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)
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
self.svalue = 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, 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)
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
self.svalue = 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,
tfunc,
spatial_value=1.,
is_overwrite=False):
"""
"""
common.check_type('fields', fields, (Fields, BufferFields))
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
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)
class IncidentDirect:
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)
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
self.svalue = 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 overlap_svalue(self, pt0, pt1, opt0, opt1, spatial_value, is_array):
if is_array:
dummied_shape = common.shape_two_points(pt0, pt1, is_dummy=True)
overlap_shape = common.shape_two_points(opt0, opt1)
shift_slices = [slice(op0-p0, op1-p0+1) \
for op0, op1, p0 in zip(opt0, opt1, pt0)]
reshaped_svalue = spatial_value.reshape(dummied_shape)
dummied_svalue = reshaped_svalue[shift_slices]
svalue = dummied_svalue.reshape(overlap_shape)
else:
svalue = spatial_value
return svalue
def update(self):
self.setf.set_fields(self.mainf.dtype( self.tfunc(self.tstep) ) * self.svalue)
self.tstep += 1
def update_e(self):
if self.e_or_h == 'e': self.update()
def update_h(self):
if self.e_or_h == 'h': self.update()
class IncidentDirect:
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)
# global variables
self.mainf = fields
self.tfunc = tfunc
self.setf = SetFields(fields, str_f, pt0, pt1, is_array, is_overwrite)
self.svalue = 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 overlap_svalue(self, pt0, pt1, opt0, opt1, spatial_value, is_array):
if is_array:
dummied_shape = common.shape_two_points(pt0, pt1, is_dummy=True)
overlap_shape = common.shape_two_points(opt0, opt1)
shift_slices = [slice(op0-p0, op1-p0+1) \
for op0, op1, p0 in zip(opt0, opt1, pt0)]
reshaped_svalue = spatial_value.reshape(dummied_shape)
dummied_svalue = reshaped_svalue[shift_slices]
svalue = dummied_svalue.reshape(overlap_shape)
else:
svalue = spatial_value
return svalue
def update(self):
self.setf.set_fields(
self.mainf.dtype(self.tfunc(self.tstep)) * self.svalue)
self.tstep += 1
def update_e(self):
if self.e_or_h == 'e': self.update()
def update_h(self):
if self.e_or_h == 'h': self.update()