Пример #1
0
class GPAW(Calculator, PAW):
    """This is the ASE-calculator frontend for doing a PAW calculation."""

    implemented_properties = [
        'energy', 'forces', 'stress', 'dipole', 'magmom', 'magmoms'
    ]

    default_parameters = {
        'mode': 'fd',
        'xc': 'LDA',
        'occupations': None,
        'poissonsolver': None,
        'h': None,  # Angstrom
        'gpts': None,
        'kpts': [(0.0, 0.0, 0.0)],
        'nbands': None,
        'charge': 0,
        'setups': {},
        'basis': {},
        'spinpol': None,
        'fixdensity': False,
        'filter': None,
        'mixer': None,
        'eigensolver': None,
        'background_charge': None,
        'external': None,
        'random': False,
        'hund': False,
        'maxiter': 333,
        'idiotproof': True,
        'symmetry': {
            'point_group': True,
            'time_reversal': True,
            'symmorphic': True,
            'tolerance': 1e-7
        },
        'convergence': {
            'energy': 0.0005,  # eV / electron
            'density': 1.0e-4,
            'eigenstates': 4.0e-8,  # eV^2
            'bands': 'occupied',
            'forces': np.inf
        },  # eV / Ang
        'dtype': None,  # Deprecated
        'width': None,  # Deprecated
        'verbose': 0
    }

    default_parallel = {
        'kpt': None,
        'domain': gpaw.parsize_domain,
        'band': gpaw.parsize_bands,
        'order': 'kdb',
        'stridebands': False,
        'augment_grids': gpaw.augment_grids,
        'sl_auto': False,
        'sl_default': gpaw.sl_default,
        'sl_diagonalize': gpaw.sl_diagonalize,
        'sl_inverse_cholesky': gpaw.sl_inverse_cholesky,
        'sl_lcao': gpaw.sl_lcao,
        'sl_lrtddft': gpaw.sl_lrtddft,
        'buffer_size': gpaw.buffer_size
    }

    def __init__(self,
                 restart=None,
                 ignore_bad_restart_file=False,
                 label=None,
                 atoms=None,
                 timer=None,
                 communicator=None,
                 txt='-',
                 parallel=None,
                 **kwargs):

        self.parallel = dict(self.default_parallel)
        if parallel:
            self.parallel.update(parallel)

        if timer is None:
            self.timer = Timer()
        else:
            self.timer = timer

        self.scf = None
        self.wfs = None
        self.occupations = None
        self.density = None
        self.hamiltonian = None

        self.observers = []  # XXX move to self.scf
        self.initialized = False

        self.world = communicator
        if self.world is None:
            self.world = mpi.world
        elif not hasattr(self.world, 'new_communicator'):
            self.world = mpi.world.new_communicator(np.asarray(self.world))

        self.log = GPAWLogger(world=self.world)
        self.log.fd = txt

        self.reader = None

        Calculator.__init__(self, restart, ignore_bad_restart_file, label,
                            atoms, **kwargs)

    def __del__(self):
        self.timer.write(self.log.fd)
        if self.reader is not None:
            self.reader.close()

    def write(self, filename, mode=''):
        self.log('Writing to {0} (mode={1!r})\n'.format(filename, mode))
        writer = Writer(filename, self.world)
        self._write(writer, mode)
        writer.close()
        self.world.barrier()

    def _write(self, writer, mode):
        from ase.io.trajectory import write_atoms
        writer.write(version=1,
                     gpaw_version=gpaw.__version__,
                     ha=Ha,
                     bohr=Bohr)

        write_atoms(writer.child('atoms'), self.atoms)
        writer.child('results').write(**self.results)
        writer.child('parameters').write(**self.todict())

        self.density.write(writer.child('density'))
        self.hamiltonian.write(writer.child('hamiltonian'))
        self.occupations.write(writer.child('occupations'))
        self.scf.write(writer.child('scf'))
        self.wfs.write(writer.child('wave_functions'), mode == 'all')

        return writer

    def read(self, filename):
        from ase.io.trajectory import read_atoms
        self.log('Reading from {0}'.format(filename))

        self.reader = reader = Reader(filename)

        self.atoms = read_atoms(reader.atoms)

        res = reader.results
        self.results = dict((key, res.get(key)) for key in res.keys())
        if self.results:
            self.log('Read {0}'.format(', '.join(sorted(self.results))))

        self.log('Reading input parameters:')
        self.parameters = self.get_default_parameters()
        dct = {}
        for key, value in reader.parameters.asdict().items():
            if (isinstance(value, dict)
                    and isinstance(self.parameters[key], dict)):
                self.parameters[key].update(value)
            else:
                self.parameters[key] = value
            dct[key] = self.parameters[key]

        self.log.print_dict(dct)
        self.log()

        self.initialize(reading=True)

        self.density.read(reader)
        self.hamiltonian.read(reader)
        self.occupations.read(reader)
        self.scf.read(reader)
        self.wfs.read(reader)

        # We need to do this in a better way:  XXX
        from gpaw.utilities.partition import AtomPartition
        atom_partition = AtomPartition(self.wfs.gd.comm,
                                       np.zeros(len(self.atoms), dtype=int))
        self.wfs.atom_partition = atom_partition
        self.density.atom_partition = atom_partition
        self.hamiltonian.atom_partition = atom_partition
        spos_ac = self.atoms.get_scaled_positions() % 1.0
        rank_a = self.density.gd.get_ranks_from_positions(spos_ac)
        new_atom_partition = AtomPartition(self.density.gd.comm, rank_a)
        for obj in [self.density, self.hamiltonian]:
            obj.set_positions_without_ruining_everything(
                spos_ac, new_atom_partition)

        self.hamiltonian.xc.read(reader)

        if self.hamiltonian.xc.name == 'GLLBSC':
            # XXX GLLB: See lcao/tdgllbsc.py test
            self.occupations.calculate(self.wfs)

        return reader

    def check_state(self, atoms, tol=1e-15):
        system_changes = Calculator.check_state(self, atoms, tol)
        if 'positions' not in system_changes:
            if self.hamiltonian:
                if self.hamiltonian.vext:
                    if self.hamiltonian.vext.vext_g is None:
                        # QMMM atoms have moved:
                        system_changes.append('positions')
        return system_changes

    def calculate(self,
                  atoms=None,
                  properties=['energy'],
                  system_changes=['cell']):
        """Calculate things."""

        Calculator.calculate(self, atoms)
        atoms = self.atoms

        if system_changes:
            self.log('System changes:', ', '.join(system_changes), '\n')
            if system_changes == ['positions']:
                # Only positions have changed:
                self.density.reset()
            else:
                # Drastic changes:
                self.wfs = None
                self.occupations = None
                self.density = None
                self.hamiltonian = None
                self.scf = None
                self.initialize(atoms)

            self.set_positions(atoms)

        if not self.initialized:
            self.initialize(atoms)
            self.set_positions(atoms)

        if not (self.wfs.positions_set and self.hamiltonian.positions_set):
            self.set_positions(atoms)

        if not self.scf.converged:
            print_cell(self.wfs.gd, self.atoms.pbc, self.log)

            with self.timer('SCF-cycle'):
                self.scf.run(self.wfs, self.hamiltonian, self.density,
                             self.occupations, self.log, self.call_observers)

            self.log('\nConverged after {0} iterations.\n'.format(
                self.scf.niter))

            e_free = self.hamiltonian.e_total_free
            e_extrapolated = self.hamiltonian.e_total_extrapolated
            self.results['energy'] = e_extrapolated * Ha
            self.results['free_energy'] = e_free * Ha

            if not self.atoms.pbc.all():
                dipole_v = self.density.calculate_dipole_moment() * Bohr
                self.log(
                    'Dipole moment: ({0:.6f}, {1:.6f}, {2:.6f}) |e|*Ang\n'.
                    format(*dipole_v))
                self.results['dipole'] = dipole_v

            if self.wfs.nspins == 2:
                magmom = self.occupations.magmom
                magmom_a = self.density.estimate_magnetic_moments(total=magmom)
                self.log('Total magnetic moment: %f' % magmom)
                self.log('Local magnetic moments:')
                symbols = self.atoms.get_chemical_symbols()
                for a, mom in enumerate(magmom_a):
                    self.log('{0:4} {1:2} {2:.6f}'.format(a, symbols[a], mom))
                self.log()
                self.results['magmom'] = self.occupations.magmom
                self.results['magmoms'] = magmom_a

            self.summary()

            self.call_observers(self.scf.niter, final=True)

        if 'forces' in properties:
            with self.timer('Forces'):
                F_av = calculate_forces(self.wfs, self.density,
                                        self.hamiltonian, self.log)
                self.results['forces'] = F_av * (Ha / Bohr)

        if 'stress' in properties:
            with self.timer('Stress'):
                try:
                    stress = calculate_stress(self).flat[[0, 4, 8, 5, 2, 1]]
                except NotImplementedError:
                    # Our ASE Calculator base class will raise
                    # PropertyNotImplementedError for us.
                    pass
                else:
                    self.results['stress'] = stress * (Ha / Bohr**3)

    def summary(self):
        self.hamiltonian.summary(self.occupations.fermilevel, self.log)
        self.density.summary(self.atoms, self.occupations.magmom, self.log)
        self.occupations.summary(self.log)
        self.wfs.summary(self.log)
        self.log.fd.flush()

    def set(self, **kwargs):
        """Change parameters for calculator.

        Examples::

            calc.set(xc='PBE')
            calc.set(nbands=20, kpts=(4, 1, 1))
        """

        changed_parameters = Calculator.set(self, **kwargs)

        for key in ['setups', 'basis']:
            if key in changed_parameters:
                dct = changed_parameters[key]
                if isinstance(dct, dict) and None in dct:
                    dct['default'] = dct.pop(None)
                    warnings.warn('Please use {key}={dct}'.format(key=key,
                                                                  dct=dct))

        # We need to handle txt early in order to get logging up and running:
        if 'txt' in changed_parameters:
            self.log.fd = changed_parameters.pop('txt')

        if not changed_parameters:
            return {}

        self.initialized = False
        self.scf = None
        self.results = {}

        self.log('Input parameters:')
        self.log.print_dict(changed_parameters)
        self.log()

        for key in changed_parameters:
            if key in ['eigensolver', 'convergence'] and self.wfs:
                self.wfs.set_eigensolver(None)

            if key in [
                    'mixer', 'verbose', 'txt', 'hund', 'random', 'eigensolver',
                    'idiotproof'
            ]:
                continue

            if key in ['convergence', 'fixdensity', 'maxiter']:
                continue

            # More drastic changes:
            if self.wfs:
                self.wfs.set_orthonormalized(False)
            if key in ['external', 'xc', 'poissonsolver']:
                self.hamiltonian = None
            elif key in ['occupations', 'width']:
                pass
            elif key in ['charge', 'background_charge']:
                self.hamiltonian = None
                self.density = None
                self.wfs = None
            elif key in ['kpts', 'nbands', 'symmetry']:
                self.wfs = None
            elif key in ['h', 'gpts', 'setups', 'spinpol', 'dtype', 'mode']:
                self.density = None
                self.hamiltonian = None
                self.wfs = None
            elif key in ['basis']:
                self.wfs = None
            else:
                raise TypeError('Unknown keyword argument: "%s"' % key)

    def initialize_positions(self, atoms=None):
        """Update the positions of the atoms."""
        self.log('Initializing position-dependent things.\n')
        if atoms is None:
            atoms = self.atoms
        else:
            # Save the state of the atoms:
            self.atoms = atoms.copy()

        mpi.synchronize_atoms(atoms, self.world)

        spos_ac = atoms.get_scaled_positions() % 1.0

        rank_a = self.wfs.gd.get_ranks_from_positions(spos_ac)
        atom_partition = AtomPartition(self.wfs.gd.comm, rank_a, name='gd')
        self.wfs.set_positions(spos_ac, atom_partition)
        self.density.set_positions(spos_ac, atom_partition)
        self.hamiltonian.set_positions(spos_ac, atom_partition)

        return spos_ac

    def set_positions(self, atoms=None):
        """Update the positions of the atoms and initialize wave functions."""
        spos_ac = self.initialize_positions(atoms)

        nlcao, nrand = self.wfs.initialize(self.density, self.hamiltonian,
                                           spos_ac)
        if nlcao + nrand:
            self.log('Creating initial wave functions:')
            if nlcao:
                self.log(' ', plural(nlcao, 'band'), 'from LCAO basis set')
            if nrand:
                self.log(' ', plural(nrand, 'band'), 'from random numbers')
            self.log()

        self.wfs.eigensolver.reset()
        self.scf.reset()
        print_positions(self.atoms, self.log)

    def initialize(self, atoms=None, reading=False):
        """Inexpensive initialization."""

