def initialize(self, spos_ac):
"""Make the object ready for a calculation."""
# Parameters
p = self.parameters
beta = p['beta']
nmaxold = p['nmaxold']
weight = p['weight']
use_pc = p['use_pc']
tolerance_sternheimer = p['tolerance_sternheimer']
max_iter_krylov = p['max_iter_krylov']
krylov_solver = p['krylov_solver']
# Initialize WaveFunctions attribute
self.wfs.initialize(spos_ac)
# Initialize interpolator and restrictor
self.interpolator.allocate()
self.restrictor.allocate()
# Initialize mixer
# weight = 1 -> no metric is used
self.mixer = BaseMixer(beta=beta, nmaxold=nmaxold,
weight=weight, dtype=self.dtype)
self.mixer.initialize_metric(self.gd)
# Linear operator in the Sternheimer equation
self.sternheimer_operator = \
SternheimerOperator(self.hamiltonian, self.wfs, self.gd,
dtype=self.gs_dtype)
# Preconditioner for the Sternheimer equation
if p['use_pc']:
pc = ScipyPreconditioner(self.gd,
self.sternheimer_operator.project,
dtype=self.gs_dtype)
else:
pc = None
#XXX K-point of the pc must be set in the k-point loop -> store a ref.
self.pc = pc
# Linear solver for the solution of Sternheimer equation
self.linear_solver = ScipyLinearSolver(method=krylov_solver,
preconditioner=pc,
tolerance=tolerance_sternheimer,
max_iter=max_iter_krylov)
self.initialized = True
class ResponseCalculator:
"""This class is a calculator for the sc density variation.
From the given perturbation, the set of coupled equations for the
first-order density response is solved self-consistently.
Parameters
----------
max_iter: int
Maximum number of iterations in the self-consistent evaluation of
the density variation.
tolerance_sc: float
Tolerance for the self-consistent loop measured in terms of
integrated absolute change of the density derivative between two
iterations.
tolerance_sternheimer: float
Tolerance for the solution of the Sternheimer equation -- passed to
the ``LinearSolver``.
beta: float (0 < beta < 1)
Mixing coefficient.
nmaxold: int
Length of history for the mixer.
weight: int
Weight for the mixer metric (=1 -> no metric used).
"""
parameters = {'verbose': False,
'max_iter': 100,
'max_iter_krylov': 1000,
'krylov_solver': 'cg',
'tolerance_sc': 1.0e-5,
'tolerance_sternheimer': 1.0e-4,
'use_pc': True,
'beta': 0.1,
'nmaxold': 6,
'weight': 50
}
def __init__(self, calc, wfs, poisson_solver=None, dtype=float, **kwargs):
"""Store calculator etc.
Parameters
----------
calc: Calculator
Calculator instance containing a ground-state calculation
(calc.set_positions must have been called before this point!).
wfs: WaveFunctions
Class taking care of wave-functions, projectors, k-point related
quantities and symmetries.
poisson_solver: PoissonSolver
Multigrid or FFT poisson solver (not required if the
``Perturbation`` to be solved for has a ``solve_poisson`` member
function).
dtype: ...
dtype of the density response.
"""
# Store ground-state quantities
self.hamiltonian = calc.hamiltonian
self.density = calc.density
self.wfs = wfs
# Get list of k-point containers
self.kpt_u = wfs.kpt_u
# Poisson solver
if poisson_solver is None:
# Solver must be provided by the perturbation
self.poisson = None
self.solve_poisson = None
else:
self.poisson = poisson_solver
self.solve_poisson = self.poisson.solve_neutral
# Store grid-descriptors
self.gd = calc.density.gd
self.finegd = calc.density.finegd
# dtype for ground-state wave-functions
self.gs_dtype = calc.wfs.dtype
# dtype for the perturbing potential and density
self.dtype = dtype
# Grid transformer -- convert array from coarse to fine grid
self.interpolator = Transformer(self.gd, self.finegd, nn=3,
dtype=self.dtype, allocate=False)
# Grid transformer -- convert array from fine to coarse grid
self.restrictor = Transformer(self.finegd, self.gd, nn=3,
dtype=self.dtype, allocate=False)
# Sternheimer operator
self.sternheimer_operator = None
# Krylov solver
self.linear_solver = None
# Phases for transformer objects - since the perturbation determines
# the form of the density response this is obtained from the
# perturbation in the ``__call__`` member function below.
self.phase_cd = None
# Array attributes
self.nt1_G = None
self.vHXC1_G = None
self.nt1_g = None
self.vH1_g = None
# Perturbation
self.perturbation = None
# Number of occupied bands
nvalence = calc.wfs.nvalence
self.nbands = nvalence/2 + nvalence%2
assert self.nbands <= calc.wfs.nbands
self.initialized = False
self.parameters = {}
self.set(**kwargs)
def clean(self):
"""Cleanup before call to ``__call__``."""
