Weird list error?

def plotIV(coordinate=None, sample_size=100, set_region=(0,999,0,999), showPosition=False, inset=False, figsize=(30,30), savepng=False, dpi=None, savepdf=False, annotations=False, data_processing=1, return_only=False):

    start = time.time()
    # voltages
    voltages =      [-1000, -500, -200, -100, 0, 100, 200, 500, 600]
    # scans (ordered by voltages)
    scans_ordered = [ 189,  188,  185,   183,181,182, 186, 187, 190]

    # convert list to array
    voltages, scans_ordered = np.array(voltages), np.array(scans_ordered)

    current_array_list = []
    current_mean = []

    # plot either with or without negative values and select if the solar cell channel should be selected for the current
    options_dic = {
        1: (False, False, "Lock in R , ohne Negativwerte"),
        2: (False, True, "Lock in R, mit Negativwerten"),
        3: (True, False, "solar cell channel, ohne Negativwerte"),
        4: (True, True, "solar cell channel, mit Negativwerten")
        }
    if not return_only:
        print(options_dic[data_processing][2])
    A = 2     # plot only from scan_ordered[A] to ...
    B = -2    # ...            scan_ordered[B]
    counter = 0
    for scan in scans_ordered[A:B]:
        positions = load_h5(scan, "positions")
        y_axis_h5 = positions["/data/encoder_fast/data"]
        z_axis_h5 = positions["/data/encoder_slow/data"]
        y_axis = np.array(y_axis_h5)
        z_axis = np.array(z_axis_h5)
        current = counts2amps(scan,solar_cell_channel_only=options_dic[data_processing][0], negative=options_dic[data_processing][1])

        y_grid, z_grid, current_array = supergrid(y_axis,z_axis,current,1000)

        if scan != 181:
            warp_matrix = ImageRegistrationDic[scan]
            current_array = cv2.warpAffine(current_array, warp_matrix, (1000, 1000), flags = cv2.INTER_LINEAR + cv2.WARP_INVERSE_MAP, borderValue = float("NaN")).astype(np.float32)

        current_array_list.append(current_array)
        current_mean.append(np.nanmean(current_array))

        print(current_mean[counter])
        print(f"Mean current for scan {scan} is {current_mean[counter]} nA. Its min/max current is {np.nanmin(current_array)}/{np.nanmax(current_array)} nA.")
        counter += 1

    pixelplotting_array = np.stack(current_array_list)

    if return_only:
        return current_array_list, pixelplotting_array