def minimize(obj,
bounds=(None, None),
method='brent',
maxiter=OPT_MAXITER,
tol=OPT_XTOL,
x0=None,
root_with_omp=False):
# Runs the chemical potential minimization with a bunch of different
# available methods, uses OpenMP on the root process only.
# Best methods are golden and lstsq, golden uses more function calls with less
# additional overhead, whereas lstsq uses fewer function calls and more overhead,
# lstsq is best unless we efficiently parallelise the objective function.
if method == 'brent':
kwargs = dict(method='bounded',
bounds=bounds,
options=dict(maxiter=maxiter, xatol=tol))
f = optimize.minimize_scalar
elif method == 'golden':
kwargs = dict(method='golden',
bounds=bounds,
options=dict(maxiter=maxiter, xtol=tol))
f = optimize.minimize_scalar
elif method == 'newton':
kwargs = dict(method='TNC',
bounds=[bounds],
x0=x0,
options=dict(maxiter=maxiter, xtol=tol))
f = optimize.minimize
elif method == 'bfgs':
kwargs = dict(method='L-BFGS-B',
bounds=[bounds],
x0=x0,
options=dict(maxiter=maxiter, ftol=tol))
f = optimize.minimize
elif method == 'lstsq':
kwargs = dict(method='SLSQP',
x0=x0,
options=dict(maxiter=maxiter, ftol=tol))
f = optimize.minimize
elif method == 'stochastic':
kwargs = dict(bounds=[(-5, 5)], maxiter=maxiter, tol=tol)
f = optimize.differential_evolution
else:
raise ValueError
if root_with_omp:
opt = None
if rank == 0:
with lib.with_omp_threads(size):
opt = f(obj, **kwargs)
if size > 1:
opt = comm.bcast(opt, root=0)
else:
opt = f(obj, **kwargs)
return opt
def run(self, **kwargs):
if self.disable_omp:
with lib.with_omp_threads(1):
self._run(**kwargs)
else:
self._run(**kwargs)
if not self._pyscf.converged:
if mpi.rank:
log.warn('%s did not converge.' % self.__class__.__name__)
return self
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
self.nelectron = self.mol.nelectron
self.charge = self.mol.charge
self.spin = self.mol.spin
self.natm = self.mol.natm
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in self.mol._atom])
self.charges = self.mol.atom_charges()
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff.shape
self.nprims = nprims
self.nmo = nmo
if (self.corr):
self.rdm1 = lib.chkfile.load(self.chkfile, 'rdm/rdm1')
natocc, natorb = numpy.linalg.eigh(self.rdm1)
natorb = numpy.dot(self.mo_coeff, natorb)
self.mo_coeff = natorb
self.mo_occ = natocc
nocc = self.mo_occ[abs(self.mo_occ) > self.occdrop]
nocc = len(nocc)
self.nocc = nocc
self.grids.verbose = 0
self.grids.stdout = self.stdout
self.grids.build()
vfree(self)
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
with lib.with_omp_threads(self.nthreads):
integrate(self)
logger.info(self, 'Hirshfeld properties done')
logger.timer(self, 'Hirshfeld build', *t0)
return self
def build(self):
t0 = time.clock()
lib.logger.TIMER_LEVEL = 3
self.mol = lib.chkfile.load_mol(self.chkfile)
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
self.nelectron = self.mol.nelectron
self.charge = self.mol.charge
self.spin = self.mol.spin
self.natm = self.mol.natm
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in self.mol._atom])
self.charges = self.mol.atom_charges()
idx = 'grid' + str(self.inucs[0])
jdx = 'grid' + str(self.inucs[1])
with h5py.File(self.surfile) as f:
self.p1 = f[idx + '/p'].value
self.w1 = f[idx + '/w'].value
self.p2 = f[jdx + '/p'].value
self.w2 = f[jdx + '/w'].value
self.npoints = numpy.zeros(2, dtype=numpy.int32)
self.npoints[0] = len(self.w1)
self.npoints[1] = len(self.w2)
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
with lib.with_omp_threads(self.nthreads):
ev = vv10_e(self)
lib.logger.info(self, 'VV10 energy %f' % ev)
logger.info(self, 'Write info to HDF5 file')
logger.info(self, 'VV10 of atoms %d %d done', *self.inucs)
logger.timer(self, 'VV10 build', t0)
return self
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
self.mol = lib.chkfile.load_mol(self.chkfile)
self.nelectron = self.mol.nelectron
self.charge = self.mol.charge
self.spin = self.mol.spin
self.natm = self.mol.natm
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in self.mol._atom])
self.charges = self.mol.atom_charges()
if (self.cas):
self.mo_coeff = lib.chkfile.load(self.chkfile, 'mcscf/mo_coeff')
else:
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff.shape
self.nprims = nprims
self.nmo = nmo
if self.charges[self.inuc] == 1:
self.rad = grid.BRAGG[self.charges[self.inuc]]
else:
self.rad = grid.BRAGG[self.charges[self.inuc]] * 0.5
if (self.corr):
self.rdm1 = lib.chkfile.load(self.chkfile, 'rdm/rdm1')
natocc, natorb = numpy.linalg.eigh(self.rdm1)
natorb = numpy.dot(self.mo_coeff, natorb)
self.mo_coeff = natorb
self.mo_occ = natocc
nocc = self.mo_occ[abs(self.mo_occ) > self.occdrop]
nocc = len(nocc)
self.nocc = nocc
idx = 'atom' + str(self.inuc)
with h5py.File(self.surfile) as f:
self.xnuc = f[idx + '/xnuc'].value
self.xyzrho = f[idx + '/xyzrho'].value
self.npang = f[idx + '/npang'].value
self.ntrial = f[idx + '/ntrial'].value
self.rmin = f[idx + '/rmin'].value
self.rmax = f[idx + '/rmax'].value
self.rsurf = f[idx + '/rsurf'].value
self.nlimsurf = f[idx + '/nlimsurf'].value
self.agrids = f[idx + '/coords'].value
self.brad = self.rmin * self.betafac
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudr == 'legendre'):
self.iqudr = 1
if (self.biqudr == 'legendre'):
self.biqudr = 1
if (self.mapr == 'becke'):
self.mapr = 1
elif (self.mapr == 'exp'):
self.mapr = 2
elif (self.mapr == 'none'):
self.mapr = 0
if (self.bmapr == 'becke'):
self.bmapr = 1
elif (self.bmapr == 'exp'):
self.bmapr = 2
elif (self.bmapr == 'none'):
self.bmapr = 0
if (self.full):
self.nocc = self.nmo
nocc = self.nmo
else:
nocc = self.mo_occ[self.mo_occ > self.occdrop]
nocc = len(nocc)
self.nocc = nocc
self.aom = numpy.zeros((nocc, nocc))
with lib.with_omp_threads(self.nthreads):
aomb = int_beta(self)
aoma = out_beta(self)
idx = 0
for i in range(nocc):
for j in range(i + 1):
self.aom[i, j] = aoma[idx] + aomb[idx]
self.aom[j, i] = self.aom[i, j]
idx += 1
if (self.nmo <= 30):
dump_tri(self.stdout, self.aom, ncol=NCOL, digits=DIGITS, start=0)
logger.info(self, 'Write info to HDF5 file')
atom_dic = {'aom': self.aom}
