# -*- coding: utf-8 -*-
import argparse
import os
from osgeo import gdal, osr
import numpy as np
import netCDF4 as nc
from datetime import datetime, timezone
import time

def nc2ENVIBin(nc_file_path,output_envi_path,utctime):
    # Input parameters (replace these with your actual values)
    time_index = -1  # Example: 0 for the first time step; adjust if needed

    # Step 1: Read the NetCDF file using netCDF4
    ds=None
    filename = "数据/测试文件.nc"
    with open(nc_file_path, 'rb') as f:
        ds = nc.Dataset('in_memory', mode='r', memory=f.read())
    print(f"Available variables: {list(ds.variables.keys())}")  # Optional: Print variables for verification
    valid_time_list=ds.variables["valid_time"][:]
    for timeID in range(0,len(valid_time_list)):
        # print(valid_time_list[timeID],utctime)
        if valid_time_list[timeID] == utctime:
            time_index = timeID
            break

    if time_index == -1:
        return -1
    else:
        print(f"time_index={time_index}")

    # Extract the variable data (assuming 3D: time, lat, lon)
    data_U10 = ds.variables["u10"][time_index, :, :].filled(np.nan)  # Handle masked values as NaN
    data_V10 = ds.variables["v10"][time_index, :, :].filled(np.nan)  # Handle masked values as NaN

    # Extract lat and lon (adjust variable names if your file uses different ones, e.g., 'latitude', 'longitude')
    lat = ds.variables['latitude'][:]
    lon = ds.variables['longitude'][:]

    # Calculate geotransform parameters
    x_res = (lon[-1] - lon[0]) / (len(lon) - 1)
    y_res = (lat[0] - lat[-1]) / (len(lat) - 1)  # Note: lat often decreases north to south
    top_left_x = lon[0] - x_res / 2
    top_left_y = lat[0] + y_res / 2
    geotransform = (top_left_x, x_res, 0, top_left_y, 0, -y_res)  # Negative y_res for north-up

    # Step 2: Create ENVI file using GDAL
    driver = gdal.GetDriverByName('ENVI')
    envi_ds = driver.Create(
        output_envi_path,
        data_U10.shape[1],  # Width (lon)
        data_U10.shape[0],  # Height (lat)
        2,  # Single band
        gdal.GDT_Float32  # Assuming float data; adjust to gdal.GDT_Float64 if needed
    )

    # Set geotransform and projection (EPSG:4326 for WGS84 lat/lon)
    envi_ds.SetGeoTransform(geotransform)
    srs = osr.SpatialReference()
    srs.ImportFromEPSG(4326)
    envi_ds.SetProjection(srs.ExportToWkt())

    # Write the data to the band
    envi_band = envi_ds.GetRasterBand(1)
    envi_band.SetNoDataValue(np.nan)  # Set NaN as no-data value (optional)
    envi_band.WriteArray(data_U10)

    envi_band = envi_ds.GetRasterBand(2)
    envi_band.SetNoDataValue(np.nan)  # Set NaN as no-data value (optional)
    envi_band.WriteArray(data_V10)

    # Add ENVI-specific metadata to the header (optional, but recommended)
    envi_ds.SetMetadataItem('wavelength units', 'None', 'ENVI')  # Example; customize as needed
    envi_ds.SetMetadataItem('data type', '4', 'ENVI')  # 4 = float32; matches GDT_Float32

    # Clean up
    envi_ds.FlushCache()
    envi_ds = None
    ds.close()

    print(f"Conversion complete: {output_envi_path} (with .hdr)")


def getParams():
    parser = argparse.ArgumentParser()
    parser.add_argument('-i','--infile',default=r'D:\风场\20250807_SAR_EC_2024年\ERA5风场\total_precipitation202410.nc', help='输入风场文件路径')
    parser.add_argument('-o', '--outfile',default=r'D:\风场\20250807_SAR_EC_2024年\ERA5风场\total_precipitation202410.bin', help='输出Bin文件路径')
    parser.add_argument('-t', '--time',type=int, default=2024100108,help='yyyymmddhh')
    args = parser.parse_args()
    return args

def timestr2utc(timeint):
    timestr = str(timeint)

    # 解析字符串为datetime对象（默认无时区信息）
    dt = datetime.strptime(timestr, "%Y%m%d%H")

    # 显式标记为UTC时间（两种等效方式）
    dt_utc = dt.replace(tzinfo=timezone.utc)  # 方式1：使用标准库
    # 或使用pytz库：dt_utc = pytz.utc.localize(dt)
    timestamp = time.mktime(dt_utc.timetuple())
    utc_timestamp = int(timestamp)  # 当前UTC时间戳（秒级）
    print("UTC时间:", dt_utc)
    print("ISO格式:", dt_utc.isoformat())  # 输出：2024-08-01T02:00:00+00:00
    print("UTC时间戳:", utc_timestamp)  # 输出：2024-08-01T02:00:00+00:00
    return utc_timestamp


if __name__ == '__main__':
    parser = getParams()
    inNcFilePath=parser.infile
    outbinpath=parser.outfile
    searchTime=parser.time
    print('infile=',inNcFilePath)
    print('outfile=',outbinpath)
    time_utc=timestr2utc(searchTime)
    nc2ENVIBin(inNcFilePath,outbinpath,time_utc)