self.perturbation = None
self.solve_poisson = None
self.nt1_G = None
self.vHXC1_G = None
self.nt1_g = None
self.vH1_g = None
def __call__(self, perturbation):
"""Calculate density response (derivative) to perturbation.
Parameters
----------
perturbation: Perturbation
Class implementing the perturbing potential. Must provide an
``apply`` member function implementing the multiplication of the
perturbing potential to a (set of) state vector(s).
"""
assert self.initialized, ("Linear response calculator "
"not initizalized.")
self.clean()
if self.poisson is None:
assert hasattr(perturbation, 'solve_poisson')
self.solve_poisson = perturbation.solve_poisson
# Store perturbation - used in other member functions
self.perturbation = perturbation
# Reset mixer
self.mixer.reset()
# Reset wave-functions
self.wfs.reset()
# Set phase attribute for Transformer objects
self.phase_cd = self.perturbation.get_phase_cd()
# Parameters for the SC-loop
p = self.parameters
max_iter = p['max_iter']
tolerance = p['tolerance_sc']
for iter in range(max_iter):
if iter == 0:
self.first_iteration()
else:
print "iter:%3i\t" % iter,
norm = self.iteration()
print "abs-norm: %6.3e\t" % norm,
print ("integrated density response (abs): % 5.2e (%5.2e) "
% (self.gd.integrate(self.nt1_G.real),
self.gd.integrate(np.absolute(self.nt1_G))))
if norm < tolerance:
print ("self-consistent loop converged in %i iterations"
% iter)
break
if iter == max_iter:
raise RuntimeError, ("self-consistent loop did not converge "
"in %i iterations" % iter)
def set(self, **kwargs):
"""Set parameters for calculation."""
# Check for legal input parameters
for key, value in kwargs.items():
if not key in ResponseCalculator.parameters:
raise TypeError("Unknown keyword argument: '%s'" % key)
# Insert default values if not given
for key, value in ResponseCalculator.parameters.items():
if key not in kwargs:
kwargs[key] = value
self.parameters.update(kwargs)
def initialize(self, spos_ac):
"""Make the object ready for a calculation."""
# Parameters
p = self.parameters
beta = p['beta']
nmaxold = p['nmaxold']
weight = p['weight']
use_pc = p['use_pc']
tolerance_sternheimer = p['tolerance_sternheimer']
max_iter_krylov = p['max_iter_krylov']
krylov_solver = p['krylov_solver']
# Initialize WaveFunctions attribute
self.wfs.initialize(spos_ac)
# Initialize interpolator and restrictor
self.interpolator.allocate()
self.restrictor.allocate()
# Initialize mixer
# weight = 1 -> no metric is used
self.mixer = BaseMixer(beta=beta, nmaxold=nmaxold,
weight=weight, dtype=self.dtype)
self.mixer.initialize_metric(self.gd)
# Linear operator in the Sternheimer equation
self.sternheimer_operator = \
SternheimerOperator(self.hamiltonian, self.wfs, self.gd,
dtype=self.gs_dtype)
# Preconditioner for the Sternheimer equation
if p['use_pc']:
pc = ScipyPreconditioner(self.gd,
self.sternheimer_operator.project,
dtype=self.gs_dtype)
else:
pc = None
#XXX K-point of the pc must be set in the k-point loop -> store a ref.
self.pc = pc
# Linear solver for the solution of Sternheimer equation
self.linear_solver = ScipyLinearSolver(method=krylov_solver,
preconditioner=pc,
tolerance=tolerance_sternheimer,
max_iter=max_iter_krylov)
self.initialized = True
def first_iteration(self):
"""Perform first iteration of sc-loop."""
self.wave_function_variations()
self.density_response()
self.mixer.mix(self.nt1_G, [], phase_cd=self.phase_cd)
self.interpolate_density()
def iteration(self):
"""Perform iteration."""
