import time
from pprint import pprint

import numpy as np
import pandas as pd

from .model.DHU_2 import DHU_2
from ._opt.algorithm.sim_config import simulate_config as sim_opt_config
from ._opt.algorithm.main import main as main_opt
from ._opt.boundary.sim_config import simulate_config as sim_config_bound
from ._opt.boundary.main import main as main_bound
from ._opt.algorithm.model.model import SystemModel

def main(*args,config=None):
    
    args = [_.reset_index(drop=True) for _ in args]
    
    var_cur = {
        'coil_1_ToutA': args[0],
        'coil_1_HoutA': args[1],
        'HzP'         : args[2],
        'HzR'         : args[3],
        'coil_1_TinW' : args[4],
        'coil_2_TinW' : args[5],
        'coil_3_TinW' : args[6],
        'coil_1_Val'  : args[7],
        'coil_2_Val'  : args[8],
        'coil_3_Val'  : args[9],
        'wheel_1_TinR': args[10],
        'wheel_2_TinR': args[11],
        'mixed_1_TinM': args[12],
        'mixed_1_HinM': args[13],
        'mixed_2_TinM': args[14],
        'mixed_2_HinM': args[15],
    }
    var_cur      = {k:v.set_axis([k],axis=1) for k,v in var_cur.items()}
    var_opt_name = ['coil_2_Val','wheel_1_TinR','wheel_2_TinR']
    var_sys_name = [_ for _ in var_cur.keys() if _ not in var_opt_name]
    var_opt_cur  = {k:v for k,v in var_cur.items() if k in var_opt_name}
    var_sys_cur  = {k:v for k,v in var_cur.items() if k in var_sys_name}
    var_opt_var  = {
        'coil_2_Val': main_bound(
            None,None,None,
            var_opt_cur['coil_2_Val'],
            config = sim_config_bound(
                opt_var    = ['coil_2_Val'],
                syn_opt    = False,
                var_type   = True,
                lb_static  = 100,
                ub_static  = 100,
                var_precis = 1
            )
        ),
        'wheel_1_TinR': main_bound(
            None,None,None,
            var_opt_cur['wheel_1_TinR'],
            config = sim_config_bound(
                opt_var    = ['wheel_1_TinR'],
                syn_opt    = False,
                var_type   = True,
                lb_static  = 50,
                ub_static  = 120,
                var_precis = 1
            )
        ),
        'wheel_2_TinR': main_bound(
            None,None,None,
            var_opt_cur['wheel_2_TinR'],
            config = sim_config_bound(
                opt_var    = ['wheel_2_TinR'],
                syn_opt    = False,
                var_type   = True,
                lb_static  = 50,
                ub_static  = 120,
                var_precis = 1
            )
        ),
    }
    
    # 获取优化结果
    opt_config = sim_opt_config(
        target        = 'Fs',
        dir_min       = True,
        var_opt       = var_opt_name,
        var_sys       = var_sys_name,
        diag_model    = False,
        algorithm     = 'soea_DE_best_1_L_templet',
        NIND          = 5000,
        MAXGEN        = 200,
        constrains    = [
            'coil_3_DoutA-[coil_3_DoutA]<0',
            # 'steamcoil_1_Fs-220<0',
            # 'steamcoil_2_Fs-100<0',
            # '40-steamcoil_1_Fs<0',
            # '30-steamcoil_2_Fs<0',
        ],
        allow_neg_opt = False,
    )
    
    system = AirSystem()
    opt_output  = main_opt(
        *list(var_opt_var.values()),
        *list(var_sys_cur.values()),
        system_model = system,
        config       = opt_config
    )
    sys_output = system.predict(
        pd.concat([*opt_output[3:],*list(var_sys_cur.values())],axis=1),
    )
    
    show_data = None
    # show_data = get_show_data(opt_res=opt_output[2])
    # print(show_data)
    
    return [
        sys_output.loc[:,['coil_2_ToutA']],
        opt_output[3:][1],
        opt_output[3:][2],
        show_data
    ]


class AirSystem(SystemModel):
    def __init__(self):
        super().__init__()
        # self.model = DHU_2().load_from_platform()
        path = r'C:\Users\zhangshenhao\Documents\WorkSpace\zsh_project\004_溧阳宁德\除湿机模型\model.pkl'
        self.model = DHU_2().load(path)
    
    def predict(self,data:pd.DataFrame) -> pd.DataFrame:
        time_start   = time.time()
        self.PENALTY = {}
        self.index   = data.index
        sys_out      = self.model.predict_system(data)
        time_end     = time.time()
        past_time    = round(time_end-time_start,2)
        self.PAST_TIME.append(past_time)
        print(f'第{len(self.PAST_TIME)}次调用系统模型，本次调用时长为:{past_time}秒 \n')    
        return sys_out


def get_show_data(opt_res:pd.DataFrame) -> pd.DataFrame:
    var_names = {
        'coil_3_DoutA'        : '送风露点(℃)',
        'coil_2_Q'            : '中表冷冷量(kW)',
        'coil_3_Q'            : '后表冷冷量(kW)',
        'steamcoil_1_Q'       : '前再生热量(kW)',
        'steamcoil_2_Q'       : '后再生热量(kW)',
        'wheel_1_E_diff'      : '前转轮焓升(kJ/kg)',
        'wheel_2_E_diff'      : '后转轮焓升(kJ/kg)',
        'summary_cost_cooling': '耗冷费用折算(元/h)',
        'summary_cost_heating': '耗热费用折算(元/h)',
        'summary_cost_total'  : '冷热费用合计(元/h)',
    }
    res = (
        opt_res
        .loc[list(var_names.keys()),['Before','After']]
        .assign(指标=list(var_names.values()))
        .rename(columns={'Before':'优化前状态','After':'优化后状态'})
        .loc[:,['指标','优化前状态','优化后状态']]
    )
    return res