def __init__(self,
fields,
str_f,
pt0,
pt1,
tfunc,
spatial_value=1.,
is_overwrite=False):
"""
"""
common.check_type('fields', fields, Fields)
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(fields.ns, pt0))
pt1 = list(common.convert_indices(fields.ns, pt1))
# local variables
e_or_h = str_f[0]
dtype = fields.dtype
is_array = True if isinstance(spatial_value, np.ndarray) else False
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
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)
# create the SetFields instance
setf = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf = setf
self.spatial_value = spatial_value
self.e_or_h = e_or_h
self.tstep = 1
# append to the update list
self.priority_type = 'incident'
fields.append_instance(self)
def __init__(self, fields, str_f, pt0, pt1):
"""
"""
common.check_type('fields', fields, Fields)
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))
pt0 = list(common.convert_indices(fields.ns, pt0))
pt1 = list(common.convert_indices(fields.ns, pt1))
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE']
values = common_gpu.macro_replace_list(pt0, pt1) + \
['DTYPE *source', \
'target[sub_idx]', 'source[idx]', '='] + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cu').read(), macros, values)
program = SourceModule(ksrc)
kernel_copy = program.get_function('copy')
# allocation
source_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
host_array = np.zeros(shape, fields.dtype)
split_host_array = np.split(host_array, len(str_fs))
split_host_array_dict = dict(zip(str_fs, split_host_array))
target_buf = cuda.to_device(host_array)
# global variables
self.mainf = fields
self.kernel_copy = kernel_copy
self.source_bufs = source_bufs
self.target_buf = target_buf
self.host_array = host_array
self.split_host_array_dict = split_host_array_dict
def __init__(self, fields, str_f, pt0, pt1):
"""
"""
common.check_type('fields', fields, Fields)
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))
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE']
values = common_gpu.macro_replace_list(pt0, pt1) + \
['DTYPE *source', \
'target[sub_idx]', 'source[idx]', '='] + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cu').read(), macros, values)
program = SourceModule(ksrc)
kernel_copy = program.get_function('copy')
# allocation
source_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
host_array = np.zeros(shape, fields.dtype)
split_host_array = np.split(host_array, len(str_fs))
split_host_array_dict = dict( zip(str_fs, split_host_array) )
target_buf = cuda.to_device(host_array)
# global variables
self.mainf = fields
self.kernel_copy = kernel_copy
self.source_bufs = source_bufs
self.target_buf = target_buf
self.host_array = host_array
self.split_host_array_dict = split_host_array_dict
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 __init__(self, fields, str_f, pt0, pt1, tfunc, spatial_value=1., is_overwrite=False):
"""
"""
common.check_type('fields', fields, Fields)
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(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
e_or_h = str_f[0]
dtype = fields.dtype
is_array = True if isinstance(spatial_value, np.ndarray) else False
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
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)
# create the SetFields instance
setf = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf = setf
self.spatial_value = spatial_value
self.e_or_h = e_or_h
self.tstep = 1
# append to the update list
self.priority_type = 'incident'
fields.append_instance(self)
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, fields, str_f, pt0, pt1):
"""
"""