lib.chkfile.save(self.surfile, 'ovlp' + str(self.inuc), atom_dic)
logger.info(self, '')
logger.info(self, 'AOM of atom %d done', self.inuc)
logger.timer(self, 'AOM build', *t0)
return self
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
mol = lib.chkfile.load_mol(self.chkfile)
self.nelectron = mol.nelectron
self.charge = mol.charge
self.spin = mol.spin
self.natm = mol.natm
self.atm = numpy.asarray(mol._atm, dtype=numpy.int32, order='C')
self.bas = numpy.asarray(mol._bas, dtype=numpy.int32, order='C')
self.nbas = self.bas.shape[0]
self.env = numpy.asarray(mol._env, dtype=numpy.double, order='C')
self.ao_loc = mol.ao_loc_nr()
self.shls_slice = (0, self.nbas)
sh0, sh1 = self.shls_slice
self.nao = self.ao_loc[sh1] - self.ao_loc[sh0]
self.non0tab = numpy.ones((1, self.nbas), dtype=numpy.int8)
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in mol._atom])
self.charges = mol.atom_charges()
#if (self.cas):
# self.mo_coeff = lib.chkfile.load(self.chkfile, 'mcscf/mo_coeff')
#else:
# self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff.shape
self.nprims = nprims
self.nmo = nmo
self.cart = mol.cart
if (not self.leb):
self.npang = self.npphi * self.nptheta
if (self.corr):
self.rdm1 = lib.chkfile.load(self.chkfile, 'rdm/rdm1')
nmo = self.rdm1.shape[0]
natocc, natorb = numpy.linalg.eigh(self.rdm1)
if (self.cas):
self.mo_coeff = lib.chkfile.load(self.chkfile,
'mcscf/mo_coeff')
natorb = numpy.dot(self.mo_coeff, natorb)
self.mo_coeff = natorb
self.mo_occ = natocc
nocc = self.mo_occ[abs(self.mo_occ) > self.occdrop]
nocc = len(nocc)
self.nocc = nocc
if (self.ntrial % 2 == 0): self.ntrial += 1
geofac = numpy.power(((self.rmaxsurf - 0.1) / self.rprimer),
(1.0 / (self.ntrial - 1.0)))
self.rpru = numpy.zeros((self.ntrial))
for i in range(self.ntrial):
self.rpru[i] = self.rprimer * numpy.power(geofac, (i + 1) - 1)
self.rsurf = numpy.zeros((self.npang, self.ntrial), order='C')
self.nlimsurf = numpy.zeros((self.npang), dtype=numpy.int32)
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudt == 'legendre'):
self.iqudt = 1
if (self.leb):
self.grids = grid.lebgrid(self.npang)
else:
self.grids = grid.anggrid(self.iqudt, self.nptheta, self.npphi)
self.xyzrho = numpy.zeros((self.natm, 3))
t = time.time()
for i in range(self.natm):
self.xyzrho[i], gradmod = gradrho(self, self.coords[i], self.step)
if (gradmod > 1e-4):
if (self.charges[i] > 2.0):
logger.info(self, 'Good rho position %.6f %.6f %.6f',
*self.xyzrho[i])
else:
raise RuntimeError('Failed finding nucleus:',
*self.xyzrho[i])
else:
logger.info(self, 'Check rho position %.6f %.6f %.6f',
*self.xyzrho[i])
logger.info(self, 'Setting xyzrho for atom to imput coords')
self.xyzrho[i] = self.coords[i]
self.xnuc = numpy.asarray(self.xyzrho[self.inuc])
logger.info(self,
'Time finding nucleus %.3f (sec)' % (time.time() - t))
if (self.backend == 'rkck'):
backend = 1
elif (self.backend == 'rkdp'):
backend = 2
else:
raise NotImplementedError(
'Only rkck or rkdp ODE solver yet available')
ct_ = numpy.asarray(self.grids[:, 0], order='C')
st_ = numpy.asarray(self.grids[:, 1], order='C')
cp_ = numpy.asarray(self.grids[:, 2], order='C')
sp_ = numpy.asarray(self.grids[:, 3], order='C')
t = time.time()
feval = 'surf_driver'
drv = getattr(libaim, feval)
with lib.with_omp_threads(self.nthreads):
drv(ctypes.c_int(self.inuc),
self.xyzrho.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.npang), ct_.ctypes.data_as(ctypes.c_void_p),
st_.ctypes.data_as(ctypes.c_void_p),
cp_.ctypes.data_as(ctypes.c_void_p),
sp_.ctypes.data_as(ctypes.c_void_p), ctypes.c_int(self.ntrial),
self.rpru.ctypes.data_as(ctypes.c_void_p),
ctypes.c_double(self.epsiscp), ctypes.c_double(self.epsroot),
ctypes.c_double(self.rmaxsurf), ctypes.c_int(backend),
ctypes.c_double(self.epsilon), ctypes.c_double(self.step),
ctypes.c_int(self.mstep), ctypes.c_int(self.natm),
self.coords.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.cart), ctypes.c_int(self.nmo),
ctypes.c_int(self.nprims),
self.atm.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.nbas),
self.bas.ctypes.data_as(ctypes.c_void_p),
self.env.ctypes.data_as(ctypes.c_void_p),
self.ao_loc.ctypes.data_as(ctypes.c_void_p),
self.mo_coeff.ctypes.data_as(ctypes.c_void_p),
self.mo_occ.ctypes.data_as(ctypes.c_void_p),
ctypes.c_double(self.occdrop),
self.nlimsurf.ctypes.data_as(ctypes.c_void_p),
self.rsurf.ctypes.data_as(ctypes.c_void_p))
logger.info(self,
'Time finding surface %.3f (sec)' % (time.time() - t))
self.rmin = 1000.0
self.rmax = 0.0
for i in range(self.npang):
nsurf = int(self.nlimsurf[i])
self.rmin = numpy.minimum(self.rmin, self.rsurf[i, 0])
self.rmax = numpy.maximum(self.rmax, self.rsurf[i, nsurf - 1])
logger.info(self, 'Rmin for surface %.6f', self.rmin)
logger.info(self, 'Rmax for surface %.6f', self.rmax)
logger.info(self, 'Write HDF5 surface file')
atom_dic = {
'inuc': self.inuc,
'xnuc': self.xnuc,
'xyzrho': self.xyzrho,
'coords': self.grids,
'npang': self.npang,
'ntrial': self.ntrial,
'rmin': self.rmin,
'rmax': self.rmax,
'nlimsurf': self.nlimsurf,
'rsurf': self.rsurf
}
lib.chkfile.save(self.surfile, 'atom' + str(self.inuc), atom_dic)
logger.info(self, 'Surface of atom %d saved', self.inuc)
logger.timer(self, 'BaderSurf build', *t0)
return self
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
self.mol = lib.chkfile.load_mol(self.chkfile)
self.nelectron = self.mol.nelectron
self.charge = self.mol.charge
self.spin = self.mol.spin
self.natm = self.mol.natm
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist() for atom in self.mol._atom])
self.charges = self.mol.atom_charges()
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff.shape
self.nprims = nprims
self.nmo = nmo
if self.charges[self.inuc] == 1:
self.rad = grid.BRAGG[self.charges[self.inuc]]
else:
self.rad = grid.BRAGG[self.charges[self.inuc]]*0.5
self.n2c = nprims/2
nocc = self.mo_occ[abs(self.mo_occ)>self.occdrop]
self.nocc = len(nocc)
pos = abs(self.mo_occ) > self.occdrop
n2c = self.n2c
self.mo_coeffL = self.mo_coeff[:n2c,pos]
c1 = 0.5/self.cspeed
self.mo_coeffS = self.mo_coeff[n2c:,n2c:n2c+self.nocc] * c1
idx = 'atom'+str(self.inuc)
