def set_savefields(self, str_f, pt0, pt1, tstep_range, dir_path, tag=0):
common.check_type('str_f', str_f, (str, list, tuple), str)
common.check_type('pt0', pt0, (list, tuple), (int, float))
common.check_type('pt1', pt1, (list, tuple), (int, float))
common.check_type('tstep_range', tstep_range, (list, tuple), int)
common.check_type('dir_path', dir_path, str)
common.check_type('tag', tag, int)
pt0 = common.convert_indices(self.ns, pt0)
pt1 = common.convert_indices(self.ns, pt1)
t0 = common.convert_index(self.max_tstep, tstep_range[0])
t1 = common.convert_index(self.max_tstep, tstep_range[1]) + 1
tgap = tstep_range[2]
tmax = self.max_tstep
tag = tag if tag not in self.savef_tag_list else max(self.savef_tag_list)+1
self.savef_tag_list.append(tag)
if is_mpi:
overlap = common.overlap_two_regions(self.node_pt0, self.node_pt1, pt0, pt1)
if overlap != None:
sx0, sy0, sz0 = self.node_pt0
ox0, oy0, oz0 = overlap[0]
ox1, oy1, oz1 = overlap[1]
local_pt0 = (ox0-sx0, oy0-sy0, oz0-sz0)
local_pt1 = (ox1-sx0, oy1-sy0, oz1-sz0)
savef = node.SaveFields(self.nodef, str_f, local_pt0, local_pt1, dir_path, tag, tmax, True, rank)
self.savef_list.append(savef)
else:
savef = node.SaveFields(self.nodef, str_f, pt0, pt1, dir_path, tag, tmax)
self.savef_list.append(savef)
# save the subdomain informations as pickle
if self.is_master:
if is_mpi:
divide_info_dict = common_mpi.divide_info_dict(size, self.mpi_shape, pt0, pt1, self.asn_dict)
else:
divide_info_dict = { \
'shape': common.shape_two_points(pt0, pt1), \
'pt0': pt0, \
'pt1': pt1, \
'anx_list': self.nodef.accum_nx_list }
divide_info_dict['str_fs'] = common.convert_to_tuple(str_f)
divide_info_dict['tmax'] = tmax
divide_info_dict['tgap'] = tgap
pkl_file = open(dir_path + 'divide_info.pkl', 'wb')
pickle.dump(divide_info_dict, pkl_file)
pkl_file.close()
self.t0 = t0
self.t1 = t1
self.tgap = tgap
def set_incident_direct(self,
str_f,
pt0,
pt1,
tfunc,
spatial_value=1.,
is_overwrite=False):
common.check_value('str_f', str_f,
('ex', 'ey', 'ez', 'hx', 'hy', 'hz'))
common.check_type('pt0', pt0, (list, tuple), (int, float))
common.check_type('pt1', pt1, (list, tuple), (int, float))
common.check_type('tfunc', tfunc, types.FunctionType)
common.check_type('spatial_value', spatial_value, \
(np.ndarray, np.number, types.FloatType, types.IntType) )
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list(common.convert_indices(self.ns, pt0))
pt1 = list(common.convert_indices(self.ns, pt1))
if is_mpi:
node_pt0 = list(self.node_pt0)
node_pt1 = list(self.node_pt1)
for i, axis in enumerate(['x', 'y', 'z']):
if self.nodef.buffer_dict.has_key('%s+' % axis):
node_pt1[i] += 1
if self.nodef.buffer_dict.has_key('%s-' % axis):
node_pt0[i] -= 1
if coord[i] == 0 and pt0[i] == 0:
pt0[i] -= 1
if coord[i] == self.mpi_shape[i] - 1 and pt1[
i] == self.ns[i] - 1:
pt1[i] += 1
overlap = common.overlap_two_regions(node_pt0, node_pt1, pt0, pt1)
if overlap != None:
