def test_rcut_vs_ke_cut(self):
xc = 'lda,'
with lib.temporary_env(multigrid, TASKS_TYPE='rcut'):
mg_df = multigrid.MultiGridFFTDF(cell_orth)
n1, exc1, v1 = multigrid.nr_rks(mg_df, xc, dm1, kpts=kpts)
self.assertEqual(len(mg_df.tasks), 3)
with lib.temporary_env(multigrid, TASKS_TYPE='ke_cut'):
mg_df = multigrid.MultiGridFFTDF(cell_orth)
n2, exc2, v2 = multigrid.nr_rks(mg_df, xc, dm1, kpts=kpts)
self.assertEqual(len(mg_df.tasks), 6)
self.assertAlmostEqual(n1, n2, 8)
self.assertAlmostEqual(exc1, exc2, 8)
self.assertAlmostEqual(abs(v1-v2).max(), 0, 8)
def test_rcut_vs_ke_cut(self):
xc = 'lda,'
with lib.temporary_env(multigrid, TASKS_TYPE='rcut'):
mg_df = multigrid.MultiGridFFTDF(cell_orth)
n1, exc1, v1 = multigrid.nr_rks(mg_df, xc, dm1, kpts=kpts)
self.assertEqual(len(mg_df.tasks), 3)
with lib.temporary_env(multigrid, TASKS_TYPE='ke_cut'):
mg_df = multigrid.MultiGridFFTDF(cell_orth)
n2, exc2, v2 = multigrid.nr_rks(mg_df, xc, dm1, kpts=kpts)
self.assertEqual(len(mg_df.tasks), 6)
self.assertAlmostEqual(n1, n2, 8)
self.assertAlmostEqual(exc1, exc2, 8)
self.assertAlmostEqual(abs(v1 - v2).max(), 0, 8)
def test_orth_rks_lda_kpts(self):
xc = 'lda,'
mydf = df.FFTDF(cell_orth)
ni = dft.numint.KNumInt()
n, exc0, ref = ni.nr_rks(cell_orth, mydf.grids, xc, dm, 0, kpts=kpts)
mydf = multigrid.MultiGridFFTDF(cell_orth)
n, exc1, vxc = multigrid.nr_rks(mydf, xc, dm, kpts=kpts)
self.assertAlmostEqual(float(abs(ref-vxc).max()), 0, 9)
self.assertAlmostEqual(abs(exc0-exc1).max(), 0, 8)
def test_orth_rks_lda_kpts(self):
xc = 'lda,'
mydf = df.FFTDF(cell_orth)
ni = dft.numint.KNumInt()
n, exc0, ref = ni.nr_rks(cell_orth, mydf.grids, xc, dm, 0, kpts=kpts)
mydf = multigrid.MultiGridFFTDF(cell_orth)
n, exc1, vxc = multigrid.nr_rks(mydf, xc, dm, kpts=kpts)
self.assertAlmostEqual(float(abs(ref - vxc).max()), 0, 9)
self.assertAlmostEqual(abs(exc0 - exc1).max(), 0, 8)
def test_orth_rks_gga_kpts(self):
xc = 'b88,'
mydf = df.FFTDF(cell_orth)
ni = dft.numint.KNumInt()
n, exc0, ref = ni.nr_rks(cell_orth, mydf.grids, xc, dm, hermi=1, kpts=kpts)
ref += mydf.get_jk(dm, hermi=1, with_k=False, kpts=kpts)[0]
mydf = multigrid.MultiGridFFTDF(cell_orth)
n, exc1, vxc = multigrid.nr_rks(mydf, xc, dm, hermi=1, kpts=kpts, with_j=True)
self.assertAlmostEqual(float(abs(ref-vxc).max()), 0, 9)
self.assertAlmostEqual(abs(exc0-exc1).max(), 0, 8)
def test_orth_rks_gga_kpts(self):
xc = 'b88,'
mydf = df.FFTDF(cell_orth)
ni = dft.numint.KNumInt()
n, exc0, ref = ni.nr_rks(cell_orth,
mydf.grids,
xc,
dm,
hermi=1,
kpts=kpts)
ref += mydf.get_jk(dm, hermi=1, with_k=False, kpts=kpts)[0]
mydf = multigrid.MultiGridFFTDF(cell_orth)
n, exc1, vxc = multigrid.nr_rks(mydf,
xc,
dm,
hermi=1,
kpts=kpts,
with_j=True)
self.assertAlmostEqual(float(abs(ref - vxc).max()), 0, 9)
self.assertAlmostEqual(abs(exc0 - exc1).max(), 0, 8)
def get_veff(ks,
cell=None,
dm=None,
dm_last=0,
vhf_last=0,
hermi=1,
kpt=None,
kpts_band=None):
'''Coulomb + XC functional
.. note::
This function will change the ks object.
