Exemple #1
0
    def __init__(self, cis, mo_coeff=None, method="incore"):
        log = logger.Logger(cis.stdout, cis.verbose)
        cput0 = (time.clock(), time.time())

        moidx = get_frozen_mask(cis)
        cell = cis._scf.cell
        nocc = cis.nocc
        nmo = cis.nmo
        nvir = nmo - nocc
        nkpts = cis.nkpts
        kpts = cis.kpts

        if mo_coeff is None:
            mo_coeff = cis.mo_coeff
        dtype = mo_coeff[0].dtype

        mo_coeff = self.mo_coeff = padded_mo_coeff(cis, mo_coeff)

        # Re-make our fock MO matrix elements from density and fock AO
        dm = cis._scf.make_rdm1(cis.mo_coeff, cis.mo_occ)
        exxdiv = cis._scf.exxdiv if cis.keep_exxdiv else None
        with lib.temporary_env(cis._scf, exxdiv=exxdiv):
            # _scf.exxdiv affects eris.fock. HF exchange correction should be
            # excluded from the Fock matrix.
            fockao = cis._scf.get_hcore() + cis._scf.get_veff(cell, dm)
        self.fock = np.asarray([
            reduce(np.dot, (mo.T.conj(), fockao[k], mo))
            for k, mo in enumerate(mo_coeff)
        ])

        self.mo_energy = [self.fock[k].diagonal().real for k in range(nkpts)]

        if not cis.keep_exxdiv:
            # Add HFX correction in the self.mo_energy to improve convergence in
            # CCSD iteration. It is useful for the 2D systems since their occupied and
            # the virtual orbital energies may overlap which may lead to numerical
            # issue in the CCSD iterations.
            # FIXME: Whether to add this correction for other exxdiv treatments?
            # Without the correction, MP2 energy may be largely off the correct value.
            madelung = tools.madelung(cell, kpts)
            self.mo_energy = [
                _adjust_occ(mo_e, nocc, -madelung)
                for k, mo_e in enumerate(self.mo_energy)
            ]

        # Get location of padded elements in occupied and virtual space.
        nocc_per_kpt = get_nocc(cis, per_kpoint=True)
        nonzero_padding = padding_k_idx(cis, kind="joint")

        # Check direct and indirect gaps for possible issues with CCSD convergence.
        mo_e = [self.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
        mo_e = np.sort([y for x in mo_e for y in x])  # Sort de-nested array
        gap = mo_e[np.sum(nocc_per_kpt)] - mo_e[np.sum(nocc_per_kpt) - 1]
        if gap < 1e-5:
            logger.warn(
                cis,
                "H**O-LUMO gap %s too small for KCCSD. "
                "May cause issues in convergence.",
                gap,
            )

        memory_needed = (nkpts**3 * nocc**2 * nvir**2) * 16 / 1e6
        # CIS only needs two terms: <aj|ib> and <aj|bi>; another factor of two for safety
        memory_needed *= 4

        memory_now = lib.current_memory()[0]
        fao2mo = cis._scf.with_df.ao2mo

        kconserv = cis.khelper.kconserv
        khelper = cis.khelper

        if cis.direct and type(cis._scf.with_df) is not df.GDF:
            raise ValueError("CIS direct method must be used with GDF")

        if (cis.direct and type(cis._scf.with_df) is df.GDF
                and cell.dimension != 2):
            # cis._scf.with_df needs to be df.GDF only (not MDF)
            _init_cis_df_eris(cis, self)
        else:
            if (method == "incore" and
                (memory_needed + memory_now < cis.max_memory)
                    or cell.incore_anyway):
                log.info("using incore ERI storage")
                self.ovov = np.empty(
                    (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir), dtype=dtype)
                self.voov = np.empty(
                    (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), dtype=dtype)

                for (ikp, ikq, ikr) in khelper.symm_map.keys():
                    iks = kconserv[ikp, ikq, ikr]
                    eri_kpt = fao2mo(
                        (mo_coeff[ikp], mo_coeff[ikq], mo_coeff[ikr],
                         mo_coeff[iks]),
                        (kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]),
                        compact=False,
                    )
                    if dtype == np.float:
                        eri_kpt = eri_kpt.real
                    eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
                    for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
                        eri_kpt_symm = khelper.transform_symm(
                            eri_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
                        self.ovov[kp, kr, kq] = (
                            eri_kpt_symm[:nocc, nocc:, :nocc, nocc:] / nkpts)
                        self.voov[kp, kr, kq] = (
                            eri_kpt_symm[nocc:, :nocc, :nocc, nocc:] / nkpts)

                self.dtype = dtype
            else:
                log.info("using HDF5 ERI storage")
                self.feri1 = lib.H5TmpFile()

                self.ovov = self.feri1.create_dataset(
                    "ovov", (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir),
                    dtype.char)
                self.voov = self.feri1.create_dataset(
                    "voov", (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir),
                    dtype.char)

