def __init__(self, E=None, value_dict=None, file=None):
"""
Initialize the BayesNet class.
Arguments
---------
*V* : a list of strings - vertices in topsort order
*E* : a dict, where key = vertex, val = list of its children
*F* : a dict,
where key = rv,
val = another dict with
keys =
'parents',
'values',
'cpt'
*V* : a dict
Notes
-----
"""
if file is not None:
import pyBN.io.read as ior
bn = ior.read_bn(file)
self.V = bn.V
self.E = bn.E
self.F = bn.F
else:
if E is not None:
#assert (value_dict is not None), 'Must set values if E is set.'
self.set_structure(E, value_dict)
else:
self.V = []
self.E = {}
self.F = {}
def __init__(self, E=None, value_dict=None, file=None):
"""
Initialize the BayesNet class.
Arguments
---------
*V* : a list of strings - vertices in topsort order
*E* : a dict, where key = vertex, val = list of its children
*F* : a dict,
where key = rv,
val = another dict with
keys =
'parents',
'values',
'cpt'
*V* : a dict
Notes
-----
"""
if file is not None:
import pyBN.io.read as ior
bn = ior.read_bn(file)
self.V = bn.V
self.E = bn.E
self.F = bn.F
else:
if E is not None:
#assert (value_dict is not None), 'Must set values if E is set.'
self.set_structure(E, value_dict)
else:
self.V = []
self.E = {}
self.F = {}