def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array, mpi_type = self.args
slices = common.slice_index_two_points(pt0, pt1)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1)
value = np.random.rand(*shape).astype(np.float32)
else:
value = np.random.ranf()
# instance
fields = Fields(nx, ny, nz, '', 'single', 0, mpi_type=mpi_type)
tfunc = lambda tstep: np.sin(0.03 * tstep)
incident = DirectIncident(fields, str_f, pt0, pt1, tfunc, value)
# host allocations
eh = np.zeros(fields.ns_pitch, dtype=fields.dtype)
getf = GetFields(fields, str_f, pt0, pt1)
# verify
eh[slices] = fields.dtype(value) * fields.dtype(tfunc(1))
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
original = eh[slices]
getf.get_event().wait()
copy = getf.get_fields()
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array, mpi_type = self.args
slices = common.slice_index_two_points(pt0, pt1)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1)
value = np.random.rand(*shape).astype(np.float32)
else:
value = np.random.ranf()
# instance
fields = Fields(nx, ny, nz, '', 'single', 0, mpi_type=mpi_type)
tfunc = lambda tstep: np.sin(0.03*tstep)
incident = DirectIncident(fields, str_f, pt0, pt1, tfunc, value)
# host allocations
eh = np.zeros(fields.ns_pitch, dtype=fields.dtype)
getf = GetFields(fields, str_f, pt0, pt1)
# verify
eh[slices] = fields.dtype(value) * fields.dtype(tfunc(1))
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
original = eh[slices]
getf.get_event().wait()
copy = getf.get_fields()
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def test(self):
nx, ny, nz = 40, 50, 60
tmax = 10
# buffer instance
if rank == 0:
fields = Fields(10, ny, nz, mpi_type='x+')
exmpi = ExchangeMpi(fields, 1, tmax)
elif rank == 1:
fields = Fields(3, ny, nz, mpi_type='x-')
exmpi = ExchangeMpi(fields, 0, tmax)
# generate random source
nx, ny, nz = fields.ns
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
fields.set_ehs(*ehs)
# verify
for tstep in xrange(1, tmax + 1):
fields.update_e()
fields.update_h()
getf_dict = {}
if rank == 0:
getf_dict['e'] = GetFields(fields, ['ey', 'ez'], \
(nx-1, 0, 0), (nx-1, ny-2, nz-2))
getf_dict['h'] = GetFields(fields, ['hy', 'hz'], \
(1, 1, 1), (1, ny-1, nz-1))
for eh in ['e', 'h']:
getf = getf_dict[eh]
getf.get_event().wait()
g0 = getf.get_fields()
g1 = np.zeros_like(g0)
comm.Recv(g1, 1, tag=10)
norm = np.linalg.norm(g0 - g1)
self.assertEqual(norm, 0, '%g, %s, %s' % (norm, 'x', 'e'))
elif rank == 1:
getf_dict['e'] = GetFields(fields, ['ey', 'ez'], \
(nx-2, 0, 0), (nx-2, ny-2, nz-2))
getf_dict['h'] = GetFields(fields, ['hy', 'hz'], \
(0, 1, 1), (0, ny-1, nz-1))
for eh in ['e', 'h']:
getf = getf_dict[eh]
getf.get_event().wait()
comm.Send(getf.get_fields(), 0, tag=10)
def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array = self.args
slice_xyz = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(nx, ny, nz, '', 'single')
setf = SetFields(fields, str_f, pt0, pt1, is_array)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1, len(str_fs))
value = np.random.rand(*shape).astype(fields.dtype)
split_value = np.split(value, len(str_fs))
split_value_dict = dict( zip(str_fs, split_value) )
