def _restore_CF_diag(self, dbg=False):
nc = self.N_centre
#Want: r[0 <= n < nc] diagonal
Ui = sp.eye(self.D[nc], dtype=self.typ)
for n in xrange(nc, 0, -1):
self.r[n - 1], Um1, Um1_i = tm.restore_LCF_r(self.A[n], self.r[n],
Ui, sanity_checks=self.sanity_checks)
Ui = Um1_i
#Now U is U_0
U = Um1
for s in xrange(self.q[0]):
self.uni_l.A[0][s] = U.dot(self.uni_l.A[0][s])
self.uni_l.A[-1][s] = self.uni_l.A[-1][s].dot(Ui)
self.uni_l.r[-1] = U.dot(self.uni_l.r[-1].dot(U.conj().T))
#And now: l[nc <= n <= N] diagonal
if dbg:
Um1 = sp.eye(self.D[nc - 1], dtype=self.typ)
else:
Um1 = mm.eyemat(self.D[nc - 1], dtype=self.typ) #FIXME: This only works if l[nc - 1] is a special matrix type
for n in xrange(nc, self.N + 1):
self.l[n], U, Ui = tm.restore_RCF_l(self.A[n], self.l[n - 1], Um1,
sanity_checks=self.sanity_checks)
Um1 = U
#Now, Um1 = U_N
Um1_i = Ui
for s in xrange(self.q[0]):
self.uni_r.A[0][s] = Um1.dot(self.uni_r.A[0][s])
self.uni_r.A[-1][s] = self.uni_r.A[-1][s].dot(Um1_i)
self.uni_r.l[-1] = Um1_i.conj().T.dot(self.uni_r.l[-1].dot(Um1_i))
def restore_LCF(self):
Gm1 = sp.eye(self.D[0], dtype=self.typ) #This is actually just the number 1
for n in xrange(1, self.N):
self.l[n], G, Gi = tm.restore_LCF_l(self.A[n], self.l[n - 1], Gm1,
zero_tol=self.zero_tol,
sanity_checks=self.sanity_checks)
Gm1 = G
#Now do A[N]...
#Apply the remaining G[N - 1] from the previous step.
for s in xrange(self.q[self.N]):
self.A[self.N][s] = Gm1.dot(self.A[self.N][s])
#Now finish off
tm.eps_l_noop_inplace(self.l[self.N - 1], self.A[self.N], self.A[self.N], out=self.l[self.N])
#normalize
GNi = 1. / sp.sqrt(self.l[self.N].squeeze().real)
self.A[self.N] *= GNi
self.l[self.N][:] = 1
if self.sanity_checks:
lN = tm.eps_l_noop(self.l[self.N - 1], self.A[self.N], self.A[self.N])
if not sp.allclose(lN, 1, atol=1E-12, rtol=1E-12):
log.warning("Sanity Fail in restore_LCF!: l_N is bad / norm failure")
#diag r
Gi = sp.eye(self.D[self.N], dtype=self.typ)
for n in xrange(self.N, 1, -1):
self.r[n - 1], Gm1, Gm1_i = tm.restore_LCF_r(self.A[n], self.r[n],
Gi, self.sanity_checks)
Gi = Gm1_i
#Apply remaining G1i to A[1]
for s in xrange(self.q[1]):
self.A[1][s] = self.A[1][s].dot(Gi)
#Deal with final, scalar r[0]
tm.eps_r_noop_inplace(self.r[1], self.A[1], self.A[1], out=self.r[0])
if self.sanity_checks:
if not sp.allclose(self.r[0], 1, atol=1E-12, rtol=1E-12):
log.warning("Sanity Fail in restore_LCF!: r_0 is bad / norm failure")
log.warning("r_0 = %s", self.r[0].squeeze().real)
for n in xrange(1, self.N + 1):
l = tm.eps_l_noop(self.l[n - 1], self.A[n], self.A[n])
if not sp.allclose(l, self.l[n], atol=1E-11, rtol=1E-11):
log.warning("Sanity Fail in restore_LCF!: l_%u is bad (off by %g)", n, la.norm(l - self.l[n]))
log.warning((l - self.l[n]).diagonal().real)
def _restore_CF_diag(self, dbg=False):
nc = self.N_centre
#Want: r[0 <= n < nc] diagonal
Ui = sp.eye(self.D[nc], dtype=self.typ)
for n in xrange(nc, 0, -1):
self.r[n - 1], Um1, Um1_i = tm.restore_LCF_r(
self.A[n], self.r[n], Ui, sanity_checks=self.sanity_checks)
Ui = Um1_i
#Now U is U_0
U = Um1
for s in xrange(self.q[0]):
self.uni_l.A[0][s] = U.dot(self.uni_l.A[0][s])
self.uni_l.A[-1][s] = self.uni_l.A[-1][s].dot(Ui)
self.uni_l.r[-1] = U.dot(self.uni_l.r[-1].dot(U.conj().T))
#And now: l[nc <= n <= N] diagonal