Args:
ks : an instance of :class:`RKS`
XC functional are controlled by ks.xc attribute. Attribute
ks.grids might be initialized.
dm : ndarray or list of ndarrays
A density matrix or a list of density matrices
Returns:
matrix Veff = J + Vxc. Veff can be a list matrices, if the input
dm is a list of density matrices.
'''
if cell is None: cell = ks.cell
if dm is None: dm = ks.make_rdm1()
if kpt is None: kpt = ks.kpt
t0 = (time.clock(), time.time())
omega, alpha, hyb = ks._numint.rsh_and_hybrid_coeff(ks.xc, spin=cell.spin)
if abs(omega) > 1e-10:
raise NotImplementedError
hybrid = abs(hyb) > 1e-10
if not hybrid and isinstance(ks.with_df, multigrid.MultiGridFFTDF):
n, exc, vxc = multigrid.nr_rks(ks.with_df,
ks.xc,
dm,
hermi,
kpt.reshape(1, 3),
kpts_band,
with_j=True,
return_j=False)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
return vxc
ground_state = (isinstance(dm, numpy.ndarray) and dm.ndim == 2
and kpts_band is None)
# Use grids.non0tab to detect whether grids are initialized. For
# UniformGrids, grids.coords as a property cannot indicate whehter grids are
# initialized.
if ks.grids.non0tab is None:
ks.grids.build(with_non0tab=True)
if (isinstance(ks.grids, gen_grid.BeckeGrids)
and ks.small_rho_cutoff > 1e-20 and ground_state):
ks.grids = prune_small_rho_grids_(ks, cell, dm, ks.grids, kpt)
t0 = logger.timer(ks, 'setting up grids', *t0)
if hermi == 2: # because rho = 0
n, exc, vxc = 0, 0, 0
else:
n, exc, vxc = ks._numint.nr_rks(cell, ks.grids, ks.xc, dm, 0, kpt,
kpts_band)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
if not hybrid:
vj = ks.get_j(cell, dm, hermi, kpt, kpts_band)
vxc += vj
else:
if getattr(ks.with_df, '_j_only', False): # for GDF and MDF
ks.with_df._j_only = False
vj, vk = ks.get_jk(cell, dm, hermi, kpt, kpts_band)
vxc += vj - vk * (hyb * .5)
if ground_state:
exc -= numpy.einsum('ij,ji', dm, vk).real * .5 * hyb * .5
if ground_state:
ecoul = numpy.einsum('ij,ji', dm, vj).real * .5
else:
ecoul = None
vxc = lib.tag_array(vxc, ecoul=ecoul, exc=exc, vj=None, vk=None)
return vxc
def get_veff(ks, cell=None, dm=None, dm_last=0, vhf_last=0, hermi=1,
kpts=None, kpts_band=None):
'''Coulomb + XC functional
.. note::
This is a replica of pyscf.dft.rks.get_veff with kpts added.
This function will change the ks object.
Args:
ks : an instance of :class:`RKS`
XC functional are controlled by ks.xc attribute. Attribute
ks.grids might be initialized.
dm : ndarray or list of ndarrays
A density matrix or a list of density matrices
Returns:
Veff : (nkpts, nao, nao) or (*, nkpts, nao, nao) ndarray
Veff = J + Vxc.
