def __init__(self,
states_df,
score_type,
max_num_mtries,
ess=1.0,
verbose=False,
vtx_to_states=None):
"""
Constructor
Parameters
----------
states_df : pandas.core.frame.DataFrame
score_type : str
max_num_mtries : int
ess : float
Equivalent Sample Size, a parameter in BDEU scorer. Fudge factor
that is supposed to grow as the amount of prior knowledge grows.
verbose : bool
vtx_to_states : dict[str, list[str]]
A dictionary mapping each node name to a list of its state names.
This information will be stored in self.bnet. If
vtx_to_states=None, constructor will learn vtx_to_states
from states_df
Returns
-------
None
"""
NetStrucLner.__init__(self, False, states_df, vtx_to_states)
self.max_num_mtries = max_num_mtries
self.score_type = score_type
self.verbose = verbose
self.vertices = states_df.columns
self.vtx_to_parents = {vtx: [] for vtx in self.vertices}
# get vtx_to_states info from self.bnet
vtx_to_states1 = {nd.name: nd.state_names for nd in self.bnet.nodes}
self.scorer = NetStrucScorer(self.states_df, self.vtx_to_parents,
vtx_to_states1, score_type, ess)
self.nx_graph = nx.DiGraph()
self.climb()
