# 用于提供对外接口
from base_optimizer.optimizer_scanbased import *
from base_optimizer.optimizer_celldivision import *
from base_optimizer.optimizer_hybridgenetic import *
from base_optimizer.optimizer_feederpriority import *
from base_optimizer.optimizer_aggregation import *
from base_optimizer.optimizer_twophase import *
from base_optimizer.optimizer_mathmodel import *

from base_optimizer.result_analysis import *


def base_optimizer(machine_index, pcb_data, component_data, feeder_data=None, method='', hinter=False):

    if method == 'cell-division':  # 基于元胞分裂的遗传算法
        component_result, cycle_result, feeder_slot_result = optimizer_celldivision(pcb_data, component_data)
        placement_result, head_sequence = greedy_placement_route_generation(component_data, pcb_data, component_result,
                                                                            cycle_result, feeder_slot_result)
    elif method == 'feeder-scan':  # 基于基座扫描的供料器优先算法
        component_result, cycle_result, feeder_slot_result = feeder_priority_assignment(component_data, pcb_data)
        placement_result, head_sequence = greedy_placement_route_generation(component_data, pcb_data, component_result,
                                                                            cycle_result, feeder_slot_result)
        # placement_result, head_sequence = beam_search_for_route_generation(component_data, pcb_data, component_result,
        #                                                                    cycle_result, feeder_slot_result)

    elif method == 'hybrid-genetic':  # 基于拾取组的混合遗传算法
        component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_hybrid_genetic(
            pcb_data, component_data, hinter=False)

    elif method == 'aggregation':  # 基于batch-level的整数规划 + 启发式算法
        component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_aggregation(
            component_data, pcb_data)
    elif method == 'genetic-scanning':
        component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_genetic_scanning(
            component_data, pcb_data, hinter=False)
    elif method == 'mip-model':
        component_result, cycle_result, feeder_slot_result, placement_result, head_sequence = optimizer_mathmodel(
            component_data, pcb_data, hinter=True)
    elif method == "two-phase":
        component_result, feeder_slot_result, cycle_result = gurobi_optimizer(pcb_data, component_data, feeder_data,
                                                                              initial=True, partition=True,
                                                                              reduction=True, hinter=hinter)

        placement_result, head_sequence = scan_based_placement_route_generation(component_data, pcb_data,
                                                                                component_result, cycle_result)
    else:
        raise 'machine optimizer method ' + method + ' is not existed'

    # 估算贴装用时
    info = placement_info_evaluation(component_data, pcb_data, component_result, cycle_result, feeder_slot_result,
                                     placement_result, head_sequence, hinter=False)

    if hinter:
        optimization_assign_result(component_data, pcb_data, component_result, cycle_result, feeder_slot_result,
                                   nozzle_hinter=True, component_hinter=True, feeder_hinter=True)

        print('----- Placement machine ' + str(machine_index) + ' ----- ')
        print('-Cycle counter: {}'.format(info.cycle_counter))

        print(f'-Nozzle change counter: {info.nozzle_change_counter: d}')
        print(f'-ANC round: {info.anc_round_counter: d}')
        print(f'-Pick operation counter: {info.pickup_counter: d}')
        print(f'-Pick time: {info.pickup_time: .3f}, distance: {info.pickup_distance: .3f}')
        print(f'-Place time: {info.place_time: .3f}, distance: {info.place_distance: .3f}')
        print('------------------------------ ')

    return info