def get_default_box(
sm: StructureModel,
node_states: Dict[str, list],
lv_name: str,
) -> Dict[str, Tuple[pd.DataFrame, pd.DataFrame]]:
"""
Get boxes with min = 0 and max = 1 for all parameters.
Args:
sm: model structure
node_states: node states
lv_name: name of latent variable
Returns:
Dictionary with a tuple of two elements: the first being the lower value constraint and the second
the maximum value constraint
"""
valid_node_set = set([lv_name] + list(sm.successors(lv_name)))
boxes = {}
for node in sm.nodes:
if node in valid_node_set:
cpd = EMSingleLatentVariable._initialise_node_cpd(node, node_states, sm)
min_vals, max_vals = cpd.copy(), cpd.copy()
min_vals.loc[:] = 0
max_vals.loc[:] = 1
boxes[node] = (min_vals, max_vals)
return boxes
def get_default_priors(
sm: StructureModel,
node_states: Dict[str, list],
lv_name: str,
) -> Dict[str, Tuple[pd.DataFrame, pd.DataFrame]]:
"""
The default dirichlet priors (zero values)
Args:
sm: model structure
node_states: node states
lv_name: name of latent variable
Returns:
Dictionary with pd dataframes initialized with zeros
"""
valid_node_set = set([lv_name] + list(sm.successors(lv_name)))
return {
node: EMSingleLatentVariable._initialise_node_cpd(node, node_states, sm)
for node in sm.nodes
if node in valid_node_set
}