                # <ia|pq> = (ip|aq)
                cput1 = time.clock(), time.time()
                for kp in range(nkpts):
                    for kq in range(nkpts):
                        for kr in range(nkpts):
                            ks = kconserv[kp, kq, kr]
                            orbo_p = mo_coeff[kp][:, :nocc]
                            orbv_r = mo_coeff[kr][:, nocc:]
                            buf_kpt = fao2mo(
                                (orbo_p, mo_coeff[kq], orbv_r, mo_coeff[ks]),
                                (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                                compact=False,
                            )
                            if mo_coeff[0].dtype == np.float:
                                buf_kpt = buf_kpt.real
                            buf_kpt = buf_kpt.reshape(nocc, nmo, nvir,
                                                      nmo).transpose(
                                                          0, 2, 1, 3)
                            self.dtype = buf_kpt.dtype
                            self.ovov[kp, kr, kq, :, :, :, :] = (
                                buf_kpt[:, :, :nocc, nocc:] / nkpts)
                            self.voov[kr, kp, ks, :, :, :, :] = (
                                buf_kpt[:, :, nocc:, :nocc].transpose(
                                    1, 0, 3, 2) / nkpts)
                cput1 = log.timer_debug1("transforming ovpq", *cput1)

        log.timer("CIS integral transformation", *cput0)
Exemple #2
0
def _make_eris_incore(cc, mo_coeff=None):
    from pyscf.pbc import tools
    from pyscf.pbc.cc.ccsd import _adjust_occ

    log = logger.Logger(cc.stdout, cc.verbose)
    cput0 = (time.clock(), time.time())
    eris = gccsd._PhysicistsERIs()
    cell = cc._scf.cell
    kpts = cc.kpts
    nkpts = cc.nkpts
    nocc = cc.nocc
    nmo = cc.nmo
    nvir = nmo - nocc
    eris.nocc = nocc

    #if any(nocc != numpy.count_nonzero(cc._scf.mo_occ[k] > 0) for k in range(nkpts)):
    #    raise NotImplementedError('Different occupancies found for different k-points')

    if mo_coeff is None:
        mo_coeff = cc.mo_coeff

    nao = mo_coeff[0].shape[0]
    dtype = mo_coeff[0].dtype

    moidx = get_frozen_mask(cc)
    nocc_per_kpt = numpy.asarray(get_nocc(cc, per_kpoint=True))
    nmo_per_kpt = numpy.asarray(get_nmo(cc, per_kpoint=True))

    padded_moidx = []
    for k in range(nkpts):
        kpt_nocc = nocc_per_kpt[k]
        kpt_nvir = nmo_per_kpt[k] - kpt_nocc
        kpt_padded_moidx = numpy.concatenate(
            (numpy.ones(kpt_nocc, dtype=numpy.bool),
             numpy.zeros(nmo - kpt_nocc - kpt_nvir, dtype=numpy.bool),
             numpy.ones(kpt_nvir, dtype=numpy.bool)))
        padded_moidx.append(kpt_padded_moidx)

    eris.mo_coeff = []
    eris.orbspin = []
    # Generate the molecular orbital coefficients with the frozen orbitals masked.
    # Each MO is tagged with orbspin, a list of 0's and 1's that give the overall
    # spin of each MO.
    #
    # Here we will work with two index arrays; one is for our original (small) moidx
    # array while the next is for our new (large) padded array.
    for k in range(nkpts):
        kpt_moidx = moidx[k]
        kpt_padded_moidx = padded_moidx[k]

        mo = numpy.zeros((nao, nmo), dtype=dtype)
        mo[:, kpt_padded_moidx] = mo_coeff[k][:, kpt_moidx]
        if getattr(mo_coeff[k], 'orbspin', None) is not None:
            orbspin_dtype = mo_coeff[k].orbspin[kpt_moidx].dtype
            orbspin = numpy.zeros(nmo, dtype=orbspin_dtype)
            orbspin[kpt_padded_moidx] = mo_coeff[k].orbspin[kpt_moidx]
            mo = lib.tag_array(mo, orbspin=orbspin)
            eris.orbspin.append(orbspin)
        # FIXME: What if the user freezes all up spin orbitals in
        # an RHF calculation?  The number of electrons will still be
        # even.
        else:  # guess orbital spin - assumes an RHF calculation
            assert (numpy.count_nonzero(kpt_moidx) % 2 == 0)
            orbspin = numpy.zeros(mo.shape[1], dtype=int)
            orbspin[1::2] = 1
            mo = lib.tag_array(mo, orbspin=orbspin)
            eris.orbspin.append(orbspin)
        eris.mo_coeff.append(mo)

    # Re-make our fock MO matrix elements from density and fock AO
    dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
    with lib.temporary_env(cc._scf, exxdiv=None):
        # _scf.exxdiv affects eris.fock. HF exchange correction should be
        # excluded from the Fock matrix.
        fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
    eris.fock = numpy.asarray([
        reduce(numpy.dot, (mo.T.conj(), fockao[k], mo))
        for k, mo in enumerate(eris.mo_coeff)
    ])

    eris.mo_energy = [eris.fock[k].diagonal().real for k in range(nkpts)]
    # Add HFX correction in the eris.mo_energy to improve convergence in
    # CCSD iteration. It is useful for the 2D systems since their occupied and
    # the virtual orbital energies may overlap which may lead to numerical
    # issue in the CCSD iterations.
    # FIXME: Whether to add this correction for other exxdiv treatments?
    # Without the correction, MP2 energy may be largely off the correct value.
    madelung = tools.madelung(cell, kpts)
    eris.mo_energy = [
        _adjust_occ(mo_e, nocc, -madelung)
        for k, mo_e in enumerate(eris.mo_energy)
    ]

    # Get location of padded elements in occupied and virtual space.
    nocc_per_kpt = get_nocc(cc, per_kpoint=True)
    nonzero_padding = padding_k_idx(cc, kind="joint")