else:
value = np.random.ranf()
# host allocations
ehs = [np.zeros(fields.ns, dtype=fields.dtype) for i in range(6)]
eh_dict = dict( zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs) )
# verify
for str_f in str_fs:
if is_array:
eh_dict[str_f][slice_xyz] = split_value_dict[str_f]
else:
eh_dict[str_f][slice_xyz] = value
setf.set_fields(value)
fields.enqueue_barrier()
for str_f in str_fs:
original = eh_dict[str_f]
copy = fields.get(str_f)[:,:,fields.slice_z]
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array = self.args
slice_xyz = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(nx, ny, nz, '', 'single')
setf = SetFields(fields, str_f, pt0, pt1, is_array)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1, len(str_fs))
value = np.random.rand(*shape).astype(fields.dtype)
split_value = np.split(value, len(str_fs))
split_value_dict = dict(zip(str_fs, split_value))
else:
value = np.random.ranf()
# host allocations
ehs = [np.zeros(fields.ns, dtype=fields.dtype) for i in range(6)]
eh_dict = dict(zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs))
# verify
for str_f in str_fs:
if is_array:
eh_dict[str_f][slice_xyz] = split_value_dict[str_f]
else:
eh_dict[str_f][slice_xyz] = value
setf.set_fields(value)
fields.enqueue_barrier()
for str_f in str_fs:
original = eh_dict[str_f]
copy = fields.get(str_f)[:, :, fields.slice_z]
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
nx, ny, nz, str_f, pt0, pt1 = self.args
slice_xyz = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(nx, ny, nz, '', 'single')
getf = GetFields(fields, str_f, pt0, pt1)
# host allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
eh_dict = dict(zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs))
fields.set_ehs(*ehs)
# verify
getf.get_event().wait()
for str_f in str_fs:
original = eh_dict[str_f][slice_xyz]
copy = getf.get_fields(str_f)
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
nx, ny, nz, str_f, pt0, pt1 = self.args
slice_xyz = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(nx, ny, nz, '', 'single')
getf = GetFields(fields, str_f, pt0, pt1)
# host allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
eh_dict = dict( zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs) )
fields.set_ehs(*ehs)
# verify
getf.get_event().wait()
for str_f in str_fs:
original = eh_dict[str_f][slice_xyz]
copy = getf.get_fields(str_f)
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def test(self):
nx, ny, nz = 40, 50, 60
tmax = 10
# buffer instance
if rank == 0:
fields = Fields(10, ny, nz, mpi_type="x+")
exmpi = ExchangeMpi(fields, 1, tmax)
elif rank == 1:
fields = Fields(3, ny, nz, mpi_type="x-")
exmpi = ExchangeMpi(fields, 0, tmax)
# generate random source
nx, ny, nz = fields.ns
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
fields.set_ehs(*ehs)
# verify
for tstep in xrange(1, tmax + 1):
fields.update_e()
fields.update_h()
getf_dict = {}
if rank == 0:
getf_dict["e"] = GetFields(fields, ["ey", "ez"], (nx - 1, 0, 0), (nx - 1, ny - 2, nz - 2))
getf_dict["h"] = GetFields(fields, ["hy", "hz"], (1, 1, 1), (1, ny - 1, nz - 1))
for eh in ["e", "h"]:
getf = getf_dict[eh]
