import numpy


def find_closest_cell(cell_capacities, target_capacity):
    closest = min(cell_capacities, key=lambda x: x-target_capacity)
    cell_capacities.remove(closest)
    return closest


def split_cells(cell_capacities, series_count):
    # get use the average cell capacity and the number of cells in series/parallel to get a target capacity
    average_cell_capacity = numpy.mean(cell_capacities)
    std_dev = numpy.std(cell_capacities)
    cells_in_parallel = int(len(cell_capacities)/series_count)
    target_bank_capacity = average_cell_capacity * cells_in_parallel
    print(f'Average Capacity: {average_cell_capacity}\n'
          f'Standard Deviation: {std_dev}\n'
          f'Target Bank Capacity: {target_bank_capacity}\n')

    # create a list of the banks
    battery_banks = []
    # sort the cells
    cell_capacities.sort(reverse=True)
    for bank_num in range(0, series_count):
        # Add the highest capacity cells to different banks
        battery_banks.append([cell_capacities.pop(bank_num)])

    # search for cells with the closest value to get to the average of the cell banks
    # subtract 1 since 1 cell has already been added
    for call_num in range(0, cells_in_parallel - 1):
        for bank in battery_banks:
            # get the target average (add one, since we are adding a cell)
            current_target_bank_capacity = average_cell_capacity * (len(bank) + 1)
            # get the current capacity
            current_bank_capacity = sum(bank)
            target_cell_capacity = current_target_bank_capacity - current_bank_capacity
            # find the closest cell and add it to the bank
            bank.append(find_closest_cell(cell_capacities, target_cell_capacity))

    return battery_banks


if __name__ == '__main__':
    battery_caps = []
    with open('C:\\Users\\Chris\\Documents\\Projects\\Telescope\\Batteries capacities.txt') as battery_list:
        battery_caps = [int(capacity) for capacity in battery_list.read().splitlines()]

    battery_bank_cells = split_cells(battery_caps, 4)
    bank_caps = [sum(b) for b in battery_bank_cells]
    mean_bank_capacity = numpy.mean(bank_caps)
    std_bank_deviation = numpy.std(bank_caps)
    print(f'Battery Bank Capacities: {bank_caps}\n'
          f'\n'
          f'Mean bank Capacity:  {mean_bank_capacity}\n'
          f'Standard Deviation:  {std_bank_deviation}\n'
          f'Percentage Variance: {100*std_bank_deviation/mean_bank_capacity:.4f}%\n'
          f'\n')
    for i in range(0, len(battery_bank_cells)):
        print(f'-----------------------------------------------------------------------------------\n'
              f'Bank {i +1}:')
        for c in battery_bank_cells[i]:
            print(f'   {c}')