wname)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_haar(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
[cA1, cD1] = pyyawt.dwt(s1, 'haar')
[cA2, cD2] = pyyawt.dwt(cA1, 'haar')
[cA3, cD3] = pyyawt.dwt(cA2, 'haar')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, 'haar')
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_bior(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
wnames = ['bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8']
for N in np.arange(len(wnames)):
wname = wnames[N]
[c,l] = pyyawt.wavedec(s1,3,wname)
[cA1,cD1] = pyyawt.dwt(s1,wname)
[cA2,cD2] = pyyawt.dwt(cA1,wname)
[cA3,cD3] = pyyawt.dwt(cA2,wname)
ca2 = pyyawt.idwt(cA3,cD3,wname,np.size(cA2))
ca1 = pyyawt.idwt(ca2,cD2,wname,np.size(cA1))
a0 = pyyawt.idwt(ca1,cD1,wname,np.size(s1))
s0 = pyyawt.waverec(c,l,wname)
np.testing.assert_almost_equal(a0, s0)
def test_type2(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
Lo_D = np.random.randn(20)
Hi_D = np.random.randn(20)
[cA1, cD1] = pyyawt.dwt(s1, Lo_D, Hi_D)
[cA2, cD2] = pyyawt.dwt(cA1, Lo_D, Hi_D)
[cA3, cD3] = pyyawt.dwt(cA2, Lo_D, Hi_D)
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_sym(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
for N in np.arange(2, 21):
wname = "sym" + str(N)
[cA1, cD1] = pyyawt.dwt(s1, wname)
[cA2, cD2] = pyyawt.dwt(cA1, wname)
[cA3, cD3] = pyyawt.dwt(cA2, wname)
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, wname)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
def test_bior(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
wnames = [
'bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8'
]
for N in np.arange(len(wnames)):
wname = wnames[N]
[c, l] = pyyawt.wavedec(s1, 3, wname)
[cA1, cD1] = pyyawt.dwt(s1, wname)
[cA2, cD2] = pyyawt.dwt(cA1, wname)
[cA3, cD3] = pyyawt.dwt(cA2, wname)
ca2 = pyyawt.idwt(cA3, cD3, wname, np.size(cA2))
ca1 = pyyawt.idwt(ca2, cD2, wname, np.size(cA1))
a0 = pyyawt.idwt(ca1, cD1, wname, np.size(s1))
s0 = pyyawt.waverec(c, l, wname)
np.testing.assert_almost_equal(a0, s0)
def test_bior3(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
ST = pyyawt.dwtmode("status", "nodisp")
wnames = [
'bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8'
]
ST = pyyawt.dwtmode("status", "nodisp")
for N in np.arange(len(wnames)):
wname = wnames[N]
[c, l] = pyyawt.wavedec(s1, 3, wname)
pyyawt.dwtmode("symh")
a0 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("symw")
a1 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("asymh")
a2 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("asymw")
a3 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("zpd")
a4 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("sp0")
a5 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("sp1")
a6 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("ppd")
a7 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode("per")
a8 = pyyawt.waverec(c, l, wname)
pyyawt.dwtmode(ST)
np.testing.assert_almost_equal(a0, a1)
np.testing.assert_almost_equal(a0, a2)
np.testing.assert_almost_equal(a0, a3)
np.testing.assert_almost_equal(a0, a4)
np.testing.assert_almost_equal(a0, a5)
np.testing.assert_almost_equal(a0, a6)
np.testing.assert_almost_equal(a0, a7)
np.testing.assert_almost_equal(a0, a8)
def test_bior3(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
ST = pyyawt.dwtmode("status","nodisp")
wnames = ['bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8']
ST = pyyawt.dwtmode("status","nodisp")
for N in np.arange(len(wnames)):
wname = wnames[N]
[c,l] = pyyawt.wavedec(s1,3,wname)
pyyawt.dwtmode("symh")
a0 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("symw")
a1 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("asymh")
a2 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("asymw")
a3 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("zpd")
a4 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("sp0")
a5 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("sp1")
a6 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("ppd")