common.check_type('fields', fields, Fields)
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))
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# allocation
shape = common.shape_two_points(pt0, pt1, len(str_fs))
host_array = np.zeros(shape, dtype=fields.dtype)
split_host_array = np.split(host_array, len(str_fs))
split_host_array_dict = dict( zip(str_fs, split_host_array) )
# global variables
self.mainf = fields
self.str_fs = str_fs
self.slice_xyz = common.slices_two_points(pt0, pt1)
self.host_array = host_array
self.split_host_array_dict = split_host_array_dict
def __init__(self, fields, str_f, pt0, pt1, is_array=False, is_overwrite=True):
"""
"""
common.check_type('fields', fields, Fields)
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('is_array', is_array, bool)
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# global variables and functions
self.mainf = fields
self.str_fs = str_fs
self.slice_xyz = common.slices_two_points(pt0, pt1)
self.shape = common.shape_two_points(pt0, pt1, len(str_fs))
self.is_overwrite = is_overwrite
if is_array:
self.func = self.set_fields_spatial_value
else:
self.func = self.set_fields_single_value
def __init__(self, fields, str_f, pt0, pt1, is_array=False, is_overwrite=True):
"""
"""
common.check_type('fields', fields, Fields)
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('is_array', is_array, bool)
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
overwrite_str = {True: '=', False: '+='}[is_overwrite]
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE']
if is_array:
values = common_gpu.macro_replace_list(pt0, pt1) + \
['DTYPE *source', \
'target[idx]', 'source[sub_idx]', overwrite_str] + \
dtype_str_list
else:
values = common_gpu.macro_replace_list(pt0, pt1) + \
['DTYPE source', \
'target[idx]', 'source', overwrite_str] + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cu').read(), macros, values)
program = SourceModule(ksrc)
kernel_copy = program.get_function('copy')
# allocation
target_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
if is_array:
tmp_array = np.zeros(shape, fields.dtype)
source_buf = cuda.to_device(tmp_array)
# global variabels and functions
self.mainf = fields
self.kernel_copy = kernel_copy
self.target_bufs = target_bufs
self.shape = shape
if is_array:
self.source_buf = source_buf
self.set_fields = self.set_fields_spatial_value
else:
self.set_fields = self.set_fields_single_value
def __init__(self,
fields,
str_f,
pt0,
pt1,
tfunc,
spatial_value=1.,
is_overwrite=False):
"""
"""
common.check_type('fields', fields, Fields)
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(fields.ns, pt0))
pt1 = list(common.convert_indices(fields.ns, pt1))
# local variables
e_or_h = str_f[0]
dtype = fields.dtype
is_buffer = True if isinstance(fields, BufferFields) else False
is_array = True if isinstance(spatial_value, np.ndarray) else False
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
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)
# create the SetFields instances
is_update_dict = {}
setf_dict = {}
svalue_dict = {}
if is_buffer:
for part in ['', 'pre', 'post']:
sl0 = common.slices_two_points(pt0, pt1)
sl1 = common_buffer.slice_dict[e_or_h][part]
overlap = common.overlap_two_slices(fields.ns, sl0, sl1)
if overlap == None:
setf_dict[part] = None
else:
opt0, opt1 = common.two_points_slices(fields.ns, overlap)
setf_dict[part] = SetFields(fields, str_f, opt0, opt1,
is_array, is_overwrite)
svalue_dict[part] = self.overlap_svalue(
pt0, pt1, opt0, opt1, spatial_value, is_array)
else:
setf_dict[''] = SetFields(fields, str_f, pt0, pt1, is_array,
is_overwrite)
svalue_dict[''] = spatial_value