getf.get_event().wait()
g0 = getf.get_fields()
g1 = np.zeros_like(g0)
comm.Recv(g1, 1, tag=10)
norm = np.linalg.norm(g0 - g1)
self.assertEqual(norm, 0, "%g, %s, %s" % (norm, "x", "e"))
elif rank == 1:
getf_dict["e"] = GetFields(fields, ["ey", "ez"], (nx - 2, 0, 0), (nx - 2, ny - 2, nz - 2))
getf_dict["h"] = GetFields(fields, ["hy", "hz"], (0, 1, 1), (0, ny - 1, nz - 1))
for eh in ["e", "h"]:
getf = getf_dict[eh]
getf.get_event().wait()
comm.Send(getf.get_fields(), 0, tag=10)
def runTest(self):
axis, nx, ny, nz, mpi_type = self.args
fields = Fields(nx, ny, nz, mpi_type=mpi_type)
self.assertRaises(ValueError, Pbc, fields, axis)
import numpy as np
import sys, os
sys.path.append(os.path.expanduser('~'))
from kemp.fdtd3d.cpu import QueueTask, Fields, Core, Pbc, IncidentDirect, GetFields
nx, ny, nz = 160, 140, 32
tmax, tgap = 150, 10
# instances
fields = Fields(QueueTask(), nx, ny, nz, 'e')
Core(fields)
Pbc(fields, 'xyz')
"""
tfunc = lambda tstep: np.sin(0.05 * tstep)
IncidentDirect(fields, 'ez', (20, 0, 0), (20, -1, -1), tfunc)
#IncidentDirect(fields, 'ez', (0, 20, 0), (-1, 20, -1), tfunc)
getf = GetFields(fields, 'ez', (0, 0, 0.5), (-1, -1, 0.5))
print fields.instance_list
# plot
import matplotlib.pyplot as plt
plt.ion()
fig = plt.figure(figsize=(12,8))
imag = plt.imshow(np.zeros((nx, ny), fields.dtype).T, interpolation='nearest', origin='lower', vmin=-1.1, vmax=1.1)
plt.colorbar()
# main loop
from datetime import datetime
t0 = datetime.now()
# Target : CPU
# Created : 2012-02-13
# Modified:
import numpy as np
import sys
from kemp.fdtd3d.cpu import QueueTask, Fields, Core, Pbc, Pml, IncidentDirect, GetFields
nx, ny, nz = 2, 250, 300
tmax, tgap = 300, 10
npml = 10
# instances
fields = Fields(QueueTask(), nx, ny, nz, use_cpu_core=1)
Pbc(fields, 'x')
Pml(fields, ('', '+-', '+-'), npml)
Core(fields)
tfunc = lambda tstep: 50 * np.sin(0.05 * tstep)
IncidentDirect(fields, 'ex', (0, 0.4, 0.3), (-1, 0.4, 0.3), tfunc)
getf = GetFields(fields, 'ex', (0.5, 0, 0), (0.5, -1, -1))
print fields.instance_list
# main loop
from datetime import datetime
t0 = datetime.now()
sys.path.append(os.path.expanduser('~'))
from kemp.fdtd3d.cpu import QueueTask, Fields, Core, Pbc, IncidentDirect
tmax = 150
tfunc = lambda tstep: np.sin(0.05 * tstep)
# plot
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rc('image', interpolation='nearest', origin='lower')
fig = plt.figure(figsize=(14, 8))
# z-axis
nx, ny, nz = 180, 160, 2
fields = Fields(QueueTask(), nx, ny, nz)
Core(fields)
Pbc(fields, 'xyz')
IncidentDirect(fields, 'ey', (20, 0, 0), (20, -1, -1), tfunc)
IncidentDirect(fields, 'ex', (0, 20, 0), (-1, 20, -1), tfunc)
for tstep in xrange(1, tmax + 1):
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
ax1 = fig.add_subplot(2, 3, 1)
ax1.imshow(fields.get('ey')[:, :, nz / 2].T, vmin=-1.1, vmax=1.1)
ax1.set_title('%s, ey[20,:,:]' % repr(fields.ns))
ax1.set_xlabel('x')
ax1.set_ylabel('y')
import numpy as np
import sys, os
sys.path.append(os.path.expanduser('~'))
from kemp.fdtd3d.cpu import Fields, Core, Pbc, IncidentDirect, GetFields
#nx, ny, nz = 160, 140, 32
#nx, ny, nz = 512, 512, 512 # 4608 MB