'''
if cell is None: cell = ks.cell
if dm is None: dm = ks.make_rdm1()
if kpts is None: kpts = ks.kpts
t0 = (logger.process_clock(), logger.perf_counter())
omega, alpha, hyb = ks._numint.rsh_and_hybrid_coeff(ks.xc, spin=cell.spin)
hybrid = abs(hyb) > 1e-10 or abs(alpha) > 1e-10
if not hybrid and isinstance(ks.with_df, multigrid.MultiGridFFTDF):
n, exc, vxc = multigrid.nr_rks(ks.with_df, ks.xc, dm, hermi,
kpts, kpts_band,
with_j=True, return_j=False)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
return vxc
# ndim = 3 : dm.shape = (nkpts, nao, nao)
ground_state = (isinstance(dm, np.ndarray) and dm.ndim == 3 and
kpts_band is None)
# For UniformGrids, grids.coords does not indicate whehter grids are initialized
if ks.grids.non0tab is None:
ks.grids.build(with_non0tab=True)
if (isinstance(ks.grids, gen_grid.BeckeGrids) and
ks.small_rho_cutoff > 1e-20 and ground_state):
ks.grids = rks.prune_small_rho_grids_(ks, cell, dm, ks.grids, kpts)
t0 = logger.timer(ks, 'setting up grids', *t0)
if hermi == 2: # because rho = 0
n, exc, vxc = 0, 0, 0
else:
n, exc, vxc = ks._numint.nr_rks(cell, ks.grids, ks.xc, dm, hermi,
kpts, kpts_band)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
weight = 1./len(kpts)
if not hybrid:
vj = ks.get_j(cell, dm, hermi, kpts, kpts_band)
vxc += vj
else:
if getattr(ks.with_df, '_j_only', False): # for GDF and MDF
ks.with_df._j_only = False
vj, vk = ks.get_jk(cell, dm, hermi, kpts, kpts_band)
vk *= hyb
if abs(omega) > 1e-10:
vklr = ks.get_k(cell, dm, hermi, kpts, kpts_band, omega=omega)
vklr *= (alpha - hyb)
vk += vklr
vxc += vj - vk * .5
if ground_state:
exc -= np.einsum('Kij,Kji', dm, vk).real * .5 * .5 * weight
if ground_state:
ecoul = np.einsum('Kij,Kji', dm, vj).real * .5 * weight
else:
ecoul = None
vxc = lib.tag_array(vxc, ecoul=ecoul, exc=exc, vj=None, vk=None)
return vxc
def get_veff(ks, cell=None, dm=None, dm_last=0, vhf_last=0, hermi=1,
kpts=None, kpts_band=None):
'''Coulomb + XC functional
.. note::
This is a replica of pyscf.dft.rks.get_veff with kpts added.
This function will change the ks object.
Args:
ks : an instance of :class:`RKS`
XC functional are controlled by ks.xc attribute. Attribute
ks.grids might be initialized.
dm : ndarray or list of ndarrays
A density matrix or a list of density matrices
Returns:
Veff : (nkpts, nao, nao) or (*, nkpts, nao, nao) ndarray
Veff = J + Vxc.
