2 files changed, 50 insertions, 2 deletions
diff --git a/beliefs/factors/bernoulli_and_cpd.py b/beliefs/factors/bernoulli_and_cpd.py
new file mode 100644
index 0000000..fdb0c25
--- /dev/null
+++ b/beliefs/factors/bernoulli_and_cpd.py
@@ -0,0 +1,45 @@
+import numpy as np
+
+from beliefs.factors.cpd import TabularCPD
+
+
+class BernoulliAndCPD(TabularCPD):
+    """CPD class for a Bernoulli random variable whose relationship to its
+    parents (also Bernoulli random variables) is described by AND logic.
+
+    If all of the variable's parents are True, then the variable
+    is True, and False otherwise.
+    """
+    def __init__(self, variable, parents=[]):
+        """
+        Args:
+          variable: int or string
+          parents: optional, list of int and/or strings
+        """
+        super().__init__(variable=variable,
+                         variable_card=2,
+                         parents=parents,
+                         parents_card=[2]*len(parents),
+                         values=[])
+        self._values = None
+
+    @property
+    def values(self):
+        if self._values is None:
+            self._values = self._build_kwise_values_array(len(self.variables))
+            self._values = self._values.reshape(self.cardinality)
+        return self._values
+
+    @staticmethod
+    def _build_kwise_values_array(k):
+        # special case a completely independent factor, and
+        # return the uniform prior
+        if k == 1:
+            return np.array([0.5, 0.5])
+
+        # values are stored as a row vector using an ordering such that
+        # the right-most variables as defined in [variable].extend(parents)
+        # cycle through their values the fastest.
+        return np.array(
+            [1.]*(2**(k-1)-1) + [0.] + [0.,]*(2**(k-1)-1) + [1.]
+        )
diff --git a/beliefs/factors/bernoulli_or_cpd.py b/beliefs/factors/bernoulli_or_cpd.py
index bfb3a95..12ee2f6 100644
--- a/beliefs/factors/bernoulli_or_cpd.py
+++ b/beliefs/factors/bernoulli_or_cpd.py
@@ -21,11 +21,11 @@ class BernoulliOrCPD(TabularCPD):
                          parents=parents,
                          parents_card=[2]*len(parents),
                          values=[])
-        self._values = []
+        self._values = None
 
     @property
     def values(self):
-        if not any(self._values):
+        if self._values is None:
             self._values = self._build_kwise_values_array(len(self.variables))
             self._values = self._values.reshape(self.cardinality)
         return self._values
@@ -37,6 +37,9 @@ class BernoulliOrCPD(TabularCPD):
         if k == 1:
             return np.array([0.5, 0.5])
 
+        # values are stored as a row vector using an ordering such that
+        # the right-most variables as defined in [variable].extend(parents)
+        # cycle through their values the fastest.
         return np.array(
             [1.,] + [0.]*(2**(k-1)-1) + [0.,] + [1.]*(2**(k-1)-1)
         )