def __init__(self):
super(DataStore, self).__init__()
self.data_objects = OrderedDict()
# create the default theoretical dataset
q = np.linspace(0.005, 0.5, 1000)
r = np.empty_like(q)
dataset = ReflectDataset()
dataset.data = (q, r)
dataset.name = "theoretical"
air = SLD(0, name="fronting")
sio2 = SLD(3.47, name="1")
si = SLD(2.07, name="backing")
structure = air(0, 0) | sio2(15, 3.0) | si(0, 3.0)
structure[1].name = "slab"
structure[1].thick.name = "thick"
structure[1].rough.name = "rough"
structure[1].sld.real.name = "sld"
structure[1].sld.imag.name = "isld"
structure[1].vfsolv.name = "vfsolv"
model = ReflectModel(structure, name="theoretical")
self.add(dataset)
self["theoretical"].model = model
def __init__(self):
super(DataStore, self).__init__()
self.data_objects = OrderedDict()
# create the default theoretical dataset
q = np.linspace(0.005, 0.5, 1000)
r = np.empty_like(q)
dataset = ReflectDataset()
dataset.data = (q, r)
dataset.name = 'theoretical'
air = SLD(0, name='fronting')
sio2 = SLD(3.47, name='1')
si = SLD(2.07, name='backing')
structure = air(0, 0) | sio2(15, 3.) | si(0, 3.)
structure[1].name = 'slab'
structure[1].thick.name = 'thick'
structure[1].rough.name = 'rough'
structure[1].sld.real.name = 'sld'
structure[1].sld.imag.name = 'isld'
structure[1].vfsolv.name = 'vfsolv'
model = ReflectModel(structure, name='theoretical')
self.add(dataset)
self['theoretical'].model = model
def snapshot(self, snapshot_name):
original = self.datastore["theoretical"]
dataset = ReflectDataset()
dataset.data = (
original.dataset.x,
original.model.model(original.dataset.x, x_err=dataset.x_err),
)
dataset.name = snapshot_name
new_model = deepcopy(original.model)
new_model.name = snapshot_name
# if the snapshot already exists then overwrite it.
if snapshot_name in self.datastore.names:
row = self.data_object_row(snapshot_name)
self._rootnode.child(row).set_dataset(dataset)
self._rootnode.child(row).set_reflect_model(new_model)
data_object = self.data_object_node(snapshot_name).data_object
else:
# otherwise you have to add it.
data_object = DataObject(dataset)
data_object.model = new_model
self._rootnode.set_data_object(data_object)
return data_object
