Performance of temporary variables vs array element, which is faster, when?

Consider these examples using Python calling several functions returning a number, using an array element:

import numpy as np

my_array = np.zeros(looplength)

for j in range(0,looplength):

    temp = my_first_function(j)
    my_array[j] = temp
    a_1 = my_first_function(j,temp)
    a_2 = my_second_function(j,temp)
    a_3 = my_third_function(j,temp)
    ....
    a_N = my_Nth_function(j,temp)

vs

import numpy as np

my_array = np.zeros(looplength)

for j in range(0,looplength):

    my_array[j] = my_first_function(j)
    a_1 = my_first_function(j,my_array[j])
    a_2 = my_second_function(j,my_array[j])
    a_3 = my_third_function(j,my_array[j])
    ....
    a_N = my_Nth_function(j,my_array[j])

My question is: for performance, is it better to use a copy in a temporary variable or an access an array element directly, if this happens repeatedly? Also: how often does an array element need to be accessed for it to become faster to copy it?

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