a7 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode("per")
a8 = pyyawt.waverec(c,l,wname)
pyyawt.dwtmode(ST)
np.testing.assert_almost_equal(a0, a1)
np.testing.assert_almost_equal(a0, a2)
np.testing.assert_almost_equal(a0, a3)
np.testing.assert_almost_equal(a0, a4)
np.testing.assert_almost_equal(a0, a5)
np.testing.assert_almost_equal(a0, a6)
np.testing.assert_almost_equal(a0, a7)
np.testing.assert_almost_equal(a0, a8)
def rsHRF_iterative_wiener_deconv(y, h, Iterations=1000):
N = y.shape[0]
nh = max(h.shape)
h = np.append(h, np.zeros((N - nh, 1)))
H = np.fft.fft(h, axis=0)
Y = np.fft.fft(y, axis=0)
[c, l] = pyyawt.wavedec(abs(y), 1, 'db2')
sigma = pyyawt.wnoisest(c, l, 1)
Phh = np.square(abs(H))
sqrdtempnorm = ((((np.linalg.norm(y - np.mean(y), 2)**2) - (N - 1) *
(sigma**2))) / (np.linalg.norm(h, 1))**2)
Nf = (sigma**2) * N
tempreg = Nf / sqrdtempnorm
Pxx0 = np.square(
abs(np.multiply(Y, (np.divide(np.conj(H), (Phh + N * tempreg))))))
Pxx = Pxx0
Sf = Pxx.reshape(-1, 1)
for i in range(0, Iterations):
M = np.divide(np.multiply(np.multiply(np.conjugate(H), Pxx), Y),
np.add(np.multiply(np.square(abs(H)), Pxx), Nf))
PxxY = np.divide(np.multiply(Pxx, Nf),
np.add(np.multiply(np.square(abs(H)), Pxx), Nf))
Pxx = np.add(PxxY, np.square(abs(M)))
Sf = np.concatenate((Sf, Pxx.reshape(-1, 1)), axis=1)
dSf = np.diff(Sf, 1, 1)
dSfmse = np.mean(np.square(dSf), axis=1)
_, idx = knee.knee_pt(dSfmse)
idm = np.argmin(dSfmse)
ratio = np.abs(dSfmse[idx] -
dSfmse[idm]) / (np.abs(np.max(dSfmse) - np.min(dSfmse)))
if ratio > 0.5:
id0 = idm
else:
id0 = idx
Pxx = Sf[:, id0 + 1]
WienerFilterEst = np.divide(
np.multiply(np.conj(H), Pxx),
np.add(np.multiply(np.square(abs(H)), Pxx), Nf))
return np.real(np.fft.ifft(np.multiply(WienerFilterEst, Y)))
def test1(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
level = 10
[c,l] = pyyawt.wavedec(s1,level,'sym10')
cA = []
cD = []
[ca,cd] = pyyawt.dwt(s1,'sym10')
cA.append(ca)
cD.append(cd)
for i in np.arange(1,level):
[ca,cd] = pyyawt.dwt(cA[i-1],'sym10')
cA.append(ca)
cD.append(cd)
cddetMax = pyyawt.detcoef(c,l)
cdet = []
for i in np.arange(level):
cdet.append(pyyawt.detcoef(c,l,i+1))
np.testing.assert_almost_equal(cddetMax, cD[level-1])
for i in np.arange(level):
np.testing.assert_almost_equal(cdet[i], cD[i])
numlog = np.shape(log[1])
level = 5
GR = log[:, 0]
NPHI = log[:, 1]
RHOB = log[:, 2]
GR = np.array(GR, dtype=float)
NPHI = np.array(NPHI, dtype=float)
RHOB = np.array(RHOB, dtype=float)
# # WAVELET DENOISING FILTER # #
# GR #
[CLog, LLog] = wavedec(GR, level, 'sym8')
[XDLog, CXDLog, LDXLog] = wden(CLog, LLog, 'heursure', 's', 'one', level,
'sym8')
deno_log_GR = waverec(CXDLog, LDXLog, 'sym8') # Use this for GR Input
# print(np.shape(deno_log_GR))
spec_log = fft(GR)
spec_log = abs(spec_log)
spec_deno_log_GR = fft(deno_log_GR)
spec_deno_log_GR = abs(spec_deno_log_GR)
# VISUALIZING BEFORE AND AFTER DENOISING
# f, ax = plt.subplots(nrows=4,ncols=2, figsize=(20,10))
# ax[0,0].plot(spec_log)
def test_bior2(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
ST = pyyawt.dwtmode("status", "nodisp")
wnames = [
'bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8'
]
for N in np.arange(len(wnames)):
wname = wnames[N]
[cA1, cD1] = pyyawt.dwt(s1, wname)
[cA2, cD2] = pyyawt.dwt(cA1, wname)
[cA3, cD3] = pyyawt.dwt(cA2, wname)
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("asymh")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'asymh')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'asymh')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'asymh')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("symw")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'symw')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'symw')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'symw')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("asymw")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'asymw')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'asymw')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'asymw')