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf_dict = setf_dict
self.svalue_dict = svalue_dict
self.e_or_h = e_or_h
self.tstep = 1
# append to the update list
self.priority_type = 'incident'
fields.append_instance(self)
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,
fields,
pt0,
pt1,
ep_inf,
drude_freq,
gamma,
mask_arrays=(1, 1, 1)):
common.check_type('fields', fields, Fields)
common.check_type('pt0', pt0, (list, tuple), (int, float))
common.check_type('pt1', pt1, (list, tuple), (int, float))
common.check_type('ep_inf', ep_inf, (int, float))
common.check_type('drude_freq', drude_freq, (int, float))
common.check_type('gamma', gamma, (int, float))
common.check_type('mask_arrays', mask_arrays, (list, tuple),
(np.ndarray, int))
# local variables
pt0 = common.convert_indices(fields.ns, pt0)
pt1 = common.convert_indices(fields.ns, pt1)
context = fields.context
queue = fields.queue
dtype = fields.dtype
shape = common.shape_two_points(pt0, pt1, is_dummy=True)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
for mask_array in mask_arrays:
if isinstance(mask_array, np.ndarray):
assert common.shape_two_points(pt0, pt1) == mask_array.shape, \
'shape mismatch : %s, %s' % (shape, mask_array.shape)
# allocations
psis = [np.zeros(shape, dtype) for i in range(3)]
psi_bufs = [
cl.Buffer(context, cl.mem_flags.READ_WRITE, psi.nbytes)
for psi in psis
]
for psi_buf, psi in zip(psi_bufs, psis):
cl.enqueue_copy(queue, psi_buf, psi)
dt = fields.dt
aa = (2 - gamma * dt) / (2 + gamma * dt)
bb = drude_freq**2 * dt / (2 + gamma * dt)
comm = 2 * ep_inf + bb * dt
ca = 2 * dt / comm
cb = -(aa + 3) * bb * dt / comm
cc = -(aa + 1) * dt / comm
cas = [ca * mask for mask in mask_arrays]
shape = common.shape_two_points(pt0, pt1, is_dummy=True)
f = np.zeros(shape, dtype)
psi_bufs = [
cl.Buffer(context, cl.mem_flags.READ_WRITE, f.nbytes)
for i in range(3)
]
for psi_buf in psi_bufs:
cl.enqueue_copy(queue, psi_buf, f)
cf = np.ones(shape, dtype)
mask_bufs = [
cl.Buffer(context, cl.mem_flags.READ_ONLY, cf.nbytes)
for i in range(3)
]
for mask_buf, mask in zip(mask_bufs, mask_arrays):
cl.enqueue_copy(queue, mask_buf, cf * mask)
# modify ce arrays
slices = common.slices_two_points(pt0, pt1)
for ce, ca in zip(fields.get_ces(), cas):
ce[slices] = ca * mask + ce[slices] * mask.__invert__()
# program
nmax_str, xid_str, yid_str, zid_str = common_gpu.macro_replace_list(
pt0, pt1)
macros = ['NMAX', 'XID', 'YID', 'ZID', 'DX', 'DTYPE', 'PRAGMA_fp64']
values = [nmax_str, xid_str, yid_str, zid_str,
str(fields.ls)] + fields.dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'drude.cl').read(), macros, values)
program = cl.Program(fields.context, ksrc).build()
# arguments
pca = aa
pcb = (aa + 1) * bb
args = fields.ns + [dtype(cb), dtype(cc), dtype(pca), dtype(pcb)] \
+ fields.eh_bufs[:3] + psi_bufs + mask_bufs
# global variables
self.mainf = fields
self.program = program
self.args = args
nx, ny, nz = fields.ns
nmax = int(nmax_str)
remainder = nmax % fields.ls
self.gs = nmax if remainder == 0 else nmax - remainder + fields.ls
# append to the update list
self.priority_type = 'material'
fields.append_instance(self)
def __init__(self, fields, str_f, pt0, pt1, is_array=False, is_overwrite=True):
"""
"""
common.check_type('fields', fields, Fields)
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('is_array', is_array, bool)
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
overwrite_str = {True: '=', False: '+='}[is_overwrite]
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE', 'PRAGMA_fp64']
nmax_str, xid_str, yid_str, zid_str = common_gpu.macro_replace_list(pt0, pt1)
if is_array:
values = [nmax_str, xid_str, yid_str, zid_str, \
