def get_combined_data(self, qmdata=None, cldata=None, spacing=None):
if qmdata is None:
qmdata = self.density.rhot_g
if cldata is None:
cldata = self.classical_material.charge_density
if spacing is None:
spacing = self.cl.gd.h_cv[0, 0]
spacing_au = spacing / Bohr # from Angstroms to a.u.
# Collect data from different processes
cln = self.cl.gd.collect(cldata)
qmn = self.qm.gd.collect(qmdata)
clgd = GridDescriptor(self.cl.gd.N_c,
self.cl.cell,
False,
serial_comm,
None)
if world.rank == 0:
cln *= self.classical_material.sign
# refine classical part
while clgd.h_cv[0, 0] > spacing_au * 1.50: # 45:
cln = Transformer(clgd, clgd.refine()).apply(cln)
clgd = clgd.refine()
# refine quantum part
qmgd = GridDescriptor(self.qm.gd.N_c,
self.qm.cell,
False,
serial_comm,
None)
while qmgd.h_cv[0, 0] < clgd.h_cv[0, 0] * 0.95:
qmn = Transformer(qmgd, qmgd.coarsen()).apply(qmn)
qmgd = qmgd.coarsen()
assert np.all(qmgd.h_cv == clgd.h_cv), " Spacings %.8f (qm) and %.8f (cl) Angstroms" % (qmgd.h_cv[0][0] * Bohr, clgd.h_cv[0][0] * Bohr)
# now find the corners
r_gv_cl = clgd.get_grid_point_coordinates().transpose((1, 2, 3, 0))
cind = self.qm.corner1 / np.diag(clgd.h_cv) - 1
n = qmn.shape
# print 'Corner points: ', self.qm.corner1*Bohr, ' - ', self.qm.corner2*Bohr
# print 'Calculated points: ', r_gv_cl[tuple(cind)]*Bohr, ' - ', r_gv_cl[tuple(cind+n+1)]*Bohr
cln[cind[0] + 1:cind[0] + n[0] + 1,
cind[1] + 1:cind[1] + n[1] + 1,
cind[2] + 1:cind[2] + n[2] + 1] += qmn
world.barrier()
return cln, clgd
def get_combined_data(self, qmdata=None, cldata=None, spacing=None):
if qmdata is None:
qmdata = self.density.rhot_g
if cldata is None:
cldata = self.classical_material.charge_density
if spacing is None:
spacing = self.cl.gd.h_cv[0, 0]
spacing_au = spacing / Bohr # from Angstroms to a.u.
# Collect data from different processes
cln = self.cl.gd.collect(cldata)
qmn = self.qm.gd.collect(qmdata)
clgd = GridDescriptor(self.cl.gd.N_c, self.cl.cell, False, serial_comm,
None)
if world.rank == 0:
cln *= self.classical_material.sign
# refine classical part
while clgd.h_cv[0, 0] > spacing_au * 1.50: # 45:
cln = Transformer(clgd, clgd.refine()).apply(cln)
clgd = clgd.refine()
# refine quantum part
qmgd = GridDescriptor(self.qm.gd.N_c, self.qm.cell, False,
serial_comm, None)
while qmgd.h_cv[0, 0] < clgd.h_cv[0, 0] * 0.95:
qmn = Transformer(qmgd, qmgd.coarsen()).apply(qmn)
qmgd = qmgd.coarsen()
assert np.all(qmgd.h_cv == clgd.h_cv
), " Spacings %.8f (qm) and %.8f (cl) Angstroms" % (
qmgd.h_cv[0][0] * Bohr, clgd.h_cv[0][0] * Bohr)
# now find the corners
r_gv_cl = clgd.get_grid_point_coordinates().transpose((1, 2, 3, 0))
cind = self.qm.corner1 / np.diag(clgd.h_cv) - 1
n = qmn.shape
# print 'Corner points: ', self.qm.corner1*Bohr, ' - ', self.qm.corner2*Bohr
# print 'Calculated points: ', r_gv_cl[tuple(cind)]*Bohr, ' - ', r_gv_cl[tuple(cind+n+1)]*Bohr
cln[cind[0] + 1:cind[0] + n[0] + 1, cind[1] + 1:cind[1] + n[1] + 1,
cind[2] + 1:cind[2] + n[2] + 1] += qmn
world.barrier()
return cln, clgd
def go(comm, ngpts, repeat, narrays, out, prec):