        self.log('Initialize ...\n')

        if atoms is None:
            atoms = self.atoms
        else:
            # Save the state of the atoms:
            self.atoms = atoms.copy()

        par = self.parameters

        natoms = len(atoms)

        cell_cv = atoms.get_cell() / Bohr
        number_of_lattice_vectors = cell_cv.any(axis=1).sum()
        if number_of_lattice_vectors < 3:
            raise ValueError(
                'GPAW requires 3 lattice vectors.  Your system has {0}.'.
                format(number_of_lattice_vectors))

        pbc_c = atoms.get_pbc()
        assert len(pbc_c) == 3
        magmom_a = atoms.get_initial_magnetic_moments()

        mpi.synchronize_atoms(atoms, self.world)

        # Generate new xc functional only when it is reset by set
        # XXX sounds like this should use the _changed_keywords dictionary.
        if self.hamiltonian is None or self.hamiltonian.xc is None:
            if isinstance(par.xc, basestring):
                xc = XC(par.xc)
            else:
                xc = par.xc
        else:
            xc = self.hamiltonian.xc

        mode = par.mode
        if isinstance(mode, basestring):
            mode = {'name': mode}
        if isinstance(mode, dict):
            mode = create_wave_function_mode(**mode)

        if par.dtype == complex:
            warnings.warn('Use mode={0}(..., force_complex_dtype=True) '
                          'instead of dtype=complex'.format(mode.name.upper()))
            mode.force_complex_dtype = True
            del par['dtype']
            par.mode = mode

        if xc.orbital_dependent and mode.name == 'lcao':
            raise ValueError('LCAO mode does not support '
                             'orbital-dependent XC functionals.')

        realspace = (mode.name != 'pw' and mode.interpolation != 'fft')

        if not realspace:
            pbc_c = np.ones(3, bool)

        self.create_setups(mode, xc)

        magnetic = magmom_a.any()

        spinpol = par.spinpol
        if par.hund:
            if natoms != 1:
                raise ValueError('hund=True arg only valid for single atoms!')
            spinpol = True
            magmom_a[0] = self.setups[0].get_hunds_rule_moment(par.charge)

        if spinpol is None:
            spinpol = magnetic
        elif magnetic and not spinpol:
            raise ValueError('Non-zero initial magnetic moment for a ' +
                             'spin-paired calculation!')

        nspins = 1 + int(spinpol)

        if spinpol:
            self.log('Spin-polarized calculation.')
            self.log('Magnetic moment:  {0:.6f}\n'.format(magmom_a.sum()))
        else:
            self.log('Spin-paired calculation\n')

        if isinstance(par.background_charge, dict):
            background = create_background_charge(**par.background_charge)
        else:
            background = par.background_charge

        nao = self.setups.nao
        nvalence = self.setups.nvalence - par.charge
        if par.background_charge is not None:
            nvalence += background.charge
        M = abs(magmom_a.sum())

        nbands = par.nbands

        orbital_free = any(setup.orbital_free for setup in self.setups)
        if orbital_free:
            nbands = 1

        if isinstance(nbands, basestring):
            if nbands[-1] == '%':
                basebands = int(nvalence + M + 0.5) // 2
                nbands = int((float(nbands[:-1]) / 100) * basebands)
            else:
                raise ValueError('Integer expected: Only use a string '
                                 'if giving a percentage of occupied bands')

        if nbands is None:
            nbands = 0
            for setup in self.setups:
                nbands_from_atom = setup.get_default_nbands()

                # Any obscure setup errors?
                if nbands_from_atom < -(-setup.Nv // 2):
                    raise ValueError('Bad setup: This setup requests %d'
                                     ' bands but has %d electrons.' %
                                     (nbands_from_atom, setup.Nv))
                nbands += nbands_from_atom
            nbands = min(nao, nbands)
        elif nbands > nao and mode.name == 'lcao':
            raise ValueError('Too many bands for LCAO calculation: '
                             '%d bands and only %d atomic orbitals!' %
                             (nbands, nao))

        if nvalence < 0:
            raise ValueError(
                'Charge %f is not possible - not enough valence electrons' %
                par.charge)

        if nbands <= 0:
            nbands = int(nvalence + M + 0.5) // 2 + (-nbands)

        if nvalence > 2 * nbands and not orbital_free:
            raise ValueError('Too few bands!  Electrons: %f, bands: %d' %
                             (nvalence, nbands))

        self.create_occupations(magmom_a.sum(), orbital_free)

        if self.scf is None:
            self.create_scf(nvalence, mode)

        self.create_symmetry(magmom_a, cell_cv)

        if not self.wfs:
            self.create_wave_functions(mode, realspace, nspins, nbands, nao,
                                       nvalence, self.setups, magmom_a,
                                       cell_cv, pbc_c)
        else:
            self.wfs.set_setups(self.setups)

        if not self.wfs.eigensolver:
            self.create_eigensolver(xc, nbands, mode)

        if self.density is None and not reading:
            assert not par.fixdensity, 'No density to fix!'

        olddens = None
        if (self.density is not None and
            (self.density.gd.parsize_c != self.wfs.gd.parsize_c).any()):
            # Domain decomposition has changed, so we need to
            # reinitialize density and hamiltonian:
            if par.fixdensity:
                olddens = self.density

            self.density = None
            self.hamiltonian = None

        if self.density is None:
            self.create_density(realspace, mode, background)

        # XXXXXXXXXX if setups change, then setups.core_charge may change.
        # But that parameter was supplied in Density constructor!
        # This surely is a bug!
        self.density.initialize(self.setups, self.timer, magmom_a, par.hund)
        self.density.set_mixer(par.mixer)
        if self.density.mixer.driver.name == 'dummy' or par.fixdensity:
            self.log('No density mixing\n')
        else:
            self.log(self.density.mixer, '\n')
        self.density.fixed = par.fixdensity
        self.density.log = self.log

        if olddens is not None:
            self.density.initialize_from_other_density(olddens,
                                                       self.wfs.kptband_comm)

        if self.hamiltonian is None:
            self.create_hamiltonian(realspace, mode, xc)

        xc.initialize(self.density, self.hamiltonian, self.wfs,
                      self.occupations)

        if xc.name == 'GLLBSC' and olddens is not None:
            xc.heeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeelp(olddens)

        self.print_memory_estimate(maxdepth=memory_estimate_depth + 1)

        print_parallelization_details(self.wfs, self.density, self.log)

        self.log('Number of atoms:', natoms)
        self.log('Number of atomic orbitals:', self.wfs.setups.nao)
        if self.nbands_parallelization_adjustment != 0:
            self.log(
                'Adjusting number of bands by %+d to match parallelization' %
                self.nbands_parallelization_adjustment)
        self.log('Number of bands in calculation:', self.wfs.bd.nbands)
        self.log('Bands to converge: ', end='')
        n = par.convergence.get('bands', 'occupied')
        if n == 'occupied':
            self.log('occupied states only')
        elif n == 'all':
            self.log('all')
        else:
            self.log('%d lowest bands' % n)
        self.log('Number of valence electrons:', self.wfs.nvalence)

        self.log(flush=True)

        self.timer.print_info(self)

        if dry_run:
            self.dry_run()

        if (realspace and self.hamiltonian.poisson.get_description()
                == 'FDTD+TDDFT'):
            self.hamiltonian.poisson.set_density(self.density)
            self.hamiltonian.poisson.print_messages(self.log)
            self.log.fd.flush()

        self.initialized = True
        self.log('... initialized\n')

    def create_setups(self, mode, xc):
        if self.parameters.filter is None and mode.name != 'pw':
            gamma = 1.6
            N_c = self.parameters.get('gpts')
            if N_c is None:
                h = (self.parameters.h or 0.2) / Bohr
            else:
                icell_vc = np.linalg.inv(self.atoms.cell)
                h = ((icell_vc**2).sum(0)**-0.5 / N_c).max() / Bohr

            def filter(rgd, rcut, f_r, l=0):
                gcut = np.pi / h - 2 / rcut / gamma
                f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
        else:
            filter = self.parameters.filter

        Z_a = self.atoms.get_atomic_numbers()
        self.setups = Setups(Z_a, self.parameters.setups,
                             self.parameters.basis, xc, filter, self.world)
        self.log(self.setups)

    def create_grid_descriptor(self, N_c, cell_cv, pbc_c, domain_comm,
                               parsize_domain):
        return GridDescriptor(N_c, cell_cv, pbc_c, domain_comm, parsize_domain)

    def create_occupations(self, magmom, orbital_free):
        occ = self.parameters.occupations

        if occ is None:
            if orbital_free:
                occ = {'name': 'orbital-free'}
            else:
                width = self.parameters.width
                if width is not None:
                    warnings.warn(
                        'Please use occupations=FermiDirac({0})'.format(width))
                elif self.atoms.pbc.any():
                    width = 0.1  # eV
                else:
                    width = 0.0
                occ = {'name': 'fermi-dirac', 'width': width}

        if isinstance(occ, dict):
            occ = create_occupation_number_object(**occ)

        if self.parameters.fixdensity:
            occ.fixed_fermilevel = True
            if self.occupations:
                occ.fermilevel = self.occupations.fermilevel

        self.occupations = occ

        # If occupation numbers are changed, and we have wave functions,
        # recalculate the occupation numbers
        if self.wfs is not None:
            self.occupations.calculate(self.wfs)

        self.occupations.magmom = magmom

        self.log(self.occupations)

    def create_scf(self, nvalence, mode):
        if mode.name == 'lcao':
            niter_fixdensity = 0
        else:
            niter_fixdensity = 2

        nv = max(nvalence, 1)
        cc = self.parameters.convergence
        self.scf = SCFLoop(
            cc.get('eigenstates', 4.0e-8) / Ha**2 * nv,
            cc.get('energy', 0.0005) / Ha * nv,
            cc.get('density', 1.0e-4) * nv,
            cc.get('forces', np.inf) / (Ha / Bohr), self.parameters.maxiter,
            niter_fixdensity, nv)
        self.log(self.scf)

    def create_symmetry(self, magmom_a, cell_cv):
        symm = self.parameters.symmetry
        if symm == 'off':
            symm = {'point_group': False, 'time_reversal': False}
        m_a = magmom_a.round(decimals=3)  # round off
        id_a = list(zip(self.setups.id_a, m_a))
        self.symmetry = Symmetry(id_a, cell_cv, self.atoms.pbc, **symm)
        self.symmetry.analyze(self.atoms.get_scaled_positions())
        self.setups.set_symmetry(self.symmetry)

    def create_eigensolver(self, xc, nbands, mode):
        # Number of bands to converge:
        nbands_converge = self.parameters.convergence.get('bands', 'occupied')
        if nbands_converge == 'all':
            nbands_converge = nbands
        elif nbands_converge != 'occupied':
            assert isinstance(nbands_converge, int)
            if nbands_converge < 0:
                nbands_converge += nbands
        eigensolver = get_eigensolver(self.parameters.eigensolver, mode,
                                      self.parameters.convergence)
        eigensolver.nbands_converge = nbands_converge
        # XXX Eigensolver class doesn't define an nbands_converge property

        if isinstance(xc, SIC):
            eigensolver.blocksize = 1

        self.wfs.set_eigensolver(eigensolver)

        self.log(self.wfs.eigensolver, '\n')

    def create_density(self, realspace, mode, background):
        gd = self.wfs.gd

        big_gd = gd.new_descriptor(comm=self.world)
        # Check whether grid is too small.  8 is smallest admissible.
        # (we decide this by how difficult it is to make the tests pass)
        # (Actually it depends on stencils!  But let the user deal with it)
        N_c = big_gd.get_size_of_global_array(pad=True)
        too_small = np.any(N_c / big_gd.parsize_c < 8)
        if self.parallel['augment_grids'] and not too_small:
            aux_gd = big_gd
        else:
            aux_gd = gd

        redistributor = GridRedistributor(self.world, self.wfs.kptband_comm,
                                          gd, aux_gd)

