Time for action – avoiding loops with vectorize

The vectorize function is a yet another trick to reduce the number of loops in your programs. We will let it calculate the profit of a single trading day:

1. First, load the data:

   o, h, l, c = np.loadtxt('BHP.csv', delimiter=',', usecols=(3,4, 5, 6), unpack=True)

2. The vectorize function is the NumPy equivalent of the Python map function. Call the vectorize function, giving it as an argument the calc_profit function that we still have to write:

   func = np.vectorize(calc_profit)

3. We can now apply func as if it is a function. Apply the func result that we got, to the price arrays:

   profits = func(o, h, l, c)

4. The calc_profit function is pretty simple. First, we try to buy slightly below the open price. If this is outside of the daily range, then, obviously our attempt failed and no profit was made, or we incurred a loss, therefore, we will return 0. Otherwise, we sell at the close price and the profit is just the difference between the buy price and the close...