N_c = np.array((ngpts, ngpts, ngpts))
a = 10.0
gd = GridDescriptor(N_c, (a, a, a), comm=comm))
gdcoarse = gd.coarsen()
gdfine = gd.refine()
kin1 = Laplace(gd, -0.5, 1).apply
laplace = Laplace(gd, -0.5, 2)
kin2 = laplace.apply
restrict = Transformer(gd, gdcoarse, 1).apply
interpolate = Transformer(gd, gdfine, 1).apply
precondition = Preconditioner(gd, laplace, np_float)
a1 = gd.empty(narrays)
a1[:] = 1.0
a2 = gd.empty(narrays)
c = gdcoarse.empty(narrays)
f = gdfine.empty(narrays)
T = [0, 0, 0, 0, 0]
for i in range(repeat):
comm.barrier()
kin1(a1, a2)
comm.barrier()
t0a = time()
kin1(a1, a2)
t0b = time()
comm.barrier()
t1a = time()
kin2(a1, a2)
t1b = time()
comm.barrier()
t2a = time()
for A, C in zip(a1,c):
restrict(A, C)
t2b = time()
comm.barrier()
t3a = time()
for A, F in zip(a1,f):
interpolate(A, F)
t3b = time()
comm.barrier()
if prec:
t4a = time()
for A in a1:
precondition(A, None, None, None)
t4b = time()
comm.barrier()
T[0] += t0b - t0a
T[1] += t1b - t1a
T[2] += t2b - t2a
T[3] += t3b - t3a
if prec:
T[4] += t4b - t4a
if mpi.rank == 0:
out.write(' %2d %2d %2d' % tuple(gd.parsize_c))
out.write(' %12.6f %12.6f %12.6f %12.6f %12.6f\n' %
tuple([t / repeat / narrays for t in T]))
out.flush()
n = 20
gd = GridDescriptor((n,n,n))
np.random.seed(8)
a = gd.empty()
a[:] = np.random.random(a.shape)
gd2 = gd.refine()
b = gd2.zeros()
for k in [2, 4, 6, 8]:
inter = Transformer(gd, gd2, k // 2).apply
inter(a, b)
assert abs(gd.integrate(a) - gd2.integrate(b)) < 1e-14
gd2 = gd.coarsen()
b = gd2.zeros()
for k in [2, 4, 6, 8]:
restr = Transformer(gd, gd2, k // 2).apply
restr(a, b)
assert abs(gd.integrate(a) - gd2.integrate(b)) < 1e-14
# complex versions
a = gd.empty(dtype=complex)
a.real = np.random.random(a.shape)
a.imag = np.random.random(a.shape)
phase = np.ones((3, 2), complex)
gd2 = gd.refine()
b = gd2.zeros(dtype=complex)
from time import time
from gpaw.transformers import Transformer
from gpaw.grid_descriptor import GridDescriptor
from gpaw.mpi import world
ngpts = 80
N_c = (ngpts, ngpts, ngpts)
a = 10.0
gd = GridDescriptor(N_c, (a, a, a))
gdcoarse = gd.coarsen()
restrict = Transformer(gd, gdcoarse, 2).apply
a1 = gd.empty()
a1[:] = 1.0
f = gdcoarse.empty()
ta = time()
r = 600
print a1.shape, f.shape
for i in range(r):
restrict(a1, f)
tb = time()
print tb - ta
#n = 8 * (1 + 2 + 4) * ngpts**3
#print '%.3f GFlops' % (r * n / (tb - ta) * 1e-9)
from gpaw.transformers import Transformer
n = 20
gd = GridDescriptor((n, n, n))
np.random.seed(8)
a = gd.empty()
a[:] = np.random.random(a.shape)
gd2 = gd.refine()
b = gd2.zeros()
for k in [2, 4, 6, 8]:
inter = Transformer(gd, gd2, k // 2).apply
inter(a, b)
assert abs(gd.integrate(a) - gd2.integrate(b)) < 1e-14
gd2 = gd.coarsen()
b = gd2.zeros()
for k in [2, 4, 6, 8]:
restr = Transformer(gd, gd2, k // 2).apply
restr(a, b)
assert abs(gd.integrate(a) - gd2.integrate(b)) < 1e-14
# complex versions
a = gd.empty(dtype=complex)
a.real = np.random.random(a.shape)
a.imag = np.random.random(a.shape)
phase = np.ones((3, 2), complex)
gd2 = gd.refine()
b = gd2.zeros(dtype=complex)