#nx, ny, nz = 480, 480, 480 # 3796 MB
nx, ny, nz = 256, 256, 256 # 576 MB
#nx, ny, nz = 128, 128, 128 # 72 MB
tmax, tgap = 1000, 10
# instances
fields = Fields(nx, ny, nz, coeff_use='e', precision_float='single')
Core(fields)
print 'ns_pitch', fields.ns_pitch
print 'nbytes (MB)', nx * ny * nz * 9 * 4. / (1024**2)
'''
Pbc(fields, 'xyz')
tfunc = lambda tstep: np.sin(0.05 * tstep)
IncidentDirect(fields, 'ez', (20, 0, 0), (20, ny-1, nz-1), tfunc)
#IncidentDirect(fields, 'ez', (0, 20, 0), (nx-1, 20, nz-1), tfunc)
getf = GetFields(fields, 'ez', (0, 0, nz/2), (nx-1, ny-1, nz/2))
print fields.instance_list
# plot
import matplotlib.pyplot as plt
import sys, os
sys.path.append( os.path.expanduser('~') )
from kemp.fdtd3d.cpu import QueueTask, Fields, Core, Pbc, IncidentDirect, GetFields
try:
ny = int(sys.argv[1])
except:
ny = 256
nx, nz = 2, 256
tmax, tgap = 1000, 10
# instances
fields = Fields(QueueTask(), nx, ny, nz, coeff_use='e', precision_float='single', use_cpu_core=1)
Core(fields)
fields2 = Fields(QueueTask(), nx, ny, nz, coeff_use='e', precision_float='single', use_cpu_core=1)
Core(fields2)
#print 'ns_pitch', fields.ns_pitch
#print 'nbytes (MB)', nx*ny*nz * 9 * 4. / (1024**2)
'''
Pbc(fields, 'xyz')
tfunc = lambda tstep: np.sin(0.05 * tstep)
IncidentDirect(fields, 'ez', (20, 0, 0), (20, ny-1, nz-1), tfunc)
#IncidentDirect(fields, 'ez', (0, 20, 0), (nx-1, 20, nz-1), tfunc)
getf = GetFields(fields, 'ez', (0, 0, nz/2), (nx-1, ny-1, nz/2))
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt1 = pt1_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fset = SetFields(s.fdtd, str_fs, pt0, pt1, np.ndarray)
values = np.random.rand(*shape_dict[axis]).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields()
assert np.linalg.norm(values - copy) == 0
if __name__ == '__main__':
nx, ny, nz = 200, 220, 256
gpu_id = 0
fdtd = Fields(nx, ny, nz, coeff_use='')
print('-' * 47 + '\nTest GetFields')
testget = TestGetFields(fdtd, nx, ny, nz)
testget.test()
testget.test_boundary()
print('-' * 47 + '\nTest SetFields')
testset = TestSetFields(fdtd, nx, ny, nz)
testset.test()
testset.test_boundary()
sys.path.append(os.path.expanduser('~'))
from kemp.fdtd3d.cpu import QueueTask, Fields, Core, Pbc, IncidentDirect, GetFields
try:
ny = int(sys.argv[1])
except:
ny = 256
nx, nz = 2, 256
tmax, tgap = 1000, 10
# instances
fields = Fields(QueueTask(),
nx,
ny,
nz,
coeff_use='e',
precision_float='single',
use_cpu_core=1)
Core(fields)
fields2 = Fields(QueueTask(),
nx,
ny,
nz,
coeff_use='e',
precision_float='single',
use_cpu_core=1)
Core(fields2)
#print 'ns_pitch', fields.ns_pitch
#print 'nbytes (MB)', nx*ny*nz * 9 * 4. / (1024**2)
import numpy as np
import sys, os
sys.path.append( os.path.expanduser('~') )
from kemp.fdtd3d.cpu import Fields, Core, Pbc, IncidentDirect, GetFields
nx, ny, nz = 160, 140, 32
tmax, tgap = 150, 10
# instances
fields = Fields(nx, ny, nz)
Core(fields)
Pbc(fields, 'xyz')
tfunc = lambda tstep: np.sin(0.05 * tstep)
IncidentDirect(fields, 'ez', (20, 0, 0), (20, ny-1, nz-1), tfunc)
#IncidentDirect(fields, 'ez', (0, 20, 0), (nx-1, 20, nz-1), tfunc)
getf = GetFields(fields, 'ez', (0, 0, nz/2), (nx-1, ny-1, nz/2))
