Source code for gpaw.density

# -*- coding: utf-8 -*-
# Copyright (C) 2003  CAMP
# Please see the accompanying LICENSE file for further information.

"""This module defines a density class."""

from math import pi, sqrt

import numpy as np
from ase.units import Bohr

from gpaw import debug
from gpaw.mixer import get_mixer_from_keywords, MixerWrapper
from gpaw.transformers import Transformer
from gpaw.lfc import LFC, BasisFunctions
from gpaw.wavefunctions.lcao import LCAOWaveFunctions
from gpaw.utilities import (unpack2, unpack_atomic_matrices,
                            pack_atomic_matrices)
from gpaw.utilities.partition import AtomPartition
from gpaw.utilities.timing import nulltimer
from gpaw.arraydict import ArrayDict


class CompensationChargeExpansionCoefficients:
    def __init__(self, setups, nspins):
        self.setups = setups
        self.nspins = nspins

    def calculate(self, D_asp):
        """Calculate multipole moments of compensation charges.

        Returns the total compensation charge in units of electron
        charge, so the number will be negative because of the
        dominating contribution from the nuclear charge."""
        atom_partition = D_asp.partition
        shape_a = [(setup.Delta_pL.shape[1],) for setup in self.setups]
        Q_aL = atom_partition.arraydict(shape_a, dtype=float)
        for a, D_sp in D_asp.items():
            setup = self.setups[a]
            Q_L = np.dot(D_sp[:self.nspins].sum(0), setup.Delta_pL)
            Q_L[0] += setup.Delta0
            Q_aL[a] = Q_L
        return Q_aL

    def get_charge(self, Q_aL):
        local_charge = sqrt(4 * pi) * sum(Q_L[0] for Q_L in Q_aL.values())
        return Q_aL.partition.comm.sum(local_charge)


