# -*- coding: utf-8 -*-
"""
Created on Mon May  2 22:44:55 2022

@author: Eidos
"""

import os
import sys
import time
# Add the top level directory in system path
top_path = os.path.dirname(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
if not top_path in sys.path:
    sys.path.append(top_path)
    
import numpy as np
import pandas as pd
import wave

import toolbox.info_detector_drone as idd
from toolbox.MFCC_extract import mfcc_extract
from toolbox.name_set import name_set_drone
from toolbox.name_set import drone_set
from toolbox import audio_processing as ap
from toolbox import pkl_gen_tool as pgt


# Declare the setting of MFCC
mfcc_setting = {}
mfcc_setting['num_filter'] = 201
mfcc_setting['num_cep'] = 201
mfcc_setting['winlen'] = 1
mfcc_setting['winstep'] = 1/2
mfcc_setting['fs'] = 44100
mfcc_setting['mfcc_d1_switch'] = True
mfcc_setting['mfcc_d2_switch'] = True
mfcc_setting['highfreq_limit'] = 8000
# All valid key
name_set_list = ['prefix','date','drone_No','state','distance','index','suffix']

dic_choose = dict([(k,[]) for k in name_set_list])
dic_aban = dict([(k,[]) for k in name_set_list])

# Decide which features will be extracted. This version only considers date.
dic_choose["date"] = [
                        '_20220304_', '_20220307_', '_20220312_', '_20220318_', '_20220319_',
                      
                       '_20220327_', '_20220328_', '_20220329_', '_20220330_', '_20220331_', 
                       '_20220401_', '_20220402_', '_20220403_', '_20220404_', '_20220405_']

# dic_choose["date"] = ['_20220304_', '_20220328_']
dic_choose["distance"] = ['_1m_','_5m_']
dic_choose['drone_No'] = ['_d1_','_d2_','_d3_','_d4_','_d5_','_d6_','_d7_','_d8_',
                          '_d9_','_d10_','_d11_','_d12_','_d13_','_d14_','_d15_','_d16_',
                          '_d17_','_d18_','_d19_','_d20_','_d21_','_d22_','_d23_','_d24_']

# Path to find stored data
originData_path = r'E:\1_Research\3_UAV_2\2_data\2_new_data'
# Path to save csv


drone_dic = dict([(k,0) for k in dic_choose['drone_No']])

if __name__ == '__main__':
    time_start = time.time()
    # Build the databse for iteration
    pkl_database = pd.DataFrame([])
    name_check = idd.FileNameProcessing(name_set_drone)
    pgt.dic_quick_check(dic_choose, dic_aban, name_check)
    
    # Save csv for each date
    for date in dic_choose["date"]:
        for distance in dic_choose['distance']:
            for drone in dic_choose['drone_No']:
                audio_data = []
                audio, audio_label = pgt.audio_select(originData_path, 
                                                  dic_choose, dic_aban, 
                                                  date, distance, drone, 
                                                  name_check)
                
                if not audio:
                    print('No drone available in this condition!')
                    continue
                
                params = audio[0].getparams()
                drone_dic[drone] = drone_dic[drone] + params[3]/params[2]
                
    print(drone_dic)
    time_end = time.time()
    print("Total running time: %f s"%(time_end-time_start))