'''
if cell is None: cell = ks.cell
if dm is None: dm = ks.make_rdm1()
if kpts is None: kpts = ks.kpts
t0 = (time.clock(), time.time())
omega, alpha, hyb = ks._numint.rsh_and_hybrid_coeff(ks.xc, spin=cell.spin)
hybrid = abs(hyb) > 1e-10
if not hybrid and isinstance(ks.with_df, multigrid.MultiGridFFTDF):
n, exc, vxc = multigrid.nr_rks(ks.with_df, ks.xc, dm, hermi,
kpts, kpts_band,
with_j=True, return_j=False)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
return vxc
# ndim = 3 : dm.shape = (nkpts, nao, nao)
ground_state = (isinstance(dm, np.ndarray) and dm.ndim == 3 and
kpts_band is None)
# For UniformGrids, grids.coords does not indicate whehter grids are initialized
if ks.grids.non0tab is None:
ks.grids.build(with_non0tab=True)
if (isinstance(ks.grids, gen_grid.BeckeGrids) and
ks.small_rho_cutoff > 1e-20 and ground_state):
ks.grids = rks.prune_small_rho_grids_(ks, cell, dm, ks.grids, kpts)
t0 = logger.timer(ks, 'setting up grids', *t0)
if hermi == 2: # because rho = 0
n, exc, vxc = 0, 0, 0
else:
n, exc, vxc = ks._numint.nr_rks(cell, ks.grids, ks.xc, dm, 0,
kpts, kpts_band)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
weight = 1./len(kpts)
if not hybrid:
vj = ks.get_j(cell, dm, hermi, kpts, kpts_band)
vxc += vj
else:
if getattr(ks.with_df, '_j_only', False): # for GDF and MDF
ks.with_df._j_only = False
vj, vk = ks.get_jk(cell, dm, hermi, kpts, kpts_band)
vxc += vj - vk * (hyb * .5)
if ground_state:
exc -= np.einsum('Kij,Kji', dm, vk).real * .5 * hyb*.5 * weight
if ground_state:
ecoul = np.einsum('Kij,Kji', dm, vj).real * .5 * weight
else:
ecoul = None
vxc = lib.tag_array(vxc, ecoul=ecoul, exc=exc, vj=None, vk=None)
return vxc
def get_veff(ks, cell=None, dm=None, dm_last=0, vhf_last=0, hermi=1,
kpt=None, kpts_band=None):
'''Coulomb + XC functional
.. note::
This function will change the ks object.
Args:
ks : an instance of :class:`RKS`
XC functional are controlled by ks.xc attribute. Attribute
ks.grids might be initialized.
dm : ndarray or list of ndarrays
A density matrix or a list of density matrices
Returns:
matrix Veff = J + Vxc. Veff can be a list matrices, if the input
dm is a list of density matrices.
'''
if cell is None: cell = ks.cell
if dm is None: dm = ks.make_rdm1()
if kpt is None: kpt = ks.kpt
t0 = (time.clock(), time.time())
omega, alpha, hyb = ks._numint.rsh_and_hybrid_coeff(ks.xc, spin=cell.spin)
hybrid = abs(hyb) > 1e-10
if not hybrid and isinstance(ks.with_df, multigrid.MultiGridFFTDF):
n, exc, vxc = multigrid.nr_rks(ks.with_df, ks.xc, dm, hermi,
kpt.reshape(1,3), kpts_band,
with_j=True, return_j=False)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
return vxc
ground_state = (isinstance(dm, numpy.ndarray) and dm.ndim == 2
and kpts_band is None)
# Use grids.non0tab to detect whether grids are initialized. For
# UniformGrids, grids.coords as a property cannot indicate whehter grids are
# initialized.
if ks.grids.non0tab is None:
ks.grids.build(with_non0tab=True)
if (isinstance(ks.grids, gen_grid.BeckeGrids) and
ks.small_rho_cutoff > 1e-20 and ground_state):
ks.grids = prune_small_rho_grids_(ks, cell, dm, ks.grids, kpt)
t0 = logger.timer(ks, 'setting up grids', *t0)
if hermi == 2: # because rho = 0
n, exc, vxc = 0, 0, 0
else:
n, exc, vxc = ks._numint.nr_rks(cell, ks.grids, ks.xc, dm, 0,
kpt, kpts_band)
logger.debug(ks, 'nelec by numeric integration = %s', n)
t0 = logger.timer(ks, 'vxc', *t0)
if not hybrid:
vj = ks.get_j(cell, dm, hermi, kpt, kpts_band)
vxc += vj
else:
if getattr(ks.with_df, '_j_only', False): # for GDF and MDF
ks.with_df._j_only = False
vj, vk = ks.get_jk(cell, dm, hermi, kpt, kpts_band)
vxc += vj - vk * (hyb * .5)
if ground_state:
exc -= numpy.einsum('ij,ji', dm, vk).real * .5 * hyb*.5
if ground_state:
ecoul = numpy.einsum('ij,ji', dm, vj).real * .5
else:
ecoul = None
vxc = lib.tag_array(vxc, ecoul=ecoul, exc=exc, vj=None, vk=None)
return vxc
