"""
Author  : XinYi Song
Time    : 2021/11/4 16:59
Desc:
"""
import rasterio
import requests

from util.xml_util import xml_to_dict, dict_to_xml


def gf4_pmi_001(file_name, xml_name):
    """

    :param file_name:     扫描文件传过来的遥感数据源文件的路径
    :param xmlPath:       解析出的xml文件存储的路径
    :param ThumbnailPath: 解析出的缩略图文件存储的路径
    :return:
    """
    file_path = 'E:/sensing/GF4_PMI_001/'
    with rasterio.open(file_path+file_name, 'r') as ds:
        # 存放xml，缩略图的文件夹，由根文件夹+数据集代码命名的文件夹组成
        print('该栅格数据的基本数据集信息:')
        CollectionCode = 'GF4_PMI_001'  # 数据集代码
        DataFormat = ds.driver  # DataFormat            数据格式
        NumberBands = ds.count  # NumberBands           波段数目
        ImageWidth = ds.width  # ImageWidth            影像宽度
        ImageHeight = ds.height  # ImageHeight           影像高度
        GeographicScope = ds.bounds  # GeographicScope       地理范围
        ReflectionParameter = ds.transform  # ReflectionParameter   反射变换参数（六参数模型）
        ProjectionDefinition = ds.crs  # ProjectionDefinition  投影定义
        # print(CRS.from_epsg(4326))
        # 获取第一个波段数据，跟GDAL一样索引从1开始
        # 直接获得numpy.ndarray类型的二维数组表示，如果read()函数不加参数，则得到所有波段（第一个维度是波段）
        band1 = ds.read(1)
        FirstBindMax = band1.max()  # FirstBindMax           第一波段的最大值

        FirstBindMin = band1.min()  # FirstBindMin           第一波段的最小值
        FirstBindAverage = band1.mean()  # FirstBindAverage       第一波段的平均值
        # 根据地理坐标得到行列号
        x, y = (ds.bounds.left + 300, ds.bounds.top - 300)  # 距离左上角东300米，南300米的投影坐标
        row, col = ds.index(x, y)  # 对应的行列号
        print(f'(投影坐标{x}, {y})对应的行列号是({row}, {col})')
        ProjectedCoordinates = x, y  # ProjectedCoordinates    投影坐标
        RowNumber = row, col  # RowNumber               对应的行列号
        # 根据行列号得到地理坐标
        x, y = ds.xy(row, col)  # 中心点的坐标
        print(f'行列号({row}, {col})对应的中心投影坐标是({x}, {y})')  #
        CenterProjectionCoordinates = x, y  # CenterProjectionCoordinates  中心投影坐标
        # 'C:/Users/HP/Desktop/Number tube/GF4_PMI_E119.8_N35.3_20210908_L1A0000417337/GF4_PMS_E119.8_N35.3_20210908_L1A0000417337.xml'
        # 传入xml文件路径，解析xml文件
        # xml_name  存储后的xml文件的路径+文件名
        xml_dict = xml_to_dict(file_path+xml_name)
        StartTime = xml_dict['ProductMetaData']['StartTime']  # 开始采集时间
        EndTime = xml_dict['ProductMetaData']['EndTime']  # 结束采集时间
        CloudPercent = xml_dict['ProductMetaData']['CloudPercent']  # 云覆盖量百分比
        TopLeftLatitude = xml_dict['ProductMetaData']['TopLeftLatitude']  # 左上纬度
        TopLeftLongitude = xml_dict['ProductMetaData']['TopLeftLongitude']  # 左上经度
        TopRightLatitude = xml_dict['ProductMetaData']['TopRightLatitude']  # 右上纬度
        TopRightLongitude = xml_dict['ProductMetaData']['TopRightLongitude']  # 右上经度
        BottomRightLatitude = xml_dict['ProductMetaData']['BottomRightLatitude']  # 右下纬度
        BottomRightLongitude = xml_dict['ProductMetaData']['BottomRightLongitude']  # 右下经度
        BottomLeftLatitude = xml_dict['ProductMetaData']['BottomLeftLatitude']  # 左下纬度
        BottomLeftLongitude = xml_dict['ProductMetaData']['BottomLeftLongitude']  # 左下经度
        boundaryGeomStr = f'POLYGON(({TopLeftLatitude} {TopLeftLongitude},' \
                          f'{TopRightLatitude} {TopRightLongitude},' \
                          f'{BottomRightLatitude} {BottomRightLongitude},' \
                          f'{BottomLeftLatitude} {BottomLeftLongitude},' \
                          f'{TopLeftLatitude} {TopLeftLongitude}))'
        # ThumbnailPath  存储后的缩略图的路径+文件名    ThumbnailName  缩略图文件名称
        # xmlPath        存储后的xml文件路径+文件名    xmlFileName    xml文件名称
        sensing_dict = {'StartTime': StartTime, 'EndTime': EndTime, 'CloudPercent': CloudPercent,
                        'boundaryGeomStr': boundaryGeomStr, 'DataFormat': DataFormat, 'NumberBands': NumberBands,
                        'ImageWidth': ImageWidth, 'ImageHeight': ImageHeight, 'GeographicScope': GeographicScope,
                        #'ReflectionParameter': ReflectionParameter, 'ProjectionDefinition': ProjectionDefinition,
                        #'FirstBindMax': FirstBindMax, 'FirstBindMin': FirstBindMin,
                        'FirstBindAverage': FirstBindAverage,
                        'ProjectedCoordinates': ProjectedCoordinates, 'RowNumber': RowNumber,
                        #'CenterProjectionCoordinates': CenterProjectionCoordinates,
                        'CollectionCode': CollectionCode,
                        "ThumbnailPath": file_path+"GF4_IRS_E119.8_N35.3_20210908_L1A0000417337_thumb.jpg",
                        "ThumbnailName": "GF4_IRS_E119.8_N35.3_20210908_L1A0000417337_thumb.jpg",
                        "xmlPath": "", "xmlFileName": "",
                        'DirectoryDepth': 'day'}
        return sensing_dict


if __name__ == '__main__':
    file_path = 'C:/Users/HP/Desktop/Number tube/GF4_PMI_E119.8_N35.3_20210908_L1A0000417337/GF4_PMS_E119.8_N35.3_20210908_L1A0000417337.tiff'
    xml_path = 'C:/Users/HP/Desktop/Number tube/GF4_PMI_E119.8_N35.3_20210908_L1A0000417337/GF4_PMS_E119.8_N35.3_20210908_L1A0000417337.xml'
    gf4_pmi_001(file_path, xml_path)