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("zpd")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'zpd')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'zpd')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'zpd')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("sp0")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'sp0')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'sp0')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'sp0')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("sp1")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'sp1')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'sp1')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'sp1')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("ppd")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'ppd')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'ppd')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'ppd')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("per")
[cA1, cD1] = pyyawt.dwt(s1, wname, 'mode', 'per')
[cA2, cD2] = pyyawt.dwt(cA1, wname, 'mode', 'per')
[cA3, cD3] = pyyawt.dwt(cA2, wname, 'mode', 'per')
Lo_D, Hi_D = pyyawt.wfilters(wname, 'd')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [
np.size(cA3),
np.size(cD3),
np.size(cD2),
np.size(cD1),
np.size(s1)
]
c, l = pyyawt.wavedec(s1, 3, Lo_D, Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode(ST)
def test_bior2(self):
s1 = self.s1
x1 = self.x1
x2 = self.x2
ST = pyyawt.dwtmode("status","nodisp")
wnames = ['bior1.1', 'bior1.3', 'bior1.5', 'bior2.2', 'bior2.4', 'bior2.6',
'bior2.8', 'bior3.1', 'bior3.3', 'bior3.5', 'bior3.7', 'bior3.9',
'bior4.4', 'bior5.5', 'bior6.8']
for N in np.arange(len(wnames)):
wname = wnames[N]
[cA1,cD1] = pyyawt.dwt(s1,wname)
[cA2,cD2] = pyyawt.dwt(cA1,wname)
[cA3,cD3] = pyyawt.dwt(cA2,wname)
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("asymh")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','asymh')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','asymh')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','asymh')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("symw")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','symw')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','symw')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','symw')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("asymw")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','asymw')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','asymw')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','asymw')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("zpd")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','zpd')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','zpd')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','zpd')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("sp0")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','sp0')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','sp0')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','sp0')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("sp1")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','sp1')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','sp1')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','sp1')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("ppd")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','ppd')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','ppd')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','ppd')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode("per")
[cA1,cD1] = pyyawt.dwt(s1,wname,'mode','per')
[cA2,cD2] = pyyawt.dwt(cA1,wname,'mode','per')
[cA3,cD3] = pyyawt.dwt(cA2,wname,'mode','per')
Lo_D,Hi_D = pyyawt.wfilters(wname,'d')
c0 = np.concatenate([cA3, cD3, cD2, cD1])
l0 = [np.size(cA3), np.size(cD3), np.size(cD2), np.size(cD1), np.size(s1)]
c, l = pyyawt.wavedec(s1,3,Lo_D,Hi_D)
np.testing.assert_almost_equal(c, c0)
np.testing.assert_almost_equal(l, l0)
pyyawt.dwtmode(ST)