'__global DTYPE *source', \
'target[idx]', 'source[sub_idx]', overwrite_str] + \
dtype_str_list
else:
values = [nmax_str, xid_str, yid_str, zid_str, \
'DTYPE source', \
'target[idx]', 'source', overwrite_str] + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cl').read(), macros, values)
program = cl.Program(fields.context, ksrc).build()
# allocation
target_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
if is_array:
tmp_array = np.zeros(shape, dtype=fields.dtype)
source_buf = cl.Buffer( \
fields.context, \
cl.mem_flags.READ_WRITE | cl.mem_flags.COPY_HOST_PTR, \
hostbuf=tmp_array)
# global variabels and functions
self.mainf = fields
self.program = program
self.target_bufs = target_bufs
self.shape = shape
nmax = int(nmax_str)
remainder = nmax % fields.ls
self.gs = nmax if remainder == 0 else nmax - remainder + fields.ls
if is_array:
self.source_buf = source_buf
self.set_fields = self.set_fields_spatial_value
else:
self.set_fields = self.set_fields_single_value
def __init__(self, fields, str_f, pt0, pt1, is_array=False, is_overwrite=True):
"""
"""
common.check_type('fields', fields, Fields)
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('is_array', is_array, bool)
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
overwrite_str = {True: '=', False: '+='}[is_overwrite]
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE', 'PRAGMA_fp64']
nmax_str, xid_str, yid_str, zid_str = common_gpu.macro_replace_list(pt0, pt1)
if is_array:
values = [nmax_str, xid_str, yid_str, zid_str, \
'__global DTYPE *source', \
'target[idx]', 'source[sub_idx]', overwrite_str] + \
dtype_str_list
else:
values = [nmax_str, xid_str, yid_str, zid_str, \
'DTYPE source', \
'target[idx]', 'source', overwrite_str] + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cl').read(), macros, values)
program = cl.Program(fields.context, ksrc).build()
# allocation
target_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
if is_array:
tmp_array = np.zeros(shape, dtype=fields.dtype)
source_buf = cl.Buffer( \
fields.context, \
cl.mem_flags.READ_WRITE | cl.mem_flags.COPY_HOST_PTR, \
hostbuf=tmp_array)
# global variabels and functions
self.mainf = fields
self.program = program
self.target_bufs = target_bufs
self.shape = shape
nmax = int(nmax_str)
remainder = nmax % fields.ls
self.gs = nmax if remainder == 0 else nmax - remainder + fields.ls
if is_array:
self.source_buf = source_buf
self.set_fields = self.set_fields_spatial_value
else:
self.set_fields = self.set_fields_single_value
def __init__(self,
fields,
pt0,
pt1,
ep_inf,
drude_freq,
gamma,
mask_arrays=(1, 1, 1)):
common.check_type('fields', fields, Fields)
common.check_type('pt0', pt0, (list, tuple), (int, float))
common.check_type('pt1', pt1, (list, tuple), (int, float))
common.check_type('ep_inf', ep_inf, (int, float))
common.check_type('drude_freq', drude_freq, (int, float))
common.check_type('gamma', gamma, (int, float))
common.check_type('mask_arrays', mask_arrays, (list, tuple),
(np.ndarray, types.IntType))
# local variables
pt0 = common.convert_indices(fields.ns, pt0)
pt1 = common.convert_indices(fields.ns, pt1)
dtype = fields.dtype
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
for mask_array in mask_arrays:
if isinstance(mask_array, np.ndarray):
assert common.shape_two_points(pt0, pt1) == mask_array.shape, \
'shape mismatch : %s, %s' % (shape, mask_array.shape)
# allocations
shape = common.shape_two_points(pt0, pt1, is_dummy=True)
psis = [np.zeros(shape, dtype) for i in range(3)]
dt = fields.dt
aa = (2 - gamma * dt) / (2 + gamma * dt)
bb = drude_freq**2 * dt / (2 + gamma * dt)
comm = 2 * ep_inf + bb * dt
ca = 2 * dt / comm
cb = -(aa + 3) * bb * dt / comm