class NullBackgroundCharge:
    charge = 0.0

    def set_grid_descriptor(self, gd):
        pass

    def add_charge_to(self, rhot_g):
        pass

    def add_fourier_space_charge_to(self, pd, rhot_q):
        pass


[docs]class Density: """Density object. Attributes: =============== ===================================================== ``gd`` Grid descriptor for coarse grids. ``finegd`` Grid descriptor for fine grids. ``interpolate`` Function for interpolating the electron density. ``mixer`` ``DensityMixer`` object. =============== ===================================================== Soft and smooth pseudo functions on uniform 3D grids: ========== ========================================= ``nt_sG`` Electron density on the coarse grid. ``nt_sg`` Electron density on the fine grid. ``nt_g`` Electron density on the fine grid. ``rhot_g`` Charge density on the fine grid. ``nct_G`` Core electron-density on the coarse grid. ========== ========================================= """ def __init__(self, gd, finegd, nspins, collinear, charge, redistributor, background_charge=None): """Create the Density object.""" self.gd = gd self.finegd = finegd self.nspins = nspins self.collinear = collinear self.charge = float(charge) self.redistributor = redistributor self.atomdist = None self.ncomponents = self.nspins if self.collinear else 1 + 3 # This can contain e.g. a Jellium background charge if background_charge is None: background_charge = NullBackgroundCharge() background_charge.set_grid_descriptor(self.finegd) self.background_charge = background_charge self.charge_eps = 1e-7 self.D_asp = None self.Q = CompensationChargeExpansionCoefficients([], self.nspins) self.Q_aL = None self.nct_G = None self.nt_xG = None self.rhot_g = None self.nt_xg = None self.nt_sg = None self.nt_vg = None self.nt_g = None self.atom_partition = None self.setups = None self.hund = None self.magmom_av = None self.fixed = False # XXX at least one test will fail because None has no 'reset()' # So we need DummyMixer I guess self.mixer = None self.set_mixer(None) self.timer = nulltimer self.error = None self.nct = None self.ghat = None self.log = None @property def nt_sG(self): return None if self.nt_xG is None else self.nt_xG[:self.nspins] @property def nt_vG(self): return None if self.nt_xG is None else self.nt_xG[self.nspins:] def __str__(self): s = 'Densities:\n' s += ' Coarse grid: {0}*{1}*{2} grid\n'.format(*self.gd.N_c) s += ' Fine grid: {0}*{1}*{2} grid\n'.format(*self.finegd.N_c) s += ' Total Charge: {0:.6f}'.format(self.charge) if self.fixed: s += '\n Fixed' return s def summary(self, atoms, magmom, log): if self.nspins == 1: return try: # XXX This doesn't always work, HGH, SIC, ... sc = self.get_spin_contamination(atoms, int(magmom < 0)) log('Spin contamination: %f electrons' % sc) except (TypeError, AttributeError): pass def initialize(self, setups, timer, magmom_av, hund): self.timer = timer self.setups = setups self.Q = CompensationChargeExpansionCoefficients(setups, self.nspins) self.hund = hund self.magmom_av = magmom_av def reset(self): # TODO: reset other parameters? self.nt_xG = None def set_positions_without_ruining_everything(self, spos_ac, atom_partition): rank_a = atom_partition.rank_a # If both old and new atomic ranks are present, start a blank dict if # it previously didn't exist but it will needed for the new atoms. if (self.atom_partition is not None and self.D_asp is None and (rank_a == self.gd.comm.rank).any()): self.update_atomic_density_matrices( self.setups.empty_atomic_matrix(self.ncomponents, self.atom_partition)) if (self.atom_partition is not None and self.D_asp is not None and self.gd.comm.size > 1): self.timer.start('Redistribute') self.D_asp.redistribute(atom_partition) self.timer.stop('Redistribute') self.atom_partition = atom_partition self.atomdist = self.redistributor.get_atom_distributions(spos_ac) def set_positions(self, spos_ac, atom_partition): self.set_positions_without_ruining_everything(spos_ac, atom_partition) self.nct.set_positions(spos_ac, atom_partition) self.ghat.set_positions(spos_ac, atom_partition) self.mixer.reset() self.nt_xg = None self.nt_sg = None self.nt_vg = None self.nt_g = None self.rhot_g = None
