"""
WRF后处理程序 最临近网格
20230201 byp
"""
import netCDF4
import wrf
import os
import glob
import re
import math
import matplotlib.pyplot as plt
import matplotlib
import cartopy.crs as ccrs
import cartopy
import numpy as np
from matplotlib.cm import get_cmap
from PIL import Image


# 读取数据###############################################################开始
dir_name = "./data/WRF/"
dir_output = './output/txt/'
list_of_files = glob.glob(dir_name+'*')

latest_file = max(list_of_files, key=os.path.getctime)  # 最新文件
mat = re.search(r"(\d{4}-\d{1,2}-\d{1,2}_\d{1,2})", latest_file)  # 正则匹配时间
dir_time_file = 'wrfout_d01_'+latest_file[mat.span()[0]:]
dir_time = latest_file[mat.span()[0]:mat.span()[1]].replace('-', '').replace('_', '')
data_nc = netCDF4.Dataset(dir_name+dir_time_file)
print(dir_time)
lat, lon = (20, 110)
x, y = wrf.ll_to_xy(data_nc, lat, lon)
# print(xy.values[0], '/', xy.values[1])
x, y = (wrf.to_np(x), wrf.to_np(y))
print(x, '/', y)
lao = wrf.xy_to_ll(data_nc, x, y)
print(wrf.to_np(lao))

idx = 1
uv = wrf.getvar(data_nc, 'uvmet10', timeidx=idx)
sd = wrf.getvar(data_nc, 'wspd_wdir10', timeidx=idx)
lats_lons = wrf.latlon_coords(uv)
print(wrf.to_np(lats_lons[1][0][x]))
print(wrf.to_np(lats_lons[0][y][0]))
print(lats_lons[1][0][x].values)
print(lats_lons[0][y][0].values)
print(uv[0][y][x].values)
u_t = wrf.to_np(uv[0][y][x])
v_t = wrf.to_np(uv[1][y][x])
wind_speed = math.sqrt(u_t ** 2 + v_t ** 2)
print(wind_speed)
print(wrf.to_np(sd[0][y][x]))

# print(wrf.to_np(lats_lons[0][y][0]))
# print(wrf.to_np(lats_lons[1][0][x]))
# print(wrf.to_np(uv[0][y][x]))
# print(wrf.to_np(uv[1][0][x]))