Fast way to select n items (drawn from a Poisson distribution) for each element in array x

Question

I am having some trouble with solving a problem I encountered.

I have an array with prices:

>>> x = np.random.randint(10, size=10)
array([6,         


        

Answer 1

I don't really see how you could do that without looping at all. What you could do is create the result array prior to looping; that way you don't need to concatenate afterwards.

Result = np.empty( arrivals.sum(), dtype='i' )

and then change the values of that array blockwise:

Result_position = np.r_[ [0], arrivals.cumsum() ]
for i, xx in enumerate(x):
    Result[ Result_position[i]:Result_position[i+1] ] = xx