import os
from awx import Awx

pathfile = r'../data/ANI_VIS_R02_20230217_1000_FY2G.AWX'
ds = Awx(pathfile)

# print file head information
print(ds)

# get satellite observation data in xarray.DataArray format
print(ds.values)

# clip data to given longitude and latitude extent
print(ds.sel(lat=slice(20, 40), lon=slice(100, 130)))

# save data to netcdf4
ds.values.to_netcdf('ANI_VIS_R02_20230217_1000_FY2G.nc')

# draw data use matplotlib

import matplotlib.pyplot as plt
from awx import Awx

fpath = r'./data/ANI_VIS_R02_20230217_1000_FY2G.AWX'
ds = Awx(pathfile=fpath)
print(ds)
dar = ds.values.squeeze()
plt.pcolormesh(dar.lon, dar.lat, dar, cmap='Greys_r')
plt.savefig('ANI_VIS_R02_20230217_1000_FY2G_NoProj.png', dpi=300)
plt.show()

# draw data in projection coordination
import os
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
from awx import Awx

# fpath = r'./sampledata/ANI_VIS_R02_20230308_1400_FY2G.AWX'  # Mercator
fpath = r'./sampledata/ANI_VIS_R01_20230308_1400_FY2G.AWX'  # lambert
ds = Awx(pathfile=fpath)
print(ds)
dar = ds.values.squeeze()

plt.figure(figsize=(8, 8))

if dar.projection == 1:
    proj = ccrs.LambertConformal(central_longitude=dar.clon / 100,
                                 central_latitude=dar.clat / 100,
                                 standard_parallels=(dar.std_lat1_or_lon / 100.,
                                                     dar.std_lat2 / 100.))
    extent = [dar.x.min(), dar.x.max(), dar.y.min(), dar.y.max()]
elif dar.projection == 2:
    proj = ccrs.Mercator(central_longitude=dar.clon / 100,
                         latitude_true_scale=dar.std_lat1_or_lon / 100.)
    extent = [dar.x.min(), dar.x.max(), dar.y.min(), dar.y.max()]
elif dar.projection == 4:
    proj = ccrs.PlateCarree(central_longitude=dar.clon / 100.)
    extent = [dar.lon.min(), dar.lon.max(), dar.lat.min(), dar.lat.max()]
else:
    raise NotImplementedError()
ax = plt.axes(projection=proj)
ax.set_extent(extent, crs=proj)
ax.coastlines(resolution='110m')
ax.gridlines(draw_labels=True)
ax.pcolormesh(dar.x, dar.y, dar, cmap='Greys_r')
plt.savefig(os.path.splitext(os.path.basename(fpath))[0] + '.png', dpi=300, bbox_inches='tight')
plt.show()