Dani Sanchez - Paper

graphs/possible_bipartition.py

@@ -1,12 +1,49 @@
 # Can be used for BFS
-from collections import deque 
+from collections import deque
+
 
 def possible_bipartition(dislikes):
     """ Will return True or False if the given graph
         can be bipartitioned without neighboring nodes put
         into the same partition.
-        Time Complexity: ?
-        Space Complexity: ?
+        Time Complexity: O(n log n)
+        Space Complexity: O(n)
     """
-    pass
+    n = len(dislikes)
+    if n < 3:
+        return True
+
+    # creates an array of length n, will keep track of nodes visited
+    visited = [False] * (n)
+
+    # initializes a queue and two sets to hold two groups of puppies
+    q = deque()
+    q.append(1)
+    visited[0] = True
+    red = set()
+    blue = set()
+    red.add(1)
+
+    #creates a dictionary to hold puppies and their enemies 
+    dislike_dict = {}
+    for i in range(0, n):
+        dislike_dict[i] = dislikes[i]
 
+    # loops through queue of nodes. 
+    while len(q) > 0:
+        pointerKey = q.popleft()
+        # appends node to queue if it has not been visited. 
+        # returns False if node is in other set already.
+        for node in dislike_dict[pointerKey]:
+            if visited[pointerKey] == False:
+                q.append(node)
+                if pointerKey not in red:
+                    red.add(node)
+                    if node in blue:
+                        return False
+                else:
+                    blue.add(node)
+                    if node in red:
+                        return False
+        visited[pointerKey] = True
+    return True