analyze/#8, analyzed optimal_binary_search_tree

Author: fridaagronberg

dynamic_programming/optimal_binary_search_tree.py

@@ -19,6 +19,14 @@
 import sys
 from random import randint
 
+flags = {
+    1: False,
+    2: False,
+    3: False,
+    4: False,
+    5: False,
+    6: False
+}
 
 class Node:
     """Binary Search Tree Node"""
@@ -118,13 +126,29 @@ def find_optimal_binary_search_tree(nodes):
             # Apply Knuth's optimization
             # Loop without optimization: for r in range(i, j + 1):
             for r in range(root[i][j - 1], root[i + 1][j] + 1):  # r is a temporal root
-                left = dp[i][r - 1] if r != i else 0  # optimal cost for left subtree
-                right = dp[r + 1][j] if r != j else 0  # optimal cost for right subtree
+                # optimal cost for left subtree
+                if r != i: # ID: 1
+                    flags[1] = True
+                    left = dp[i][r - 1] 
+                else: # ID: 2
+                    flags[2] = True
+                    left = 0  
+                # optimal cost for right subtree
+                if r != j: # ID: 3
+                    flags[3] = True
+                    right = dp[r + 1][j] 
+                else: # ID: 4
+                    flags[4] = True
+                    right = 0 
+
                 cost = left + total[i][j] + right
 
-                if dp[i][j] > cost:
+                if dp[i][j] > cost: # ID: 5
+                    flags[5] = True
                     dp[i][j] = cost
                     root[i][j] = r
+                else: # ID: 6
+                    flags[6] = True
 
     print("Binary search tree nodes:")
     for node in nodes:
@@ -141,4 +165,7 @@ def main():
 
 
 if __name__ == "__main__":
-    main()
+    import doctest
+    doctest.testmod()
+
+    print(flags)