with h5py.File(self.surfile) as f:
self.xnuc = f[idx+'/xnuc'].value
self.xyzrho = f[idx+'/xyzrho'].value
self.npang = f[idx+'/npang'].value
self.ntrial = f[idx+'/ntrial'].value
self.rmin = f[idx+'/rmin'].value
self.rmax = f[idx+'/rmax'].value
self.rsurf = f[idx+'/rsurf'].value
self.nlimsurf = f[idx+'/nlimsurf'].value
self.agrids = f[idx+'/coords'].value
self.brad = self.rmin*self.betafac
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudr == 'legendre'):
self.iqudr = 1
if (self.biqudr == 'legendre'):
self.biqudr = 1
if (self.mapr == 'becke'):
self.mapr = 1
elif (self.mapr == 'exp'):
self.mapr = 2
elif (self.mapr == 'none'):
self.mapr = 0
if (self.bmapr == 'becke'):
self.bmapr = 1
elif (self.bmapr == 'exp'):
self.bmapr = 2
elif (self.bmapr == 'none'):
self.bmapr = 0
with lib.with_omp_threads(self.nthreads):
brprops = int_beta(self)
rprops = out_beta(self)
logger.info(self,'Write info to HDF5 file')
atom_dic = {'inprops':brprops,
'outprops':rprops,
'totprops':(brprops+rprops)}
lib.chkfile.save(self.surfile, 'atom_props'+str(self.inuc), atom_dic)
for i in range(NPROPS):
logger.info(self,'*-> Total %s density %8.5f ', PROPS[i], (rprops[i]+brprops[i]))
logger.info(self,'')
logger.info(self,'Basim properties of atom %d done',self.inuc)
logger.timer(self,'Basin build', *t0)
return self
def kernel(myci, h1e, eri, norb, nelec, ci0=None,
tol=None, lindep=None, max_cycle=None, max_space=None,
nroots=None, davidson_only=None,
max_memory=None, verbose=None, ecore=0, **kwargs):
if tol is None: tol = myci.conv_tol
if lindep is None: lindep = myci.lindep
if max_cycle is None: max_cycle = myci.max_cycle
if max_space is None: max_space = myci.max_space
if max_memory is None: max_memory = myci.max_memory
if nroots is None: nroots = myci.nroots
if verbose is None: verbose = logger.Logger(myci.stdout, myci.verbose)
tol_residual = None #getattr(fci, 'conv_tol_residual', None)
myci.dump_flags()
nelec = direct_spin1._unpack_nelec(nelec, myci.spin)
eri = ao2mo.restore(1, eri, norb)
eri = eri.ravel()
logger.info(myci, 'CI in the selected space')
# Initial guess
if ci0 is None:
t_start = time.time()
if (myci.model == 'fci'):
dets = cistring.gen_full_space(range(norb), nelec)
ndets = dets.shape[0]
if (myci.noise):
numpy.random.seed()
ci0 = [cistring.as_SCIvector(numpy.random.uniform(low=1e-3,high=1e-2,size=ndets), dets)]
ci0[0][0] = 0.99
ci0[0] *= 1./numpy.linalg.norm(ci0[0])
else:
ci0 = [cistring.as_SCIvector(numpy.zeros(ndets), dets)]
ci0[0][0] = 1.0
else:
raise RuntimeError('''Unknown CI model''')
t_current = time.time() - t_start
#logger.info(myci, 'Initial CI vector = %s', ci0[0][:])
logger.info(myci, 'Timing for generating strings: %10.3f', t_current)
else:
assert(nroots == len(ci0))
def hop(c):
hc = myci.contract_2e((h1e, eri), cistring.as_SCIvector(c, ci_strs), norb, nelec, hdiag)
return hc.ravel()
precond = lambda x, e, *args: x/(hdiag-e+myci.level_shift)
ci_strs = ci0[0]._strs
logger.info(myci, 'Number of CI configurations: %d', ci_strs.shape[0])
t_start = time.time()
hdiag = myci.make_hdiag(h1e, eri, ci_strs, norb, nelec)
t_current = time.time() - t_start
logger.info(myci, 'Timing for diagonal hamiltonian: %10.3f', t_current)
t_start = time.time()
with lib.with_omp_threads(myci.threads):
#e, c = myci.eig(hop, ci0, precond, tol=tol, lindep=lindep,
# max_cycle=max_cycle, max_space=max_space, nroots=nroots,
# max_memory=max_memory, verbose=verbose, **kwargs)
#
e, c = myci.eig(hop, ci0, precond, tol=tol, lindep=lindep,
max_cycle=max_cycle, max_space=max_space, nroots=nroots,
max_memory=max_memory, verbose=verbose, follow_state=True,
tol_residual=tol_residual, **kwargs)
t_current = time.time() - t_start
logger.info(myci, 'Timing for solving the eigenvalue problem: %10.3f', t_current)
if not isinstance(c, (tuple, list)):
c = [c]
e = [e]
logger.info(myci, 'CI E = %s', numpy.array(e)+ecore)
#myci.eci = e+ecore
#myci.ci = e
#for i in range(nroots):
# norm = numpy.einsum('i,i->', ci0[i][:], ci0[i][:])
# s = myci.spin_square(ci0[i], norb, nelec)
# logger.info(myci, 'E(CI) = %10.5f, CI E = %10.5f, Norm = %1.3f, Spin = %s'\
# % (numpy.array(e[i]), numpy.array(e[i])+ecore, norm, s))
# #logger.info(myci, 'CI E = %s', numpy.array(e)+ecore)
# #logger.info(mc,"* Norm info for state %d : %s" % (i,norm))
# #logger.info(mc,"* Spin info for state %d : %s" % (i,s))
return (numpy.array(e)+ecore), [cistring.as_SCIvector(ci, ci_strs) for ci in c]
def kernel_ms1(fci,
h1e,
eri,
norb,
nelec,
ci0=None,
link_index=None,
tol=None,
lindep=None,
max_cycle=None,
max_space=None,
nroots=None,
davidson_only=None,
pspace_size=None,
max_memory=None,
verbose=None,
ecore=0,
**kwargs):
if nroots is None: nroots = fci.nroots
if davidson_only is None: davidson_only = fci.davidson_only
if pspace_size is None: pspace_size = fci.pspace_size
if max_memory is None:
max_memory = fci.max_memory - lib.current_memory()[0]
log = logger.new_logger(fci, verbose)
nelec = _unpack_nelec(nelec, fci.spin)
assert (0 <= nelec[0] <= norb and 0 <= nelec[1] <= norb)
link_indexa, link_indexb = _unpack(norb, nelec, link_index)
na = link_indexa.shape[0]
nb = link_indexb.shape[0]
if max_memory < na * nb * 6 * 8e-6:
log.warn(
'Not enough memory for FCI solver. '
'The minimal requirement is %.0f MB', na * nb * 60e-6)
hdiag = fci.make_hdiag(h1e, eri, norb, nelec)
nroots = min(hdiag.size, nroots)
try:
addr, h0 = fci.pspace(h1e, eri, norb, nelec, hdiag,
max(pspace_size, nroots))
if pspace_size > 0:
pw, pv = fci.eig(h0)
else:
pw = pv = None
if pspace_size >= na * nb and ci0 is None and not davidson_only:
# The degenerated wfn can break symmetry. The davidson iteration with proper
# initial guess doesn't have this issue
if na * nb == 1:
return pw[0] + ecore, pv[:, 0].reshape(1, 1)
elif nroots > 1:
civec = numpy.empty((nroots, na * nb))
civec[:, addr] = pv[:, :nroots].T
return pw[:nroots] + ecore, [c.reshape(na, nb) for c in civec]
elif abs(pw[0] - pw[1]) > 1e-12:
civec = numpy.empty((na * nb))
civec[addr] = pv[:, 0]
return pw[0] + ecore, civec.reshape(na, nb)
except NotImplementedError:
addr = [0]
pw = pv = None
precond = fci.make_precond(hdiag, pw, pv, addr)