[docs] def calculate_pseudo_density(self, wfs): """Calculate nt_sG from scratch. nt_sG will be equal to nct_G plus the contribution from wfs.add_to_density(). """ wfs.calculate_density_contribution(self.nt_xG) self.nt_sG[:] += self.nct_G
def update_atomic_density_matrices(self, value): if isinstance(value, dict): tmp = self.setups.empty_atomic_matrix(self.ncomponents, self.atom_partition) tmp.update(value) value = tmp assert isinstance(value, ArrayDict) or value is None, type(value) if value is not None: value.check_consistency() self.D_asp = value def update(self, wfs): self.timer.start('Density') with self.timer('Pseudo density'): self.calculate_pseudo_density(wfs) with self.timer('Atomic density matrices'): wfs.calculate_atomic_density_matrices(self.D_asp) with self.timer('Multipole moments'): comp_charge, _Q_aL = self.calculate_multipole_moments() if isinstance(wfs, LCAOWaveFunctions): self.timer.start('Normalize') self.normalize(comp_charge) self.timer.stop('Normalize') self.timer.start('Mix') self.mix(comp_charge) self.timer.stop('Mix') self.timer.stop('Density')
[docs] def normalize(self, comp_charge): """Normalize pseudo density.""" pseudo_charge = self.gd.integrate(self.nt_sG).sum() if (pseudo_charge + self.charge + comp_charge - self.background_charge.charge != 0): if pseudo_charge != 0: x = (self.background_charge.charge - self.charge - comp_charge) / pseudo_charge self.nt_xG *= x else: # Use homogeneous background. # # We have to use the volume per actual grid point, # which is not the same as gd.volume as the latter # includes ghost points. volume = self.gd.get_size_of_global_array().prod() * self.gd.dv total_charge = (self.charge + comp_charge - self.background_charge.charge) self.nt_sG[:] = -total_charge / volume
def mix(self, comp_charge): assert isinstance(self.mixer, MixerWrapper), self.mixer self.error = self.mixer.mix(self.nt_xG, self.D_asp) assert self.error is not None, self.mixer comp_charge = None self.interpolate_pseudo_density(comp_charge) self.calculate_pseudo_charge() def calculate_multipole_moments(self): D_asp = self.atomdist.to_aux(self.D_asp) Q_aL = self.Q.calculate(D_asp) self.Q_aL = Q_aL return self.Q.get_charge(Q_aL), Q_aL def get_initial_occupations(self, a): # distribute charge on all atoms # XXX interaction with background charge may be finicky c = (self.charge - self.background_charge.charge) / len(self.setups) M_v = self.magmom_av[a] M = np.linalg.norm(M_v) f_si = self.setups[a].calculate_initial_occupation_numbers( M, self.hund, charge=c, nspins=self.nspins if self.collinear else 2) if self.collinear: if M_v[2] < 0: f_si = f_si[::-1].copy() else: f_i = f_si.sum(0) fm_i = f_si[0] - f_si[1] f_si = np.zeros((4, len(f_i))) f_si[0] = f_i if M > 0: f_si[1:] = M_v[:, np.newaxis] / M * fm_i return f_si
[docs] def initialize_from_atomic_densities(self, basis_functions): """Initialize D_asp, nt_sG and Q_aL from atomic densities. nt_sG is initialized from atomic orbitals, and will be constructed with the specified magnetic moments and obeying Hund's rules if ``hund`` is true.""" # XXX does this work with blacs? What should be distributed? # Apparently this doesn't use blacs at all, so it's serial # with respect to the blacs distribution. That means it works # but is not particularly efficient (not that this is a time # consuming step) self.log('Density initialized from atomic densities') self.update_atomic_density_matrices( self.setups.empty_atomic_matrix(self.ncomponents, self.atom_partition)) f_asi = {} for a in basis_functions.atom_indices: f_asi[a] = self.get_initial_occupations(a) # D_asp does not have the same distribution as the basis functions, # so we have to loop over atoms separately. for a in self.D_asp: f_si = f_asi.get(a) if f_si is None: f_si = self.get_initial_occupations(a) self.D_asp[a][:] = self.setups[a].initialize_density_matrix(f_si) self.nt_xG = self.gd.zeros(self.ncomponents) basis_functions.add_to_density(self.nt_xG, f_asi) self.nt_sG[:] += self.nct_G self.calculate_normalized_charges_and_mix()
