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Author: heineman

1.5 Big O SideBar/README.txt

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+Module 1.5 Big O SideBar
+
+This module contains a few functions used to demonstrate the basic timed
+performance of sort and add. It also has some small code to demonstrate O(n^2)
+behavior
+
+

1.5 Big O SideBar/performance.py

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+from time import time
+import random
+
+def performance_sum():
+    """Evaluate performance of sum"""
+        
+    scores = {}
+    trial = 1
+    while trial <= 20:
+        numbers = [random.randint(1,9) for i in range(2**trial)]
+        now = time()
+        sum = 0
+        for d in numbers:
+            sum = sum + d
+        done = time()
+
+        scores[trial] = (done-now)
+        trial += 1
+
+    for i in scores:
+        print 2**i, '\t', scores[i]
+        
+def performance_sort():
+    """Evaluate performance of sorting"""
+
+    scores = {}
+
+    trial = 1
+
+    while trial <= 16:
+        numbers = [random.randint(1,2**trial) for i in range(2**trial)]
+        now = time()
+        numbers.sort()
+        done = time()
+        
+        scores[trial] = (done-now)
+        trial += 1
+
+    for i in scores:
+        print 2**i, '\t', scores[i]
+
+def hasDuplicates(X):
+    """Determine whether X contains a duplicate value"""
+    for i in range(len(X)-1):
+        for j in range(i+1,len(X)):
+            if X[i] == X[j]:
+                return True
+    return False
+
+def hasDuplicateOrNone(X):
+    """Determine whether X contains None or a duplicate value"""
+    for i in range(len(X)):
+        if X[i] == None:
+            return True
+    for i in range(len(X)-1):
+        for j in range(i+1,len(X)):
+            if X[i] == X[j]:
+                return True
+    return False
+