    # Check direct and indirect gaps for possible issues with CCSD convergence.
    mo_e = [eris.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
    mo_e = numpy.sort([y for x in mo_e for y in x])  # Sort de-nested array
    gap = mo_e[numpy.sum(nocc_per_kpt)] - mo_e[numpy.sum(nocc_per_kpt) - 1]
    if gap < 1e-5:
        logger.warn(
            cc, 'H**O-LUMO gap %s too small for KCCSD. '
            'May cause issues in convergence.', gap)

    kconserv = kpts_helper.get_kconserv(cell, kpts)
    if getattr(mo_coeff[0], 'orbspin', None) is None:
        # The bottom nao//2 coefficients are down (up) spin while the top are up (down).
        mo_a_coeff = [mo[:nao // 2] for mo in eris.mo_coeff]
        mo_b_coeff = [mo[nao // 2:] for mo in eris.mo_coeff]

        eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo),
                          dtype=numpy.complex128)
        fao2mo = cc._scf.with_df.ao2mo
        for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
            ks = kconserv[kp, kq, kr]
            eri_kpt = fao2mo((mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr],
                              mo_a_coeff[ks]),
                             (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                             compact=False)
            eri_kpt += fao2mo((mo_b_coeff[kp], mo_b_coeff[kq], mo_b_coeff[kr],
                               mo_b_coeff[ks]),
                              (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                              compact=False)
            eri_kpt += fao2mo((mo_a_coeff[kp], mo_a_coeff[kq], mo_b_coeff[kr],
                               mo_b_coeff[ks]),
                              (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                              compact=False)
            eri_kpt += fao2mo((mo_b_coeff[kp], mo_b_coeff[kq], mo_a_coeff[kr],
                               mo_a_coeff[ks]),
                              (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                              compact=False)

            eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
            eri[kp, kq, kr] = eri_kpt
    else:
        mo_a_coeff = [mo[:nao // 2] + mo[nao // 2:] for mo in eris.mo_coeff]

        eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo),
                          dtype=numpy.complex128)
        fao2mo = cc._scf.with_df.ao2mo
        for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
            ks = kconserv[kp, kq, kr]
            eri_kpt = fao2mo((mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr],
                              mo_a_coeff[ks]),
                             (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                             compact=False)

            eri_kpt[(eris.orbspin[kp][:, None] !=
                     eris.orbspin[kq]).ravel()] = 0
            eri_kpt[:,
                    (eris.orbspin[kr][:,
                                      None] != eris.orbspin[ks]).ravel()] = 0
            eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
            eri[kp, kq, kr] = eri_kpt

    # Check some antisymmetrized properties of the integrals
    if DEBUG:
        check_antisymm_3412(cc, cc.kpts, eri)

    # Antisymmetrizing (pq|rs)-(ps|rq), where the latter integral is equal to
    # (rq|ps); done since we aren't tracking the kpoint of orbital 's'
    eri = eri - eri.transpose(2, 1, 0, 5, 4, 3, 6)
    # Chemist -> physics notation
    eri = eri.transpose(0, 2, 1, 3, 5, 4, 6)

    # Set the various integrals
    eris.dtype = eri.dtype
    eris.oooo = eri[:, :, :, :nocc, :nocc, :nocc, :nocc].copy() / nkpts
    eris.ooov = eri[:, :, :, :nocc, :nocc, :nocc, nocc:].copy() / nkpts
    eris.ovoo = eri[:, :, :, :nocc, nocc:, :nocc, :nocc].copy() / nkpts
    eris.oovv = eri[:, :, :, :nocc, :nocc, nocc:, nocc:].copy() / nkpts
    eris.ovov = eri[:, :, :, :nocc, nocc:, :nocc, nocc:].copy() / nkpts
    eris.ovvv = eri[:, :, :, :nocc, nocc:, nocc:, nocc:].copy() / nkpts
    eris.vvvv = eri[:, :, :, nocc:, nocc:, nocc:, nocc:].copy() / nkpts

    log.timer('CCSD integral transformation', *cput0)
    return eris
Exemple #3
0
def _make_eris_incore(cc, mo_coeff=None):
    from pyscf.pbc import tools
    from pyscf.pbc.cc.ccsd import _adjust_occ

    log = logger.Logger(cc.stdout, cc.verbose)
    cput0 = (time.clock(), time.time())
    eris = gccsd._PhysicistsERIs()
    cell = cc._scf.cell
    kpts = cc.kpts
    nkpts = cc.nkpts
    nocc = cc.nocc
    nmo = cc.nmo
    nvir = nmo - nocc
    eris.nocc = nocc

    #if any(nocc != numpy.count_nonzero(cc._scf.mo_occ[k] > 0) for k in range(nkpts)):
    #    raise NotImplementedError('Different occupancies found for different k-points')

    if mo_coeff is None:
        mo_coeff = cc.mo_coeff

    nao = mo_coeff[0].shape[0]
    dtype = mo_coeff[0].dtype

    moidx = get_frozen_mask(cc)
    nocc_per_kpt = numpy.asarray(get_nocc(cc, per_kpoint=True))
    nmo_per_kpt  = numpy.asarray(get_nmo(cc, per_kpoint=True))

