import json
import os
from enum import Enum


class LaneDirectionType(int, Enum):
    LaneDirectionType_Unknown = -1  # 类型未知
    OneWay = 1  # 单向
    TwoWay = 2  # 双向


# 颜色类型
class ColorCombo(int, Enum):
    NOUSE = 0  # 默认值
    UNKNOWN = 1000  # 未定义
    WHITE = 1  # 白色(默认值)
    YELLOW = 2  # 黄色
    ORANGE = 3  # 橙色
    BLUE = 4  # 蓝色
    GREEN = 5  # 绿色
    LEFT_WHITE_RIGHT_YELLOW = 6  # 左白右黄
    LEFT_YELLOW_RIGHT_WHITE = 7  # 左黄右白
    RED = 8  # 红色


class LaneTurnType(int, Enum):
    NOUSE = 0  # 默认值
    UNKNOWN = 1000  # 未定义
    AHEAD = 1  # 直行
    LEFT = 2  # 左转
    RIGHT = 3  # 右转
    U_TURN = 4  # 掉头


class ObjectLaneType(int, Enum):
    NOUSE = 0  # 默认值
    UNKNOWN = 1000  # 未分类
    VIRTUAL_WIRE = 1  # 虚拟线
    THICK_DASHED_LINE_SEGMENT = 2  # 粗虚线段
    SINGLE_DASHED_LINE = 3  # 单虚线
    SINGLE_SOLID_LINE = 4  # 单实线
    DOUBLE_DASHED_LINE = 5  # 双虚线
    DOUBLE_SOLID_LINE = 6  # 双实线
    LEFT_SOLID_RIGHT_DASHED_LINE = 7  # 左实右虚线
    RIGHT_SOLID_LEFT_DASHED_LINE = 8  # 右实左虚线
    FOUR_SOLID_LINE = 9  # 四实线


class LongitudinalType(int, Enum):
    COMMON = 0  # 常规标线
    DISTANCE_CONFIRM_LINE = 1  # 白色半圆状车距确认线
    LOW_SPEED_LINE = 2  # 车行道纵向减速标线
    GORE_AREA_LINE = 3  # 导流区边线
    NO_PARKING_LINE = 4  # 禁停区边线
    PARKING_LINE = 5  # 停车位边线
    VARIABLE_GUIDANCE_LINE = 6  # 可变导向车道线


# 路边条带枚举定义
class ObjectFenceType(int, Enum):
    NOUSE = 0  # 默认值
    UNKNOWN = 1000  # 未分类
    CURB = 1  # 路缘石
    GUARDRAIL = 2  # 护栏
    WALL = 3  # 墙体
    GEOGRAPHICAL_BOUNDARTES = 4  # 地理边界
    GREENBELTS = 5  # 绿化带
    OTHER_HARD_ISOLATION = 6  # 其它硬隔离
    PARKING_POST = 7  # 停车场柱子


def read_data(input_data):#./data3转换/output/semantic
    feature = []
    for _file_name in os.scandir(input_data):#会遍历该目录下的所有文件和子目录
        with open(_file_name, encoding='utf-8') as fh:
            feature_collection = json.loads(fh.read())#fh.read()会读取文件的所有内容作为字符串
            feature.append(feature_collection)
    return feature


def transform_line_properties(id="", groupid="", color=ColorCombo.NOUSE, color_tf=100, type=ObjectLaneType.NOUSE,
                              type_tf=100,
                              longitudinal_type=str(LongitudinalType.COMMON.value), aggregation_count=1,
                              taskid="0", update_time=0):
    properties = {
        "id": str(id),
        "groupid": groupid,

        "color": color,
        # 置信度默认赋值 100
        "color_tf": color_tf,
        "type": type,
        # 置信度默认赋值 100
        "type_tf": type_tf,
        "longitudinal_type": longitudinal_type,
        # 聚类次数默认赋值 1
        "aggregation_count": aggregation_count,
        "taskid": taskid,
        "update_time": update_time
    }
    return properties


def transform_boundary_properties(id="", type=6, type_tf=100, aggregation_count=1, taskid="0", update_time=0):
    properties = {
        "id": str(id),
        "type": type,
        # 置信度默认赋值 100
        "type_tf": type_tf,
        # 聚类次数默认赋值 1
        "aggregation_count": aggregation_count,
        "taskid": taskid,
        "update_time": update_time
    }
    return properties


