def _get_tFock1_2b(self, p, q, kappa):
rsH = self.rs.conjugate().T
rs2q = r2q = rsH @ q
q2rs = q2r = rs2q.conjugate().T
svals_rinq = linalg.svd(rs2q)[1].sum()
rs2p = rsH @ p
svals_rinp = linalg.svd(rs2p)[1].sum()
rinq = abs(svals_rinq - self.rs.shape[-1]) < 1e-5
rinp = abs(svals_rinp - self.rs.shape[-1]) < 1e-5
if rinp:
return np.zeros(
(p.shape[-1], q.shape[-1]
)) # Hack to keep both F_pq and F_qp in the rinq case
elif not rinq:
raise RuntimeError(
"Totally off-diagonal Hessian elements not supported ({} {} {})"
.format(svals_rinq, svals_rinp, self.rs.shape[-1]))
m2p = self.ints.ao2loc @ p
m2q = self.ints.ao2loc @ q
p2m = m2p.conjugate().T
ao2loc = self.ints.ao2loc
loc2ao = ao2loc.conjugate().T
dm1 = self.oneRDMs[0] + self.oneRDMs[1]
tdm1 = ao2loc @ (kappa @ dm1 - dm1 @ kappa) @ loc2ao
tdm1 = numpy_helper.pack_tril(tdm1 + tdm1.T - np.diag(np.diag(tdm1)))
vj_pq = np.zeros((p.shape[-1], q.shape[-1]), dtype=tdm1.dtype)
for cderi in self.ints.with_df.loop():
rho = np.dot(cderi, tdm1)
vj_pq += p2m @ numpy_helper.unpack_tril(np.dot(rho, cderi)) @ m2q
pH = p.conjugate().T
qH = q.conjugate().T
dm1_pp = pH @ dm1 @ p
dm1_qq = qH @ dm1 @ q
tFock1 = vj_pq @ dm1_qq - dm1_pp @ vj_pq
return tFock1
def restore(self, filename, inplace=True):
'''Read diis contents from a diis file and replace the attributes of
current diis object if needed, then construct the vector.
'''
fdiis = misc.H5TmpFile(filename)
if inplace:
self.filename = filename
self._diisfile = fdiis
diis_keys = fdiis.keys()
x_keys = [k for k in diis_keys if k[0] == 'x']
e_keys = [k for k in diis_keys if k[0] == 'e']
# errvec may be incomplete if program is terminated when generating errvec.
# The last vector or errvec should be excluded.
nd = min(len(x_keys), len(e_keys))
if nd == 0:
return self
if inplace:
if fdiis[x_keys[0]].size < INCORE_SIZE or self.incore:
for key in diis_keys:
self._buffer[key] = numpy.asarray(fdiis[key])
if 'xprev' in diis_keys:
self._xprev = fdiis['xprev']
else:
for key in diis_keys:
self._store(key, fdiis[key].value)
if 'xprev' in diis_keys:
self._store('xprev', numpy.asarray(fdiis['xprev']))
if 'xprev' in self._buffer: # incore
self._xprev = self._buffer['xprev']
else:
self._xprev = self._diisfile['xprev']
self._bookkeep = list(range(nd))
self._head = nd
vecsize = 0
e_mat = []
for i in range(nd):
dti = numpy.asarray(self.get_err_vec(i))
vecsize = dti.size
for j in range(i + 1):
dtj = self.get_err_vec(j)
assert (dtj.size == vecsize)
tmp = 0
for p0, p1 in misc.prange(0, vecsize, BLOCK_SIZE):
tmp += numpy.dot(dti[p0:p1].conj(), dtj[p0:p1])
e_mat.append(tmp)
dti = dtj = None
e_mat = numpy_helper.unpack_tril(e_mat)
space = max(nd, self.space)
self._H = numpy.zeros((space + 1, space + 1), e_mat.dtype)
self._H[0, 1:] = self._H[1:, 0] = 1
self._H[1:nd + 1, 1:nd + 1] = e_mat
return self