Max in a sliding window in NumPy array

Question

I want to create an array which holds all the max()es of a window moving through a given numpy array. I\'m sorry if this sounds confusing. I\'ll give an examp

Answer 1

If you have two dimension data, for example stock price and want to get rolling max or whatever, this will works. Caculating without using iteration.

n = 5  # size of rolling window

data_expanded = np.expand_dims(data, 1)
data_shift = [np.roll(data_expanded, shift=-i, axis=2) for i in range(n)]
data_shift = np.concatenate(data_shift, axis=1)

data_max = np.max(data_shift, axis=1)  # max, mean, std...