        # Construct grid descriptor for fine grids for densities
        # and potentials:
        finegd = aux_gd.refine()

        kwargs = dict(gd=gd,
                      finegd=finegd,
                      nspins=self.wfs.nspins,
                      charge=self.parameters.charge +
                      self.wfs.setups.core_charge,
                      redistributor=redistributor,
                      background_charge=background)

        if realspace:
            self.density = RealSpaceDensity(stencil=mode.interpolation,
                                            **kwargs)
        else:
            self.density = pw.ReciprocalSpaceDensity(**kwargs)

        self.log(self.density, '\n')

    def create_hamiltonian(self, realspace, mode, xc):
        dens = self.density
        kwargs = dict(gd=dens.gd,
                      finegd=dens.finegd,
                      nspins=dens.nspins,
                      setups=dens.setups,
                      timer=self.timer,
                      xc=xc,
                      world=self.world,
                      redistributor=dens.redistributor,
                      vext=self.parameters.external,
                      psolver=self.parameters.poissonsolver)
        if realspace:
            self.hamiltonian = RealSpaceHamiltonian(stencil=mode.interpolation,
                                                    **kwargs)
            xc.set_grid_descriptor(self.hamiltonian.finegd)  # XXX
        else:
            self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
                pd2=dens.pd2, pd3=dens.pd3, realpbc_c=self.atoms.pbc, **kwargs)
            xc.set_grid_descriptor(dens.xc_redistributor.aux_gd)  # XXX

        self.log(self.hamiltonian, '\n')

    def create_wave_functions(self, mode, realspace, nspins, nbands, nao,
                              nvalence, setups, magmom_a, cell_cv, pbc_c):
        par = self.parameters

        bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
        kd = KPointDescriptor(bzkpts_kc, nspins)

        self.timer.start('Set symmetry')
        kd.set_symmetry(self.atoms, self.symmetry, comm=self.world)
        self.timer.stop('Set symmetry')

        self.log(kd)

        parallelization = mpi.Parallelization(self.world, nspins * kd.nibzkpts)

        parsize_kpt = self.parallel['kpt']
        parsize_domain = self.parallel['domain']
        parsize_bands = self.parallel['band']

        ndomains = None
        if parsize_domain is not None:
            ndomains = np.prod(parsize_domain)
        if mode.name == 'pw':
            if ndomains is not None and ndomains > 1:
                raise ValueError('Planewave mode does not support '
                                 'domain decomposition.')
            ndomains = 1
        parallelization.set(kpt=parsize_kpt,
                            domain=ndomains,
                            band=parsize_bands)
        comms = parallelization.build_communicators()
        domain_comm = comms['d']
        kpt_comm = comms['k']
        band_comm = comms['b']
        kptband_comm = comms['D']
        domainband_comm = comms['K']

        self.comms = comms

        if par.gpts is not None:
            if par.h is not None:
                raise ValueError("""You can't use both "gpts" and "h"!""")
            N_c = np.array(par.gpts)
        else:
            h = par.h
            if h is not None:
                h /= Bohr
            N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
                                            kd.symmetry)

        self.symmetry.check_grid(N_c)

        kd.set_communicator(kpt_comm)

        parstride_bands = self.parallel['stridebands']

        # Unfortunately we need to remember that we adjusted the
        # number of bands so we can print a warning if it differs
        # from the number specified by the user.  (The number can
        # be inferred from the input parameters, but it's tricky
        # because we allow negative numbers)
        self.nbands_parallelization_adjustment = -nbands % band_comm.size
        nbands += self.nbands_parallelization_adjustment

        bd = BandDescriptor(nbands, band_comm, parstride_bands)

        # Construct grid descriptor for coarse grids for wave functions:
        gd = self.create_grid_descriptor(N_c, cell_cv, pbc_c, domain_comm,
                                         parsize_domain)

        if hasattr(self, 'time') or mode.force_complex_dtype:
            dtype = complex
        else:
            if kd.gamma:
                dtype = float
            else:
                dtype = complex

        wfs_kwargs = dict(gd=gd,
                          nvalence=nvalence,
                          setups=setups,
                          bd=bd,
                          dtype=dtype,
                          world=self.world,
                          kd=kd,
                          kptband_comm=kptband_comm,
                          timer=self.timer)

        if self.parallel['sl_auto']:
            # Choose scalapack parallelization automatically

            for key, val in self.parallel.items():
                if (key.startswith('sl_') and key != 'sl_auto'
                        and val is not None):
                    raise ValueError("Cannot use 'sl_auto' together "
                                     "with '%s'" % key)
            max_scalapack_cpus = bd.comm.size * gd.comm.size
            nprow = max_scalapack_cpus
            npcol = 1

            # Get a sort of reasonable number of columns/rows
            while npcol < nprow and nprow % 2 == 0:
                npcol *= 2
                nprow //= 2
            assert npcol * nprow == max_scalapack_cpus

            # ScaLAPACK creates trouble if there aren't at least a few
            # whole blocks; choose block size so there will always be
            # several blocks.  This will crash for small test systems,
            # but so will ScaLAPACK in any case
            blocksize = min(-(-nbands // 4), 64)
            sl_default = (nprow, npcol, blocksize)
        else:
            sl_default = self.parallel['sl_default']

        if mode.name == 'lcao':
            # Layouts used for general diagonalizer
            sl_lcao = self.parallel['sl_lcao']
            if sl_lcao is None:
                sl_lcao = sl_default
            lcaoksl = get_KohnSham_layouts(sl_lcao,
                                           'lcao',
                                           gd,
                                           bd,
                                           domainband_comm,
                                           dtype,
                                           nao=nao,
                                           timer=self.timer)

            self.wfs = mode(lcaoksl, **wfs_kwargs)

        elif mode.name == 'fd' or mode.name == 'pw':
            # buffer_size keyword only relevant for fdpw
            buffer_size = self.parallel['buffer_size']
            # Layouts used for diagonalizer
            sl_diagonalize = self.parallel['sl_diagonalize']
            if sl_diagonalize is None:
                sl_diagonalize = sl_default
            diagksl = get_KohnSham_layouts(
                sl_diagonalize,
                'fd',  # XXX
                # choice of key 'fd' not so nice
                gd,
                bd,
                domainband_comm,
                dtype,
                buffer_size=buffer_size,
                timer=self.timer)

            # Layouts used for orthonormalizer
            sl_inverse_cholesky = self.parallel['sl_inverse_cholesky']
            if sl_inverse_cholesky is None:
                sl_inverse_cholesky = sl_default
            if sl_inverse_cholesky != sl_diagonalize:
                message = 'sl_inverse_cholesky != sl_diagonalize ' \
                    'is not implemented.'
                raise NotImplementedError(message)
            orthoksl = get_KohnSham_layouts(sl_inverse_cholesky,
                                            'fd',
                                            gd,
                                            bd,
                                            domainband_comm,
                                            dtype,
                                            buffer_size=buffer_size,
                                            timer=self.timer)

            # Use (at most) all available LCAO for initialization
            lcaonbands = min(nbands, nao // band_comm.size * band_comm.size)

            try:
                lcaobd = BandDescriptor(lcaonbands, band_comm, parstride_bands)
            except RuntimeError:
                initksl = None
            else:
                # Layouts used for general diagonalizer
                # (LCAO initialization)
                sl_lcao = self.parallel['sl_lcao']
                if sl_lcao is None:
                    sl_lcao = sl_default
                initksl = get_KohnSham_layouts(sl_lcao,
                                               'lcao',
                                               gd,
                                               lcaobd,
                                               domainband_comm,
                                               dtype,
                                               nao=nao,
                                               timer=self.timer)

            self.wfs = mode(diagksl, orthoksl, initksl, **wfs_kwargs)
        else:
            self.wfs = mode(self, **wfs_kwargs)

        self.log(self.wfs, '\n')

    def dry_run(self):
        # Can be overridden like in gpaw.atom.atompaw
        print_cell(self.wfs.gd, self.atoms.pbc, self.log)
        print_positions(self.atoms, self.log)
        self.log.fd.flush()
        raise SystemExit
Пример #2
0
    def initialize(self, atoms=None):
        """Inexpensive initialization."""

        if atoms is None:
            atoms = self.atoms
        else:
            # Save the state of the atoms:
            self.atoms = atoms.copy()

        par = self.input_parameters

        world = par.communicator
        if world is None:
            world = mpi.world
        elif hasattr(world, 'new_communicator'):
            # Check for whether object has correct type already
            #
            # Using isinstance() is complicated because of all the
            # combinations, serial/parallel/debug...
            pass
        else:
            # world should be a list of ranks:
            world = mpi.world.new_communicator(np.asarray(world))
        self.wfs.world = world

        if 'txt' in self._changed_keywords:
            self.set_txt(par.txt)
        self.verbose = par.verbose

        natoms = len(atoms)

        cell_cv = atoms.get_cell() / Bohr
        pbc_c = atoms.get_pbc()
        Z_a = atoms.get_atomic_numbers()
        magmom_av = atoms.get_initial_magnetic_moments()

        self.check_atoms()

        # Generate new xc functional only when it is reset by set
        # XXX sounds like this should use the _changed_keywords dictionary.
        if self.hamiltonian is None or self.hamiltonian.xc is None:
            if isinstance(par.xc, str):
                xc = XC(par.xc)
            else:
                xc = par.xc
        else:
            xc = self.hamiltonian.xc

        mode = par.mode

        if mode == 'fd':
            mode = FD()
        elif mode == 'pw':
            mode = pw.PW()
        elif mode == 'lcao':
            mode = LCAO()
        else:
            assert hasattr(mode, 'name'), str(mode)

        if xc.orbital_dependent and mode.name == 'lcao':
            raise NotImplementedError('LCAO mode does not support '
                                      'orbital-dependent XC functionals.')

        if par.realspace is None:
            realspace = (mode.name != 'pw')
        else:
            realspace = par.realspace
            if mode.name == 'pw':
                assert not realspace

        if par.filter is None and mode.name != 'pw':
            gamma = 1.6
            if par.gpts is not None:
                h = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5 / par.gpts).max()
            else:
                h = (par.h or 0.2) / Bohr

            def filter(rgd, rcut, f_r, l=0):
                gcut = np.pi / h - 2 / rcut / gamma
                f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
        else:
            filter = par.filter

        setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc, filter,
                        world)

        if magmom_av.ndim == 1:
            collinear = True
            magmom_av, magmom_a = np.zeros((natoms, 3)), magmom_av
            magmom_av[:, 2] = magmom_a
        else:
            collinear = False

        magnetic = magmom_av.any()

        spinpol = par.spinpol
        if par.hund:
            if natoms != 1:
                raise ValueError('hund=True arg only valid for single atoms!')
            spinpol = True
            magmom_av[0] = (0, 0, setups[0].get_hunds_rule_moment(par.charge))

        if spinpol is None:
            spinpol = magnetic
        elif magnetic and not spinpol:
            raise ValueError('Non-zero initial magnetic moment for a ' +
                             'spin-paired calculation!')

        if collinear:
            nspins = 1 + int(spinpol)
            ncomp = 1
        else:
            nspins = 1
            ncomp = 2

        if par.usesymm != 'default':
            warnings.warn('Use "symmetry" keyword instead of ' +
                          '"usesymm" keyword')
            par.symmetry = usesymm2symmetry(par.usesymm)

        symm = par.symmetry
        if symm == 'off':
            symm = {'point_group': False, 'time_reversal': False}

        bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
        kd = KPointDescriptor(bzkpts_kc, nspins, collinear)
        m_av = magmom_av.round(decimals=3)  # round off
        id_a = zip(setups.id_a, *m_av.T)
        symmetry = Symmetry(id_a, cell_cv, atoms.pbc, **symm)
        kd.set_symmetry(atoms, symmetry, comm=world)
        setups.set_symmetry(symmetry)

        if par.gpts is not None:
            N_c = np.array(par.gpts)
        else:
            h = par.h
            if h is not None:
                h /= Bohr
            N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
                                            kd.symmetry)

        symmetry.check_grid(N_c)

        width = par.width
        if width is None:
            if pbc_c.any():
                width = 0.1  # eV
            else:
                width = 0.0
        else:
            assert par.occupations is None

        if hasattr(self, 'time') or par.dtype == complex:
            dtype = complex
        else:
            if kd.gamma:
                dtype = float
            else:
                dtype = complex

        nao = setups.nao
        nvalence = setups.nvalence - par.charge
        M_v = magmom_av.sum(0)
        M = np.dot(M_v, M_v)**0.5

        nbands = par.nbands

        orbital_free = any(setup.orbital_free for setup in setups)
        if orbital_free:
            nbands = 1

        if isinstance(nbands, basestring):
            if nbands[-1] == '%':
                basebands = int(nvalence + M + 0.5) // 2
                nbands = int((float(nbands[:-1]) / 100) * basebands)
            else:
                raise ValueError('Integer Expected: Only use a string '
                                 'if giving a percentage of occupied bands')

        if nbands is None:
            nbands = 0
            for setup in setups:
                nbands_from_atom = setup.get_default_nbands()

                # Any obscure setup errors?
                if nbands_from_atom < -(-setup.Nv // 2):
                    raise ValueError('Bad setup: This setup requests %d'
                                     ' bands but has %d electrons.' %
                                     (nbands_from_atom, setup.Nv))
                nbands += nbands_from_atom
            nbands = min(nao, nbands)
        elif nbands > nao and mode.name == 'lcao':
            raise ValueError('Too many bands for LCAO calculation: '
                             '%d bands and only %d atomic orbitals!' %
                             (nbands, nao))

        if nvalence < 0:
            raise ValueError(
                'Charge %f is not possible - not enough valence electrons' %
                par.charge)

        if nbands <= 0:
            nbands = int(nvalence + M + 0.5) // 2 + (-nbands)

        if nvalence > 2 * nbands and not orbital_free:
            raise ValueError('Too few bands!  Electrons: %f, bands: %d' %
                             (nvalence, nbands))

        nbands *= ncomp

        if par.width is not None:
            self.text('**NOTE**: please start using '
                      'occupations=FermiDirac(width).')
        if par.fixmom:
            self.text('**NOTE**: please start using '
                      'occupations=FermiDirac(width, fixmagmom=True).')

