def __init__(self, path):
super(LocalConnectivityH5, self).__init__(path)
self.surface = Reference(LocalConnectivity.surface, self)
# this multidataset accessor works but something is off about it
# this would be clearer
# self.matrix, self.matrixindices, self.matrixindptr
self.matrix = SparseMatrix(LocalConnectivity.matrix, self)
# equation is an inlined reference
# should this be a special equation scalar field?
# or this?
# this is clear about the structure, but obviously breaks the default store/load
# self.equation_equation = Scalar(Equation.equation, self)
# self.equation_parameters = Scalar(Equation.parameters, self)
self.equation = Scalar(Attr(str), self, name='equation')
self.cutoff = Scalar(LocalConnectivity.cutoff, self)
class LocalConnectivityH5(H5File):
def __init__(self, path):
super(LocalConnectivityH5, self).__init__(path)
self.surface = Reference(LocalConnectivity.surface, self)
self.matrix = SparseMatrix(LocalConnectivity.matrix, self)
self.equation = Scalar(Attr(str), self, name='equation')
self.cutoff = Scalar(LocalConnectivity.cutoff, self)
def store(self, datatype, scalars_only=False, store_references=True):
# type: (LocalConnectivity, bool, bool) -> None
super(LocalConnectivityH5, self).store(datatype, scalars_only,
store_references)
# equations are such a special case that we will have to implement custom load store
self.equation.store(datatype.equation.to_json(datatype.equation))
def load_into(self, datatype):
# type: (LocalConnectivity) -> None
super(LocalConnectivityH5, self).load_into(datatype)
eq = self.equation.load()
eq = datatype.equation.from_json(eq)
datatype.equation = eq
def get_min_max_values(self):
metadata = self.matrix.get_metadata()
return metadata.min, metadata.max
class LocalConnectivityH5(H5File):
def __init__(self, path):
super(LocalConnectivityH5, self).__init__(path)
self.surface = Reference(LocalConnectivity.surface, self)
# this multidataset accessor works but something is off about it
# this would be clearer
# self.matrix, self.matrixindices, self.matrixindptr
self.matrix = SparseMatrix(LocalConnectivity.matrix, self)
# equation is an inlined reference
# should this be a special equation scalar field?
# or this?
# this is clear about the structure, but obviously breaks the default store/load
# self.equation_equation = Scalar(Equation.equation, self)
# self.equation_parameters = Scalar(Equation.parameters, self)
self.equation = Scalar(Attr(str), self, name='equation')
self.cutoff = Scalar(LocalConnectivity.cutoff, self)
# equations are such a special case that we will have to implement custom load store
def store(self, datatype, scalars_only=False):
self.surface.store(datatype.surface)
self.matrix.store(datatype.matrix)
self.cutoff.store(datatype.cutoff)
self.equation.store(datatype.equation.to_json(datatype.equation))
def load_into(self, datatype):
datatype.gid = self.gid.load()
datatype.matrix = self.matrix.load()
datatype.cutoff = self.cutoff.load()
eq = self.equation.load()
eq = datatype.equation.from_json(eq)
datatype.equation = eq
def get_min_max_values(self):
metadata = self.matrix.get_metadata()
return metadata.min, metadata.max
class LocalConnectivityH5(H5File):
def __init__(self, path):
super(LocalConnectivityH5, self).__init__(path)
self.surface = Reference(LocalConnectivity.surface, self)
self.matrix = SparseMatrix(LocalConnectivity.matrix, self)
self.equation = EquationScalar(LocalConnectivity.equation, self)
self.cutoff = Scalar(LocalConnectivity.cutoff, self)
def store(self, datatype, scalars_only=False, store_references=True):
# type: (LocalConnectivity, bool, bool) -> None
super(LocalConnectivityH5, self).store(datatype, scalars_only, store_references)
def load_into(self, datatype):
# type: (LocalConnectivity) -> None
super(LocalConnectivityH5, self).load_into(datatype)
def get_min_max_values(self):
metadata = self.matrix.get_metadata()
return metadata.min, metadata.max
def _generate_accessors(self, view_model_fields):
for attr_name in view_model_fields:
attr = getattr(self.view_model, attr_name)
if not issubclass(type(attr), Attr):
raise ValueError('expected a Attr, got a {}'.format(
type(attr)))
if isinstance(attr, DataTypeGidAttr):
ref = Uuid(attr, self)
elif isinstance(attr, NArray):
ref = DataSet(attr, self)
elif isinstance(attr, List):
if issubclass(attr.element_type, HasTraits):
ref = ReferenceList(attr, self)
else:
ref = Json(attr, self)
elif issubclass(type(attr), Attr):
if attr.field_type is scipy.sparse.spmatrix:
ref = SparseMatrix(attr, self)
elif attr.field_type is numpy.random.RandomState:
continue
elif attr.field_type is uuid.UUID:
ref = Uuid(attr, self)
elif issubclass(attr.field_type, (Equation, EquationsEnum)):
ref = EquationScalar(attr, self)
elif attr.field_type is Range:
ref = JsonRange(attr, self)
elif isinstance(attr, Final):
if attr.field_type == dict:
ref = JsonFinal(attr, self)
elif attr.field_type == list:
ref = Json(attr, self)
else:
ref = Scalar(attr, self)
elif issubclass(attr.field_type, (HasTraits, TupleEnum)):
ref = Reference(attr, self)
elif issubclass(attr.field_type, TVBEnum):
ref = Enum(attr, self)
else:
ref = Scalar(attr, self)
else:
ref = Accessor(attr, self)
setattr(self, attr.field_name, ref)
def __init__(self, path):
super(LocalConnectivityH5, self).__init__(path)
self.surface = Reference(LocalConnectivity.surface, self)
self.matrix = SparseMatrix(LocalConnectivity.matrix, self)
self.equation = EquationScalar(LocalConnectivity.equation, self)
self.cutoff = Scalar(LocalConnectivity.cutoff, self)