[docs] def initialize_from_wavefunctions(self, wfs): """Initialize D_asp, nt_sG and Q_aL from wave functions.""" self.log('Density initialized from wave functions') self.timer.start('Density initialized from wave functions') self.nt_xG = self.gd.zeros(self.ncomponents) self.calculate_pseudo_density(wfs) self.update_atomic_density_matrices( self.setups.empty_atomic_matrix(self.ncomponents, wfs.atom_partition)) wfs.calculate_atomic_density_matrices(self.D_asp) self.calculate_normalized_charges_and_mix() self.timer.stop('Density initialized from wave functions')
[docs] def initialize_directly_from_arrays(self, nt_sG, nt_vG, D_asp): """Set D_asp and nt_sG directly.""" self.nt_xG = self.gd.zeros(self.ncomponents) self.nt_sG[:] = nt_sG if nt_vG is not None: self.nt_vG[:] = nt_vG self.update_atomic_density_matrices(D_asp) D_asp.check_consistency()
# No calculate multipole moments? Tests will fail because of # improperly initialized mixer def calculate_normalized_charges_and_mix(self): comp_charge, _Q_aL = self.calculate_multipole_moments() self.normalize(comp_charge) self.mix(comp_charge) def set_mixer(self, mixer): if mixer is None: mixer = {} if isinstance(mixer, dict): mixer = get_mixer_from_keywords(self.gd.pbc_c.any(), self.ncomponents, **mixer) if not hasattr(mixer, 'mix'): raise ValueError('Not a mixer: %s' % mixer) self.mixer = MixerWrapper(mixer, self.ncomponents, self.gd) def estimate_magnetic_moments(self): magmom_av = np.zeros_like(self.magmom_av) magmom_v = np.zeros(3) if self.nspins == 2: for a, D_sp in self.D_asp.items(): M_p = D_sp[0] - D_sp[1] magmom_av[a, 2] = np.dot(M_p, self.setups[a].N0_p) magmom_v[2] += (np.dot(M_p, self.setups[a].Delta_pL[:, 0]) * sqrt(4 * pi)) self.gd.comm.sum(magmom_av) self.gd.comm.sum(magmom_v) magmom_v[2] += self.gd.integrate(self.nt_sG[0] - self.nt_sG[1]) elif not self.collinear: for a, D_sp in self.D_asp.items(): magmom_av[a] = np.dot(D_sp[1:4], self.setups[a].N0_p) magmom_v += (np.dot(D_sp[1:4], self.setups[a].Delta_pL[:, 0]) * sqrt(4 * pi)) # XXXX probably untested code self.gd.comm.sum(magmom_av) self.gd.comm.sum(magmom_v) magmom_v += self.gd.integrate(self.nt_vG) return magmom_v, magmom_av
[docs] def get_correction(self, a, spin): """Integrated atomic density correction. Get the integrated correction to the pseuso density relative to the all-electron density. """ setup = self.setups[a] return sqrt(4 * pi) * ( np.dot(self.D_asp[a][spin], setup.Delta_pL[:, 0]) + setup.Delta0 / self.nspins)
[docs] def get_all_electron_density(self, atoms=None, gridrefinement=2, spos_ac=None, skip_core=False): """Return real all-electron density array. Usage: Either get_all_electron_density(atoms) or get_all_electron_density(spos_ac=spos_ac) skip_core=True theoretically returns the all-electron valence density (use with care; will not in general integrate to valence) """ if spos_ac is None: spos_ac = atoms.get_scaled_positions() % 1.0 # Refinement of coarse grid, for representation of the AE-density # XXXXXXXXXXXX think about distribution depending on gridrefinement! if gridrefinement == 1: gd = self.redistributor.aux_gd n_sg = self.nt_sG.copy() # This will get the density with the same distribution # as finegd: n_sg = self.redistributor.distribute(n_sg) elif gridrefinement == 2: gd = self.finegd if self.nt_sg is None: self.interpolate_pseudo_density() n_sg = self.nt_sg.copy() elif gridrefinement == 4: # Extra fine grid gd = self.finegd.refine() # Interpolation function for the density: interpolator = Transformer(self.finegd, gd, 3) # XXX grids! # Transfer the pseudo-density to the fine grid: n_sg = gd.empty(self.nspins) if self.nt_sg is None: self.interpolate_pseudo_density() for s in range(self.nspins): interpolator.apply(self.nt_sg[s], n_sg[s]) else: raise NotImplementedError # Add corrections to pseudo-density to get the AE-density splines = {} phi_aj = [] phit_aj = [] nc_a = [] nct_a = [] for a, id in enumerate(self.setups.id_a): if id in splines: phi_j, phit_j, nc, nct = splines[id] else: # Load splines: phi_j, phit_j, nc, nct = self.setups[a].get_partial_waves()[:4] splines[id] = (phi_j, phit_j, nc, nct) phi_aj.append(phi_j) phit_aj.append(phit_j) nc_a.append([nc]) nct_a.append([nct]) # Create localized functions from splines phi = BasisFunctions(gd, phi_aj) phit = BasisFunctions(gd, phit_aj) nc = LFC(gd, nc_a) nct = LFC(gd, nct_a) phi.set_positions(spos_ac) phit.set_positions(spos_ac) nc.set_positions(spos_ac) nct.set_positions(spos_ac) I_sa = np.zeros((self.nspins, len(spos_ac))) a_W = np.empty(len(phi.M_W), np.intc) W = 0 for a in phi.atom_indices: nw = len(phi.sphere_a[a].M_w) a_W[W:W + nw] = a W += nw x_W = phi.create_displacement_arrays()[0] # We need the charges for the density matrices in order to add # nuclear charges at each atom. Hence we use the aux partition: # The one where atoms are distributed according to which realspace # domain they belong to. D_asp = self.atomdist.to_aux(self.D_asp) rho_MM = np.zeros((phi.Mmax, phi.Mmax)) for s, I_a in enumerate(I_sa): M1 = 0 for a, setup in enumerate(self.setups): ni = setup.ni D_sp = D_asp.get(a) if D_sp is None: D_sp = np.empty((self.nspins, ni * (ni + 1) // 2)) else: I_a[a] = ((setup.Nct) / self.nspins - sqrt(4 * pi) * np.dot(D_sp[s], setup.Delta_pL[:, 0])) if not skip_core: I_a[a] -= setup.Nc / self.nspins rank = D_asp.partition.rank_a[a] D_asp.partition.comm.broadcast(D_sp, rank) M2 = M1 + ni rho_MM[M1:M2, M1:M2] = unpack2(D_sp[s]) M1 = M2 assert np.all(n_sg[s].shape == phi.gd.n_c) phi.lfc.ae_valence_density_correction(rho_MM, n_sg[s], a_W, I_a, x_W) phit.lfc.ae_valence_density_correction(-rho_MM, n_sg[s], a_W, I_a, x_W) # wth is this? a_W = np.empty(len(nc.M_W), np.intc) W = 0 for a in nc.atom_indices: nw = len(nc.sphere_a[a].M_w) a_W[W:W + nw] = a W += nw scale = 1.0 / self.nspins for s, I_a in enumerate(I_sa): if not skip_core: nc.lfc.ae_core_density_correction(scale, n_sg[s], a_W, I_a) nct.lfc.ae_core_density_correction(-scale, n_sg[s], a_W, I_a) D_asp.partition.comm.sum(I_a) N_c = gd.N_c g_ac = np.around(N_c * spos_ac).astype(int) % N_c - gd.beg_c if not skip_core: for I, g_c in zip(I_a, g_ac): if (g_c >= 0).all() and (g_c < gd.n_c).all(): n_sg[s][tuple(g_c)] -= I / gd.dv return n_sg, gd
def estimate_memory(self, mem): nspins = self.nspins nbytes = self.gd.bytecount() nfinebytes = self.finegd.bytecount() arrays = mem.subnode('Arrays') for name, size in [('nt_sG', nbytes * nspins), ('nt_sg', nfinebytes * nspins), ('nt_g', nfinebytes), ('rhot_g', nfinebytes), ('nct_G', nbytes)]: arrays.subnode(name, size) lfs = mem.subnode('Localized functions') for name, obj in [('nct', self.nct), ('ghat', self.ghat)]: obj.estimate_memory(lfs.subnode(name)) self.mixer.estimate_memory(mem.subnode('Mixer'), self.gd) # TODO # The implementation of interpolator memory use is not very # accurate; 20 MiB vs 13 MiB estimated in one example, probably # worse for parallel calculations.
[docs] def get_spin_contamination(self, atoms, majority_spin=0): """Calculate the spin contamination. Spin contamination is defined as the integral over the spin density difference, where it is negative (i.e. the minority spin density is larger than the majority spin density. """ if majority_spin == 0: smaj = 0 smin = 1 else: smaj = 1 smin = 0 nt_sg, gd = self.get_all_electron_density(atoms) dt_sg = nt_sg[smin] - nt_sg[smaj] dt_sg = np.where(dt_sg > 0, dt_sg, 0.0) return gd.integrate(dt_sg)
def write(self, writer): writer.write(density=self.gd.collect(self.nt_xG) / Bohr**3, atomic_density_matrices=pack_atomic_matrices(self.D_asp)) def read(self, reader): nt_xG = self.gd.empty(self.ncomponents) self.gd.distribute(reader.density.density, nt_xG) nt_xG *= reader.bohr**3 # Read atomic density matrices natoms = len(self.setups) atom_partition = AtomPartition(self.gd.comm, np.zeros(natoms, int), 'density-gd') D_asp = self.setups.empty_atomic_matrix(self.ncomponents, atom_partition) self.atom_partition = atom_partition # XXXXXX spos_ac = np.zeros((natoms, 3)) # XXXX self.atomdist = self.redistributor.get_atom_distributions(spos_ac) D_sP = reader.density.atomic_density_matrices if self.gd.comm.rank == 0: D_asp.update(unpack_atomic_matrices(D_sP, self.setups)) D_asp.check_consistency() if self.collinear: nt_sG = nt_xG nt_vG = None else: nt_sG = nt_xG[:1] nt_vG = nt_xG[1:] self.initialize_directly_from_arrays(nt_sG, nt_vG, D_asp)
[docs] def initialize_from_other_density(self, dens, kptband_comm): """Redistribute pseudo density and atomic density matrices. Collect dens.nt_sG and dens.D_asp to world master and distribute.""" new_nt_sG = redistribute_array(dens.nt_sG, dens.gd, self.gd, self.nspins, kptband_comm) self.atom_partition, self.atomdist = \ create_atom_partition_and_distibutions(self.gd, self.nspins, self.setups, self.redistributor, kptband_comm) D_asp = \ redistribute_atomic_matrices(dens.D_asp, self.gd, self.nspins, self.setups, self.atom_partition, kptband_comm) self.initialize_directly_from_arrays(new_nt_sG, None, D_asp)
