def __init__(self, model):
self.model = model.copy()
init_np_func = np.ones
self.factors_adj_to_ = {
var: self.model.get_adj_factors(var)
for var in self.model.variables
}
self.messages = dict()
for fac in model.factors:
for var in fac.variables:
self.messages[(fac, var)] = Factor.initialize_with_(
default_message_name(), [var], init_np_func,
model.get_cardinality_for_(var))
self.messages[(fac, var)].normalize()
for fac in model.factors:
for var in fac.variables:
self.messages[(var, fac)] = Factor.initialize_with_(
default_message_name(), [var], init_np_func,
model.get_cardinality_for_(var))
self.messages[(var, fac)].normalize()
def __init__(self, model, **kwargs):
self.model = model.copy()
mean_field_init_method = kwargs.get('mean_field_init_method')
if mean_field_init_method == 'random':
init_np_func = np.ones
elif mean_field_init_method == 'uniform':
init_np_func = np.random.random
else:
init_np_func = np.ones
self.mean_fields = {}
for var in self.model.variables:
self.mean_fields[var] = Factor.initialize_with_(default_message_name(),
[var], init_np_func,
model.get_cardinality_for_(var))
self.mean_fields[var].normalize()