h2e = fci.absorb_h1e(h1e, eri, norb, nelec, .5)
def hop(c):
hc = fci.contract_2e(h2e, c, norb, nelec, (link_indexa, link_indexb))
return hc.ravel()
if ci0 is None:
if callable(getattr(fci, 'get_init_guess', None)):
ci0 = lambda: fci.get_init_guess(norb, nelec, nroots, hdiag)
else:
def ci0(): # lazy initialization to reduce memory footprint
x0 = []
for i in range(nroots):
x = numpy.zeros(na * nb)
x[addr[i]] = 1
x0.append(x)
return x0
elif not callable(ci0):
if isinstance(ci0, numpy.ndarray) and ci0.size == na * nb:
ci0 = [ci0.ravel()]
else:
ci0 = [x.ravel() for x in ci0]
# Add vectors if not enough initial guess is given
if len(ci0) < nroots:
if callable(getattr(fci, 'get_init_guess', None)):
ci0.extend(
fci.get_init_guess(norb, nelec, nroots, hdiag)[len(ci0):])
else:
for i in range(len(ci0), nroots):
x = numpy.zeros(na * nb)
x[addr[i]] = 1
ci0.append(x)
if tol is None: tol = fci.conv_tol
if lindep is None: lindep = fci.lindep
if max_cycle is None: max_cycle = fci.max_cycle
if max_space is None: max_space = fci.max_space
tol_residual = getattr(fci, 'conv_tol_residual', None)
with lib.with_omp_threads(fci.threads):
#e, c = lib.davidson(hop, ci0, precond, tol=fci.conv_tol, lindep=fci.lindep)
e, c = fci.eig(hop,
ci0,
precond,
tol=tol,
lindep=lindep,
max_cycle=max_cycle,
max_space=max_space,
nroots=nroots,
max_memory=max_memory,
verbose=log,
follow_state=True,
tol_residual=tol_residual,
**kwargs)
if nroots > 1:
return e + ecore, [ci.reshape(na, nb) for ci in c]
else:
return e + ecore, c.reshape(na, nb)
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
self.cell = libpbc.chkfile.load_cell(self.chkfile)
self.a = self.cell.lattice_vectors()
self.b = self.cell.reciprocal_vectors()
self.vol = self.cell.vol
self.nelectron = self.cell.nelectron
self.charge = self.cell.charge
self.spin = self.cell.spin
self.natm = self.cell.natm
self.ls = self.cell.get_lattice_Ls(dimension=self.cell.dimension)
self.ls = self.ls[numpy.argsort(lib.norm(self.ls, axis=1))]
self.kpts = lib.chkfile.load(self.chkfile, 'kcell/kpts')
self.nkpts = len(self.kpts)
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in self.cell._atom])
self.charges = self.cell.atom_charges()
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff[0].shape
self.nprims = nprims
self.nmo = nmo
if self.charges[self.inuc] == 1:
self.rad = grid.BRAGG[self.charges[self.inuc]]
else:
self.rad = grid.BRAGG[self.charges[self.inuc]] * 0.5
idx = 'atom' + str(self.inuc)
with h5py.File(self.surfile) as f:
self.xnuc = f[idx + '/xnuc'].value
self.xyzrho = f[idx + '/xyzrho'].value
self.npang = f[idx + '/npang'].value
self.ntrial = f[idx + '/ntrial'].value
self.rmin = f[idx + '/rmin'].value
self.rmax = f[idx + '/rmax'].value
self.rsurf = f[idx + '/rsurf'].value
self.nlimsurf = f[idx + '/nlimsurf'].value
self.agrids = f[idx + '/coords'].value
self.brad = self.rmin * self.betafac
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudr == 'legendre'):
self.iqudr = 1
if (self.biqudr == 'legendre'):
self.biqudr = 1
if (self.mapr == 'becke'):
self.mapr = 1
elif (self.mapr == 'exp'):
self.mapr = 2
elif (self.mapr == 'none'):
self.mapr = 0
if (self.bmapr == 'becke'):
self.bmapr = 1
elif (self.bmapr == 'exp'):
self.bmapr = 2
elif (self.bmapr == 'none'):
self.bmapr = 0
with lib.with_omp_threads(self.nthreads):
brprops = int_beta(self)
rprops = out_beta(self)
logger.info(self, 'Write info to HDF5 file')
atom_dic = {
'inprops': brprops,
'outprops': rprops,
'totprops': (brprops + rprops)
}
lib.chkfile.save(self.surfile, 'atom_props' + str(self.inuc), atom_dic)
for i in range(NPROPS):
logger.info(self, '*-> Total %s %8.5f ', PROPS[i],
(rprops[i] + brprops[i]))
logger.info(self, 'Basim properties of atom %d done', self.inuc)
logger.timer(self, 'Basin build', *t0)
return self
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
self.cell = libpbc.chkfile.load_cell(self.chkfile)
self.a = self.cell.lattice_vectors()
self.b = self.cell.reciprocal_vectors()
self.vol = self.cell.vol
self.nelectron = self.cell.nelectron
self.charge = self.cell.charge
self.spin = self.cell.spin
self.natm = self.cell.natm
self.ls = self.cell.get_lattice_Ls(dimension=self.cell.dimension)
self.ls = self.ls[numpy.argsort(lib.norm(self.ls, axis=1))]
self.kpts = lib.chkfile.load(self.chkfile, 'kcell/kpts')
self.nkpts = len(self.kpts)
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in self.cell._atom])
self.charges = self.cell.atom_charges()
if self.charges[self.inuc] == 1:
self.rad = grid.BRAGG[self.charges[self.inuc]]
else:
self.rad = grid.BRAGG[self.charges[self.inuc]] * 0.5
idx = 'atom' + str(self.inuc)
with h5py.File(self.surfile) as f:
self.xnuc = f[idx + '/xnuc'].value
self.xyzrho = f[idx + '/xyzrho'].value
self.npang = f[idx + '/npang'].value
self.ntrial = f[idx + '/ntrial'].value
self.rmin = f[idx + '/rmin'].value
self.rmax = f[idx + '/rmax'].value
self.rsurf = f[idx + '/rsurf'].value
self.nlimsurf = f[idx + '/nlimsurf'].value
self.agrids = f[idx + '/coords'].value
self.brad = self.rmin * self.betafac
# TODO: general orbitals
mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
nprims, nmo = mo_coeff[0].shape
if (self.orbs == -1):
self.orbs = nmo
self.nprims = nprims
self.nmo = self.orbs * self.nkpts
self.mo_coeff = numpy.zeros((self.nprims, self.nmo),
dtype=numpy.complex128)
self.tags = numpy.zeros(self.nmo, dtype=numpy.int32)
ii = 0
for k in range(self.nkpts):
for i in range(self.orbs):
self.mo_coeff[:, ii] = mo_coeff[k][:, i]
self.tags[ii] = k
ii += 1
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudr == 'legendre'):
self.iqudr = 1
if (self.biqudr == 'legendre'):
self.biqudr = 1
if (self.mapr == 'becke'):
self.mapr = 1
elif (self.mapr == 'exp'):
self.mapr = 2
elif (self.mapr == 'none'):
self.mapr = 0
if (self.bmapr == 'becke'):
self.bmapr = 1
elif (self.bmapr == 'exp'):
self.bmapr = 2
elif (self.bmapr == 'none'):
self.bmapr = 0
self.aom = numpy.zeros((self.nmo, self.nmo), dtype=numpy.complex128)
with lib.with_omp_threads(self.nthreads):
aomb = int_beta(self)
aoma = out_beta(self)
idx = 0
for i in range(self.nmo):
for j in range(i + 1):
self.aom[i, j] = aoma[idx] + aomb[idx]
