class KineticEnergyPreconditioner:
def __init__(self, gd, kin, dtype):
self.preconditioner = Preconditioner(gd, kin, dtype)
self.preconditioner.allocate()
def apply(self, kpt, psi, psin):
for i in range(len(psi)):
psin[i][:] = self.preconditioner(psi[i], kpt.phase_cd, None, None)
class KineticEnergyPreconditioner:
def __init__(self, gd, kin, dtype):
self.preconditioner = Preconditioner(gd, kin, dtype)
self.preconditioner.allocate()
def apply(self, kpt, psi, psin):
for i in range(len(psi)):
psin[i][:] = self.preconditioner(psi[i], kpt.phase_cd, None, None)
class ScipyPreconditioner:
def __init__(self, gd, project, dtype=float):
"""Init the gpaw preconditioner.
Parameters
----------
gd: GridDescriptor
Coarse grid
"""
self.project = project
self.gd = gd
# K-point for the preconditioner
self.kpt = None
kin = Laplace(gd, scale=-0.5, n=3, dtype=dtype, allocate=True)
self.pc = Preconditioner(gd, kin, dtype=dtype)
self.pc.allocate()
# For scipy's linear solver
N = np.prod(gd.n_c)
self.shape = (N,N)
self.dtype = dtype
def set_kpt(self, kpt):
"""Set k-point for ``Transformer`` objects inside the preconditioner.
Parameters
----------
kpt: KPoint or KPointContainer
Only requirement is that it must have an ``phase_cd`` attribute.
"""
self.kpt = kpt
def matvec(self, x):
"""Matrix vector multiplication for ``scipy.sparse.linalg`` solvers.
Parameters
----------
x: ndarry
1-dimensional array holding the grid representation of the vector
"""
# Output array
y_G = self.gd.zeros(dtype=self.dtype)
shape = y_G.shape
size = x.size
assert size == np.prod(shape)
x_G = x.reshape(shape)
# Call gpaw preconditioner
y_G = self.pc(x_G, kpt=self.kpt)
# Project out undesired (numerical) components
self.project(y_G)
y = y_G.ravel()
return y