        if self.occupations is None:
            if par.occupations is None:
                # Create object for occupation numbers:
                if orbital_free:
                    width = 0.0  # even for PBC
                    self.occupations = occupations.TFOccupations(
                        width, par.fixmom)
                else:
                    self.occupations = occupations.FermiDirac(
                        width, par.fixmom)
            else:
                self.occupations = par.occupations

            # If occupation numbers are changed, and we have wave functions,
            # recalculate the occupation numbers
            if self.wfs is not None and not isinstance(self.wfs,
                                                       EmptyWaveFunctions):
                self.occupations.calculate(self.wfs)

        self.occupations.magmom = M_v[2]

        cc = par.convergence

        if mode.name == 'lcao':
            niter_fixdensity = 0
        else:
            niter_fixdensity = None

        if self.scf is None:
            force_crit = cc['forces']
            if force_crit is not None:
                force_crit /= Hartree / Bohr
            self.scf = SCFLoop(cc['eigenstates'] / Hartree**2 * nvalence,
                               cc['energy'] / Hartree * max(nvalence, 1),
                               cc['density'] * nvalence, par.maxiter,
                               par.fixdensity, niter_fixdensity, force_crit)

        parsize_kpt = par.parallel['kpt']
        parsize_domain = par.parallel['domain']
        parsize_bands = par.parallel['band']

        if not realspace:
            pbc_c = np.ones(3, bool)

        if not self.wfs:
            if parsize_domain == 'domain only':  # XXX this was silly!
                parsize_domain = world.size

            parallelization = mpi.Parallelization(world, nspins * kd.nibzkpts)
            ndomains = None
            if parsize_domain is not None:
                ndomains = np.prod(parsize_domain)
            if mode.name == 'pw':
                if ndomains > 1:
                    raise ValueError('Planewave mode does not support '
                                     'domain decomposition.')
                ndomains = 1
            parallelization.set(kpt=parsize_kpt,
                                domain=ndomains,
                                band=parsize_bands)
            comms = parallelization.build_communicators()
            domain_comm = comms['d']
            kpt_comm = comms['k']
            band_comm = comms['b']
            kptband_comm = comms['D']
            domainband_comm = comms['K']

            self.comms = comms
            kd.set_communicator(kpt_comm)

            parstride_bands = par.parallel['stridebands']

            # Unfortunately we need to remember that we adjusted the
            # number of bands so we can print a warning if it differs
            # from the number specified by the user.  (The number can
            # be inferred from the input parameters, but it's tricky
            # because we allow negative numbers)
            self.nbands_parallelization_adjustment = -nbands % band_comm.size
            nbands += self.nbands_parallelization_adjustment

            # I would like to give the following error message, but apparently
            # there are cases, e.g. gpaw/test/gw_ppa.py, which involve
            # nbands > nao and are supposed to work that way.
            #if nbands > nao:
            #    raise ValueError('Number of bands %d adjusted for band '
            #                     'parallelization %d exceeds number of atomic '
            #                     'orbitals %d.  This problem can be fixed '
            #                     'by reducing the number of bands a bit.'
            #                     % (nbands, band_comm.size, nao))
            bd = BandDescriptor(nbands, band_comm, parstride_bands)

            if (self.density is not None
                    and self.density.gd.comm.size != domain_comm.size):
                # Domain decomposition has changed, so we need to
                # reinitialize density and hamiltonian:
                if par.fixdensity:
                    raise RuntimeError(
                        'Density reinitialization conflict ' +
                        'with "fixdensity" - specify domain decomposition.')
                self.density = None
                self.hamiltonian = None

            # Construct grid descriptor for coarse grids for wave functions:
            gd = self.grid_descriptor_class(N_c, cell_cv, pbc_c, domain_comm,
                                            parsize_domain)

            # do k-point analysis here? XXX
            args = (gd, nvalence, setups, bd, dtype, world, kd, kptband_comm,
                    self.timer)

            if par.parallel['sl_auto']:
                # Choose scalapack parallelization automatically

                for key, val in par.parallel.items():
                    if (key.startswith('sl_') and key != 'sl_auto'
                            and val is not None):
                        raise ValueError("Cannot use 'sl_auto' together "
                                         "with '%s'" % key)
                max_scalapack_cpus = bd.comm.size * gd.comm.size
                nprow = max_scalapack_cpus
                npcol = 1

                # Get a sort of reasonable number of columns/rows
                while npcol < nprow and nprow % 2 == 0:
                    npcol *= 2
                    nprow //= 2
                assert npcol * nprow == max_scalapack_cpus

                # ScaLAPACK creates trouble if there aren't at least a few
                # whole blocks; choose block size so there will always be
                # several blocks.  This will crash for small test systems,
                # but so will ScaLAPACK in any case
                blocksize = min(-(-nbands // 4), 64)
                sl_default = (nprow, npcol, blocksize)
            else:
                sl_default = par.parallel['sl_default']

            if mode.name == 'lcao':
                # Layouts used for general diagonalizer
                sl_lcao = par.parallel['sl_lcao']
                if sl_lcao is None:
                    sl_lcao = sl_default
                lcaoksl = get_KohnSham_layouts(sl_lcao,
                                               'lcao',
                                               gd,
                                               bd,
                                               domainband_comm,
                                               dtype,
                                               nao=nao,
                                               timer=self.timer)

                self.wfs = mode(collinear, lcaoksl, *args)

            elif mode.name == 'fd' or mode.name == 'pw':
                # buffer_size keyword only relevant for fdpw
                buffer_size = par.parallel['buffer_size']
                # Layouts used for diagonalizer
                sl_diagonalize = par.parallel['sl_diagonalize']
                if sl_diagonalize is None:
                    sl_diagonalize = sl_default
                diagksl = get_KohnSham_layouts(
                    sl_diagonalize,
                    'fd',  # XXX
                    # choice of key 'fd' not so nice
                    gd,
                    bd,
                    domainband_comm,
                    dtype,
                    buffer_size=buffer_size,
                    timer=self.timer)

                # Layouts used for orthonormalizer
                sl_inverse_cholesky = par.parallel['sl_inverse_cholesky']
                if sl_inverse_cholesky is None:
                    sl_inverse_cholesky = sl_default
                if sl_inverse_cholesky != sl_diagonalize:
                    message = 'sl_inverse_cholesky != sl_diagonalize ' \
                        'is not implemented.'
                    raise NotImplementedError(message)
                orthoksl = get_KohnSham_layouts(sl_inverse_cholesky,
                                                'fd',
                                                gd,
                                                bd,
                                                domainband_comm,
                                                dtype,
                                                buffer_size=buffer_size,
                                                timer=self.timer)

                # Use (at most) all available LCAO for initialization
                lcaonbands = min(nbands, nao)

                try:
                    lcaobd = BandDescriptor(lcaonbands, band_comm,
                                            parstride_bands)
                except RuntimeError:
                    initksl = None
                else:
                    # Layouts used for general diagonalizer
                    # (LCAO initialization)
                    sl_lcao = par.parallel['sl_lcao']
                    if sl_lcao is None:
                        sl_lcao = sl_default
                    initksl = get_KohnSham_layouts(sl_lcao,
                                                   'lcao',
                                                   gd,
                                                   lcaobd,
                                                   domainband_comm,
                                                   dtype,
                                                   nao=nao,
                                                   timer=self.timer)

                if hasattr(self, 'time'):
                    assert mode.name == 'fd'
                    from gpaw.tddft import TimeDependentWaveFunctions
                    self.wfs = TimeDependentWaveFunctions(
                        par.stencils[0], diagksl, orthoksl, initksl, gd,
                        nvalence, setups, bd, world, kd, kptband_comm,
                        self.timer)
                elif mode.name == 'fd':
                    self.wfs = mode(par.stencils[0], diagksl, orthoksl,
                                    initksl, *args)
                else:
                    assert mode.name == 'pw'
                    self.wfs = mode(diagksl, orthoksl, initksl, *args)
            else:
                self.wfs = mode(self, *args)
        else:
            self.wfs.set_setups(setups)

        if not self.wfs.eigensolver:
            # Number of bands to converge:
            nbands_converge = cc['bands']
            if nbands_converge == 'all':
                nbands_converge = nbands
            elif nbands_converge != 'occupied':
                assert isinstance(nbands_converge, int)
                if nbands_converge < 0:
                    nbands_converge += nbands
            eigensolver = get_eigensolver(par.eigensolver, mode,
                                          par.convergence)
            eigensolver.nbands_converge = nbands_converge
            # XXX Eigensolver class doesn't define an nbands_converge property

            if isinstance(xc, SIC):
                eigensolver.blocksize = 1
            self.wfs.set_eigensolver(eigensolver)

        if self.density is None:
            gd = self.wfs.gd
            if par.stencils[1] != 9:
                # Construct grid descriptor for fine grids for densities
                # and potentials:
                finegd = gd.refine()
            else:
                # Special case (use only coarse grid):
                finegd = gd

            if realspace:
                self.density = RealSpaceDensity(
                    gd, finegd, nspins, par.charge + setups.core_charge,
                    collinear, par.stencils[1])
            else:
                self.density = pw.ReciprocalSpaceDensity(
                    gd, finegd, nspins, par.charge + setups.core_charge,
                    collinear)

        self.density.initialize(setups, self.timer, magmom_av, par.hund)
        self.density.set_mixer(par.mixer)

        if self.hamiltonian is None:
            gd, finegd = self.density.gd, self.density.finegd
            if realspace:
                self.hamiltonian = RealSpaceHamiltonian(
                    gd, finegd, nspins, setups, self.timer, xc, world,
                    self.wfs.kptband_comm, par.external, collinear,
                    par.poissonsolver, par.stencils[1])
            else:
                self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
                    gd, finegd, self.density.pd2, self.density.pd3, nspins,
                    setups, self.timer, xc, world, self.wfs.kptband_comm,
                    par.external, collinear)

        xc.initialize(self.density, self.hamiltonian, self.wfs,
                      self.occupations)

        self.text()
        self.print_memory_estimate(self.txt, maxdepth=memory_estimate_depth)
        self.txt.flush()

        self.timer.print_info(self)

        if dry_run:
            self.dry_run()

        if realspace and \
                self.hamiltonian.poisson.get_description() == 'FDTD+TDDFT':
            self.hamiltonian.poisson.set_density(self.density)
            self.hamiltonian.poisson.print_messages(self.text)
            self.txt.flush()

        self.initialized = True
        self._changed_keywords.clear()
Пример #3
0
class GPAW(PAW, Calculator):
    """This is the ASE-calculator frontend for doing a PAW calculation."""

    implemented_properties = [
        'energy', 'forces', 'stress', 'dipole', 'magmom', 'magmoms'
    ]

    default_parameters = {
        'mode': 'fd',
        'xc': 'LDA',
        'occupations': None,
        'poissonsolver': None,
        'h': None,  # Angstrom
        'gpts': None,
        'kpts': [(0.0, 0.0, 0.0)],
        'nbands': None,
        'charge': 0,
        'setups': {},
        'basis': {},
        'spinpol': None,
        'fixdensity': False,
        'filter': None,
        'mixer': None,
        'eigensolver': None,
        'background_charge': None,
        'experimental': {
            'reuse_wfs_method': 'paw',
            'niter_fixdensity': 0,
            'magmoms': None,
            'soc': None,
            'kpt_refine': None
        },
        'external': None,
        'random': False,
        'hund': False,
        'maxiter': 333,
        'idiotproof': True,
        'symmetry': {
            'point_group': True,
            'time_reversal': True,
            'symmorphic': True,
            'tolerance': 1e-7,
            'do_not_symmetrize_the_density': False
        },
        'convergence': {
            'energy': 0.0005,  # eV / electron
            'density': 1.0e-4,
            'eigenstates': 4.0e-8,  # eV^2
            'bands': 'occupied',
            'forces': np.inf
        },  # eV / Ang
        'dtype': None,  # Deprecated
        'width': None,  # Deprecated
        'verbose': 0
    }

    default_parallel = {
        'kpt': None,
        'domain': gpaw.parsize_domain,
        'band': gpaw.parsize_bands,
        'order': 'kdb',
        'stridebands': False,
        'augment_grids': gpaw.augment_grids,
        'sl_auto': False,
        'sl_default': gpaw.sl_default,
        'sl_diagonalize': gpaw.sl_diagonalize,
        'sl_inverse_cholesky': gpaw.sl_inverse_cholesky,
        'sl_lcao': gpaw.sl_lcao,
        'sl_lrtddft': gpaw.sl_lrtddft,
        'use_elpa': False,
        'elpasolver': '2stage',
        'buffer_size': gpaw.buffer_size
    }

    def __init__(self,
                 restart=None,
                 ignore_bad_restart_file=False,
                 label=None,
                 atoms=None,
                 timer=None,
                 communicator=None,
                 txt='-',
                 parallel=None,
                 **kwargs):

        self.parallel = dict(self.default_parallel)
        if parallel:
            for key in parallel:
                if key not in self.default_parallel:
                    allowed = ', '.join(list(self.default_parallel.keys()))
                    raise TypeError('Unexpected keyword "{}" in "parallel" '
                                    'dictionary.  Must be one of: {}'.format(
                                        key, allowed))
            self.parallel.update(parallel)

        if timer is None:
            self.timer = Timer()
        else:
            self.timer = timer

        self.scf = None
        self.wfs = None
        self.occupations = None
        self.density = None
        self.hamiltonian = None
        self.spos_ac = None  # XXX store this in some better way.

        self.observers = []  # XXX move to self.scf
        self.initialized = False

        self.world = communicator
        if self.world is None:
            self.world = mpi.world
        elif not hasattr(self.world, 'new_communicator'):
            self.world = mpi.world.new_communicator(np.asarray(self.world))

        self.log = GPAWLogger(world=self.world)
        self.log.fd = txt

        self.reader = None

        Calculator.__init__(self, restart, ignore_bad_restart_file, label,
                            atoms, **kwargs)

    def __del__(self):
        # Write timings and close reader if necessary.