    padded_moidx = []
    for k in range(nkpts):
        kpt_nocc = nocc_per_kpt[k]
        kpt_nvir = nmo_per_kpt[k] - kpt_nocc
        kpt_padded_moidx = numpy.concatenate((numpy.ones(kpt_nocc, dtype=numpy.bool),
                                              numpy.zeros(nmo - kpt_nocc - kpt_nvir, dtype=numpy.bool),
                                              numpy.ones(kpt_nvir, dtype=numpy.bool)))
        padded_moidx.append(kpt_padded_moidx)

    eris.mo_coeff = []
    eris.orbspin = []
    # Generate the molecular orbital coefficients with the frozen orbitals masked.
    # Each MO is tagged with orbspin, a list of 0's and 1's that give the overall
    # spin of each MO.
    #
    # Here we will work with two index arrays; one is for our original (small) moidx
    # array while the next is for our new (large) padded array.
    for k in range(nkpts):
        kpt_moidx = moidx[k]
        kpt_padded_moidx = padded_moidx[k]

        mo = numpy.zeros((nao, nmo), dtype=dtype)
        mo[:, kpt_padded_moidx] = mo_coeff[k][:, kpt_moidx]
        if getattr(mo_coeff[k], 'orbspin', None) is not None:
            orbspin_dtype = mo_coeff[k].orbspin[kpt_moidx].dtype
            orbspin = numpy.zeros(nmo, dtype=orbspin_dtype)
            orbspin[kpt_padded_moidx] = mo_coeff[k].orbspin[kpt_moidx]
            mo = lib.tag_array(mo, orbspin=orbspin)
            eris.orbspin.append(orbspin)
        # FIXME: What if the user freezes all up spin orbitals in
        # an RHF calculation?  The number of electrons will still be
        # even.
        else:  # guess orbital spin - assumes an RHF calculation
            assert (numpy.count_nonzero(kpt_moidx) % 2 == 0)
            orbspin = numpy.zeros(mo.shape[1], dtype=int)
            orbspin[1::2] = 1
            mo = lib.tag_array(mo, orbspin=orbspin)
            eris.orbspin.append(orbspin)
        eris.mo_coeff.append(mo)

    # Re-make our fock MO matrix elements from density and fock AO
    dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
    with lib.temporary_env(cc._scf, exxdiv=None):
        # _scf.exxdiv affects eris.fock. HF exchange correction should be
        # excluded from the Fock matrix.
        fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
    eris.fock = numpy.asarray([reduce(numpy.dot, (mo.T.conj(), fockao[k], mo))
                               for k, mo in enumerate(eris.mo_coeff)])

    eris.mo_energy = [eris.fock[k].diagonal().real for k in range(nkpts)]
    # Add HFX correction in the eris.mo_energy to improve convergence in
    # CCSD iteration. It is useful for the 2D systems since their occupied and
    # the virtual orbital energies may overlap which may lead to numerical
    # issue in the CCSD iterations.
    # FIXME: Whether to add this correction for other exxdiv treatments?
    # Without the correction, MP2 energy may be largely off the correct value.
    madelung = tools.madelung(cell, kpts)
    eris.mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
                      for k, mo_e in enumerate(eris.mo_energy)]

    # Get location of padded elements in occupied and virtual space.
    nocc_per_kpt = get_nocc(cc, per_kpoint=True)
    nonzero_padding = padding_k_idx(cc, kind="joint")

    # Check direct and indirect gaps for possible issues with CCSD convergence.
    mo_e = [eris.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
    mo_e = numpy.sort([y for x in mo_e for y in x])  # Sort de-nested array
    gap = mo_e[numpy.sum(nocc_per_kpt)] - mo_e[numpy.sum(nocc_per_kpt)-1]
    if gap < 1e-5:
        logger.warn(cc, 'H**O-LUMO gap %s too small for KCCSD. '
                        'May cause issues in convergence.', gap)

    kconserv = kpts_helper.get_kconserv(cell, kpts)
    if getattr(mo_coeff[0], 'orbspin', None) is None:
        # The bottom nao//2 coefficients are down (up) spin while the top are up (down).
        mo_a_coeff = [mo[:nao // 2] for mo in eris.mo_coeff]
        mo_b_coeff = [mo[nao // 2:] for mo in eris.mo_coeff]

        eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo), dtype=numpy.complex128)
        fao2mo = cc._scf.with_df.ao2mo
        for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
            ks = kconserv[kp, kq, kr]
            eri_kpt = fao2mo(
                (mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr], mo_a_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                compact=False)
            eri_kpt += fao2mo(
                (mo_b_coeff[kp], mo_b_coeff[kq], mo_b_coeff[kr], mo_b_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                compact=False)
            eri_kpt += fao2mo(
                (mo_a_coeff[kp], mo_a_coeff[kq], mo_b_coeff[kr], mo_b_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                compact=False)
            eri_kpt += fao2mo(
                (mo_b_coeff[kp], mo_b_coeff[kq], mo_a_coeff[kr], mo_a_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                compact=False)

            eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
            eri[kp, kq, kr] = eri_kpt
    else:
        mo_a_coeff = [mo[:nao // 2] + mo[nao // 2:] for mo in eris.mo_coeff]

        eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo), dtype=numpy.complex128)
        fao2mo = cc._scf.with_df.ao2mo
        for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
            ks = kconserv[kp, kq, kr]
            eri_kpt = fao2mo(
                (mo_a_coeff[kp], mo_a_coeff[kq], mo_a_coeff[kr], mo_a_coeff[ks]), (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
                compact=False)

            eri_kpt[(eris.orbspin[kp][:, None] != eris.orbspin[kq]).ravel()] = 0
            eri_kpt[:, (eris.orbspin[kr][:, None] != eris.orbspin[ks]).ravel()] = 0
            eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
            eri[kp, kq, kr] = eri_kpt

