Worked on three different recursive ways to calculate fibonacci and graph its time complexity.

fibonacci/Fibonacci.py

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+def fib(n):
+    if n == 0 or n == 1:
+        return n
+    return fib(n-1) + fib(n-2)
+
+
+def fibHelper(n, a, b):
+    if n == 0:
+        return a
+    elif n == 1:
+        return b
+    return fibHelper(n-1, b, a+b)
+
+
+def fibIterative(n):
+    return fibHelper(n, 0, 1)
+
+
+def multiply(a,b):
+    product = [0,0,0]
+    product[0] = a[0]*b[0] + a[1]*b[1]
+    product[1] = a[0]*b[1] + a[1]*b[2]
+    product[2] = a[1]*b[1] + a[2]*b[2]
+    return product
+
+
+def power(l, k):
+    if k == 1:
+        return l
+    temp = power(l, k//2)
+    if k%2 == 0:
+        return multiply(temp, temp)
+    else:
+        return multiply(l, multiply(temp, temp))
+
+
+def fibPower(n):
+    l = [1,1,0]
+    return power(l, n)[1]
+
+
+"""
+Makes sure that other programs don't execute the main
+"""
+if __name__ == '__main__':
+    try:
+        print(fib(30))
+    except KeyboardInterrupt:
+        exit()

fibonacci/PlotTimeComplexity.py

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+import matplotlib.pyplot as plt
+import time
+from fibonacci import Fibonacci as fib
+
+
+def measureTime(n):
+
+    total = 0
+    for i in range(0, 200):
+        start_time = time.time()
+        fib.fibPower(n)
+        end_time = time.time()
+        total += end_time - start_time
+    return total/200
+
+
+def generateData():
+    time = []
+    input = []
+
+    for i in range(1, 2000, 20):
+        input.append(i)
+        time.append(measureTime(i))
+    return input, time
+
+
+data = generateData()
+plt.plot(data[0], data[1])
+plt.xlabel('Fibonacci Term')
+plt.ylabel('Seconds')
+
+plt.show()