        # If we crashed in the constructor (e.g. a bad keyword), we may not
        # have the normally expected attributes:
        if hasattr(self, 'timer'):
            self.timer.write(self.log.fd)

        if hasattr(self, 'reader') and self.reader is not None:
            self.reader.close()

    def write(self, filename, mode=''):
        self.log('Writing to {} (mode={!r})\n'.format(filename, mode))
        writer = Writer(filename, self.world)
        self._write(writer, mode)
        writer.close()
        self.world.barrier()

    def _write(self, writer, mode):
        from ase.io.trajectory import write_atoms
        writer.write(version=1,
                     gpaw_version=gpaw.__version__,
                     ha=Ha,
                     bohr=Bohr)

        write_atoms(writer.child('atoms'), self.atoms)
        writer.child('results').write(**self.results)
        writer.child('parameters').write(**self.todict())

        self.density.write(writer.child('density'))
        self.hamiltonian.write(writer.child('hamiltonian'))
        self.occupations.write(writer.child('occupations'))
        self.scf.write(writer.child('scf'))
        self.wfs.write(writer.child('wave_functions'), mode == 'all')

        return writer

    def _set_atoms(self, atoms):
        check_atoms_too_close(atoms)
        self.atoms = atoms
        # GPAW works in terms of the scaled positions.  We want to
        # extract the scaled positions in only one place, and that is
        # here.  No other place may recalculate them, or we might end up
        # with rounding errors and inconsistencies.
        self.spos_ac = atoms.get_scaled_positions() % 1.0

    def read(self, filename):
        from ase.io.trajectory import read_atoms
        self.log('Reading from {}'.format(filename))

        self.reader = reader = Reader(filename)

        atoms = read_atoms(reader.atoms)
        self._set_atoms(atoms)

        res = reader.results
        self.results = dict((key, res.get(key)) for key in res.keys())
        if self.results:
            self.log('Read {}'.format(', '.join(sorted(self.results))))

        self.log('Reading input parameters:')
        # XXX param
        self.parameters = self.get_default_parameters()
        dct = {}
        for key, value in reader.parameters.asdict().items():
            if (isinstance(value, dict)
                    and isinstance(self.parameters[key], dict)):
                self.parameters[key].update(value)
            else:
                self.parameters[key] = value
            dct[key] = self.parameters[key]

        self.log.print_dict(dct)
        self.log()

        self.initialize(reading=True)

        self.density.read(reader)
        self.hamiltonian.read(reader)
        self.occupations.read(reader)
        self.scf.read(reader)
        self.wfs.read(reader)

        # We need to do this in a better way:  XXX
        from gpaw.utilities.partition import AtomPartition
        atom_partition = AtomPartition(self.wfs.gd.comm,
                                       np.zeros(len(self.atoms), dtype=int))
        self.wfs.atom_partition = atom_partition
        self.density.atom_partition = atom_partition
        self.hamiltonian.atom_partition = atom_partition
        rank_a = self.density.gd.get_ranks_from_positions(self.spos_ac)
        new_atom_partition = AtomPartition(self.density.gd.comm, rank_a)
        for obj in [self.density, self.hamiltonian]:
            obj.set_positions_without_ruining_everything(
                self.spos_ac, new_atom_partition)

        self.hamiltonian.xc.read(reader)

        if self.hamiltonian.xc.name == 'GLLBSC':
            # XXX GLLB: See test/lcaotddft/gllbsc.py
            self.occupations.calculate(self.wfs)

        return reader

    def check_state(self, atoms, tol=1e-15):
        system_changes = Calculator.check_state(self, atoms, tol)
        if 'positions' not in system_changes:
            if self.hamiltonian:
                if self.hamiltonian.vext:
                    if self.hamiltonian.vext.vext_g is None:
                        # QMMM atoms have moved:
                        system_changes.append('positions')
        return system_changes

    def calculate(self,
                  atoms=None,
                  properties=['energy'],
                  system_changes=['cell']):
        """Calculate things."""

        Calculator.calculate(self, atoms)
        atoms = self.atoms

        if system_changes:
            self.log('System changes:', ', '.join(system_changes), '\n')
            if system_changes == ['positions']:
                # Only positions have changed:
                self.density.reset()
            else:
                # Drastic changes:
                self.wfs = None
                self.occupations = None
                self.density = None
                self.hamiltonian = None
                self.scf = None
                self.initialize(atoms)

            self.set_positions(atoms)

        if not self.initialized:
            self.initialize(atoms)
            self.set_positions(atoms)

        if not (self.wfs.positions_set and self.hamiltonian.positions_set):
            self.set_positions(atoms)

        if not self.scf.converged:
            print_cell(self.wfs.gd, self.atoms.pbc, self.log)

            with self.timer('SCF-cycle'):
                self.scf.run(self.wfs, self.hamiltonian, self.density,
                             self.occupations, self.log, self.call_observers)

            self.log('\nConverged after {} iterations.\n'.format(
                self.scf.niter))

            e_free = self.hamiltonian.e_total_free
            e_extrapolated = self.hamiltonian.e_total_extrapolated
            self.results['energy'] = e_extrapolated * Ha
            self.results['free_energy'] = e_free * Ha

            dipole_v = self.density.calculate_dipole_moment() * Bohr
            self.log(
                'Dipole moment: ({:.6f}, {:.6f}, {:.6f}) |e|*Ang\n'.format(
                    *dipole_v))
            self.results['dipole'] = dipole_v

            if self.wfs.nspins == 2 or not self.density.collinear:
                totmom_v, magmom_av = self.density.estimate_magnetic_moments()
                self.log(
                    'Total magnetic moment: ({:.6f}, {:.6f}, {:.6f})'.format(
                        *totmom_v))
                self.log('Local magnetic moments:')
                symbols = self.atoms.get_chemical_symbols()
                for a, mom_v in enumerate(magmom_av):
                    self.log('{:4} {:2} ({:9.6f}, {:9.6f}, {:9.6f})'.format(
                        a, symbols[a], *mom_v))
                self.log()
                self.results['magmom'] = self.occupations.magmom
                self.results['magmoms'] = magmom_av[:, 2].copy()

            self.summary()

            self.call_observers(self.scf.niter, final=True)

        if 'forces' in properties:
            with self.timer('Forces'):
                F_av = calculate_forces(self.wfs, self.density,
                                        self.hamiltonian, self.log)
                self.results['forces'] = F_av * (Ha / Bohr)

        if 'stress' in properties:
            with self.timer('Stress'):
                try:
                    stress = calculate_stress(self).flat[[0, 4, 8, 5, 2, 1]]
                except NotImplementedError:
                    # Our ASE Calculator base class will raise
                    # PropertyNotImplementedError for us.
                    pass
                else:
                    self.results['stress'] = stress * (Ha / Bohr**3)

    def summary(self):
        efermi = self.occupations.fermilevel
        self.hamiltonian.summary(efermi, self.log)
        self.density.summary(self.atoms, self.occupations.magmom, self.log)
        self.occupations.summary(self.log)
        self.wfs.summary(self.log)
        try:
            bandgap(self, output=self.log.fd, efermi=efermi * Ha)
        except ValueError:
            pass
        self.log.fd.flush()

    def set(self, **kwargs):
        """Change parameters for calculator.

        Examples::

            calc.set(xc='PBE')
            calc.set(nbands=20, kpts=(4, 1, 1))
        """

        # Verify that keys are consistent with default ones.
        for key in kwargs:
            if key != 'txt' and key not in self.default_parameters:
                raise TypeError('Unknown GPAW parameter: {}'.format(key))

            if key in ['convergence', 'symmetry', 'experimental'
                       ] and isinstance(kwargs[key], dict):
                # For values that are dictionaries, verify subkeys, too.
                default_dict = self.default_parameters[key]
                for subkey in kwargs[key]:
                    if subkey not in default_dict:
                        allowed = ', '.join(list(default_dict.keys()))
                        raise TypeError('Unknown subkeyword "{}" of keyword '
                                        '"{}".  Must be one of: {}'.format(
                                            subkey, key, allowed))

        changed_parameters = Calculator.set(self, **kwargs)

        for key in ['setups', 'basis']:
            if key in changed_parameters:
                dct = changed_parameters[key]
                if isinstance(dct, dict) and None in dct:
                    dct['default'] = dct.pop(None)
                    warnings.warn('Please use {key}={dct}'.format(key=key,
                                                                  dct=dct))

        # We need to handle txt early in order to get logging up and running:
        if 'txt' in changed_parameters:
            self.log.fd = changed_parameters.pop('txt')

        if not changed_parameters:
            return {}

        self.initialized = False
        self.scf = None
        self.results = {}

        self.log('Input parameters:')
        self.log.print_dict(changed_parameters)
        self.log()

        for key in changed_parameters:
            if key in ['eigensolver', 'convergence'] and self.wfs:
                self.wfs.set_eigensolver(None)

            if key in [
                    'mixer', 'verbose', 'txt', 'hund', 'random', 'eigensolver',
                    'idiotproof'
            ]:
                continue

            if key in ['convergence', 'fixdensity', 'maxiter']:
                continue

            # Check nested arguments
            if key in ['experimental']:
                changed_parameters2 = changed_parameters[key]
                for key2 in changed_parameters2:
                    if key2 in ['kpt_refine', 'magmoms', 'soc']:
                        self.wfs = None
                    elif key2 in ['reuse_wfs_method', 'niter_fixdensity']:
                        continue
                    else:
                        raise TypeError('Unknown keyword argument:', key2)
                continue

            # More drastic changes:
            if self.wfs:
                self.wfs.set_orthonormalized(False)
            if key in ['external', 'xc', 'poissonsolver']:
                self.hamiltonian = None
            elif key in ['occupations', 'width']:
                pass
            elif key in ['charge', 'background_charge']:
                self.hamiltonian = None
                self.density = None
                self.wfs = None
            elif key in ['kpts', 'nbands', 'symmetry']:
                self.wfs = None
            elif key in ['h', 'gpts', 'setups', 'spinpol', 'dtype', 'mode']:
                self.density = None
                self.hamiltonian = None
                self.wfs = None
            elif key in ['basis']:
                self.wfs = None
            else:
                raise TypeError('Unknown keyword argument: "%s"' % key)

    def initialize_positions(self, atoms=None):
        """Update the positions of the atoms."""
        self.log('Initializing position-dependent things.\n')
        if atoms is None:
            atoms = self.atoms
        else:
            atoms = atoms.copy()
            self._set_atoms(atoms)

        mpi.synchronize_atoms(atoms, self.world)

        rank_a = self.wfs.gd.get_ranks_from_positions(self.spos_ac)
        atom_partition = AtomPartition(self.wfs.gd.comm, rank_a, name='gd')
        self.wfs.set_positions(self.spos_ac, atom_partition)
        self.density.set_positions(self.spos_ac, atom_partition)
        self.hamiltonian.set_positions(self.spos_ac, atom_partition)

    def set_positions(self, atoms=None):
        """Update the positions of the atoms and initialize wave functions."""
        self.initialize_positions(atoms)

        nlcao, nrand = self.wfs.initialize(self.density, self.hamiltonian,
                                           self.spos_ac)
        if nlcao + nrand:
            self.log('Creating initial wave functions:')
            if nlcao:
                self.log(' ', plural(nlcao, 'band'), 'from LCAO basis set')
            if nrand:
                self.log(' ', plural(nrand, 'band'), 'from random numbers')
            self.log()

        self.wfs.eigensolver.reset()
        self.scf.reset()
        print_positions(self.atoms, self.log, self.density.magmom_av)

    def initialize(self, atoms=None, reading=False):
        """Inexpensive initialization."""

