From 8dc7ae89677fca16ee974a30cff8c4df53c955ce Mon Sep 17 00:00:00 2001
From: Cathy Yeh <cathy@driver.xyz>
Date: Sun, 3 Dec 2017 19:16:32 -0800
Subject: PR comments

---
 beliefs/factors/cpd.py | 45 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 45 insertions(+)
 create mode 100644 beliefs/factors/cpd.py

(limited to 'beliefs/factors/cpd.py')

diff --git a/beliefs/factors/cpd.py b/beliefs/factors/cpd.py
new file mode 100644
index 0000000..a286aaa
--- /dev/null
+++ b/beliefs/factors/cpd.py
@@ -0,0 +1,45 @@
+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 implementing explicit factor methods
+    """
+    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
+        self._values = np.array(values)
+
+    @property
+    def values(self):
+        return self._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:]))
+
+    def copy(self):
+        return self.__class__(self.variable,
+                              self.cardinality[0],
+                              self.parents,
+                              self.cardinality[1:],
+                              self._values)
-- 
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