def transform_trajectory_properties(id=0,
                                    lanenode_id_s=-1,
                                    lanenode_id_e=-1,
                                    speed=0,
                                    turn_type=LaneTurnType.NOUSE,
                                    collect_num=1,
                                    direction=LaneDirectionType.LaneDirectionType_Unknown,
                                    taskid="0",
                                    update_time=0):
    properties = {
        "id": id,
        "lanenode_id_s": lanenode_id_s,
        "lanenode_id_e": lanenode_id_e,
        "speed": speed,
        "turn_type": turn_type,
        "collect_num": collect_num,
        "direction": direction,
        "taskid": taskid,
        "update_time": update_time
    }
    return properties


def transform_line(data):
    # if isinstance(data["properties"]["longitudinal_type"], list):
    #     longitudinal_type = ','.join([str(x) for x in data["properties"]["longitudinal_type"]])
    # elif isinstance(data["properties"]["longitudinal_type"], str):
    #     longitudinal_type = data["properties"]["longitudinal_type"]
    # else:
    #     longitudinal_type = ""
    new_properties = transform_line_properties(id=data["properties"]["id"],
                                               color=data["properties"]["color"],
                                               color_tf=data["properties"]["color_tf"],
                                               type=ObjectLaneType.SINGLE_DASHED_LINE)
    data["properties"] = new_properties


def transform_boundary(data):
    new_properties = transform_boundary_properties(id=data["properties"]["id"],
                                                   type=ObjectFenceType.OTHER_HARD_ISOLATION)
    data["properties"] = new_properties

#修改参数，可以改上层参数 
def transform_trajectory(data):
    new_properties = transform_trajectory_properties(id=data["properties"]["id"])
    data["properties"] = new_properties


def save_data(data_list, out_data_path):
    directory = os.path.dirname(out_data_path)
    if not os.path.exists(directory):
        os.makedirs(directory)
    # out_data_path = out_data_path + save_type + ".geojson"
    out_data= {"type": "FeatureCollection",
            "features":data_list}
    with open(out_data_path, 'w', encoding='utf-8') as fp:
        fp.write(json.dumps(out_data, ensure_ascii=False))

def transform_format(in_data_path,out_path):
    # 读取semantic数据   转成字典保存在list中返回
    semantic_features = read_data(os.path.join(in_data_path, "semantic"))#./data3转换/output/semantic
    boundary_data = []#道路边线
    line_data = []#车道线
    for data_features in semantic_features:
        for data_feature in data_features["features"]:#遍历list 包括几何信息，属性信息
            # 云端建图后续可能会有字段枚举值
            if data_feature["properties"]["type"] == 6:
                transform_boundary(data_feature)#只更新对象里的属性值,其他的保留
                boundary_data.append(data_feature)
            if data_feature["properties"]["type"] == 1:
                transform_line(data_feature)
                line_data.append(data_feature)
    out_boundary_data_path = os.path.join(out_path, "semantic", "Boundary.geojson")
    out_line_data_path = os.path.join(out_path, "semantic", "Line.geojson")
    save_data(boundary_data, out_boundary_data_path)
    save_data(line_data, out_line_data_path)
if __name__ == '__main__':# 用于确保该代码块只在作为主程序运行时才执行，而在被导入为模块时不执行
    in_data_path = "/home/linux/下载/557040098/output"
    out_path = "/home/linux/下载/557040098/output"
    transform_format(in_data_path, out_path)
    # # 读取trajectory数据
    # trajectory_features = read_data(os.path.join(in_data_path,"trajectory"))
    #
    # for data_features in trajectory_features.items():
    #     for data_feature in data_features["features"]:
    #         transform_trajectory(data_feature)
    # out_trajectory_data_path = os.path.join(out_path, "trajectory", "Lane")
    # save_data(trajectory_features, out_trajectory_data_path)

json.load() 和 json.loads() 都是用于读取 JSON 格式数据的函数，其中 json.load() 用于读取文件（File）对象，而 json.loads() 用于读取字符串（str）对象。

具体来说，json.load() 的参数应该是一个打开的文件对象，而 json.loads() 的参数应该是一个字符串对象。json.loads() 会将这个字符串解码为 Python 对象，而 json.load() 则会将文件中的 JSON 数据解码为 Python 对象。