sx0, sy0, sz0 = self.node_pt0
ox0, oy0, oz0 = overlap[0]
ox1, oy1, oz1 = overlap[1]
local_pt0 = (ox0 - sx0, oy0 - sy0, oz0 - sz0)
local_pt1 = (ox1 - sx0, oy1 - sy0, oz1 - sz0)
node.IncidentDirect(self.nodef, str_f, local_pt0, local_pt1,
tfunc, spatial_value, is_overwrite)
else:
node.IncidentDirect(self.nodef, str_f, pt0, pt1, tfunc,
spatial_value, is_overwrite)
def set_incident_direct(self, str_f, pt0, pt1, tfunc, spatial_value=1., is_overwrite=False):
common.check_value('str_f', str_f, ('ex', 'ey', 'ez', 'hx', 'hy', 'hz'))
common.check_type('pt0', pt0, (list, tuple), (int, float))
common.check_type('pt1', pt1, (list, tuple), (int, float))
common.check_type('tfunc', tfunc, types.FunctionType)
common.check_type('spatial_value', spatial_value, \
(np.ndarray, np.number, types.FloatType, types.IntType) )
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list( common.convert_indices(self.ns, pt0) )
pt1 = list( common.convert_indices(self.ns, pt1) )
if is_mpi:
node_pt0 = list(self.node_pt0)
node_pt1 = list(self.node_pt1)
for i, axis in enumerate(['x', 'y', 'z']):
if self.nodef.buffer_dict.has_key('%s+' % axis):
node_pt1[i] += 1
if self.nodef.buffer_dict.has_key('%s-' % axis):
node_pt0[i] -= 1
if coord[i] == 0 and pt0[i] == 0:
pt0[i] -= 1
if coord[i] == self.mpi_shape[i]-1 and pt1[i] == self.ns[i]-1:
pt1[i] += 1
overlap = common.overlap_two_regions(node_pt0, node_pt1, pt0, pt1)
if overlap != None:
sx0, sy0, sz0 = self.node_pt0
ox0, oy0, oz0 = overlap[0]
ox1, oy1, oz1 = overlap[1]
local_pt0 = (ox0-sx0, oy0-sy0, oz0-sz0)
local_pt1 = (ox1-sx0, oy1-sy0, oz1-sz0)
node.IncidentDirect(self.nodef, str_f, local_pt0, local_pt1, tfunc, spatial_value, is_overwrite)
else:
node.IncidentDirect(self.nodef, str_f, pt0, pt1, tfunc, spatial_value, is_overwrite)
def __init__(self,
node_fields,
str_f,
pt0,
pt1,
tfunc,
spatial_value=1.,
is_overwrite=False):
"""
"""
common.check_type('node_fields', node_fields, Fields)
common.check_value('str_f', str_f,
('ex', 'ey', 'ez', 'hx', 'hy', 'hz'))
common.check_type('pt0', pt0, (list, tuple), int)
common.check_type('pt1', pt1, (list, tuple), int)
common.check_type('tfunc', tfunc, types.FunctionType)
common.check_type('spatial_value', spatial_value, \
(np.ndarray, np.number, types.FloatType, types.IntType) )
common.check_type('is_overwrite', is_overwrite, bool)
# local variables
nodef = node_fields
dtype = nodef.dtype
is_array = True if isinstance(spatial_value, np.ndarray) else False
mainf_list = nodef.mainf_list
buffer_dict = nodef.buffer_dict
anx = nodef.accum_nx_list
nx, ny, nz = nodef.ns
for axis, n, p0, p1 in zip(['x', 'y', 'z'], nodef.ns, pt0, pt1):
start, end = 0, n
if buffer_dict.has_key(axis + '+'):
end = n + 1
if buffer_dict.has_key(axis + '-'):
start = -1
common.check_value('pt0 %s' % axis, p0, range(start, end))
common.check_value('pt1 %s' % axis, p1, range(start, end))
if is_array:
shape = common.shape_two_points(pt0, pt1)
