## This was all for testing, should be removed once the app is tested
# This stuff assigns each letter as a target
N_target = np.repeat(Constants.N_stream, 6, axis=0)
random.shuffle(N_target)
my_count = -1
N_range = list(range(Constants.N,len(N_target)))
N_range_tracker = []
for NN in Constants.N_stream:
    my_count = my_count+1
    # choose random trial to have the target
    temp_idx = random.choice(N_range)
    # make sure that I don't overwrite any random target indices
    while (temp_idx in N_range_tracker) or (temp_idx-Constants.N in N_range_tracker):
        temp_idx = random.choice(N_range)
    else: N_range_tracker.extend([temp_idx, (temp_idx - Constants.N)])

    N_target[[temp_idx, (temp_idx-Constants.N)]] = NN
    print(NN)



# Because the above loop randomly assigns letters wherever no target is indexed, some duplicates may randomly occur.
# This loops counts how many duplicates I have and collects their indices in N_targets
my_count = -1
one_timer = pd.DataFrame(columns = ['Letter', 'row'])
indx_count = -1
for NN in N_target:
    my_count = my_count + 1
    # runs through each row up until end - Nth row
    if my_count < (len(N_target)-Constants.N):
        if N_target[my_count] == NN and N_target[my_count+Constants.N] == NN:
            indx_count = indx_count+1
            one_timer.loc[indx_count] = [NN, my_count]


# This loop removes all duplicates so that I have exactly one target per letter
for NN in Constants.N_stream:
    tar_idx = one_timer[one_timer['Letter'] == NN]["row"]
    for ii in range(0, len(tar_idx)-1):
        idx_to_change = int(one_timer.loc[tar_idx.index[ii], 'row'])
        while N_target[idx_to_change] == N_target[idx_to_change + Constants.N] or N_target[idx_to_change] == N_target[idx_to_change - Constants.N]:
            N_target[idx_to_change] = random.choice(Constants.N_stream)