print fields.instance_list
# plot
import matplotlib.pyplot as plt
plt.ion()
fig = plt.figure(figsize=(12,8))
imag = plt.imshow(np.zeros((nx, ny), fields.dtype).T, interpolation='nearest', origin='lower', vmin=-1.1, vmax=1.1)
plt.colorbar()
# main loop
from datetime import datetime
sys.path.append(os.path.expanduser('~'))
from kemp.fdtd3d.cpu import QueueTask, Fields, Core, Pbc, IncidentDirect, GetFields
#nx, ny, nz = 160, 140, 32
#nx, ny, nz = 512, 512, 512 # 4608 MB
#nx, ny, nz = 480, 480, 480 # 3796 MB
nx, ny, nz = 3, 256, 256 # 576 MB
#nx, ny, nz = 128, 128, 128 # 72 MB
tmax, tgap = 1000, 10
# instances
qtask = QueueTask()
fields = Fields(qtask,
nx,
ny,
nz,
coeff_use='e',
precision_float='single',
use_cpu_core=0)
Core(fields)
print 'ns_pitch', fields.ns_pitch
print 'nbytes (MB)', nx * ny * nz * 9 * 4. / (1024**2)
'''
Pbc(fields, 'xyz')
tfunc = lambda tstep: np.sin(0.05 * tstep)
IncidentDirect(fields, 'ez', (20, 0, 0), (20, ny-1, nz-1), tfunc)
#IncidentDirect(fields, 'ez', (0, 20, 0), (nx-1, 20, nz-1), tfunc)
getf = GetFields(fields, 'ez', (0, 0, nz/2), (nx-1, ny-1, nz/2))
def runTest(self):
axis, nx, ny, nz, mpi_type = self.args
fields = Fields(nx, ny, nz, mpi_type=mpi_type)
core = Core(fields)
pbc = Pbc(fields, axis)
# allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
fields.set_ehs(*ehs)
# update
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
# verify
getf0, getf1 = {}, {}
strfs_e = {
'x': ['ey', 'ez'],
'y': ['ex', 'ez'],
'z': ['ex', 'ey']
}[axis]
strfs_h = {
'x': ['hy', 'hz'],
'y': ['hx', 'hz'],
'z': ['hx', 'hy']
}[axis]
pt0 = (0, 0, 0)
pt1 = { 'x': (0, ny-2, nz-2), \
'y': (nx-2, 0, nz-2), \
'z': (nx-2, ny-2, 0) }[axis]
getf0['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (nx-1, 0, 0), \
'y': (0, ny-1, 0), \
'z': (0, 0, nz-1) }[axis]
pt1 = { 'x': (nx-1, ny-2, nz-2), \
'y': (nx-2, ny-1, nz-2), \
'z': (nx-2, ny-2, nz-1) }[axis]
getf1['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (0, 1, 1), \
'y': (1, 0, 1), \
'z': (1, 1, 0) }[axis]
pt1 = { 'x': (0, ny-1, nz-1), \
'y': (nx-1, 0, nz-1), \
'z': (nx-1, ny-1, 0) }[axis]
getf0['h'] = GetFields(fields, strfs_h, pt0, pt1)
pt0 = { 'x': (nx-1, 1, 1), \
'y': (1, ny-1, 1), \
'z': (1, 1, nz-1) }[axis]
pt1 = (nx - 1, ny - 1, nz - 1)
getf1['h'] = GetFields(fields, strfs_h, pt0, pt1)
for getf in getf0.values() + getf1.values():
getf.get_event().wait()
for eh in ['e', 'h']:
g0 = getf0[eh].get_fields()
g1 = getf1[eh].get_fields()
norm = np.linalg.norm(g0 - g1)
'''
print eh
print g0
print g1
'''
self.assertEqual(norm, 0, '%g, %s, %s' % (norm, self.args, eh))
def runTest(self):
ufunc, nx, ny, nz, coeff_use, precision_float, use_cpu_core, split, tmax = self.args
fields = Fields(nx, ny, nz, coeff_use, precision_float, use_cpu_core)
core = Core(fields)
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
slice_xyz = [slice(None, None), slice(None, None), fields.slice_z]
# allocations
ns = fields.ns
dtype = fields.dtype
ehs = common_update.generate_random_ehs(nx, ny, nz, dtype, ufunc)
fields.set_ehs(*ehs)
ces, chs = common_update.generate_random_cs(coeff_use, nx, ny, nz,
dtype)
if 'e' in coeff_use:
fields.set_ces(*ces)
