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