# Update variation in the effective potential
self.effective_potential_variation()
# Update wave function variations
self.wave_function_variations()
# Update density
self.density_response()
# Mix - supply phase_cd here for metric inside the mixer
self.mixer.mix(self.nt1_G, [], phase_cd=self.phase_cd)
norm = self.mixer.get_charge_sloshing()
self.interpolate_density()
return norm
def interpolate_density(self):
"""Interpolate density derivative onto the fine grid."""
self.nt1_g = self.finegd.zeros(dtype=self.dtype)
self.interpolator.apply(self.nt1_G, self.nt1_g, phases=self.phase_cd)
def effective_potential_variation(self):
"""Calculate derivative of the effective potential (Hartree + XC)."""
# Hartree part
vHXC1_g = self.finegd.zeros(dtype=self.dtype)
self.solve_poisson(vHXC1_g, self.nt1_g)
# Store for evaluation of second order derivative
self.vH1_g = vHXC1_g.copy()
# XC part
nt_sg = self.density.nt_sg
fxct_sg = np.zeros_like(nt_sg)
self.hamiltonian.xc.calculate_fxc(self.finegd, nt_sg, fxct_sg)
vHXC1_g += fxct_sg[0] * self.nt1_g
# Transfer to coarse grid
self.vHXC1_G = self.gd.zeros(dtype=self.dtype)
self.restrictor.apply(vHXC1_g, self.vHXC1_G, phases=self.phase_cd)
def wave_function_variations(self):
"""Calculate variation in the wave-functions.
Parameters
----------
v1_G: ndarray
Variation of the local effective potential (Hartree + XC).
"""
verbose = self.parameters['verbose']
if verbose:
print "Calculating wave function variations"
if self.perturbation.has_q():
q_c = self.perturbation.get_q()
kplusq_k = self.wfs.kd.find_k_plus_q(q_c)
else:
kplusq_k = None
# Calculate wave-function variations for all k-points.
for kpt in self.kpt_u:
k = kpt.k
if verbose:
print "k-point %2.1i" % k
# Index of k+q vector
if kplusq_k is None:
kplusq = k
kplusqpt = kpt
else:
kplusq = kplusq_k[k]
kplusqpt = self.kpt_u[kplusq]
# Ground-state and first-order wave-functions
psit_nG = kpt.psit_nG
psit1_nG = kpt.psit1_nG
# Update the SternheimerOperator
self.sternheimer_operator.set_k(k)
self.sternheimer_operator.set_kplusq(kplusq)
# Update preconditioner
if self.pc is not None:
# k+q
self.pc.set_kpt(kplusqpt)
# Right-hand side of Sternheimer equations
# k and k+q
# XXX should only be done once for all k-points but maybe too cheap
# to bother ??
rhs_nG = self.gd.zeros(n=self.nbands, dtype=self.gs_dtype)
self.perturbation.apply(psit_nG, rhs_nG, self.wfs, k, kplusq)
if self.vHXC1_G is not None:
rhs_nG += self.vHXC1_G * psit_nG
# Project out occupied subspace
self.sternheimer_operator.project(rhs_nG)
# Loop over occupied bands
for n in range(self.nbands):
# Update band index in SternheimerOperator
self.sternheimer_operator.set_band(n)
# Get view of the Bloch function derivative
psit1_G = psit1_nG[n]
# Rhs of Sternheimer equation
rhs_G = -1 * rhs_nG[n]
# Solve Sternheimer equation
iter, info = self.linear_solver.solve(self.sternheimer_operator,
psit1_G, rhs_G)
if verbose:
print "\tBand %2.1i -" % n,
if info == 0:
if verbose:
print "linear solver converged in %i iterations" % iter
elif info > 0:
assert False, ("linear solver did not converge in maximum "
"number (=%i) of iterations for "
"k-point number %d" % (iter, k))
else:
assert False, ("linear solver failed to converge")
def density_response(self):
"""Calculate density response from variation in the wave-functions."""
# Density might be complex
self.nt1_G = self.gd.zeros(dtype=self.dtype)
for kpt in self.kpt_u:
# The weight of the k-points includes spin-degeneracy
w = kpt.weight
# Wave functions
psit_nG = kpt.psit_nG
psit1_nG = kpt.psit1_nG
for psit_G, psit1_G in zip(psit_nG, psit1_nG):
# NOTICE: this relies on the automatic down-cast of the complex
# array on the rhs to a real array when the lhs is real !!
# Factor 2 for time-reversal symmetry
self.nt1_G += 2 * w * psit_G.conj() * psit1_G