self.aom[j, i] = self.aom[i, j].conj()
idx += 1
norm = float(1.0 / self.nkpts)
self.aom = self.aom * norm
if (self.nmo <= 30):
dump_tri(self.stdout, self.aom, ncol=NCOL, digits=DIGITS, start=0)
logger.info(self, 'Write info to HDF5 file')
atom_dic = {'aom': self.aom}
lib.chkfile.save(self.surfile, 'ovlp' + str(self.inuc), atom_dic)
logger.info(self, '')
logger.info(self, 'AOM of atom %d done', self.inuc)
logger.timer(self, 'AOM build', *t0)
return self
from dftpart.eda import scfeda
from pyscf import lib
with lib.with_omp_threads(4):
test1 = scfeda.EDA()
test1.gjf = 'c8b_nofrg.gjf'
test1.method = ['pbe0', '6-31gss']
test1.output = 'c8b_nofrg'
test1.verbose = 9
#test1.build()
#test1.showinter=True
#test1.lso = 'c8b/c8b.lso'
test1.kernel()
from dftpart import gfea3
from pyscf import lib
par = 8
with lib.with_omp_threads(par):
fr0 = gfea3.GFEA()
fr0.inputstyle = 'frg'
fr0.method = ['hf', '6-31gs', 'cart', 'charge']
fr0.gjfname = 'w19'
fr0.output = 'w19'
fr0.verbose = 9
fr0.showinter = True
#fr0.do_deriv = True
fr0.kernel()
def kernel_ms1(fci,
h1e,
eri,
norb,
nelec,
ci0=None,
link_index=None,
tol=None,
lindep=None,
max_cycle=None,
max_space=None,
nroots=None,
davidson_only=None,
pspace_size=None,
max_memory=None,
verbose=None,
ecore=0,
**kwargs):
'''
Args:
h1e: ndarray
1-electron Hamiltonian
eri: ndarray
2-electron integrals in chemist's notation
norb: int
Number of orbitals
nelec: int or (int, int)
Number of electrons of the system
Kwargs:
ci0: ndarray
Initial guess
link_index: ndarray
A lookup table to cache the addresses of CI determinants in
wave-function vector
tol: float
Convergence tolerance
lindep: float
Linear dependence threshold
max_cycle: int
Max. iterations for diagonalization
max_space: int
Max. trial vectors to store for sub-space diagonalization method
nroots: int
Number of states to solve
davidson_only: bool
Whether to call subspace diagonlization (davidson solver) or do a
full diagonlization (lapack eigh) for small systems
pspace_size: int
Number of determinants as the threshold of "small systems",
Note: davidson solver requires more arguments. For the parameters not
dispatched, they can be passed to davidson solver via the extra keyword
arguments **kwargs
'''
if nroots is None: nroots = fci.nroots
if davidson_only is None: davidson_only = fci.davidson_only
if pspace_size is None: pspace_size = fci.pspace_size
if max_memory is None:
max_memory = fci.max_memory - lib.current_memory()[0]
log = logger.new_logger(fci, verbose)
nelec = _unpack_nelec(nelec, fci.spin)
assert (0 <= nelec[0] <= norb and 0 <= nelec[1] <= norb)
link_indexa, link_indexb = _unpack(norb, nelec, link_index)
na = link_indexa.shape[0]
nb = link_indexb.shape[0]
if max_memory < na * nb * 6 * 8e-6:
log.warn(
'Not enough memory for FCI solver. '
'The minimal requirement is %.0f MB', na * nb * 60e-6)
hdiag = fci.make_hdiag(h1e, eri, norb, nelec)
nroots = min(hdiag.size, nroots)
try:
addr, h0 = fci.pspace(h1e, eri, norb, nelec, hdiag,
max(pspace_size, nroots))
if pspace_size > 0:
pw, pv = fci.eig(h0)
else:
pw = pv = None
if pspace_size >= na * nb and ci0 is None and not davidson_only:
# The degenerated wfn can break symmetry. The davidson iteration with proper
# initial guess doesn't have this issue
if na * nb == 1:
return pw[0] + ecore, pv[:, 0].reshape(1, 1)
elif nroots > 1:
civec = numpy.empty((nroots, na * nb))
civec[:, addr] = pv[:, :nroots].T
return pw[:nroots] + ecore, [c.reshape(na, nb) for c in civec]
elif abs(pw[0] - pw[1]) > 1e-12:
civec = numpy.empty((na * nb))
civec[addr] = pv[:, 0]
return pw[0] + ecore, civec.reshape(na, nb)
except NotImplementedError:
addr = [0]
pw = pv = None
precond = fci.make_precond(hdiag, pw, pv, addr)
h2e = fci.absorb_h1e(h1e, eri, norb, nelec, .5)
def hop(c):
hc = fci.contract_2e(h2e, c, norb, nelec, (link_indexa, link_indexb))
return hc.ravel()
if ci0 is None:
if callable(getattr(fci, 'get_init_guess', None)):
ci0 = lambda: fci.get_init_guess(norb, nelec, nroots, hdiag)
else:
def ci0(): # lazy initialization to reduce memory footprint
x0 = []
for i in range(nroots):
x = numpy.zeros(na * nb)
x[addr[i]] = 1
x0.append(x)
return x0
elif not callable(ci0):
if isinstance(ci0, numpy.ndarray) and ci0.size == na * nb:
ci0 = [ci0.ravel()]
else:
ci0 = [x.ravel() for x in ci0]
# Add vectors if not enough initial guess is given
if len(ci0) < nroots:
if callable(getattr(fci, 'get_init_guess', None)):
ci0.extend(
fci.get_init_guess(norb, nelec, nroots, hdiag)[len(ci0):])
else:
for i in range(len(ci0), nroots):
x = numpy.zeros(na * nb)
x[addr[i]] = 1
ci0.append(x)
if tol is None: tol = fci.conv_tol
if lindep is None: lindep = fci.lindep
if max_cycle is None: max_cycle = fci.max_cycle
if max_space is None: max_space = fci.max_space
tol_residual = getattr(fci, 'conv_tol_residual', None)
with lib.with_omp_threads(fci.threads):
#e, c = lib.davidson(hop, ci0, precond, tol=fci.conv_tol, lindep=fci.lindep)
e, c = fci.eig(hop,
ci0,
precond,
tol=tol,
lindep=lindep,
max_cycle=max_cycle,
max_space=max_space,
nroots=nroots,
max_memory=max_memory,
verbose=log,
follow_state=True,
tol_residual=tol_residual,
**kwargs)
if nroots > 1:
return e + ecore, [ci.reshape(na, nb) for ci in c]
else:
return e + ecore, c.reshape(na, nb)
def kernel_ms1(fci,
h1e,
eri,
norb,
nelec,
ci0=None,
link_index=None,
tol=None,
lindep=None,
max_cycle=None,
max_space=None,
nroots=None,
davidson_only=None,
pspace_size=None,
max_memory=None,
verbose=None,
ecore=0,
**kwargs):
if nroots is None: nroots = fci.nroots
if davidson_only is None: davidson_only = fci.davidson_only
if pspace_size is None: pspace_size = fci.pspace_size
nelec = _unpack_nelec(nelec, fci.spin)
link_indexa, link_indexb = _unpack(norb, nelec, link_index)
na = link_indexa.shape[0]
nb = link_indexb.shape[0]
hdiag = fci.make_hdiag(h1e, eri, norb, nelec)
try:
addr, h0 = fci.pspace(h1e, eri, norb, nelec, hdiag,
max(pspace_size, nroots))
if pspace_size > 0:
pw, pv = fci.eig(h0)
else:
pw = pv = None
if pspace_size >= na * nb and ci0 is None and not davidson_only:
# The degenerated wfn can break symmetry. The davidson iteration with proper
# initial guess doesn't have this issue
if na * nb == 1:
return pw[0] + ecore, pv[:, 0].reshape(1, 1)
elif nroots > 1:
civec = numpy.empty((nroots, na * nb))
civec[:, addr] = pv[:, :nroots].T
return pw[:nroots] + ecore, [c.reshape(na, nb) for c in civec]
elif abs(pw[0] - pw[1]) > 1e-12:
civec = numpy.empty((na * nb))
civec[addr] = pv[:, 0]
return pw[0] + ecore, civec.reshape(na, nb)
except NotImplementedError:
addr = [0]
pw = pv = None
precond = fci.make_precond(hdiag, pw, pv, addr)
h2e = fci.absorb_h1e(h1e, eri, norb, nelec, .5)
def hop(c):
hc = fci.contract_2e(h2e, c, norb, nelec, (link_indexa, link_indexb))
return hc.ravel()
if ci0 is None:
if hasattr(fci, 'get_init_guess'):
ci0 = fci.get_init_guess(norb, nelec, nroots, hdiag)
else:
ci0 = []
for i in range(nroots):
x = numpy.zeros(na * nb)
x[addr[i]] = 1
ci0.append(x)
else:
if isinstance(ci0, numpy.ndarray) and ci0.size == na * nb:
ci0 = [ci0.ravel()]
else:
ci0 = [x.ravel() for x in ci0]
if tol is None: tol = fci.conv_tol
if lindep is None: lindep = fci.lindep
if max_cycle is None: max_cycle = fci.max_cycle
if max_space is None: max_space = fci.max_space
if max_memory is None: max_memory = fci.max_memory
if verbose is None: verbose = logger.Logger(fci.stdout, fci.verbose)
with lib.with_omp_threads(fci.threads):
#e, c = lib.davidson(hop, ci0, precond, tol=fci.conv_tol, lindep=fci.lindep)
e, c = fci.eig(hop,
ci0,
precond,
tol=tol,
lindep=lindep,
max_cycle=max_cycle,
max_space=max_space,
nroots=nroots,
max_memory=max_memory,
verbose=verbose,
follow_state=True,
**kwargs)
if nroots > 1:
return e + ecore, [ci.reshape(na, nb) for ci in c]
else:
return e + ecore, c.reshape(na, nb)
def kernel_ms1(fci, h1e, eri, norb, nelec, ci0=None, link_index=None,
tol=None, lindep=None, max_cycle=None, max_space=None,
nroots=None, davidson_only=None, pspace_size=None,
max_memory=None, verbose=None, ecore=0, **kwargs):
if nroots is None: nroots = fci.nroots
if davidson_only is None: davidson_only = fci.davidson_only
if pspace_size is None: pspace_size = fci.pspace_size
nelec = _unpack_nelec(nelec, fci.spin)
assert(0 <= nelec[0] <= norb and 0 <= nelec[1] <= norb)
link_indexa, link_indexb = _unpack(norb, nelec, link_index)
na = link_indexa.shape[0]
nb = link_indexb.shape[0]
hdiag = fci.make_hdiag(h1e, eri, norb, nelec)
nroots = min(hdiag.size, nroots)
try:
addr, h0 = fci.pspace(h1e, eri, norb, nelec, hdiag, max(pspace_size,nroots))
if pspace_size > 0:
pw, pv = fci.eig(h0)
else:
pw = pv = None
if pspace_size >= na*nb and ci0 is None and not davidson_only:
# The degenerated wfn can break symmetry. The davidson iteration with proper
# initial guess doesn't have this issue
if na*nb == 1:
return pw[0]+ecore, pv[:,0].reshape(1,1)
elif nroots > 1:
civec = numpy.empty((nroots,na*nb))
civec[:,addr] = pv[:,:nroots].T
return pw[:nroots]+ecore, [c.reshape(na,nb) for c in civec]
elif abs(pw[0]-pw[1]) > 1e-12:
civec = numpy.empty((na*nb))
civec[addr] = pv[:,0]
return pw[0]+ecore, civec.reshape(na,nb)
except NotImplementedError:
addr = [0]
pw = pv = None
precond = fci.make_precond(hdiag, pw, pv, addr)
h2e = fci.absorb_h1e(h1e, eri, norb, nelec, .5)
def hop(c):
hc = fci.contract_2e(h2e, c, norb, nelec, (link_indexa,link_indexb))
return hc.ravel()
if ci0 is None:
if callable(getattr(fci, 'get_init_guess', None)):
ci0 = lambda: fci.get_init_guess(norb, nelec, nroots, hdiag)
else:
def ci0(): # lazy initialization to reduce memory footprint
x0 = []
for i in range(nroots):
x = numpy.zeros(na*nb)
x[addr[i]] = 1
x0.append(x)
return x0
elif not callable(ci0):
if isinstance(ci0, numpy.ndarray) and ci0.size == na*nb:
ci0 = [ci0.ravel()]
else:
ci0 = [x.ravel() for x in ci0]
if tol is None: tol = fci.conv_tol
if lindep is None: lindep = fci.lindep
if max_cycle is None: max_cycle = fci.max_cycle
if max_space is None: max_space = fci.max_space
if max_memory is None: max_memory = fci.max_memory
if verbose is None: verbose = logger.Logger(fci.stdout, fci.verbose)
tol_residual = getattr(fci, 'conv_tol_residual', None)
with lib.with_omp_threads(fci.threads):
#e, c = lib.davidson(hop, ci0, precond, tol=fci.conv_tol, lindep=fci.lindep)
e, c = fci.eig(hop, ci0, precond, tol=tol, lindep=lindep,
max_cycle=max_cycle, max_space=max_space, nroots=nroots,
max_memory=max_memory, verbose=verbose, follow_state=True,
tol_residual=tol_residual, **kwargs)
if nroots > 1:
return e+ecore, [ci.reshape(na,nb) for ci in c]
else:
return e+ecore, c.reshape(na,nb)
def kernel_ms0(fci,
h1e,
eri,
norb,
nelec,
ci0=None,
link_index=None,
tol=None,
lindep=None,
max_cycle=None,
max_space=None,
nroots=None,
davidson_only=None,
pspace_size=None,
max_memory=None,
verbose=None,
ecore=0,
**kwargs):
if nroots is None: nroots = fci.nroots
if davidson_only is None: davidson_only = fci.davidson_only
if pspace_size is None: pspace_size = fci.pspace_size
if max_memory is None:
max_memory = fci.max_memory - lib.current_memory()[0]
log = logger.new_logger(fci, verbose)
assert (fci.spin is None or fci.spin == 0)
assert (0 <= numpy.sum(nelec) <= norb * 2)
link_index = _unpack(norb, nelec, link_index)
h1e = numpy.ascontiguousarray(h1e)
eri = numpy.ascontiguousarray(eri)
na = link_index.shape[0]
if max_memory < na**2 * 6 * 8e-6:
log.warn(
'Not enough memory for FCI solver. '
'The minimal requirement is %.0f MB', na**2 * 60e-6)
hdiag = fci.make_hdiag(h1e, eri, norb, nelec)
nroots = min(hdiag.size, nroots)
try:
addr, h0 = fci.pspace(h1e, eri, norb, nelec, hdiag,
max(pspace_size, nroots))
if pspace_size > 0:
pw, pv = fci.eig(h0)
else:
pw = pv = None
if pspace_size >= na * na and ci0 is None and not davidson_only:
# The degenerated wfn can break symmetry. The davidson iteration with proper
# initial guess doesn't have this issue
if na * na == 1:
return pw[0] + ecore, pv[:, 0].reshape(1, 1)
elif nroots > 1:
civec = numpy.empty((nroots, na * na))
civec[:, addr] = pv[:, :nroots].T
civec = civec.reshape(nroots, na, na)
try:
return pw[:nroots] + ecore, [_check_(ci) for ci in civec]
except ValueError:
pass
elif abs(pw[0] - pw[1]) > 1e-12:
civec = numpy.empty((na * na))
civec[addr] = pv[:, 0]
civec = civec.reshape(na, na)