        self.log('Initialize ...\n')

        if atoms is None:
            atoms = self.atoms
        else:
            atoms = atoms.copy()
            self._set_atoms(atoms)

        par = self.parameters

        natoms = len(atoms)

        cell_cv = atoms.get_cell() / Bohr
        number_of_lattice_vectors = cell_cv.any(axis=1).sum()
        if number_of_lattice_vectors < 3:
            raise ValueError(
                'GPAW requires 3 lattice vectors.  Your system has {}.'.format(
                    number_of_lattice_vectors))

        pbc_c = atoms.get_pbc()
        assert len(pbc_c) == 3
        magmom_a = atoms.get_initial_magnetic_moments()

        if par.experimental.get('magmoms') is not None:
            magmom_av = np.array(par.experimental['magmoms'], float)
            collinear = False
        else:
            magmom_av = np.zeros((natoms, 3))
            magmom_av[:, 2] = magmom_a
            collinear = True

        mpi.synchronize_atoms(atoms, self.world)

        # Generate new xc functional only when it is reset by set
        # XXX sounds like this should use the _changed_keywords dictionary.
        if self.hamiltonian is None or self.hamiltonian.xc is None:
            if isinstance(par.xc, (basestring, dict)):
                xc = XC(par.xc, collinear=collinear, atoms=atoms)
            else:
                xc = par.xc
        else:
            xc = self.hamiltonian.xc

        mode = par.mode
        if isinstance(mode, basestring):
            mode = {'name': mode}
        if isinstance(mode, dict):
            mode = create_wave_function_mode(**mode)

        if par.dtype == complex:
            warnings.warn('Use mode={}(..., force_complex_dtype=True) '
                          'instead of dtype=complex'.format(mode.name.upper()))
            mode.force_complex_dtype = True
            del par['dtype']
            par.mode = mode

        if xc.orbital_dependent and mode.name == 'lcao':
            raise ValueError('LCAO mode does not support '
                             'orbital-dependent XC functionals.')

        realspace = (mode.name != 'pw' and mode.interpolation != 'fft')

        if not realspace:
            pbc_c = np.ones(3, bool)

        self.create_setups(mode, xc)

        if par.hund:
            if natoms != 1:
                raise ValueError('hund=True arg only valid for single atoms!')
            spinpol = True
            magmom_av[0, 2] = self.setups[0].get_hunds_rule_moment(par.charge)

        if collinear:
            magnetic = magmom_av.any()

            spinpol = par.spinpol
            if spinpol is None:
                spinpol = magnetic
            elif magnetic and not spinpol:
                raise ValueError('Non-zero initial magnetic moment for a ' +
                                 'spin-paired calculation!')
            nspins = 1 + int(spinpol)

            if spinpol:
                self.log('Spin-polarized calculation.')
                self.log('Magnetic moment: {:.6f}\n'.format(magmom_av.sum()))
            else:
                self.log('Spin-paired calculation\n')
        else:
            nspins = 1
            self.log('Non-collinear calculation.')
            self.log('Magnetic moment: ({:.6f}, {:.6f}, {:.6f})\n'.format(
                *magmom_av.sum(0)))

        if isinstance(par.background_charge, dict):
            background = create_background_charge(**par.background_charge)
        else:
            background = par.background_charge

        nao = self.setups.nao
        nvalence = self.setups.nvalence - par.charge
        if par.background_charge is not None:
            nvalence += background.charge

        M = np.linalg.norm(magmom_av.sum(0))

        nbands = par.nbands

        orbital_free = any(setup.orbital_free for setup in self.setups)
        if orbital_free:
            nbands = 1

        if isinstance(nbands, basestring):
            if nbands == 'nao':
                nbands = nao
            elif nbands[-1] == '%':
                basebands = (nvalence + M) / 2
                nbands = int(np.ceil(float(nbands[:-1]) / 100 * basebands))
            else:
                raise ValueError('Integer expected: Only use a string '
                                 'if giving a percentage of occupied bands')

        if nbands is None:
            # Number of bound partial waves:
            nbandsmax = sum(setup.get_default_nbands()
                            for setup in self.setups)
            nbands = int(np.ceil((1.2 * (nvalence + M) / 2))) + 4
            if nbands > nbandsmax:
                nbands = nbandsmax
            if mode.name == 'lcao' and nbands > nao:
                nbands = nao
        elif nbands <= 0:
            nbands = max(1, int(nvalence + M + 0.5) // 2 + (-nbands))

        if nbands > nao and mode.name == 'lcao':
            raise ValueError('Too many bands for LCAO calculation: '
                             '%d bands and only %d atomic orbitals!' %
                             (nbands, nao))

        if nvalence < 0:
            raise ValueError(
                'Charge %f is not possible - not enough valence electrons' %
                par.charge)

        if nvalence > 2 * nbands and not orbital_free:
            raise ValueError('Too few bands!  Electrons: %f, bands: %d' %
                             (nvalence, nbands))

        self.create_occupations(magmom_av[:, 2].sum(), orbital_free)

        if self.scf is None:
            self.create_scf(nvalence, mode)

        self.create_symmetry(magmom_av, cell_cv)

        if not collinear:
            nbands *= 2

        if not self.wfs:
            self.create_wave_functions(mode, realspace, nspins, collinear,
                                       nbands, nao, nvalence, self.setups,
                                       cell_cv, pbc_c)
        else:
            self.wfs.set_setups(self.setups)

        if not self.wfs.eigensolver:
            self.create_eigensolver(xc, nbands, mode)

        if self.density is None and not reading:
            assert not par.fixdensity, 'No density to fix!'

        olddens = None
        if (self.density is not None and
            (self.density.gd.parsize_c != self.wfs.gd.parsize_c).any()):
            # Domain decomposition has changed, so we need to
            # reinitialize density and hamiltonian:
            if par.fixdensity:
                olddens = self.density

            self.density = None
            self.hamiltonian = None

        if self.density is None:
            self.create_density(realspace, mode, background)

        # XXXXXXXXXX if setups change, then setups.core_charge may change.
        # But that parameter was supplied in Density constructor!
        # This surely is a bug!
        self.density.initialize(self.setups, self.timer, magmom_av, par.hund)
        self.density.set_mixer(par.mixer)
        if self.density.mixer.driver.name == 'dummy' or par.fixdensity:
            self.log('No density mixing\n')
        else:
            self.log(self.density.mixer, '\n')
        self.density.fixed = par.fixdensity
        self.density.log = self.log

        if olddens is not None:
            self.density.initialize_from_other_density(olddens,
                                                       self.wfs.kptband_comm)

        if self.hamiltonian is None:
            self.create_hamiltonian(realspace, mode, xc)

        xc.initialize(self.density, self.hamiltonian, self.wfs,
                      self.occupations)
        description = xc.get_description()
        if description is not None:
            self.log('XC parameters: {}\n'.format('\n  '.join(
                description.splitlines())))

        if xc.name == 'GLLBSC' and olddens is not None:
            xc.heeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeelp(olddens)

        self.print_memory_estimate(maxdepth=memory_estimate_depth + 1)

        print_parallelization_details(self.wfs, self.hamiltonian, self.log)

        self.log('Number of atoms:', natoms)
        self.log('Number of atomic orbitals:', self.wfs.setups.nao)
        self.log('Number of bands in calculation:', self.wfs.bd.nbands)
        self.log('Bands to converge: ', end='')
        n = par.convergence.get('bands', 'occupied')
        if n == 'occupied':
            self.log('occupied states only')
        elif n == 'all':
            self.log('all')
        else:
            self.log('%d lowest bands' % n)
        self.log('Number of valence electrons:', self.wfs.nvalence)

        self.log(flush=True)

        self.timer.print_info(self)

        if dry_run:
            self.dry_run()

        if (realspace and self.hamiltonian.poisson.get_description()
                == 'FDTD+TDDFT'):
            self.hamiltonian.poisson.set_density(self.density)
            self.hamiltonian.poisson.print_messages(self.log)
            self.log.fd.flush()

        self.initialized = True
        self.log('... initialized\n')

    def create_setups(self, mode, xc):
        if self.parameters.filter is None and mode.name != 'pw':
            gamma = 1.6
            N_c = self.parameters.get('gpts')
            if N_c is None:
                h = (self.parameters.h or 0.2) / Bohr
            else:
                icell_vc = np.linalg.inv(self.atoms.cell)
                h = ((icell_vc**2).sum(0)**-0.5 / N_c).max() / Bohr

            def filter(rgd, rcut, f_r, l=0):
                gcut = np.pi / h - 2 / rcut / gamma
                ftmp = rgd.filter(f_r, rcut * gamma, gcut, l)
                f_r[:] = ftmp[:len(f_r)]
        else:
            filter = self.parameters.filter

        Z_a = self.atoms.get_atomic_numbers()
        self.setups = Setups(Z_a, self.parameters.setups,
                             self.parameters.basis, xc, filter, self.world)
        self.log(self.setups)

    def create_grid_descriptor(self, N_c, cell_cv, pbc_c, domain_comm,
                               parsize_domain):
        return GridDescriptor(N_c, cell_cv, pbc_c, domain_comm, parsize_domain)

    def create_occupations(self, magmom, orbital_free):
        occ = self.parameters.occupations

        if occ is None:
            if orbital_free:
                occ = {'name': 'orbital-free'}
            else:
                width = self.parameters.width
                if width is not None:
                    warnings.warn(
                        'Please use occupations=FermiDirac({})'.format(width))
                elif self.atoms.pbc.any():
                    width = 0.1  # eV
                else:
                    width = 0.0
                occ = {'name': 'fermi-dirac', 'width': width}

        if isinstance(occ, dict):
            occ = create_occupation_number_object(**occ)

        if self.parameters.fixdensity:
            occ.fixed_fermilevel = True
            if self.occupations:
                occ.fermilevel = self.occupations.fermilevel

        self.occupations = occ

        # If occupation numbers are changed, and we have wave functions,
        # recalculate the occupation numbers
        if self.wfs is not None:
            self.occupations.calculate(self.wfs)

        self.occupations.magmom = magmom

        self.log(self.occupations)

    def create_scf(self, nvalence, mode):
        # if mode.name == 'lcao':
        #     niter_fixdensity = 0
        # else:
        #     niter_fixdensity = 2

        nv = max(nvalence, 1)
        cc = self.parameters.convergence
        self.scf = SCFLoop(
            cc.get('eigenstates', 4.0e-8) / Ha**2 * nv,
            cc.get('energy', 0.0005) / Ha * nv,
            cc.get('density', 1.0e-4) * nv,
            cc.get('forces', np.inf) / (Ha / Bohr),
            self.parameters.maxiter,
            # XXX make sure niter_fixdensity value is *always* set from default
            # Subdictionary defaults seem to not be set when user provides
            # e.g. {}.  We should change that so it works like the ordinary
            # parameters.
            self.parameters.experimental.get('niter_fixdensity', 0),
            nv)
        self.log(self.scf)

    def create_symmetry(self, magmom_av, cell_cv):
        symm = self.parameters.symmetry
        if symm == 'off':
            symm = {'point_group': False, 'time_reversal': False}
        m_av = magmom_av.round(decimals=3)  # round off
        id_a = [id + tuple(m_v) for id, m_v in zip(self.setups.id_a, m_av)]
        self.symmetry = Symmetry(id_a, cell_cv, self.atoms.pbc, **symm)
        self.symmetry.analyze(self.spos_ac)
        self.setups.set_symmetry(self.symmetry)

    def create_eigensolver(self, xc, nbands, mode):
        # Number of bands to converge:
        nbands_converge = self.parameters.convergence.get('bands', 'occupied')
        if nbands_converge == 'all':
            nbands_converge = nbands
        elif nbands_converge != 'occupied':
            assert isinstance(nbands_converge, int)
            if nbands_converge < 0:
                nbands_converge += nbands
        eigensolver = get_eigensolver(self.parameters.eigensolver, mode,
                                      self.parameters.convergence)
        eigensolver.nbands_converge = nbands_converge
        # XXX Eigensolver class doesn't define an nbands_converge property

        if isinstance(xc, SIC):
            eigensolver.blocksize = 1

        self.wfs.set_eigensolver(eigensolver)

        self.log('Eigensolver\n  ', self.wfs.eigensolver, '\n')

    def create_density(self, realspace, mode, background):
        gd = self.wfs.gd

        big_gd = gd.new_descriptor(comm=self.world)
        # Check whether grid is too small.  8 is smallest admissible.
        # (we decide this by how difficult it is to make the tests pass)
        # (Actually it depends on stencils!  But let the user deal with it)
        N_c = big_gd.get_size_of_global_array(pad=True)
        too_small = np.any(N_c / big_gd.parsize_c < 8)
        if (self.parallel['augment_grids'] and not too_small
                and mode.name != 'pw'):
            aux_gd = big_gd
        else:
            aux_gd = gd

        redistributor = GridRedistributor(self.world, self.wfs.kptband_comm,
                                          gd, aux_gd)