    # Check some antisymmetrized properties of the integrals
    if DEBUG:
        check_antisymm_3412(cc, cc.kpts, eri)

    # Antisymmetrizing (pq|rs)-(ps|rq), where the latter integral is equal to
    # (rq|ps); done since we aren't tracking the kpoint of orbital 's'
    eri = eri - eri.transpose(2, 1, 0, 5, 4, 3, 6)
    # Chemist -> physics notation
    eri = eri.transpose(0, 2, 1, 3, 5, 4, 6)

    # Set the various integrals
    eris.dtype = eri.dtype
    eris.oooo = eri[:, :, :, :nocc, :nocc, :nocc, :nocc].copy() / nkpts
    eris.ooov = eri[:, :, :, :nocc, :nocc, :nocc, nocc:].copy() / nkpts
    eris.ovoo = eri[:, :, :, :nocc, nocc:, :nocc, :nocc].copy() / nkpts
    eris.oovv = eri[:, :, :, :nocc, :nocc, nocc:, nocc:].copy() / nkpts
    eris.ovov = eri[:, :, :, :nocc, nocc:, :nocc, nocc:].copy() / nkpts
    eris.ovvv = eri[:, :, :, :nocc, nocc:, nocc:, nocc:].copy() / nkpts
    eris.vvvv = eri[:, :, :, nocc:, nocc:, nocc:, nocc:].copy() / nkpts

    log.timer('CCSD integral transformation', *cput0)
    return eris
Exemple #4
0
    def __init__(self, cc, mo_coeff=None, method='incore'):
        from pyscf.pbc import df
        from pyscf.pbc import tools
        from pyscf.pbc.cc.ccsd import _adjust_occ
        log = logger.Logger(cc.stdout, cc.verbose)
        cput0 = (time.clock(), time.time())
        moidx = get_frozen_mask(cc)
        cell = cc._scf.cell
        kpts = cc.kpts
        nkpts = cc.nkpts
        nocc = cc.nocc
        nmo = cc.nmo
        nvir = nmo - nocc

        # if any(nocc != np.count_nonzero(cc._scf.mo_occ[k]>0)
        #       for k in range(nkpts)):
        #    raise NotImplementedError('Different occupancies found for different k-points')

        if mo_coeff is None:
            mo_coeff = cc.mo_coeff
        dtype = mo_coeff[0].dtype

        mo_coeff = self.mo_coeff = padded_mo_coeff(cc, mo_coeff)

        # Re-make our fock MO matrix elements from density and fock AO
        dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
        with lib.temporary_env(cc._scf, exxdiv=None):
            # _scf.exxdiv affects eris.fock. HF exchange correction should be
            # excluded from the Fock matrix.
            fockao = cc._scf.get_hcore() + cc._scf.get_veff(cell, dm)
        self.fock = np.asarray([reduce(np.dot, (mo.T.conj(), fockao[k], mo))
                                for k, mo in enumerate(mo_coeff)])

        self.mo_energy = [self.fock[k].diagonal().real for k in range(nkpts)]
        # Add HFX correction in the self.mo_energy to improve convergence in
        # CCSD iteration. It is useful for the 2D systems since their occupied and
        # the virtual orbital energies may overlap which may lead to numerical
        # issue in the CCSD iterations.
        # FIXME: Whether to add this correction for other exxdiv treatments?
        # Without the correction, MP2 energy may be largely off the correct value.
        madelung = tools.madelung(cell, kpts)
        self.mo_energy = [_adjust_occ(mo_e, nocc, -madelung)
                          for k, mo_e in enumerate(self.mo_energy)]

        # Get location of padded elements in occupied and virtual space.
        nocc_per_kpt = get_nocc(cc, per_kpoint=True)
        nonzero_padding = padding_k_idx(cc, kind="joint")

        # Check direct and indirect gaps for possible issues with CCSD convergence.
        mo_e = [self.mo_energy[kp][nonzero_padding[kp]] for kp in range(nkpts)]
        mo_e = np.sort([y for x in mo_e for y in x])  # Sort de-nested array
        gap = mo_e[np.sum(nocc_per_kpt)] - mo_e[np.sum(nocc_per_kpt)-1]
        if gap < 1e-5:
            logger.warn(cc, 'H**O-LUMO gap %s too small for KCCSD. '
                            'May cause issues in convergence.', gap)

        mem_incore, mem_outcore, mem_basic = _mem_usage(nkpts, nocc, nvir)
        mem_now = lib.current_memory()[0]
        fao2mo = cc._scf.with_df.ao2mo

        kconserv = cc.khelper.kconserv
        khelper = cc.khelper
        orbo = np.asarray(mo_coeff[:,:,:nocc], order='C')
        orbv = np.asarray(mo_coeff[:,:,nocc:], order='C')