civec = lib.transpose_sum(civec) * .5
# direct diagonalization may lead to triplet ground state
##TODO: optimize initial guess. Using pspace vector as initial guess may have
## spin problems. The 'ground state' of psapce vector may have different spin
## state to the true ground state.
try:
return pw[0] + ecore, _check_(civec.reshape(na, na))
except ValueError:
pass
except NotImplementedError:
addr = [0]
pw = pv = None
precond = fci.make_precond(hdiag, pw, pv, addr)
h2e = fci.absorb_h1e(h1e, eri, norb, nelec, .5)
def hop(c):
hc = fci.contract_2e(h2e, c.reshape(na, na), norb, nelec, link_index)
return hc.ravel()
#TODO: check spin of initial guess
if ci0 is None:
if callable(getattr(fci, 'get_init_guess', None)):
ci0 = lambda: fci.get_init_guess(norb, nelec, nroots, hdiag)
else:
def ci0():
x0 = []
for i in range(nroots):
x = numpy.zeros((na, na))
addra = addr[i] // na
addrb = addr[i] % na
if addra == addrb:
x[addra, addrb] = 1
else:
x[addra, addrb] = x[addrb, addra] = numpy.sqrt(.5)
x0.append(x.ravel())
return x0
elif not callable(ci0):
if isinstance(ci0, numpy.ndarray) and ci0.size == na * na:
ci0 = [ci0.ravel()]
else:
ci0 = [x.ravel() for x in ci0]
if tol is None: tol = fci.conv_tol
if lindep is None: lindep = fci.lindep
if max_cycle is None: max_cycle = fci.max_cycle
if max_space is None: max_space = fci.max_space
tol_residual = getattr(fci, 'conv_tol_residual', None)
with lib.with_omp_threads(fci.threads):
#e, c = lib.davidson(hop, ci0, precond, tol=fci.conv_tol, lindep=fci.lindep)
e, c = fci.eig(hop,
ci0,
precond,
tol=tol,
lindep=lindep,
max_cycle=max_cycle,
max_space=max_space,
nroots=nroots,
max_memory=max_memory,
verbose=log,
follow_state=True,
tol_residual=tol_residual,
**kwargs)
if nroots > 1:
return e + ecore, [_check_(ci.reshape(na, na)) for ci in c]
else:
return e + ecore, _check_(c.reshape(na, na))
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
self.mol = lib.chkfile.load_mol(self.chkfile)
self.nelectron = self.mol.nelectron
self.charge = self.mol.charge
self.spin = self.mol.spin
self.natm = self.mol.natm
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist()
for atom in self.mol._atom])
self.charges = self.mol.atom_charges()
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff.shape
self.nprims = nprims
self.nmo = nmo
if self.charges[self.inuc] == 1:
self.rad = grid.BRAGG[self.charges[self.inuc]]
else:
self.rad = grid.BRAGG[self.charges[self.inuc]] * 0.5
if (self.corr):
self.rdm1 = lib.chkfile.load(self.chkfile, 'rdm/rdm1')
natocc, natorb = numpy.linalg.eigh(self.rdm1)
natorb = numpy.dot(self.mo_coeff, natorb)
self.mo_coeff = natorb
self.mo_occ = natocc
nocc = self.mo_occ[abs(self.mo_occ) > self.occdrop]
nocc = len(nocc)
self.nocc = nocc
idx = 'atom' + str(self.inuc)
with h5py.File(self.surfile) as f:
self.xnuc = f[idx + '/xnuc'].value
self.xyzrho = f[idx + '/xyzrho'].value
self.npang = f[idx + '/npang'].value
self.ntrial = f[idx + '/ntrial'].value
self.rmin = f[idx + '/rmin'].value
self.rmax = f[idx + '/rmax'].value
self.rsurf = f[idx + '/rsurf'].value
self.nlimsurf = f[idx + '/nlimsurf'].value
self.agrids = f[idx + '/coords'].value
self.brad = self.rmin * self.betafac
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudr == 'legendre'):
self.iqudr = 1
if (self.biqudr == 'legendre'):
self.biqudr = 1
if (self.mapr == 'becke'):
self.mapr = 1
elif (self.mapr == 'exp'):
self.mapr = 2
elif (self.mapr == 'none'):
self.mapr = 0
if (self.bmapr == 'becke'):
self.bmapr = 1
elif (self.bmapr == 'exp'):
self.bmapr = 2
elif (self.bmapr == 'none'):
self.bmapr = 0
with lib.with_omp_threads(self.nthreads):
brprops = int_beta(self)
rprops = out_beta(self)
logger.info(self, 'Write info to HDF5 file')
atom_dic = {
'inprops': brprops,
'outprops': rprops,
'blmax': self.blmax,
'lmax': self.lmax,
'totprops': (brprops + rprops)
}
lib.chkfile.save(self.surfile, 'qlm' + str(self.inuc), atom_dic)
logger.info(
self, '*-> Total Qlm(0,0) (s) %f' % (rprops[0] + brprops[0]))
logger.info(
self, '*-> Total Qlm(1,-1) (py) %f' % (rprops[1] + brprops[1]))
logger.info(
self, '*-> Total Qlm(1,0) (pz) %f' % (rprops[2] + brprops[2]))
logger.info(
self, '*-> Total Qlm(1,1) (px) %f' % (rprops[3] + brprops[3]))
logger.info(
self, '*-> Total Qlm(2,-2) (dxy) %f' % (rprops[4] + brprops[4]))
logger.info(
self, '*-> Total Qlm(2,-1) (dyz) %f' % (rprops[5] + brprops[5]))
logger.info(
self, '*-> Total Qlm(2,0) (dz2) %f' % (rprops[6] + brprops[6]))
logger.info(
self, '*-> Total Qlm(2,1) (xz) %f' % (rprops[7] + brprops[7]))
logger.info(
self, '*-> Total Qlm(2,2) (dx2-y2) %f' % (rprops[8] + brprops[8]))
logger.info(self, '')
logger.info(self, 'Qlm of atom %d done', self.inuc)
logger.timer(self, 'Qlm build', *t0)
return self
def build(self):
t0 = (time.clock(), time.time())
lib.logger.TIMER_LEVEL = 3
cell = libpbc.chkfile.load_cell(self.chkfile)
cell.ecp = None
self.cell = cell
self.a = self.cell.lattice_vectors()
self.b = self.cell.reciprocal_vectors()
self.vol = self.cell.vol
self.nelectron = self.cell.nelectron
self.charge = self.cell.charge
self.spin = self.cell.spin
self.natm = self.cell.natm
self.kpts = lib.chkfile.load(self.chkfile, 'kcell/kpts')
self.nkpts = len(self.kpts)
self.ls = cell.get_lattice_Ls(dimension=3)
self.ls = self.ls[numpy.argsort(lib.norm(self.ls, axis=1))]
self.atm = numpy.asarray(cell._atm, dtype=numpy.int32, order='C')
self.bas = numpy.asarray(cell._bas, dtype=numpy.int32, order='C')
self.env = numpy.asarray(cell._env, dtype=numpy.double, order='C')
self.nbas = self.bas.shape[0]
self.ao_loc = cell.ao_loc_nr()
self.shls_slice = (0, self.nbas)
sh0, sh1 = self.shls_slice
self.nao = self.ao_loc[sh1] - self.ao_loc[sh0]
self.non0tab = numpy.empty((1,self.nbas), dtype=numpy.int8)
