blob: 8de47b36e1e62a1eef4094444efed17bb1e15fbf (
plain) (
blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
|
import numpy as np
class TabularCPD:
"""
Defines the conditional probability table for a discrete variable
whose parents are also discrete.
TODO: have this inherit from DiscreteFactor
"""
def __init__(self, variable, variable_card,
parents=[], parents_card=[], values=[]):
"""
Args:
variable: int or string
variable_card: int
parents: optional, list of int and/or strings
parents_card: optional, list of int
values: optional, 2d list or array
"""
self.variable = variable
self.parents = parents
self.variables = [variable] + parents
self.cardinality = [variable_card] + parents_card
if values:
self.values = np.array(values)
def get_values(self):
"""
Returns the tabular cpd form of the values.
"""
if len(self.cardinality) == 1:
return self.values.reshape(1, np.prod(self.cardinality))
else:
return self.values.reshape(self.cardinality[0], np.prod(self.cardinality[1:]))
|