if dbg:
Um1 = sp.eye(self.D[nc - 1], dtype=self.typ)
else:
Um1 = mm.eyemat(
self.D[nc - 1], dtype=self.typ
) #FIXME: This only works if l[nc - 1] is a special matrix type
for n in xrange(nc, self.N + 1):
self.l[n], U, Ui = tm.restore_RCF_l(
self.A[n],
self.l[n - 1],
Um1,
sanity_checks=self.sanity_checks)
Um1 = U
#Now, Um1 = U_N
Um1_i = Ui
for s in xrange(self.q[0]):
self.uni_r.A[0][s] = Um1.dot(self.uni_r.A[0][s])
self.uni_r.A[-1][s] = self.uni_r.A[-1][s].dot(Um1_i)
self.uni_r.l[-1] = Um1_i.conj().T.dot(self.uni_r.l[-1].dot(Um1_i))
def _restore_CF_diag(self):
nc = self.N_centre
self.S_hc = sp.zeros((self.N + 1), dtype=sp.complex128)
#Want: r[0 <= n < nc] diagonal
Ui = sp.eye(self.D[nc], dtype=self.typ)
for n in xrange(nc, 0, -1):
self.r[n - 1], Um1, Um1_i = tm.restore_LCF_r(self.A[n], self.r[n],
Ui, sanity_checks=self.sanity_checks)
self.S_hc[n - 1] = -sp.sum(self.r[n - 1].diag * sp.log2(self.r[n - 1].diag))
Ui = Um1_i
#Now U is U_0
U = Um1
for s in xrange(self.q[0]):
self.A[0][s] = U.dot(self.A[0][s]).dot(Ui)
self.uni_l.r = U.dot(self.uni_l.r.dot(U.conj().T))
#And now: l[nc <= n <= N] diagonal
Um1 = mm.eyemat(self.D[nc - 1], dtype=self.typ)
for n in xrange(nc, self.N + 1):
self.l[n], U, Ui = tm.restore_RCF_l(self.A[n], self.l[n - 1], Um1,
sanity_checks=self.sanity_checks)
self.S_hc[n] = -sp.sum(self.l[n].diag * sp.log2(self.l[n].diag))
Um1 = U
#Now, Um1 = U_N
Um1_i = Ui
for s in xrange(self.q[0]):
self.A[self.N + 1][s] = Um1.dot(self.A[self.N + 1][s]).dot(Um1_i)
self.uni_r.l = Um1_i.conj().T.dot(self.uni_r.l.dot(Um1_i))
def restore_LCF(self):
Gm1 = sp.eye(self.D[0],
dtype=self.typ) #This is actually just the number 1
for n in xrange(1, self.N):
self.l[n], G, Gi = tm.restore_LCF_l(
self.A[n],
self.l[n - 1],
Gm1,
zero_tol=self.zero_tol,
sanity_checks=self.sanity_checks)
Gm1 = G
#Now do A[N]...
#Apply the remaining G[N - 1] from the previous step.
for s in xrange(self.q[self.N]):
self.A[self.N][s] = Gm1.dot(self.A[self.N][s])
#Now finish off
tm.eps_l_noop_inplace(self.l[self.N - 1],
self.A[self.N],
self.A[self.N],
out=self.l[self.N])
#normalize
GNi = 1. / sp.sqrt(self.l[self.N].squeeze().real)
self.A[self.N] *= GNi
self.l[self.N][:] = 1
if self.sanity_checks:
lN = tm.eps_l_noop(self.l[self.N - 1], self.A[self.N],
self.A[self.N])
if not sp.allclose(lN, 1, atol=1E-12, rtol=1E-12):
log.warning(
"Sanity Fail in restore_LCF!: l_N is bad / norm failure")
#diag r
Gi = sp.eye(self.D[self.N], dtype=self.typ)
for n in xrange(self.N, 1, -1):
self.r[n - 1], Gm1, Gm1_i = tm.restore_LCF_r(
self.A[n], self.r[n], Gi, self.sanity_checks)
Gi = Gm1_i
#Apply remaining G1i to A[1]
for s in xrange(self.q[1]):
self.A[1][s] = self.A[1][s].dot(Gi)
#Deal with final, scalar r[0]
tm.eps_r_noop_inplace(self.r[1], self.A[1], self.A[1], out=self.r[0])
if self.sanity_checks:
if not sp.allclose(self.r[0], 1, atol=1E-12, rtol=1E-12):
log.warning(
"Sanity Fail in restore_LCF!: r_0 is bad / norm failure")
log.warning("r_0 = %s", self.r[0].squeeze().real)
for n in xrange(1, self.N + 1):
l = tm.eps_l_noop(self.l[n - 1], self.A[n], self.A[n])
if not sp.allclose(l, self.l[n], atol=1E-11, rtol=1E-11):
log.warning(
"Sanity Fail in restore_LCF!: l_%u is bad (off by %g)",
n, la.norm(l - self.l[n]))
log.warning((l - self.l[n]).diagonal().real)
