def test_incore_s4(self):
eri4 = ao2mo.restore(4, mf._eri, nmo)
dm = mf.make_rdm1()
vj0, vk0 = _vhf.incore(eri4, dm, hermi=1)
vj1, vk1 = scf.hf.get_jk(mol, dm, hermi=1)
self.assertTrue(numpy.allclose(vj0, vj1))
self.assertTrue(numpy.allclose(vk0, vk1))
def test_incore_s4(self):
eri4 = ao2mo.restore(4, mf._eri, nmo)
dm = mf.make_rdm1()
vj0, vk0 = _vhf.incore(eri4, dm, hermi=1)
vj1, vk1 = scf.hf.get_jk(mol, dm, hermi=1)
self.assertTrue(numpy.allclose(vj0,vj1))
self.assertTrue(numpy.allclose(vk0,vk1))
def dot_eri_dm(eri, dm, hermi=0):
'''Compute J, K matrices in terms of the given 2-electron integrals and
density matrix:
J ~ numpy.einsum('pqrs,qp->rs', eri, dm)
K ~ numpy.einsum('pqrs,qr->ps', eri, dm)
Args:
eri : ndarray
8-fold or 4-fold ERIs
dm : ndarray or list of ndarrays
A density matrix or a list of density matrices
Kwargs:
hermi : int
Whether J, K matrix is hermitian
| 0 : no hermitian or symmetric
| 1 : hermitian
| 2 : anti-hermitian
Returns:
Depending on the given dm, the function returns one J and one K matrix,
or a list of J matrices and a list of K matrices, corresponding to the
input density matrices.
Examples:
>>> from pyscf import gto, scf
>>> from pyscf.scf import _vhf
>>> mol = gto.M(atom='H 0 0 0; H 0 0 1.1')
>>> eri = _vhf.int2e_sph(mol._atm, mol._bas, mol._env)
>>> dms = numpy.random.random((3,mol.nao_nr(),mol.nao_nr()))
>>> j, k = scf.hf.dot_eri_dm(eri, dms, hermi=0)
>>> print(j.shape)
(3, 2, 2)
'''
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
vj, vk = _vhf.incore(eri, dm, hermi=hermi)
else:
dm = numpy.asarray(dm, order='C')
nao = dm.shape[-1]
dms = dm.reshape(-1, nao, nao)
vjk = [_vhf.incore(eri, dmi, hermi=hermi) for dmi in dms]
vj = numpy.array([v[0] for v in vjk]).reshape(dm.shape)
vk = numpy.array([v[1] for v in vjk]).reshape(dm.shape)
return vj, vk
def get_jk(agf2, eri, rdm1, with_j=True, with_k=True):
''' Get the J/K matrices.
Args:
eri : ndarray or H5 dataset
Electronic repulsion integrals (NOT as _ChemistsERIs)
rdm1 : 2D array
Reduced density matrix
Kwargs:
with_j : bool
Whether to compute J. Default value is True
with_k : bool
Whether to compute K. Default value is True
Returns:
tuple of ndarrays corresponding to J and K, if either are
not requested then they are set to None.
'''
if isinstance(eri, np.ndarray):
vj, vk = _vhf.incore(eri, rdm1, with_j=with_j, with_k=with_k)
else:
nmo = rdm1.shape[0]
npair = nmo * (nmo + 1) // 2
vj = vk = None
if with_j:
rdm1_tril = lib.pack_tril(rdm1 + np.tril(rdm1, k=-1))
vj = np.zeros_like(rdm1_tril)
if with_k:
vk = np.zeros_like(rdm1)
blksize = _agf2.get_blksize(agf2.max_memory, (nmo * npair, nmo**3))
blksize = min(1, max(BLKMIN, blksize))
logger.debug1(agf2, 'blksize (ragf2.get_jk) = %d' % blksize)
tril2sq = lib.square_mat_in_trilu_indices(nmo)
for p0, p1 in lib.prange(0, nmo, blksize):
idx = list(np.concatenate(tril2sq[p0:p1]))
eri0 = eri[idx]
# vj built in tril layout with scaled rdm1_tril
if with_j:
vj[idx] = np.dot(eri0, rdm1_tril)
if with_k:
eri0 = lib.unpack_tril(eri0, axis=-1)
eri0 = eri0.reshape(p1 - p0, nmo, nmo, nmo)
vk[p0:p1] = lib.einsum('ijkl,jk->il', eri0, rdm1)
if with_j:
vj = lib.unpack_tril(vj)
return vj, vk
def dot_eri_dm(eri, dm, hermi=0):
'''Compute J, K matrices in terms of the given 2-electron integrals and
density matrix:
J ~ numpy.einsum('pqrs,qp->rs', eri, dm)
K ~ numpy.einsum('pqrs,qr->ps', eri, dm)
Args:
eri : ndarray
8-fold or 4-fold ERIs
dm : ndarray or list of ndarrays
A density matrix or a list of density matrices
Kwargs:
hermi : int
Whether J, K matrix is hermitian
| 0 : no hermitian or symmetric
| 1 : hermitian
| 2 : anti-hermitian
Returns:
Depending on the given dm, the function returns one J and one K matrix,
or a list of J matrices and a list of K matrices, corresponding to the
input density matrices.
Examples:
>>> from pyscf import gto, scf
>>> from pyscf.scf import _vhf
>>> mol = gto.M(atom='H 0 0 0; H 0 0 1.1')
>>> eri = _vhf.int2e_sph(mol._atm, mol._bas, mol._env)
>>> dms = numpy.random.random((3,mol.nao_nr(),mol.nao_nr()))
>>> j, k = scf.hf.dot_eri_dm(eri, dms, hermi=0)
>>> print(j.shape)
(3, 2, 2)
'''
if isinstance(dm, numpy.ndarray) and dm.ndim == 2:
vj, vk = _vhf.incore(eri, dm, hermi=hermi)
else:
vjk = [_vhf.incore(eri, dmi, hermi=hermi) for dmi in dm]
vj = numpy.array([v[0] for v in vjk])
vk = numpy.array([v[1] for v in vjk])
return vj, vk