        if (method == 'incore' and (mem_incore + mem_now < cc.max_memory)
                or cell.incore_anyway):
            log.info('using incore ERI storage')
            self.oooo = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nocc,nocc), dtype=dtype)
            self.ooov = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nocc,nvir), dtype=dtype)
            self.oovv = np.empty((nkpts,nkpts,nkpts,nocc,nocc,nvir,nvir), dtype=dtype)
            self.ovov = np.empty((nkpts,nkpts,nkpts,nocc,nvir,nocc,nvir), dtype=dtype)
            self.voov = np.empty((nkpts,nkpts,nkpts,nvir,nocc,nocc,nvir), dtype=dtype)
            self.vovv = np.empty((nkpts,nkpts,nkpts,nvir,nocc,nvir,nvir), dtype=dtype)
            #self.vvvv = np.empty((nkpts,nkpts,nkpts,nvir,nvir,nvir,nvir), dtype=dtype)
            self.vvvv = cc._scf.with_df.ao2mo_7d(orbv, factor=1./nkpts).transpose(0,2,1,3,5,4,6)

            for (ikp,ikq,ikr) in khelper.symm_map.keys():
                iks = kconserv[ikp,ikq,ikr]
                eri_kpt = fao2mo((mo_coeff[ikp],mo_coeff[ikq],mo_coeff[ikr],mo_coeff[iks]),
                                 (kpts[ikp],kpts[ikq],kpts[ikr],kpts[iks]), compact=False)
                if dtype == np.float: eri_kpt = eri_kpt.real
                eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
                for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
                    eri_kpt_symm = khelper.transform_symm(eri_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
                    self.oooo[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, :nocc, :nocc] / nkpts
                    self.ooov[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, :nocc, nocc:] / nkpts
                    self.oovv[kp, kr, kq] = eri_kpt_symm[:nocc, :nocc, nocc:, nocc:] / nkpts
                    self.ovov[kp, kr, kq] = eri_kpt_symm[:nocc, nocc:, :nocc, nocc:] / nkpts
                    self.voov[kp, kr, kq] = eri_kpt_symm[nocc:, :nocc, :nocc, nocc:] / nkpts
                    self.vovv[kp, kr, kq] = eri_kpt_symm[nocc:, :nocc, nocc:, nocc:] / nkpts
                    #self.vvvv[kp, kr, kq] = eri_kpt_symm[nocc:, nocc:, nocc:, nocc:] / nkpts

            self.dtype = dtype
        else:
            log.info('using HDF5 ERI storage')
            self.feri1 = lib.H5TmpFile()

            self.oooo = self.feri1.create_dataset('oooo', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nocc), dtype.char)
            self.ooov = self.feri1.create_dataset('ooov', (nkpts, nkpts, nkpts, nocc, nocc, nocc, nvir), dtype.char)
            self.oovv = self.feri1.create_dataset('oovv', (nkpts, nkpts, nkpts, nocc, nocc, nvir, nvir), dtype.char)
            self.ovov = self.feri1.create_dataset('ovov', (nkpts, nkpts, nkpts, nocc, nvir, nocc, nvir), dtype.char)
            self.voov = self.feri1.create_dataset('voov', (nkpts, nkpts, nkpts, nvir, nocc, nocc, nvir), dtype.char)
            self.vovv = self.feri1.create_dataset('vovv', (nkpts, nkpts, nkpts, nvir, nocc, nvir, nvir), dtype.char)

            vvvv_required = ((not cc.direct)
                             # cc._scf.with_df needs to be df.GDF only (not MDF)
                             or type(cc._scf.with_df) is not df.GDF
                             # direct-vvvv for pbc-2D is not supported so far
                             or cell.dimension == 2)
            if vvvv_required:
                self.vvvv = self.feri1.create_dataset('vvvv', (nkpts,nkpts,nkpts,nvir,nvir,nvir,nvir), dtype.char)

            # <ij|pq>  = (ip|jq)
            cput1 = time.clock(), time.time()
            for kp in range(nkpts):
                for kq in range(nkpts):
                    for kr in range(nkpts):
                        ks = kconserv[kp, kq, kr]
                        orbo_p = mo_coeff[kp][:, :nocc]
                        orbo_r = mo_coeff[kr][:, :nocc]
                        buf_kpt = fao2mo((orbo_p, mo_coeff[kq], orbo_r, mo_coeff[ks]),
                                         (kpts[kp], kpts[kq], kpts[kr], kpts[ks]), compact=False)
                        if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
                        buf_kpt = buf_kpt.reshape(nocc, nmo, nocc, nmo).transpose(0, 2, 1, 3)
                        self.dtype = buf_kpt.dtype
                        self.oooo[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, :nocc] / nkpts
                        self.ooov[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, nocc:] / nkpts
                        self.oovv[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, nocc:, nocc:] / nkpts
            cput1 = log.timer_debug1('transforming oopq', *cput1)

            # <ia|pq> = (ip|aq)
            cput1 = time.clock(), time.time()
            for kp in range(nkpts):
                for kq in range(nkpts):
                    for kr in range(nkpts):
                        ks = kconserv[kp, kq, kr]
                        orbo_p = mo_coeff[kp][:, :nocc]
                        orbv_r = mo_coeff[kr][:, nocc:]
                        buf_kpt = fao2mo((orbo_p, mo_coeff[kq], orbv_r, mo_coeff[ks]),
                                         (kpts[kp], kpts[kq], kpts[kr], kpts[ks]), compact=False)
                        if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
                        buf_kpt = buf_kpt.reshape(nocc, nmo, nvir, nmo).transpose(0, 2, 1, 3)
                        self.ovov[kp, kr, kq, :, :, :, :] = buf_kpt[:, :, :nocc, nocc:] / nkpts
                        # TODO: compute vovv on the fly
                        self.vovv[kr, kp, ks, :, :, :, :] = buf_kpt[:, :, nocc:, nocc:].transpose(1, 0, 3, 2) / nkpts
                        self.voov[kr, kp, ks, :, :, :, :] = buf_kpt[:, :, nocc:, :nocc].transpose(1, 0, 3, 2) / nkpts
            cput1 = log.timer_debug1('transforming ovpq', *cput1)