        # Construct grid descriptor for fine grids for densities
        # and potentials:
        finegd = aux_gd.refine()

        kwargs = dict(gd=gd,
                      finegd=finegd,
                      nspins=self.wfs.nspins,
                      collinear=self.wfs.collinear,
                      charge=self.parameters.charge +
                      self.wfs.setups.core_charge,
                      redistributor=redistributor,
                      background_charge=background)

        if realspace:
            self.density = RealSpaceDensity(stencil=mode.interpolation,
                                            **kwargs)
        else:
            self.density = pw.ReciprocalSpaceDensity(**kwargs)

        self.log(self.density, '\n')

    def create_hamiltonian(self, realspace, mode, xc):
        dens = self.density
        kwargs = dict(gd=dens.gd,
                      finegd=dens.finegd,
                      nspins=dens.nspins,
                      collinear=dens.collinear,
                      setups=dens.setups,
                      timer=self.timer,
                      xc=xc,
                      world=self.world,
                      redistributor=dens.redistributor,
                      vext=self.parameters.external,
                      psolver=self.parameters.poissonsolver)
        if realspace:
            self.hamiltonian = RealSpaceHamiltonian(stencil=mode.interpolation,
                                                    **kwargs)
            xc.set_grid_descriptor(self.hamiltonian.finegd)
        else:
            # This code will work if dens.redistributor uses
            # ordinary density.gd as aux_gd
            gd = dens.finegd

            xc_redist = None
            if self.parallel['augment_grids']:
                from gpaw.grid_descriptor import BadGridError
                try:
                    aux_gd = gd.new_descriptor(comm=self.world)
                except BadGridError as err:
                    import warnings
                    warnings.warn('Ignoring augment_grids: {}'.format(err))
                else:
                    bcast_comm = dens.redistributor.broadcast_comm
                    xc_redist = GridRedistributor(self.world, bcast_comm, gd,
                                                  aux_gd)

            self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
                pd2=dens.pd2,
                pd3=dens.pd3,
                realpbc_c=self.atoms.pbc,
                xc_redistributor=xc_redist,
                **kwargs)
            xc.set_grid_descriptor(self.hamiltonian.xc_gd)

        self.hamiltonian.soc = self.parameters.experimental.get('soc')
        self.log(self.hamiltonian, '\n')

    def create_kpoint_descriptor(self, nspins):
        par = self.parameters

        bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
        kpt_refine = par.experimental.get('kpt_refine')
        if kpt_refine is None:
            kd = KPointDescriptor(bzkpts_kc, nspins)

            self.timer.start('Set symmetry')
            kd.set_symmetry(self.atoms, self.symmetry, comm=self.world)
            self.timer.stop('Set symmetry')

        else:
            self.timer.start('Set k-point refinement')
            kd = create_kpoint_descriptor_with_refinement(kpt_refine,
                                                          bzkpts_kc,
                                                          nspins,
                                                          self.atoms,
                                                          self.symmetry,
                                                          comm=self.world,
                                                          timer=self.timer)
            self.timer.stop('Set k-point refinement')
            # Update quantities which might have changed, if symmetry
            # was changed
            self.symmetry = kd.symmetry
            self.setups.set_symmetry(kd.symmetry)

        self.log(kd)

        return kd

    def create_wave_functions(self, mode, realspace, nspins, collinear, nbands,
                              nao, nvalence, setups, cell_cv, pbc_c):
        par = self.parameters

        kd = self.create_kpoint_descriptor(nspins)

        parallelization = mpi.Parallelization(self.world, nspins * kd.nibzkpts)

        parsize_kpt = self.parallel['kpt']
        parsize_domain = self.parallel['domain']
        parsize_bands = self.parallel['band']

        ndomains = None
        if parsize_domain is not None:
            ndomains = np.prod(parsize_domain)
        parallelization.set(kpt=parsize_kpt,
                            domain=ndomains,
                            band=parsize_bands)
        comms = parallelization.build_communicators()
        domain_comm = comms['d']
        kpt_comm = comms['k']
        band_comm = comms['b']
        kptband_comm = comms['D']
        domainband_comm = comms['K']

        self.comms = comms

        if par.gpts is not None:
            if par.h is not None:
                raise ValueError("""You can't use both "gpts" and "h"!""")
            N_c = np.array(par.gpts)
        else:
            h = par.h
            if h is not None:
                h /= Bohr
            N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
                                            kd.symmetry)

        self.symmetry.check_grid(N_c)

        kd.set_communicator(kpt_comm)

        parstride_bands = self.parallel['stridebands']

        bd = BandDescriptor(nbands, band_comm, parstride_bands)

        # Construct grid descriptor for coarse grids for wave functions:
        gd = self.create_grid_descriptor(N_c, cell_cv, pbc_c, domain_comm,
                                         parsize_domain)

        if hasattr(self, 'time') or mode.force_complex_dtype or not collinear:
            dtype = complex
        else:
            if kd.gamma:
                dtype = float
            else:
                dtype = complex

        wfs_kwargs = dict(gd=gd,
                          nvalence=nvalence,
                          setups=setups,
                          bd=bd,
                          dtype=dtype,
                          world=self.world,
                          kd=kd,
                          kptband_comm=kptband_comm,
                          timer=self.timer)

        if self.parallel['sl_auto']:
            # Choose scalapack parallelization automatically

            for key, val in self.parallel.items():
                if (key.startswith('sl_') and key != 'sl_auto'
                        and val is not None):
                    raise ValueError("Cannot use 'sl_auto' together "
                                     "with '%s'" % key)

            max_scalapack_cpus = bd.comm.size * gd.comm.size
            sl_default = suggest_blocking(nbands, max_scalapack_cpus)
        else:
            sl_default = self.parallel['sl_default']

        if mode.name == 'lcao':
            assert collinear
            # Layouts used for general diagonalizer
            sl_lcao = self.parallel['sl_lcao']
            if sl_lcao is None:
                sl_lcao = sl_default

            elpasolver = None
            if self.parallel['use_elpa']:
                elpasolver = self.parallel['elpasolver']
            lcaoksl = get_KohnSham_layouts(sl_lcao,
                                           'lcao',
                                           gd,
                                           bd,
                                           domainband_comm,
                                           dtype,
                                           nao=nao,
                                           timer=self.timer,
                                           elpasolver=elpasolver)

            self.wfs = mode(lcaoksl, **wfs_kwargs)

        elif mode.name == 'fd' or mode.name == 'pw':
            # Use (at most) all available LCAO for initialization
            lcaonbands = min(nbands, nao)

            try:
                lcaobd = BandDescriptor(lcaonbands, band_comm, parstride_bands)
            except RuntimeError:
                initksl = None
            else:
                # Layouts used for general diagonalizer
                # (LCAO initialization)
                sl_lcao = self.parallel['sl_lcao']
                if sl_lcao is None:
                    sl_lcao = sl_default
                initksl = get_KohnSham_layouts(sl_lcao,
                                               'lcao',
                                               gd,
                                               lcaobd,
                                               domainband_comm,
                                               dtype,
                                               nao=nao,
                                               timer=self.timer)

            reuse_wfs_method = par.experimental.get('reuse_wfs_method', 'paw')
            sl = (domainband_comm, ) + (self.parallel['sl_diagonalize']
                                        or sl_default or (1, 1, None))
            self.wfs = mode(sl,
                            initksl,
                            reuse_wfs_method=reuse_wfs_method,
                            collinear=collinear,
                            **wfs_kwargs)
        else:
            self.wfs = mode(self, collinear=collinear, **wfs_kwargs)

        self.log(self.wfs, '\n')

    def dry_run(self):
        # Can be overridden like in gpaw.atom.atompaw
        print_cell(self.wfs.gd, self.atoms.pbc, self.log)
        print_positions(self.atoms, self.log, self.density.magmom_av)
        self.log.fd.flush()

        # Write timing info now before the interpreter shuts down:
        self.__del__()

        # Disable timing output during shut-down:
        del self.timer

        raise SystemExit
Пример #4
0
    def initialize(self, atoms=None):
        """Inexpensive initialization."""

        if atoms is None:
            atoms = self.atoms
        else:
            # Save the state of the atoms:
            self.atoms = atoms.copy()

        par = self.input_parameters

        world = par.communicator
        if world is None:
            world = mpi.world
        elif hasattr(world, 'new_communicator'):
            # Check for whether object has correct type already
            #
            # Using isinstance() is complicated because of all the
            # combinations, serial/parallel/debug...
            pass
        else:
            # world should be a list of ranks:
            world = mpi.world.new_communicator(np.asarray(world))
        self.wfs.world = world

        if 'txt' in self._changed_keywords:
            self.set_txt(par.txt)
        self.verbose = par.verbose

        natoms = len(atoms)

        cell_cv = atoms.get_cell() / Bohr
        pbc_c = atoms.get_pbc()
        Z_a = atoms.get_atomic_numbers()
        magmom_av = atoms.get_initial_magnetic_moments()

        self.check_atoms()

        # Generate new xc functional only when it is reset by set
        # XXX sounds like this should use the _changed_keywords dictionary.
        if self.hamiltonian is None or self.hamiltonian.xc is None:
            if isinstance(par.xc, str):
                xc = XC(par.xc)
            else:
                xc = par.xc
        else:
            xc = self.hamiltonian.xc

        mode = par.mode

        if mode == 'fd':
            mode = FD()
        elif mode == 'pw':
            mode = pw.PW()
        elif mode == 'lcao':
            mode = LCAO()
        else:
            assert hasattr(mode, 'name'), str(mode)

        if xc.orbital_dependent and mode.name == 'lcao':
            raise NotImplementedError('LCAO mode does not support '
                                      'orbital-dependent XC functionals.')

        if par.realspace is None:
            realspace = (mode.name != 'pw')
        else:
            realspace = par.realspace
            if mode.name == 'pw':
                assert not realspace

        if par.filter is None and mode.name != 'pw':
            gamma = 1.6
            if par.gpts is not None:
                h = ((np.linalg.inv(cell_cv)**2).sum(0)**-0.5
                     / par.gpts).max()
            else:
                h = (par.h or 0.2) / Bohr

            def filter(rgd, rcut, f_r, l=0):
                gcut = np.pi / h - 2 / rcut / gamma
                f_r[:] = rgd.filter(f_r, rcut * gamma, gcut, l)
        else:
            filter = par.filter

        setups = Setups(Z_a, par.setups, par.basis, par.lmax, xc,
                        filter, world)

        if magmom_av.ndim == 1:
            collinear = True
            magmom_av, magmom_a = np.zeros((natoms, 3)), magmom_av
            magmom_av[:, 2] = magmom_a
        else:
            collinear = False

        magnetic = magmom_av.any()

        spinpol = par.spinpol
        if par.hund:
            if natoms != 1:
                raise ValueError('hund=True arg only valid for single atoms!')
            spinpol = True
            magmom_av[0] = (0, 0, setups[0].get_hunds_rule_moment(par.charge))

        if spinpol is None:
            spinpol = magnetic
        elif magnetic and not spinpol:
            raise ValueError('Non-zero initial magnetic moment for a ' +
                             'spin-paired calculation!')