# non0tab stores the number of images to be summed in real space.
# Initializing it to 255 means all images are summed
self.non0tab[:] = 0xff
self.coords = numpy.asarray([(numpy.asarray(atom[1])).tolist() for atom in cell._atom])
self.charges = cell.atom_charges()
self.mo_coeff = lib.chkfile.load(self.chkfile, 'scf/mo_coeff')
self.mo_occ = lib.chkfile.load(self.chkfile, 'scf/mo_occ')
nprims, nmo = self.mo_coeff[0].shape
self.nprims = nprims
self.nmo = nmo
self.cart = cell.cart
if (not self.leb):
self.npang = self.npphi*self.nptheta
self.rcut = _estimate_rcut(self)
kpts = numpy.reshape(self.kpts, (-1,3))
kpts_lst = numpy.reshape(kpts, (-1,3))
self.explk = numpy.exp(1j * numpy.asarray(numpy.dot(self.ls, kpts_lst.T), order='C'))
if (self.ntrial%2 == 0): self.ntrial += 1
geofac = numpy.power(((self.rmaxsurf-0.1)/self.rprimer),(1.0/(self.ntrial-1.0)))
self.rpru = numpy.zeros((self.ntrial))
for i in range(self.ntrial):
self.rpru[i] = self.rprimer*numpy.power(geofac,(i+1)-1)
self.rsurf = numpy.zeros((self.npang,self.ntrial), order='C')
self.nlimsurf = numpy.zeros((self.npang), dtype=numpy.int32)
if self.verbose >= logger.WARN:
self.check_sanity()
if self.verbose > logger.NOTE:
self.dump_input()
if (self.iqudt == 'legendre'):
self.iqudt = 1
if (self.leb):
self.grids = grid.lebgrid(self.npang)
else:
self.grids = grid.anggrid(self.iqudt,self.nptheta,self.npphi)
self.xyzrho = numpy.zeros((self.natm,3))
t = time.time()
logger.info(self,'Time finding nucleus %.3f (sec)' % (time.time()-t))
if (self.backend == 'rkck'):
backend = 1
elif (self.backend == 'rkdp'):
backend = 2
else:
raise NotImplementedError('Only rkck or rkdp ODE solver yet available')
ct_ = numpy.asarray(self.grids[:,0], order='C')
st_ = numpy.asarray(self.grids[:,1], order='C')
cp_ = numpy.asarray(self.grids[:,2], order='C')
sp_ = numpy.asarray(self.grids[:,3], order='C')
mo_coeff = numpy.zeros((self.nkpts,self.nprims,self.nmo), dtype=numpy.complex128)
mo_occ = numpy.zeros((self.nkpts,self.nmo))
for k in range(self.nkpts):
mo_coeff[k,:,:] = self.mo_coeff[k][:,:]
mo_occ[k,:] = self.mo_occ[k][:]
t = time.time()
feval = 'surf_driver'
drv = getattr(libaim, feval)
with lib.with_omp_threads(self.nthreads):
drv(ctypes.c_int(self.inuc),
self.xyzrho.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.npang),
ct_.ctypes.data_as(ctypes.c_void_p),
st_.ctypes.data_as(ctypes.c_void_p),
cp_.ctypes.data_as(ctypes.c_void_p),
sp_.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.ntrial),
self.rpru.ctypes.data_as(ctypes.c_void_p),
ctypes.c_double(self.epsiscp),
ctypes.c_double(self.epsroot),
ctypes.c_double(self.rmaxsurf),
ctypes.c_int(backend),
ctypes.c_double(self.epsilon),
ctypes.c_double(self.step),
ctypes.c_int(self.mstep),
ctypes.c_int(self.natm),
self.coords.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.cart),
ctypes.c_int(self.nmo),
ctypes.c_int(self.nprims),
self.atm.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.nbas),
self.bas.ctypes.data_as(ctypes.c_void_p),
self.env.ctypes.data_as(ctypes.c_void_p),
self.ao_loc.ctypes.data_as(ctypes.c_void_p),
mo_coeff.ctypes.data_as(ctypes.c_void_p),
mo_occ.ctypes.data_as(ctypes.c_void_p),
ctypes.c_double(self.occdrop),
#
self.a.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(len(self.ls)),
self.ls.ctypes.data_as(ctypes.c_void_p),
ctypes.c_int(self.nkpts),
self.explk.ctypes.data_as(ctypes.c_void_p),
self.rcut.ctypes.data_as(ctypes.c_void_p),
self.non0tab.ctypes.data_as(ctypes.c_void_p),
#
self.nlimsurf.ctypes.data_as(ctypes.c_void_p),
self.rsurf.ctypes.data_as(ctypes.c_void_p))
for i in range(self.nkpts):
print k,self.mo_occ[k][:]
logger.info(self,'Time finding surface %.3f (sec)' % (time.time()-t))
r = numpy.array([0.00000, 0.00000, 0.00000])
r = numpy.reshape(r, (-1,3))
ao = dft.numint.eval_ao_kpts(self.cell, r, kpts=self.kpts, deriv=1)
print rhograd(self,[0,0,0])
logger.info(self,'Surface of atom %d saved',self.inuc)
logger.timer(self,'BaderSurf build', *t0)
return self
def kernel_ms0(fci, h1e, eri, norb, nelec, ci0=None, link_index=None,
tol=None, lindep=None, max_cycle=None, max_space=None,
nroots=None, davidson_only=None, pspace_size=None,
max_memory=None, verbose=None, ecore=0, **kwargs):
if nroots is None: nroots = fci.nroots
if davidson_only is None: davidson_only = fci.davidson_only
if pspace_size is None: pspace_size = fci.pspace_size
assert(fci.spin is None or fci.spin == 0)
assert(0 <= numpy.sum(nelec) <= norb*2)
link_index = _unpack(norb, nelec, link_index)
h1e = numpy.ascontiguousarray(h1e)
eri = numpy.ascontiguousarray(eri)
na = link_index.shape[0]
hdiag = fci.make_hdiag(h1e, eri, norb, nelec)
nroots = min(hdiag.size, nroots)
try:
addr, h0 = fci.pspace(h1e, eri, norb, nelec, hdiag, max(pspace_size,nroots))
if pspace_size > 0:
pw, pv = fci.eig(h0)
else:
pw = pv = None
if pspace_size >= na*na and ci0 is None and not davidson_only:
# The degenerated wfn can break symmetry. The davidson iteration with proper
# initial guess doesn't have this issue
if na*na == 1:
return pw[0]+ecore, pv[:,0].reshape(1,1)
elif nroots > 1:
civec = numpy.empty((nroots,na*na))
civec[:,addr] = pv[:,:nroots].T
civec = civec.reshape(nroots,na,na)
try:
return pw[:nroots]+ecore, [_check_(ci) for ci in civec]
except ValueError:
pass
elif abs(pw[0]-pw[1]) > 1e-12:
civec = numpy.empty((na*na))
civec[addr] = pv[:,0]
civec = civec.reshape(na,na)
civec = lib.transpose_sum(civec) * .5
# direct diagonalization may lead to triplet ground state
##TODO: optimize initial guess. Using pspace vector as initial guess may have
## spin problems. The 'ground state' of psapce vector may have different spin
## state to the true ground state.
try:
return pw[0]+ecore, _check_(civec.reshape(na,na))
except ValueError:
pass
except NotImplementedError:
addr = [0]
pw = pv = None
precond = fci.make_precond(hdiag, pw, pv, addr)
h2e = fci.absorb_h1e(h1e, eri, norb, nelec, .5)
def hop(c):
hc = fci.contract_2e(h2e, c.reshape(na,na), norb, nelec, link_index)
return hc.ravel()
#TODO: check spin of initial guess
if ci0 is None:
if callable(getattr(fci, 'get_init_guess', None)):
ci0 = lambda: fci.get_init_guess(norb, nelec, nroots, hdiag)
else:
def ci0():
x0 = []
for i in range(nroots):
x = numpy.zeros((na,na))
addra = addr[i] // na
addrb = addr[i] % na
if addra == addrb:
x[addra,addrb] = 1
else:
x[addra,addrb] = x[addrb,addra] = numpy.sqrt(.5)
x0.append(x.ravel())
return x0
elif not callable(ci0):
if isinstance(ci0, numpy.ndarray) and ci0.size == na*na:
ci0 = [ci0.ravel()]
else:
ci0 = [x.ravel() for x in ci0]
if tol is None: tol = fci.conv_tol
if lindep is None: lindep = fci.lindep
if max_cycle is None: max_cycle = fci.max_cycle
if max_space is None: max_space = fci.max_space
if max_memory is None: max_memory = fci.max_memory
if verbose is None: verbose = logger.Logger(fci.stdout, fci.verbose)
tol_residual = getattr(fci, 'conv_tol_residual', None)
with lib.with_omp_threads(fci.threads):
#e, c = lib.davidson(hop, ci0, precond, tol=fci.conv_tol, lindep=fci.lindep)
e, c = fci.eig(hop, ci0, precond, tol=tol, lindep=lindep,
max_cycle=max_cycle, max_space=max_space, nroots=nroots,
max_memory=max_memory, verbose=verbose, follow_state=True,
tol_residual=tol_residual, **kwargs)
if nroots > 1:
return e+ecore, [_check_(ci.reshape(na,na)) for ci in c]
else:
return e+ecore, _check_(c.reshape(na,na))