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/inference/belief_propagation.py | 44 +++++++++++++++++++--------------
 1 file changed, 25 insertions(+), 19 deletions(-)

(limited to 'beliefs/inference/belief_propagation.py')

diff --git a/beliefs/inference/belief_propagation.py b/beliefs/inference/belief_propagation.py
index 02f5595..7ec648d 100644
--- a/beliefs/inference/belief_propagation.py
+++ b/beliefs/inference/belief_propagation.py
@@ -1,11 +1,17 @@
 import numpy as np
 from collections import namedtuple
+import logging
 
-from beliefs.models.beliefupdate.Node import InvalidLambdaMsgToParent
-from beliefs.models.beliefupdate.BeliefUpdateNodeModel import BeliefUpdateNodeModel
+from beliefs.models.belief_update_node_model import (
+    InvalidLambdaMsgToParent,
+    BeliefUpdateNodeModel
+)
 from beliefs.utils.math_helper import is_kronecker_delta
 
 
+logger = logging.getLogger(__name__)
+
+
 MsgPassers = namedtuple('MsgPassers', ['msg_receiver', 'msg_sender'])
 
 
@@ -51,7 +57,7 @@ class BeliefPropagation:
             return
 
         node_to_update_label_id, msg_sender_label_id = nodes_to_update.pop()
-        print("Node", node_to_update_label_id)
+        logging.info("Node: %s", node_to_update_label_id)
 
         node = self.model.nodes_dict[node_to_update_label_id]
 
@@ -59,8 +65,8 @@ class BeliefPropagation:
         # outgoing msg from the node to update
         parent_ids = set(node.parents) - set([msg_sender_label_id])
         child_ids = set(node.children) - set([msg_sender_label_id])
-        print("parent_ids:", parent_ids)
-        print("child_ids:", child_ids)
+        logging.info("parent_ids: %s", str(parent_ids))
+        logging.info("child_ids: %s", str(child_ids))
 
         if msg_sender_label_id is not None:
             # update triggered by receiving a message, not pinning to evidence
@@ -68,9 +74,9 @@ class BeliefPropagation:
 
         if node_to_update_label_id not in evidence:
             node.compute_pi_agg()
-            print("belief propagation pi_agg", node.pi_agg)
+            logging.info("belief propagation pi_agg: %s", np.array2string(node.pi_agg))
             node.compute_lambda_agg()
-            print("belief propagation lambda_agg", node.lambda_agg)
+            logging.info("belief propagation lambda_agg: %s", np.array2string(node.lambda_agg))
 
         for parent_id in parent_ids:
             try:
@@ -114,13 +120,13 @@ class BeliefPropagation:
             for child in node.lambda_received_msgs.keys():
                 node.update_lambda_msg_from_child(child=child,
                                                   new_value=ones_vector)
-        print("Finished initializing Lambda(x) and lambda_received_msgs per node.")
+        logging.info("Finished initializing Lambda(x) and lambda_received_msgs per node.")
 
-        print("Start downward sweep from nodes.  Sending Pi messages only.")
+        logging.info("Start downward sweep from nodes.  Sending Pi messages only.")
         topdown_order = self.model.get_topologically_sorted_nodes(reverse=False)
 
         for node_id in topdown_order:
-            print('label in iteration through top-down order:', node_id)
+            logging.info('label in iteration through top-down order: %s', str(node_id))
 
             node_sending_msg = self.model.nodes_dict[node_id]
             child_ids = node_sending_msg.children
@@ -129,9 +135,9 @@ class BeliefPropagation:
                 node_sending_msg.compute_pi_agg()
 
             for child_id in child_ids:
-                print("child", child_id)
+                logging.info("child: %s", str(child_id))
                 new_pi_msg = node_sending_msg.compute_pi_msg_to_child(child_k=child_id)
-                print(new_pi_msg)
+                logging.info("new_pi_msg: %s", np.array2string(new_pi_msg))
 
                 child_node = self.model.nodes_dict[child_id]
                 child_node.update_pi_msg_from_parent(parent=node_id,
@@ -158,10 +164,9 @@ class BeliefPropagation:
                 self.model.nodes_dict[evidence_id].lambda_agg = \
                     self.model.nodes_dict[evidence_id].lambda_agg * observed_value
 
-            nodes_to_update.add(MsgPassers(msg_receiver=evidence_id,
-                                           msg_sender=None))
+            nodes_to_update = [MsgPassers(msg_receiver=evidence_id, msg_sender=None)]
 
-            self._belief_propagation(nodes_to_update=nodes_to_update,
+            self._belief_propagation(nodes_to_update=set(nodes_to_update),
                                      evidence=evidence)
 
     def query(self, evidence={}):
@@ -179,12 +184,13 @@ class BeliefPropagation:
 
         Example
         -------
-        >> from label_graph_service.pgm.inference.belief_propagation import BeliefPropagation
-        >> from label_graph_service.pgm.models.BernoulliOrModel import BernoulliOrModel
+        >> import numpy as np
+        >> from beliefs.inference.belief_propagation import BeliefPropagation
+        >> from beliefs.models.belief_update_node_model import BeliefUpdateNodeModel, BernoulliOrNode
         >> edges = [('1', '3'), ('2', '3'), ('3', '5')]
-        >> model = BernoulliOrModel(edges)
+        >> model = BeliefUpdateNodeModel.init_from_edges(edges, BernoulliOrNode)
         >> infer = BeliefPropagation(model)
-        >> result = infer.query({'2': np.array([0, 1])})
+        >> result = infer.query(evidence={'2': np.array([0, 1])})
         """
         if not self.model.all_nodes_are_fully_initialized:
             self.initialize_model()
-- 
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