cc = -(aa + 1) * dt / comm
cas = [ca * mask for mask in mask_arrays]
cbs = [cb * mask for mask in mask_arrays]
ccs = [cc * mask for mask in mask_arrays]
# modify ce arrays
slices = common.slices_two_points(pt0, pt1)
for ce, ca in zip(fields.get_ces(), cas):
ce[slices] = ca
# global variables
self.mainf = fields
self.psis = psis
self.cbs = cbs
self.ccs = ccs
self.pcs = aa, (aa + 1) * bb
self.slices = slices
# append to the update list
self.priority_type = 'material'
fields.append_instance(self)
def __init__(self,
fields,
str_f,
pt0,
pt1,
is_array=False,
is_overwrite=True):
"""
"""
common.check_type('fields', fields, Fields)
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('is_array', is_array, bool)
common.check_type('is_overwrite', is_overwrite, bool)
pt0 = list(common.convert_indices(fields.ns, pt0))
pt1 = list(common.convert_indices(fields.ns, pt1))
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
overwrite_str = {True: '=', False: '+='}[is_overwrite]
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE']
if is_array:
values = common_gpu.macro_replace_list(pt0, pt1) + \
['DTYPE *source', \
'target[idx]', 'source[sub_idx]', overwrite_str] + \
dtype_str_list
else:
values = common_gpu.macro_replace_list(pt0, pt1) + \
['DTYPE source', \
'target[idx]', 'source', overwrite_str] + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cu').read(), macros, values)
program = SourceModule(ksrc)
kernel_copy = program.get_function('copy')
# allocation
target_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
if is_array:
tmp_array = np.zeros(shape, fields.dtype)
source_buf = cuda.to_device(tmp_array)
# global variabels and functions
self.mainf = fields
self.kernel_copy = kernel_copy
self.target_bufs = target_bufs
self.shape = shape
if is_array:
self.source_buf = source_buf
self.set_fields = self.set_fields_spatial_value
else:
self.set_fields = self.set_fields_single_value
def __init__(self, fields, str_f, pt0, pt1, process=''):
"""
"""
common.check_type('fields', fields, Fields)
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('process', process, str)
pt0 = list( common.convert_indices(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
str_fs = common.convert_to_tuple(str_f)
dtype_str_list = fields.dtype_str_list
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# program
macros = ['NMAX', 'XID', 'YID', 'ZID', \
'ARGS', \
'TARGET', 'SOURCE', 'OVERWRITE', \
'DTYPE', 'PRAGMA_fp64']
nmax_str, xid_str, yid_str, zid_str = common_gpu.macro_replace_list(pt0, pt1)
if process == '':
process_str_list = ['target[sub_idx]', 'source[idx]', '=']
elif process == 'square_sum':
process_str_list = ['target[sub_idx]', 'pown(source[idx], 2)', '+=']
values = [nmax_str, xid_str, yid_str, zid_str, \
'__global DTYPE *source'] + \
process_str_list + \
dtype_str_list
ksrc = common.replace_template_code( \
open(common_gpu.src_path + 'copy.cl').read(), macros, values)
program = cl.Program(fields.context, ksrc).build()
# allocation
source_bufs = [fields.get_buf(str_f) for str_f in str_fs]
shape = common.shape_two_points(pt0, pt1, len(str_fs))
host_array = np.zeros(shape, dtype=fields.dtype)
split_host_array = np.split(host_array, len(str_fs))
split_host_array_dict = dict( zip(str_fs, split_host_array) )
target_buf = cl.Buffer( \
fields.context, \
cl.mem_flags.READ_WRITE | cl.mem_flags.COPY_HOST_PTR, \
hostbuf=host_array)
# global variables
self.mainf = fields
self.program = program
self.source_bufs = source_bufs
self.target_buf = target_buf
self.host_array = host_array
self.split_host_array_dict = split_host_array_dict
nmax = int(nmax_str)
remainder = nmax % fields.ls
self.gs = nmax if remainder == 0 else nmax - remainder + fields.ls