            ## Without k-point symmetry
            # cput1 = time.clock(), time.time()
            # for kp in range(nkpts):
            #    for kq in range(nkpts):
            #        for kr in range(nkpts):
            #            ks = kconserv[kp,kq,kr]
            #            orbv_p = mo_coeff[kp][:,nocc:]
            #            orbv_q = mo_coeff[kq][:,nocc:]
            #            orbv_r = mo_coeff[kr][:,nocc:]
            #            orbv_s = mo_coeff[ks][:,nocc:]
            #            for a in range(nvir):
            #                orbva_p = orbv_p[:,a].reshape(-1,1)
            #                buf_kpt = fao2mo((orbva_p,orbv_q,orbv_r,orbv_s),
            #                                 (kpts[kp],kpts[kq],kpts[kr],kpts[ks]), compact=False)
            #                if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
            #                buf_kpt = buf_kpt.reshape((1,nvir,nvir,nvir)).transpose(0,2,1,3)
            #                self.vvvv[kp,kr,kq,a,:,:,:] = buf_kpt[:] / nkpts
            # cput1 = log.timer_debug1('transforming vvvv', *cput1)

            cput1 = time.clock(), time.time()
            mem_now = lib.current_memory()[0]
            if not vvvv_required:
                _init_df_eris(cc, self)

            elif nvir ** 4 * 16 / 1e6 + mem_now < cc.max_memory:
                for (ikp, ikq, ikr) in khelper.symm_map.keys():
                    iks = kconserv[ikp, ikq, ikr]
                    orbv_p = mo_coeff[ikp][:, nocc:]
                    orbv_q = mo_coeff[ikq][:, nocc:]
                    orbv_r = mo_coeff[ikr][:, nocc:]
                    orbv_s = mo_coeff[iks][:, nocc:]
                    # unit cell is small enough to handle vvvv in-core
                    buf_kpt = fao2mo((orbv_p,orbv_q,orbv_r,orbv_s),
                                     kpts[[ikp,ikq,ikr,iks]], compact=False)
                    if dtype == np.float: buf_kpt = buf_kpt.real
                    buf_kpt = buf_kpt.reshape((nvir, nvir, nvir, nvir))
                    for (kp, kq, kr) in khelper.symm_map[(ikp, ikq, ikr)]:
                        buf_kpt_symm = khelper.transform_symm(buf_kpt, kp, kq, kr).transpose(0, 2, 1, 3)
                        self.vvvv[kp, kr, kq] = buf_kpt_symm / nkpts
            else:
                raise MemoryError('Minimal memory requirements %s MB'
                                  % (mem_now + nvir ** 4 / 1e6 * 16 * 2))
                for (ikp, ikq, ikr) in khelper.symm_map.keys():
                    for a in range(nvir):
                        orbva_p = orbv_p[:, a].reshape(-1, 1)
                        buf_kpt = fao2mo((orbva_p, orbv_q, orbv_r, orbv_s),
                                         (kpts[ikp], kpts[ikq], kpts[ikr], kpts[iks]), compact=False)
                        if mo_coeff[0].dtype == np.float: buf_kpt = buf_kpt.real
                        buf_kpt = buf_kpt.reshape((1, nvir, nvir, nvir)).transpose(0, 2, 1, 3)

                        self.vvvv[ikp, ikr, ikq, a, :, :, :] = buf_kpt[0, :, :, :] / nkpts
                        # Store symmetric permutations
                        self.vvvv[ikr, ikp, iks, :, a, :, :] = buf_kpt.transpose(1, 0, 3, 2)[:, 0, :, :] / nkpts
                        self.vvvv[ikq, iks, ikp, :, :, a, :] = buf_kpt.transpose(2, 3, 0, 1).conj()[:, :, 0, :] / nkpts
                        self.vvvv[iks, ikq, ikr, :, :, :, a] = buf_kpt.transpose(3, 2, 1, 0).conj()[:, :, :, 0] / nkpts
            cput1 = log.timer_debug1('transforming vvvv', *cput1)

        log.timer('CCSD integral transformation', *cput0)
Exemple #5
0
def _make_eris_incore(cc, mo_coeff=None):
    log = logger.Logger(cc.stdout, cc.verbose)
    cput0 = (time.clock(), time.time())
    eris = gccsd._PhysicistsERIs()
    kpts = cc.kpts
    nkpts = cc.nkpts
    nocc = cc.nocc
    nmo = cc.nmo
    nvir = nmo - nocc
    eris.nocc = nocc