class RealSpaceDensity(Density): def __init__(self, gd, finegd, nspins, collinear, charge, redistributor, stencil=3, background_charge=None): Density.__init__(self, gd, finegd, nspins, collinear, charge, redistributor, background_charge=background_charge) self.stencil = stencil self.interpolator = None def initialize(self, setups, timer, magmom_a, hund): Density.initialize(self, setups, timer, magmom_a, hund) # Interpolation function for the density: self.interpolator = Transformer(self.redistributor.aux_gd, self.finegd, self.stencil) spline_aj = [] for setup in setups: if setup.nct is None: spline_aj.append([]) else: spline_aj.append([setup.nct]) self.nct = LFC(self.gd, spline_aj, integral=[setup.Nct for setup in setups], forces=True, cut=True) self.ghat = LFC(self.finegd, [setup.ghat_l for setup in setups], integral=sqrt(4 * pi), forces=True) def set_positions(self, spos_ac, atom_partition): Density.set_positions(self, spos_ac, atom_partition) self.nct_G = self.gd.zeros() self.nct.add(self.nct_G, 1.0 / self.nspins) def interpolate_pseudo_density(self, comp_charge=None): """Interpolate pseudo density to fine grid.""" if comp_charge is None: comp_charge, _Q_aL = self.calculate_multipole_moments() self.nt_sg = self.distribute_and_interpolate(self.nt_sG, self.nt_sg) # With periodic boundary conditions, the interpolation will # conserve the number of electrons. if not self.gd.pbc_c.all(): # With zero-boundary conditions in one or more directions, # this is not the case. pseudo_charge = (self.background_charge.charge - self.charge - comp_charge) if abs(pseudo_charge) > 1.0e-14: x = (pseudo_charge / self.finegd.integrate(self.nt_sg).sum()) self.nt_sg *= x def interpolate(self, in_xR, out_xR=None): """Interpolate array(s).""" # ndim will be 3 in finite-difference mode and 1 when working # with the AtomPAW class (spherical atoms and 1d grids) ndim = self.gd.ndim if out_xR is None: out_xR = self.finegd.empty(in_xR.shape[:-ndim]) a_xR = in_xR.reshape((-1,) + in_xR.shape[-ndim:]) b_xR = out_xR.reshape((-1,) + out_xR.shape[-ndim:]) for in_R, out_R in zip(a_xR, b_xR): self.interpolator.apply(in_R, out_R) return out_xR def distribute_and_interpolate(self, in_xR, out_xR=None): in_xR = self.redistributor.distribute(in_xR) return self.interpolate(in_xR, out_xR) def calculate_pseudo_charge(self): self.nt_g = self.nt_sg.sum(axis=0) self.rhot_g = self.nt_g.copy() self.calculate_multipole_moments() self.ghat.add(self.rhot_g, self.Q_aL) self.background_charge.add_charge_to(self.rhot_g) if debug: charge = self.finegd.integrate(self.rhot_g) + self.charge if abs(charge) > self.charge_eps: raise RuntimeError('Charge not conserved: excess=%.9f' % charge) def get_pseudo_core_kinetic_energy_density_lfc(self): return LFC(self.gd, [[setup.tauct] for setup in self.setups], forces=True, cut=True) def calculate_dipole_moment(self): return self.finegd.calculate_dipole_moment(self.rhot_g) def redistribute_array(nt_sG, gd1, gd2, nspins, kptband_comm): nt_sG = gd1.collect(nt_sG) new_nt_sG = gd2.empty(nspins) if kptband_comm.rank == 0: gd2.distribute(nt_sG, new_nt_sG) kptband_comm.broadcast(new_nt_sG, 0) return new_nt_sG def create_atom_partition_and_distibutions(gd2, nspins, setups, redistributor, kptband_comm): natoms = len(setups) atom_partition = AtomPartition(gd2.comm, np.zeros(natoms, int), 'density-gd') spos_ac = np.zeros((natoms, 3)) # XXXX atomdist = redistributor.get_atom_distributions(spos_ac) return atom_partition, atomdist def redistribute_atomic_matrices(D_asp, gd2, nspins, setups, atom_partition, kptband_comm): D_sP = pack_atomic_matrices(D_asp) D_asp = setups.empty_atomic_matrix(nspins, atom_partition) if gd2.comm.rank == 0: if kptband_comm.rank > 0: nP = sum(setup.ni * (setup.ni + 1) // 2 for setup in setups) D_sP = np.empty((nspins, nP)) kptband_comm.broadcast(D_sP, 0) D_asp.update(unpack_atomic_matrices(D_sP, setups)) D_asp.check_consistency() return D_asp