From 7053fefc6f9e43b1e252d1f551401a7a70b52e93 Mon Sep 17 00:00:00 2001
From: Cathy Yeh <cathy@driver.xyz>
Date: Wed, 13 Dec 2017 18:47:32 -0800
Subject: cleanup print statements, stale comments, minor TODOs

---
 beliefs/utils/math_helper.py      | 14 ++++++++++----
 beliefs/utils/random_variables.py | 17 +++++++++++------
 2 files changed, 21 insertions(+), 10 deletions(-)

(limited to 'beliefs/utils')

diff --git a/beliefs/utils/math_helper.py b/beliefs/utils/math_helper.py
index a25ea68..12325e1 100644
--- a/beliefs/utils/math_helper.py
+++ b/beliefs/utils/math_helper.py
@@ -1,10 +1,16 @@
-"""Random math utils."""
+"""Math utils"""
 
 
 def is_kronecker_delta(vector):
-    """Returns True if vector is a kronecker delta vector, False otherwise.
-    Specific evidence ('YES' or 'NO') is a kronecker delta vector, whereas
-    virtual evidence ('MAYBE') is not.
+    """
+    Check if vector is a kronecker delta.
+
+    Args:
+        vector: iterable of numbers
+    Returns:
+        bool, True if vector is a kronecker delta vector, False otherwise.
+        In belief propagation, specific evidence (variable is directly observed)
+        is a kronecker delta vector, but virtual evidence is not.
     """
     count = 0
     for x in vector:
diff --git a/beliefs/utils/random_variables.py b/beliefs/utils/random_variables.py
index 1a0b0f7..cad07aa 100644
--- a/beliefs/utils/random_variables.py
+++ b/beliefs/utils/random_variables.py
@@ -1,3 +1,4 @@
+"""Utilities for working with models and random variables."""
 
 
 def get_reachable_observed_variables_for_inferred_variables(model, observed=set()):
@@ -6,12 +7,16 @@ def get_reachable_observed_variables_for_inferred_variables(model, observed=set(
     ("reachable observed variables") that influenced the beliefs of variables inferred
     to be in a definite state.
 
-    INPUT
-      model: instance of BayesianModel class or subclass
-      observed: set of labels (strings) corresponding to vars pinned to definite
-        state during inference.
-    RETURNS
-      dict, of form key - source label (a string), value - a list of strings
+    Args
+        model: instance of BayesianModel class or subclass
+        observed: set,
+            set of labels (strings) corresponding to variables pinned to a definite
+            state during inference.
+    Returns
+        dict,
+            key, value pairs {source_label_id: reachable_observed_vars}, where
+            source_label_id is an int or string, and reachable_observed_vars is a list
+            of label_ids
     """
     if not observed:
         return {}
-- 
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