def __init__(self, fields, str_f, pt0, pt1, tfunc, spatial_value=1., is_overwrite=False):
"""
"""
common.check_type('fields', fields, Fields)
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(fields.ns, pt0) )
pt1 = list( common.convert_indices(fields.ns, pt1) )
# local variables
e_or_h = str_f[0]
dtype = fields.dtype
is_buffer = True if isinstance(fields, BufferFields) else False
is_array = True if isinstance(spatial_value, np.ndarray) else False
for axis, n, p0, p1 in zip(['x', 'y', 'z'], fields.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
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)
# create the SetFields instances
is_update_dict = {}
setf_dict = {}
svalue_dict = {}
if is_buffer:
for part in ['', 'pre', 'post']:
sl0 = common.slices_two_points(pt0, pt1)
sl1 = common_buffer.slice_dict[e_or_h][part]
overlap = common.overlap_two_slices(fields.ns, sl0, sl1)
if overlap == None:
setf_dict[part] = None
else:
opt0, opt1 = common.two_points_slices(fields.ns, overlap)
setf_dict[part] = SetFields(fields, str_f, opt0, opt1, is_array, is_overwrite)
svalue_dict[part] = self.overlap_svalue(pt0, pt1, opt0, opt1, spatial_value, is_array)
else:
setf_dict[''] = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
svalue_dict[''] = spatial_value
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf_dict = setf_dict
self.svalue_dict = svalue_dict
self.e_or_h = e_or_h
self.tstep = 1
# append to the update list
self.priority_type = 'incident'
fields.append_instance(self)
def __init__(self, node_fields, str_f, pt0, pt1, process=''):
"""
"""
common.check_type('node_fields', node_fields, Fields)
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))
pt0 = list(common.convert_indices(node_fields.ns, pt0))
pt1 = list(common.convert_indices(node_fields.ns, pt1))
# local variables
nodef = node_fields
str_fs = common.convert_to_tuple(str_f)
mainf_list = nodef.mainf_list
anx = nodef.accum_nx_list
for strf in str_fs:
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
common.check_value('str_f', strf, strf_list)
for axis, n, p0, p1 in zip(['x', 'y', 'z'], nodef.ns, pt0, pt1):
common.check_value('pt0 %s' % axis, p0, range(n))
common.check_value('pt1 %s' % axis, p1, range(n))
# allocation
shape = common.shape_two_points(pt0, pt1, len(str_fs))
dummied_shape = common.shape_two_points(pt0, pt1, is_dummy=True)
host_array = np.zeros(shape, dtype=nodef.dtype)
split_host_array = np.split(host_array, len(str_fs))
split_host_array_dict = dict(zip(str_fs, split_host_array))
device_type_list = [f.device_type for f in nodef.updatef_list]
if 'gpu' in device_type_list:
from kemp.fdtd3d import gpu
getclass = getattr(gpu, 'GetFields')
if 'cpu' in device_type_list:
from kemp.fdtd3d import cpu
getclass = getattr(cpu, 'GetFields')
getf_list = []
slices_list = []
for i, mainf in enumerate(mainf_list):
nx0 = anx[i]
nx1 = anx[i + 1] - 1 if i < len(mainf_list) - 1 else anx[i + 1]
overlap = common.overlap_two_lines((nx0, nx1), (pt0[0], pt1[0]))
if overlap != None:
x0, y0, z0 = pt0
x1, y1, z1 = pt1
slice_pt0 = (overlap[0] - x0, 0, 0)
slice_pt1 = (overlap[1] - x0, y1 - y0, z1 - z0)
slices = []
for j, p0, p1 in zip([0, 1, 2], slice_pt0, slice_pt1):
if dummied_shape[j] != 1:
slices.append(slice(p0, p1 + 1))
slices_list.append(slices if slices != [] else [slice(0, 1)])
local_pt0 = (overlap[0] - nx0, y0, z0)
local_pt1 = (overlap[1] - nx0, y1, z1)
getf_list.append(
getclass(mainf, str_fs, local_pt0, local_pt1, process))
# global variables
self.str_fs = str_fs
self.host_array = host_array
self.split_host_array_dict = split_host_array_dict
self.getf_list = getf_list
self.slices_list = slices_list
