Python GridDescriptor.refine方法代码示例

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
    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

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
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()

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
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))
gdfine = gd.refine()
interpolate = Transformer(gd, gdfine, 3).apply
a1 = gd.empty()
a1[:] = 1.0
f = gdfine.empty()
ta = time()
r = 600
for i in range(r):
    interpolate(a1, f)
tb = time()
n = 8 * (1 + 2 + 4) * ngpts**3
print '%.3f GFlops' % (r * n / (tb - ta) * 1e-9)

"""
python: 0.330 GFlops
mpirun -np 2 gpaw-python: 0.500 GFlops
gpaw-python + OMP: 0.432 GFlops
"""

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
    def abstract_boundary(self):
        # Abtract the effective potential, hartree potential, and average density
        #out from the electrode calculation.
        map = {'-': '0', '+': '1'}
	data = self.tio.read_data(filename='Lead_' + 
	                          map[self.direction], option='Lead')
        nn = data['fine_N_c'][2]
	ns = data['nspins']
        N_c = data['N_c']
	cell_cv = data['cell_cv']
	pbc_c = data['pbc_c']
	#parsize_c = data['parsize_c']
        if type(parsize_domain) is int:
            parsize_c = None
            assert parsize_domain == self.domain_comm.size
        else:
            parsize_c = parsize_domain
        if parsize_c is None:
            parsize_c = decompose_domain(N_c, self.domain_comm.size)
        parsize_c = np.array(parsize_c)
        d1 = N_c[0] // 2
        d2 = N_c[1] // 2
       
        vHt_g = data['vHt_g']
        vt_sg = data['vt_sg']
        nt_sg = data['nt_sg']
        rhot_g = data['rhot_g']
        vt_sG = data['vt_sG']
        nt_sG = data['nt_sG']
        self.D_asp = data['D_asp']
	self.dH_asp = data['dH_asp']
        gd = GridDescriptor(N_c, cell_cv, pbc_c, self.domain_comm, parsize_c)
	finegd = gd.refine()
	
        self.boundary_vHt_g = None
        self.boundary_vHt_g1 = None
        self.boundary_vt_sg_line = None
        self.boundary_nt_sg = None
        self.boundary_rhot_g_line = None
        self.boundary_vt_sG = None
        self.boundary_nt_sG = None

        if self.tio.domain_comm.rank == 0:
            self.boundary_vHt_g = self.slice(nn, vHt_g)
            self.boundary_nt_sg = self.slice(nn, nt_sg)
            if self.direction == '-':
                other_direction= '+'
            else:
                other_direction= '-'
            h = self.h_cz / 2.0
            b_vHt_g0 = self.boundary_vHt_g.copy()
            b_vHt_g1 = self.boundary_vHt_g.copy()

            self.boundary_vHt_g = interpolate_array(b_vHt_g0,
                                                    finegd, h, 
						    self.direction)
            self.boundary_vHt_g1 = interpolate_array(b_vHt_g1,
                                                     finegd, h, 
						     other_direction)
            vt_sg = interpolate_array(vt_sg, finegd, 
	                              h, self.direction)
            self.boundary_vt_sg_line =  aa1d(vt_sg)
            self.boundary_nt_sg = interpolate_array(self.boundary_nt_sg,
                                                    finegd, h, self.direction)
            rhot_g = interpolate_array(rhot_g, finegd, h, self.direction)
            self.boundary_rhot_g_line = aa1d(rhot_g)

            nn /= 2
            h *= 2
            self.boundary_vt_sG = self.slice(nn, vt_sG)
            self.boundary_nt_sG = self.slice(nn, nt_sG)
            self.boundary_vt_sG = interpolate_array(self.boundary_vt_sG,
                                                    gd, h, self.direction)
            self.boundary_nt_sG = interpolate_array(self.boundary_nt_sG,
                                                    gd, h, self.direction)

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
from gpaw.transformers import Transformer
import numpy.random as ra
from gpaw.grid_descriptor import GridDescriptor

p = 0
n = 20
gd1 = GridDescriptor((n, n, n), (8.0, 8.0, 8.0), pbc_c=p)
a1 = gd1.zeros()
ra.seed(8)
a1[:] = ra.random(a1.shape)
gd2 = gd1.refine()
a2 = gd2.zeros()
i = Transformer(gd1, gd2).apply
i(a1, a2)
assert abs(gd1.integrate(a1) - gd2.integrate(a2)) < 1e-10
r = Transformer(gd2, gd1).apply
a2[0] = 0.0
a2[:, 0] = 0.0
a2[:, :, 0] = 0.0
a2[-1] = 0.0
a2[:, -1] = 0.0
a2[:, :, -1] = 0.0
r(a2, a1)
assert abs(gd1.integrate(a1) - gd2.integrate(a2)) < 1e-10

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
# Copyright (C) 2003  CAMP
# Please see the accompanying LICENSE file for further information.
from __future__ import print_function
from gpaw.grid_descriptor import GridDescriptor
from gpaw.transformers import Transformer
import time


n = 6
gda = GridDescriptor((n, n, n))
gdb = gda.refine()
gdc = gdb.refine()
a = gda.zeros()
b = gdb.zeros()
c = gdc.zeros()

inter = Transformer(gdb, gdc, 2).apply
restr = Transformer(gdb, gda, 2).apply

t = time.clock()
for i in range(8 * 300):
    inter(b, c)
print(time.clock() - t)

t = time.clock()
for i in range(8 * 3000):
    restr(b, a)
print(time.clock() - t)

# 需要导入模块: from gpaw.grid_descriptor import GridDescriptor [as 别名]
# 或者: from gpaw.grid_descriptor.GridDescriptor import refine [as 别名]
# Copyright (C) 2003  CAMP
# Please see the accompanying LICENSE file for further information.

import numpy as np
from gpaw.grid_descriptor import GridDescriptor
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)