Exercise 1
# collect timing data into arrays/lists here
ns = np.linspace(1, 10000, 20, dtype=int)
ts = [timeit.timeit('f1(lst)',
                    setup='lst=list(range({}))'.format(n),
                    number=10, 
                    globals=globals()) 
      for n in ns]


# plot your data and bounding functions here
plt.plot(ns, ts, 'or');
plt.plot(ns, [0.0001 for n in ns], '-b')
plt.plot(ns, [0.00015 for n in ns], '-g');

CONSTANT


Exercise 2
# collect timing data into arrays/lists here
ns = np.linspace(1, 100, 20, dtype=int)
ts = [timeit.timeit('f2({})'.format(n), 
                    number=10, 
                    globals=globals()) 
      for n in ns]

# plot your data and bounding functions here
plt.plot(ns, ts, 'or');
plt.plot(ns, [0.00002*math.log(n) for n in ns], '-b')
plt.plot(ns, [0.00001*math.log(n) for n in ns], '-g');

LOGARITHMIC



Exercise 3
# collect timing data into arrays/lists here
ns = np.linspace(100, 1000, 20, dtype=int)
ts = [timeit.timeit('f3(l)',
                    setup='l = list(reversed(range({})))'.format(n),
                    number=10, 
                    globals=globals()) 
      for n in ns]

# plot your data and bounding functions here
plt.plot(ns, ts, 'or');
plt.plot(ns, [n*n*0.00000025 for n in ns], '-b')
plt.plot(ns, [n*n*0.00000015 for n in ns], '-g');

QUADRATIC



Exercise 4
# collect timing data into arrays/lists here
ns = np.linspace(2, 15, 20, dtype=int)
ts = [timeit.timeit('f4({})'.format(n),
                    number=5,
                    globals=globals())
      for n in ns]

# plot your data and bounding functions here
plt.plot(ns, ts, 'or');
plt.plot(ns, [0.000005*2**n for n in ns], '-b')
plt.plot(ns, [0.000001*2**n for n in ns], '-g');

2^N


Exercise 5
# collect timing data into arrays/lists here
ns = np.linspace(100, 1000, 20, dtype=int)
ts = [timeit.timeit('f5(l)',
                    setup='l = list(range({}))'.format(n),
                    number=5, 
                    globals=globals()) 
      for n in ns]


# plot your data and bounding functions here
plt.plot(ns, ts, 'or');
plt.plot(ns, [0.0009*n for n in ns], '-b')
plt.plot(ns, [0.0006*n for n in ns], '-g');

LINEAR