assert shape == spatial_value.shape, \
'shape mismatch : %s, %s' % (shape, spatial_value.shape)
assert dtype == spatial_value.dtype, \
'dtype mismatch : %s, %s' % (dtype, spatial_value.dtype)
else:
spatial_value = dtype(spatial_value)
# global valriables
self.str_f = str_f
self.pt0 = pt0
self.pt1 = pt1
self.tfunc = tfunc
self.spatial_value = spatial_value
self.is_overwrite = is_overwrite
self.is_array = is_array
self.cpu = cpu
if 'gpu' in [f.device_type for f in nodef.updatef_list]:
from kemp.fdtd3d import gpu
self.gpu = gpu
# create IncidentDirect instance
for i, mainf in enumerate(mainf_list):
fields_pt0 = (anx[i], 0, 0)
fields_pt1 = (anx[i + 1] - 1, ny - 1, nz - 1)
overlap = common.overlap_two_regions(fields_pt0, fields_pt1, pt0,
pt1)
if overlap != None:
self.create_instance(mainf, fields_pt0, fields_pt1, overlap[0],
overlap[1])
# for buffer
for direction, buffer in buffer_dict.items():
fields_pt0 = { \
'x+': (anx[-1]-1, 0, 0), \
'y+': (0, ny-2, 0), \
'z+': (0, 0, nz-2), \
'x-': (-1, 0, 0), \
'y-': (0, -1, 0), \
'z-': (0, 0, -1) }[direction]
fields_pt1 = { \
'x+': (anx[-1]+1, ny-1, nz-1), \
'y+': (nx-1, ny, nz-1), \
'z+': (nx-1, ny-1, nz), \
'x-': (1, ny-1, nz-1), \
'y-': (nx-1, 1, nz-1), \
'z-': (nx-1, ny-1, 1) }[direction]
overlap = common.overlap_two_regions(fields_pt0, fields_pt1, pt0,
pt1)
if overlap != None:
self.create_instance(buffer, fields_pt0, fields_pt1,
overlap[0], overlap[1])
def set_savefields(self, str_f, pt0, pt1, tstep_range, dir_path, tag=0):
common.check_type('str_f', str_f, (str, list, tuple), str)
common.check_type('pt0', pt0, (list, tuple), (int, float))
common.check_type('pt1', pt1, (list, tuple), (int, float))
common.check_type('tstep_range', tstep_range, (list, tuple), int)
common.check_type('dir_path', dir_path, str)
common.check_type('tag', tag, int)
pt0 = common.convert_indices(self.ns, pt0)
pt1 = common.convert_indices(self.ns, pt1)
t0 = common.convert_index(self.max_tstep, tstep_range[0])
t1 = common.convert_index(self.max_tstep, tstep_range[1]) + 1
tgap = tstep_range[2]
tmax = self.max_tstep
tag = tag if tag not in self.savef_tag_list else max(
self.savef_tag_list) + 1
self.savef_tag_list.append(tag)
if is_mpi:
overlap = common.overlap_two_regions(self.node_pt0, self.node_pt1,
pt0, pt1)
if overlap != None:
sx0, sy0, sz0 = self.node_pt0
ox0, oy0, oz0 = overlap[0]
ox1, oy1, oz1 = overlap[1]
local_pt0 = (ox0 - sx0, oy0 - sy0, oz0 - sz0)
local_pt1 = (ox1 - sx0, oy1 - sy0, oz1 - sz0)
savef = node.SaveFields(self.nodef, str_f, local_pt0,
local_pt1, dir_path, tag, tmax, True,
rank)
self.savef_list.append(savef)
else:
savef = node.SaveFields(self.nodef, str_f, pt0, pt1, dir_path, tag,
tmax)
self.savef_list.append(savef)
# save the subdomain informations as pickle
if self.is_master:
if is_mpi:
divide_info_dict = common_mpi.divide_info_dict(
size, self.mpi_shape, pt0, pt1, self.asn_dict)
else:
divide_info_dict = { \