if 'h' in coeff_use:
fields.set_chs(*chs)
# update
if ufunc == 'e':
for tstep in xrange(0, tmax):
fields.update_e()
common_update.update_e(ehs, ces)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[:3]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(
norm, 0,
'%s, %s, %g, %g' % (self.args, strf, norm, max_diff))
if fields.pad != 0:
if strf == 'ez':
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad:])
else:
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad - 1:])
self.assertEqual(
norm2, 0,
'%s, %s, %g, padding' % (self.args, strf, norm2))
elif ufunc == 'h':
for tstep in xrange(0, tmax):
fields.update_h()
common_update.update_h(ehs, chs)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[3:]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(norm, 0, '%s, %s, %g, %g' % \
(self.args, strf, norm, max_diff) )
if fields.pad != 0:
if strf == 'hz':
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad:])
else:
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad:])
self.assertEqual(
norm2, 0,
'%s, %s, %g, padding' % (self.args, strf, norm2))
#!/usr/bin/env python
import sys
sys.path.append('/home/kifang')
from kemp.fdtd3d.cpu import Fields, DirectSrc, GetFields
import numpy as np
nx, ny, nz = 240, 320, 320
tmax, tgap = 200, 10
fdtd = Fields(nx, ny, nz, coeff_use='', use_cpu_core=0)
src = DirectSrc(fdtd, 'ez', (nx/5*4, ny/2, 0), (nx/5*4, ny/2, nz-1), lambda tstep: np.sin(0.1 * tstep))
output = GetFields(fdtd, 'ez', (0, 0, nz/2), (nx-1, ny-1, nz/2))
# Plot
import matplotlib.pyplot as plt
plt.ion()
imag = plt.imshow(fdtd.ez[:,:,nz/2].T, cmap=plt.cm.hot, origin='lower', vmin=0, vmax=0.05)
plt.colorbar()
# Main loop
from datetime import datetime
t0 = datetime.now()
for tstep in xrange(1, tmax+1):
fdtd.update_e()
src.update(tstep)
def runTest(self):
axis, nx, ny, nz, mpi_type = self.args
fields = Fields(nx, ny, nz, mpi_type=mpi_type)
core = Core(fields)
pbc = Pbc(fields, axis)
# allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
fields.set_ehs(*ehs)
# update
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
# verify
getf0, getf1 = {}, {}
strfs_e = {'x':['ey', 'ez'], 'y':['ex', 'ez'], 'z':['ex', 'ey']}[axis]
strfs_h = {'x':['hy', 'hz'], 'y':['hx', 'hz'], 'z':['hx', 'hy']}[axis]
pt0 = (0, 0, 0)
pt1 = { 'x': (0, ny-2, nz-2), \
'y': (nx-2, 0, nz-2), \
'z': (nx-2, ny-2, 0) }[axis]
getf0['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (nx-1, 0, 0), \
'y': (0, ny-1, 0), \
'z': (0, 0, nz-1) }[axis]
pt1 = { 'x': (nx-1, ny-2, nz-2), \
'y': (nx-2, ny-1, nz-2), \
'z': (nx-2, ny-2, nz-1) }[axis]
getf1['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (0, 1, 1), \
'y': (1, 0, 1), \
'z': (1, 1, 0) }[axis]
pt1 = { 'x': (0, ny-1, nz-1), \
'y': (nx-1, 0, nz-1), \
'z': (nx-1, ny-1, 0) }[axis]
getf0['h'] = GetFields(fields, strfs_h, pt0, pt1)
pt0 = { 'x': (nx-1, 1, 1), \
'y': (1, ny-1, 1), \
'z': (1, 1, nz-1) }[axis]
pt1 = (nx-1, ny-1, nz-1)
getf1['h'] = GetFields(fields, strfs_h, pt0, pt1)
for getf in getf0.values() + getf1.values():
getf.get_event().wait()
for eh in ['e', 'h']:
g0 = getf0[eh].get_fields()
g1 = getf1[eh].get_fields()
norm = np.linalg.norm(g0 - g1)
'''