        if collinear:
            nspins = 1 + int(spinpol)
            ncomp = 1
        else:
            nspins = 1
            ncomp = 2

        if par.usesymm != 'default':
            warnings.warn('Use "symmetry" keyword instead of ' +
                          '"usesymm" keyword')
            par.symmetry = usesymm2symmetry(par.usesymm)

        symm = par.symmetry
        if symm == 'off':
            symm = {'point_group': False, 'time_reversal': False}

        bzkpts_kc = kpts2ndarray(par.kpts, self.atoms)
        kd = KPointDescriptor(bzkpts_kc, nspins, collinear)
        m_av = magmom_av.round(decimals=3)  # round off
        id_a = zip(setups.id_a, *m_av.T)
        symmetry = Symmetry(id_a, cell_cv, atoms.pbc, **symm)
        kd.set_symmetry(atoms, symmetry, comm=world)
        setups.set_symmetry(symmetry)

        if par.gpts is not None:
            N_c = np.array(par.gpts)
        else:
            h = par.h
            if h is not None:
                h /= Bohr
            N_c = get_number_of_grid_points(cell_cv, h, mode, realspace,
                                            kd.symmetry)

        symmetry.check_grid(N_c)

        width = par.width
        if width is None:
            if pbc_c.any():
                width = 0.1  # eV
            else:
                width = 0.0
        else:
            assert par.occupations is None

        if hasattr(self, 'time') or par.dtype == complex:
            dtype = complex
        else:
            if kd.gamma:
                dtype = float
            else:
                dtype = complex

        nao = setups.nao
        nvalence = setups.nvalence - par.charge
        M_v = magmom_av.sum(0)
        M = np.dot(M_v, M_v) ** 0.5

        nbands = par.nbands
        
        orbital_free = any(setup.orbital_free for setup in setups)
        if orbital_free:
            nbands = 1

        if isinstance(nbands, basestring):
            if nbands[-1] == '%':
                basebands = int(nvalence + M + 0.5) // 2
                nbands = int((float(nbands[:-1]) / 100) * basebands)
            else:
                raise ValueError('Integer Expected: Only use a string '
                                 'if giving a percentage of occupied bands')

        if nbands is None:
            nbands = 0
            for setup in setups:
                nbands_from_atom = setup.get_default_nbands()

                # Any obscure setup errors?
                if nbands_from_atom < -(-setup.Nv // 2):
                    raise ValueError('Bad setup: This setup requests %d'
                                     ' bands but has %d electrons.'
                                     % (nbands_from_atom, setup.Nv))
                nbands += nbands_from_atom
            nbands = min(nao, nbands)
        elif nbands > nao and mode.name == 'lcao':
            raise ValueError('Too many bands for LCAO calculation: '
                             '%d bands and only %d atomic orbitals!' %
                             (nbands, nao))

        if nvalence < 0:
            raise ValueError(
                'Charge %f is not possible - not enough valence electrons' %
                par.charge)

        if nbands <= 0:
            nbands = int(nvalence + M + 0.5) // 2 + (-nbands)

        if nvalence > 2 * nbands and not orbital_free:
            raise ValueError('Too few bands!  Electrons: %f, bands: %d'
                             % (nvalence, nbands))

        nbands *= ncomp

        if par.width is not None:
            self.text('**NOTE**: please start using '
                      'occupations=FermiDirac(width).')
        if par.fixmom:
            self.text('**NOTE**: please start using '
                      'occupations=FermiDirac(width, fixmagmom=True).')

        if self.occupations is None:
            if par.occupations is None:
                # Create object for occupation numbers:
                if orbital_free:
                    width = 0.0  # even for PBC
                    self.occupations = occupations.TFOccupations(width,
                                                                 par.fixmom)
                else:
                    self.occupations = occupations.FermiDirac(width,
                                                              par.fixmom)
            else:
                self.occupations = par.occupations

            # If occupation numbers are changed, and we have wave functions,
            # recalculate the occupation numbers
            if self.wfs is not None and not isinstance(
                    self.wfs,
                    EmptyWaveFunctions):
                self.occupations.calculate(self.wfs)

        self.occupations.magmom = M_v[2]

        cc = par.convergence

        if mode.name == 'lcao':
            niter_fixdensity = 0
        else:
            niter_fixdensity = None

        if self.scf is None:
            force_crit = cc['forces']
            if force_crit is not None:
                force_crit /= Hartree / Bohr
            self.scf = SCFLoop(
                cc['eigenstates'] / Hartree**2 * nvalence,
                cc['energy'] / Hartree * max(nvalence, 1),
                cc['density'] * nvalence,
                par.maxiter, par.fixdensity,
                niter_fixdensity,
                force_crit)

        parsize_kpt = par.parallel['kpt']
        parsize_domain = par.parallel['domain']
        parsize_bands = par.parallel['band']

        if not realspace:
            pbc_c = np.ones(3, bool)

        if not self.wfs:
            if parsize_domain == 'domain only':  # XXX this was silly!
                parsize_domain = world.size

            parallelization = mpi.Parallelization(world,
                                                  nspins * kd.nibzkpts)
            ndomains = None
            if parsize_domain is not None:
                ndomains = np.prod(parsize_domain)
            if mode.name == 'pw':
                if ndomains > 1:
                    raise ValueError('Planewave mode does not support '
                                     'domain decomposition.')
                ndomains = 1
            parallelization.set(kpt=parsize_kpt,
                                domain=ndomains,
                                band=parsize_bands)
            comms = parallelization.build_communicators()
            domain_comm = comms['d']
            kpt_comm = comms['k']
            band_comm = comms['b']
            kptband_comm = comms['D']
            domainband_comm = comms['K']

            self.comms = comms
            kd.set_communicator(kpt_comm)

            parstride_bands = par.parallel['stridebands']

            # Unfortunately we need to remember that we adjusted the
            # number of bands so we can print a warning if it differs
            # from the number specified by the user.  (The number can
            # be inferred from the input parameters, but it's tricky
            # because we allow negative numbers)
            self.nbands_parallelization_adjustment = -nbands % band_comm.size
            nbands += self.nbands_parallelization_adjustment

            # I would like to give the following error message, but apparently
            # there are cases, e.g. gpaw/test/gw_ppa.py, which involve
            # nbands > nao and are supposed to work that way.
            #if nbands > nao:
            #    raise ValueError('Number of bands %d adjusted for band '
            #                     'parallelization %d exceeds number of atomic '
            #                     'orbitals %d.  This problem can be fixed '
            #                     'by reducing the number of bands a bit.'
            #                     % (nbands, band_comm.size, nao))
            bd = BandDescriptor(nbands, band_comm, parstride_bands)

            if (self.density is not None and
                    self.density.gd.comm.size != domain_comm.size):
                # Domain decomposition has changed, so we need to
                # reinitialize density and hamiltonian:
                if par.fixdensity:
                    raise RuntimeError(
                        'Density reinitialization conflict ' +
                        'with "fixdensity" - specify domain decomposition.')
                self.density = None
                self.hamiltonian = None

            # Construct grid descriptor for coarse grids for wave functions:
            gd = self.grid_descriptor_class(N_c, cell_cv, pbc_c,
                                            domain_comm, parsize_domain)

            # do k-point analysis here? XXX
            args = (gd, nvalence, setups, bd, dtype, world, kd,
                    kptband_comm, self.timer)

            if par.parallel['sl_auto']:
                # Choose scalapack parallelization automatically

                for key, val in par.parallel.items():
                    if (key.startswith('sl_') and key != 'sl_auto'
                            and val is not None):
                        raise ValueError("Cannot use 'sl_auto' together "
                                         "with '%s'" % key)
                max_scalapack_cpus = bd.comm.size * gd.comm.size
                nprow = max_scalapack_cpus
                npcol = 1

                # Get a sort of reasonable number of columns/rows
                while npcol < nprow and nprow % 2 == 0:
                    npcol *= 2
                    nprow //= 2
                assert npcol * nprow == max_scalapack_cpus

                # ScaLAPACK creates trouble if there aren't at least a few
                # whole blocks; choose block size so there will always be
                # several blocks.  This will crash for small test systems,
                # but so will ScaLAPACK in any case
                blocksize = min(-(-nbands // 4), 64)
                sl_default = (nprow, npcol, blocksize)
            else:
                sl_default = par.parallel['sl_default']

            if mode.name == 'lcao':
                # Layouts used for general diagonalizer
                sl_lcao = par.parallel['sl_lcao']
                if sl_lcao is None:
                    sl_lcao = sl_default
                lcaoksl = get_KohnSham_layouts(sl_lcao, 'lcao',
                                               gd, bd, domainband_comm, dtype,
                                               nao=nao, timer=self.timer)

                self.wfs = mode(collinear, lcaoksl, *args)

            elif mode.name == 'fd' or mode.name == 'pw':
                # buffer_size keyword only relevant for fdpw
                buffer_size = par.parallel['buffer_size']
                # Layouts used for diagonalizer
                sl_diagonalize = par.parallel['sl_diagonalize']
                if sl_diagonalize is None:
                    sl_diagonalize = sl_default
                diagksl = get_KohnSham_layouts(sl_diagonalize, 'fd',  # XXX
                                               # choice of key 'fd' not so nice
                                               gd, bd, domainband_comm, dtype,
                                               buffer_size=buffer_size,
                                               timer=self.timer)

                # Layouts used for orthonormalizer
                sl_inverse_cholesky = par.parallel['sl_inverse_cholesky']
                if sl_inverse_cholesky is None:
                    sl_inverse_cholesky = sl_default
                if sl_inverse_cholesky != sl_diagonalize:
                    message = 'sl_inverse_cholesky != sl_diagonalize ' \
                        'is not implemented.'
                    raise NotImplementedError(message)
                orthoksl = get_KohnSham_layouts(sl_inverse_cholesky, 'fd',
                                                gd, bd, domainband_comm, dtype,
                                                buffer_size=buffer_size,
                                                timer=self.timer)

                # Use (at most) all available LCAO for initialization
                lcaonbands = min(nbands, nao)

                try:
                    lcaobd = BandDescriptor(lcaonbands, band_comm,
                                            parstride_bands)
                except RuntimeError:
                    initksl = None
                else:
                    # Layouts used for general diagonalizer
                    # (LCAO initialization)
                    sl_lcao = par.parallel['sl_lcao']
                    if sl_lcao is None:
                        sl_lcao = sl_default
                    initksl = get_KohnSham_layouts(sl_lcao, 'lcao',
                                                   gd, lcaobd, domainband_comm,
                                                   dtype, nao=nao,
                                                   timer=self.timer)

                if hasattr(self, 'time'):
                    assert mode.name == 'fd'
                    from gpaw.tddft import TimeDependentWaveFunctions
                    self.wfs = TimeDependentWaveFunctions(
                        par.stencils[0],
                        diagksl,
                        orthoksl,
                        initksl,
                        gd,
                        nvalence,
                        setups,
                        bd,
                        world,
                        kd,
                        kptband_comm,
                        self.timer)
                elif mode.name == 'fd':
                    self.wfs = mode(par.stencils[0], diagksl,
                                    orthoksl, initksl, *args)
                else:
                    assert mode.name == 'pw'
                    self.wfs = mode(diagksl, orthoksl, initksl, *args)
            else:
                self.wfs = mode(self, *args)
        else:
            self.wfs.set_setups(setups)

        if not self.wfs.eigensolver:
            # Number of bands to converge:
            nbands_converge = cc['bands']
            if nbands_converge == 'all':
                nbands_converge = nbands
            elif nbands_converge != 'occupied':
                assert isinstance(nbands_converge, int)
                if nbands_converge < 0:
                    nbands_converge += nbands
            eigensolver = get_eigensolver(par.eigensolver, mode,
                                          par.convergence)
            eigensolver.nbands_converge = nbands_converge
            # XXX Eigensolver class doesn't define an nbands_converge property

            if isinstance(xc, SIC):
                eigensolver.blocksize = 1
            self.wfs.set_eigensolver(eigensolver)

        if self.density is None:
            gd = self.wfs.gd
            if par.stencils[1] != 9:
                # Construct grid descriptor for fine grids for densities
                # and potentials:
                finegd = gd.refine()
            else:
                # Special case (use only coarse grid):
                finegd = gd

            if realspace:
                self.density = RealSpaceDensity(
                    gd, finegd, nspins, par.charge + setups.core_charge,
                    collinear, par.stencils[1])
            else:
                self.density = pw.ReciprocalSpaceDensity(
                    gd, finegd, nspins, par.charge + setups.core_charge,
                    collinear)

        self.density.initialize(setups, self.timer, magmom_av, par.hund)
        self.density.set_mixer(par.mixer)

        if self.hamiltonian is None:
            gd, finegd = self.density.gd, self.density.finegd
            if realspace:
                self.hamiltonian = RealSpaceHamiltonian(
                    gd, finegd, nspins, setups, self.timer, xc,
                    world, self.wfs.kptband_comm, par.external,
                    collinear, par.poissonsolver, par.stencils[1])
            else:
                self.hamiltonian = pw.ReciprocalSpaceHamiltonian(
                    gd, finegd, self.density.pd2, self.density.pd3,
                    nspins, setups, self.timer, xc, world,
                    self.wfs.kptband_comm, par.external, collinear)

        xc.initialize(self.density, self.hamiltonian, self.wfs,
                      self.occupations)

        self.text()
        self.print_memory_estimate(self.txt, maxdepth=memory_estimate_depth)
        self.txt.flush()

        self.timer.print_info(self)

        if dry_run:
            self.dry_run()

        if realspace and \
                self.hamiltonian.poisson.get_description() == 'FDTD+TDDFT':
            self.hamiltonian.poisson.set_density(self.density)
            self.hamiltonian.poisson.print_messages(self.text)
            self.txt.flush()

        self.initialized = True
        self._changed_keywords.clear()