    #if any(nocc != numpy.count_nonzero(cc._scf.mo_occ[k] > 0) for k in range(nkpts)):
    #    raise NotImplementedError('Different occupancies found for different k-points')

    if mo_coeff is None:
        mo_coeff = cc.mo_coeff
    #else:
    #    # If mo_coeff is not canonical orbital
    #    # TODO does this work for k-points? changed to conjugate.
    #    raise NotImplementedError
    nao = mo_coeff[0].shape[0]
    dtype = mo_coeff[0].dtype

    moidx = get_frozen_mask(cc)
    nocc_per_kpt = numpy.asarray(get_nocc(cc, per_kpoint=True))
    nmo_per_kpt = numpy.asarray(get_nmo(cc, per_kpoint=True))

    padded_moidx = []
    for k in range(nkpts):
        kpt_nocc = nocc_per_kpt[k]
        kpt_nvir = nmo_per_kpt[k] - kpt_nocc
        kpt_padded_moidx = numpy.concatenate(
            (numpy.ones(kpt_nocc, dtype=numpy.bool),
             numpy.zeros(nmo - kpt_nocc - kpt_nvir, dtype=numpy.bool),
             numpy.ones(kpt_nvir, dtype=numpy.bool)))
        padded_moidx.append(kpt_padded_moidx)

    eris.mo_coeff = []
    eris.orbspin = []
    # Generate the molecular orbital coefficients with the frozen orbitals masked.
    # Each MO is tagged with orbspin, a list of 0's and 1's that give the overall
    # spin of each MO.
    #
    # Here we will work with two index arrays; one is for our original (small) moidx
    # array while the next is for our new (large) padded array.
    for k in range(nkpts):
        kpt_moidx = moidx[k]
        kpt_padded_moidx = padded_moidx[k]

        mo = numpy.zeros((nao, nmo), dtype=dtype)
        mo[:, kpt_padded_moidx] = mo_coeff[k][:, kpt_moidx]
        if hasattr(mo_coeff[k], 'orbspin'):
            orbspin_dtype = mo_coeff[k].orbspin[kpt_moidx].dtype
            orbspin = numpy.zeros(nmo, dtype=orbspin_dtype)
            orbspin[kpt_padded_moidx] = mo_coeff[k].orbspin[kpt_moidx]
            mo = lib.tag_array(mo, orbspin=orbspin)
            eris.orbspin.append(orbspin)
        # FIXME: What if the user freezes all up spin orbitals in
        # an RHF calculation?  The number of electrons will still be
        # even.
        else:  # guess orbital spin - assumes an RHF calculation
            assert (numpy.count_nonzero(kpt_moidx) % 2 == 0)
            orbspin = numpy.zeros(mo.shape[1], dtype=int)
            orbspin[1::2] = 1
            mo = lib.tag_array(mo, orbspin=orbspin)
            eris.orbspin.append(orbspin)
        eris.mo_coeff.append(mo)

    # Re-make our fock MO matrix elements from density and fock AO
    dm = cc._scf.make_rdm1(cc.mo_coeff, cc.mo_occ)
    fockao = cc._scf.get_hcore() + cc._scf.get_veff(cc._scf.cell, dm)
    eris.fock = numpy.asarray([
        reduce(numpy.dot, (mo.T.conj(), fockao[k], mo))
        for k, mo in enumerate(eris.mo_coeff)
    ])

    kconserv = kpts_helper.get_kconserv(cc._scf.cell, cc.kpts)
    # The bottom nao//2 coefficients are down (up) spin while the top are up (down).
    # These are 'spin-less' quantities; spin-conservation will be added manually.
    so_coeff = [mo[:nao // 2] + mo[nao // 2:] for mo in eris.mo_coeff]

    eri = numpy.empty((nkpts, nkpts, nkpts, nmo, nmo, nmo, nmo),
                      dtype=numpy.complex128)
    fao2mo = cc._scf.with_df.ao2mo
    for kp, kq, kr in kpts_helper.loop_kkk(nkpts):
        ks = kconserv[kp, kq, kr]
        eri_kpt = fao2mo(
            (so_coeff[kp], so_coeff[kq], so_coeff[kr], so_coeff[ks]),
            (kpts[kp], kpts[kq], kpts[kr], kpts[ks]),
            compact=False)
        eri_kpt[(eris.orbspin[kp][:, None] != eris.orbspin[kq]).ravel()] = 0
        eri_kpt[:, (eris.orbspin[kr][:, None] != eris.orbspin[ks]).ravel()] = 0
        eri_kpt = eri_kpt.reshape(nmo, nmo, nmo, nmo)
        eri[kp, kq, kr] = eri_kpt

    # Check some antisymmetrized properties of the integrals
    if DEBUG:
        check_antisymm_3412(cc, cc.kpts, eri)

    # Antisymmetrizing (pq|rs)-(ps|rq), where the latter integral is equal to
    # (rq|ps); done since we aren't tracking the kpoint of orbital 's'
    eri = eri - eri.transpose(2, 1, 0, 5, 4, 3, 6)
    # Chemist -> physics notation
    eri = eri.transpose(0, 2, 1, 3, 5, 4, 6)

    # Set the various integrals
    eris.dtype = eri.dtype
    eris.oooo = eri[:, :, :, :nocc, :nocc, :nocc, :nocc].copy() / nkpts
    eris.ooov = eri[:, :, :, :nocc, :nocc, :nocc, nocc:].copy() / nkpts
    eris.ovoo = eri[:, :, :, :nocc, nocc:, :nocc, :nocc].copy() / nkpts
    eris.oovv = eri[:, :, :, :nocc, :nocc, nocc:, nocc:].copy() / nkpts
    eris.ovov = eri[:, :, :, :nocc, nocc:, :nocc, nocc:].copy() / nkpts
    eris.ovvv = eri[:, :, :, :nocc, nocc:, nocc:, nocc:].copy() / nkpts
    eris.vvvv = eri[:, :, :, nocc:, nocc:, nocc:, nocc:].copy() / nkpts

    log.timer('CCSD integral transformation', *cput0)
    return eris