print eh
print g0
print g1
'''
self.assertEqual(norm, 0, '%g, %s, %s' % (norm, self.args, eh))
def runTest(self):
ufunc, nx, ny, nz, coeff_use, precision_float, use_cpu_core, split, tmax = self.args
fields = Fields(nx, ny, nz, coeff_use, precision_float, use_cpu_core)
core = Core(fields)
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
slice_xyz = [slice(None, None), slice(None, None), fields.slice_z]
# allocations
ns = fields.ns
dtype = fields.dtype
ehs = common_update.generate_random_ehs(nx, ny, nz, dtype, ufunc)
fields.set_ehs(*ehs)
ces, chs = common_update.generate_random_cs(coeff_use, nx, ny, nz, dtype)
if 'e' in coeff_use:
fields.set_ces(*ces)
if 'h' in coeff_use:
fields.set_chs(*chs)
# update
if ufunc == 'e':
for tstep in xrange(0, tmax):
fields.update_e()
common_update.update_e(ehs, ces)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[:3]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(norm, 0, '%s, %s, %g, %g' % (self.args, strf, norm, max_diff) )
if fields.pad != 0:
if strf == 'ez':
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad:])
else:
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad-1:])
self.assertEqual(norm2, 0, '%s, %s, %g, padding' % (self.args, strf, norm2) )
elif ufunc == 'h':
for tstep in xrange(0, tmax):
fields.update_h()
common_update.update_h(ehs, chs)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[3:]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(norm, 0, '%s, %s, %g, %g' % \
(self.args, strf, norm, max_diff) )
if fields.pad != 0:
if strf == 'hz':
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad:])
else:
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad:])
self.assertEqual(norm2, 0, '%s, %s, %g, padding' % (self.args, strf, norm2) )
tmax = 150
tfunc = lambda tstep: np.sin(0.05 * tstep)
# plot
import matplotlib.pyplot as plt
import matplotlib as mpl
mpl.rc('image', interpolation='nearest', origin='lower')
plt.ion()
fig = plt.figure(figsize=(14,8))
# z-axis
nx, ny, nz = 180, 160, 2
fields = Fields(nx, ny, nz)
Core(fields)
Pbc(fields, 'xyz')
IncidentDirect(fields, 'ey', (20, 0, 0), (20, ny-1, nz-1), tfunc)
IncidentDirect(fields, 'ex', (0, 20, 0), (nx-1, 20, nz-1), tfunc)
for tstep in xrange(1, tmax+1):
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
ax1 = fig.add_subplot(2, 3, 1)
ax1.imshow(fields.get('ey')[:,:,nz/2].T, vmin=-1.1, vmax=1.1)
ax1.set_title('%s, ey[20,:,:]' % repr(fields.ns))
ax1.set_xlabel('x')
ax1.set_ylabel('y')
#!/usr/bin/env python
import sys
sys.path.append('/home/kifang')
from kemp.fdtd3d.common_cpu import QueueTask, LockQueueTask
from kemp.fdtd3d.cpu import Fields, DirectSrc, GetFields
import numpy as np
nx, ny, nz = 240, 320, 320
tmax, tgap = 200, 1
qtask = QueueTask()
fdtd = Fields(nx, ny, nz, coeff_use='', use_cpu_core=0)
src = DirectSrc(fdtd, 'ez', (nx / 5 * 4, ny / 2, 0),
(nx / 5 * 4, ny / 2, nz - 1),
lambda tstep: np.sin(0.1 * tstep))
output = GetFields(fdtd, 'ez', (0, 0, nz / 2), (nx - 1, ny - 1, nz / 2))
# Plot
import matplotlib.pyplot as plt
plt.ion()
imag = plt.imshow(fdtd.ez[:, :, nz / 2].T,
cmap=plt.cm.hot,
origin='lower',
vmin=0,
vmax=0.05)
plt.colorbar()
# Main loop
