# coding:utf-8
import json
import os
import sys

import matplotlib.pyplot as plt

RECORD_RESULT_DIR = os.path.join(sys.path[0], "DebugRecord")
if not os.path.exists(RECORD_RESULT_DIR):
    os.makedirs(RECORD_RESULT_DIR)

file_list = os.listdir(RECORD_RESULT_DIR)

for file_name in file_list:
    with open(os.path.join(RECORD_RESULT_DIR, file_name), "r", encoding="utf-8_sig") as file:
        data = json.load(file)

    # 对数据进行排序
    data = sorted(data, key=lambda x: x['record_time'])
    # 修复测距失败的数据
    result = []
    last_distance = {}
    last_correct_time = {}
    for row in data:
        is_successful = row["is_successful"]
        tag_id = row["tag_id"]
        distance = row["distance"]
        first_rssi = row["first_rssi"]
        total_rssi = row["total_rssi"]
        record_time = row["record_time"]
        if distance > 3000:
            continue
        # case1 差距过大
        if abs(first_rssi - total_rssi) < 5:
            continue
        if is_successful:
            last_distance[tag_id] = distance
            last_correct_time[tag_id] = record_time
            result.append({
                "distance": distance,
                "first_rssi": first_rssi,
                "total_rssi": total_rssi,
                "error": 0
            })
        else:
            if tag_id in last_correct_time.keys() and record_time - last_correct_time[tag_id] < 1:
                result.append({
                    "distance": last_distance[tag_id],
                    "first_rssi": first_rssi,
                    "total_rssi": total_rssi,
                    "error": distance - last_distance[tag_id]
                })
    print(len(result) / len(data))
    # 统计数据
    first_rssi_data_list = [
        fail_data["first_rssi"]
        for fail_data in result
    ]
    total_rssi_data_list = [
        fail_data["total_rssi"]
        for fail_data in result
    ]
    distance_data_list = [
        fail_data["distance"]
        for fail_data in result
    ]
    error_data_list = [
        fail_data["error"]
        for fail_data in result
    ]
    desire_data_list = [
        [
            [fail_data["distance"], fail_data["distance"]],
            [fail_data["first_rssi"], fail_data["total_rssi"]]
        ]
        for fail_data in result
    ]
    plt.scatter(x=distance_data_list, y=total_rssi_data_list, c="hotpink", alpha=0.5, linewidths=0, s=32)
    plt.scatter(x=distance_data_list, y=first_rssi_data_list, c="cornflowerblue", alpha=0.5, linewidths=0, s=32)
    # plt.scatter(x=distance_data_list, y=error_data_list, c="red", alpha=0.5, linewidths=0, s=32)
    # for desire in desire_data_list:
    #     plt.plot(desire[0], desire[1], c="green", alpha=0.1)
plt.show()