'shape': common.shape_two_points(pt0, pt1), \
'pt0': pt0, \
'pt1': pt1, \
'anx_list': self.nodef.accum_nx_list }
divide_info_dict['str_fs'] = common.convert_to_tuple(str_f)
divide_info_dict['tmax'] = tmax
divide_info_dict['tgap'] = tgap
pkl_file = open(dir_path + 'divide_info.pkl', 'wb')
pickle.dump(divide_info_dict, pkl_file)
pkl_file.close()
self.t0 = t0
self.t1 = t1
self.tgap = tgap
def __init__(self, node_fields, str_f, pt0, pt1, tfunc, spatial_value=1., is_overwrite=False):
"""
"""
common.check_type('node_fields', node_fields, Fields)
common.check_value('str_f', str_f, ('ex', 'ey', 'ez', 'hx', 'hy', 'hz'))
common.check_type('pt0', pt0, (list, tuple), int)
common.check_type('pt1', pt1, (list, tuple), int)
common.check_type('tfunc', tfunc, types.FunctionType)
common.check_type('spatial_value', spatial_value, \
(np.ndarray, np.number, types.FloatType, types.IntType) )
common.check_type('is_overwrite', is_overwrite, bool)
# local variables
nodef = node_fields
dtype = nodef.dtype
is_array = True if isinstance(spatial_value, np.ndarray) else False
mainf_list = nodef.mainf_list
buffer_dict = nodef.buffer_dict
anx = nodef.accum_nx_list
nx, ny, nz = nodef.ns
for axis, n, p0, p1 in zip(['x', 'y', 'z'], nodef.ns, pt0, pt1):
start, end = 0, n
if buffer_dict.has_key(axis+'+'):
end = n + 1
if buffer_dict.has_key(axis+'-'):
start = -1
common.check_value('pt0 %s' % axis, p0, range(start, end))
common.check_value('pt1 %s' % axis, p1, range(start, end))
if is_array:
shape = common.shape_two_points(pt0, pt1)
assert shape == spatial_value.shape, \
'shape mismatch : %s, %s' % (shape, spatial_value.shape)
assert dtype == spatial_value.dtype, \
'dtype mismatch : %s, %s' % (dtype, spatial_value.dtype)
else:
spatial_value = dtype(spatial_value)
# global valriables
self.str_f = str_f
self.pt0 = pt0
self.pt1 = pt1
self.tfunc= tfunc
self.spatial_value = spatial_value
self.is_overwrite = is_overwrite
self.is_array = is_array
self.cpu = cpu
if 'gpu' in [f.device_type for f in nodef.updatef_list]:
from kemp.fdtd3d import gpu
self.gpu = gpu
# create IncidentDirect instance
for i, mainf in enumerate(mainf_list):
fields_pt0 = (anx[i], 0, 0)
fields_pt1 = (anx[i+1]-1, ny-1, nz-1)
overlap = common.overlap_two_regions(fields_pt0, fields_pt1, pt0, pt1)
if overlap != None:
self.create_instance(mainf, fields_pt0, fields_pt1, overlap[0], overlap[1])
# for buffer
for direction, buffer in buffer_dict.items():
fields_pt0 = { \
'x+': (anx[-1]-1, 0, 0), \
'y+': (0, ny-2, 0), \
'z+': (0, 0, nz-2), \
'x-': (-1, 0, 0), \
'y-': (0, -1, 0), \
'z-': (0, 0, -1) }[direction]
fields_pt1 = { \
'x+': (anx[-1]+1, ny-1, nz-1), \
'y+': (nx-1, ny, nz-1), \
'z+': (nx-1, ny-1, nz), \
'x-': (1, ny-1, nz-1), \
'y-': (nx-1, 1, nz-1), \
'z-': (nx-1, ny-1, 1) }[direction]
overlap = common.overlap_two_regions(fields_pt0, fields_pt1, pt0, pt1)
if overlap != None:
self.create_instance(buffer, fields_pt0, fields_pt1, overlap[0], overlap[1])
