from py_eddy_tracker import start_logger
start_logger().setLevel('DEBUG') # Available options: ERROR, WARNING, INFO, DEBUG


grid_name, lon_name, lat_name = (
    "X:\MasterStudent_HY\Some data\Simulated SWOT data\SWOT_L2_LR_SSH_Expert_266_008_20150101T003140_20150101T012245_DG10_01.nc",
    "longitude",
    "latitude",
)



from datetime import datetime
from py_eddy_tracker.dataset.grid import UnRegularGridDataset
h = UnRegularGridDataset(grid_name, lon_name, lat_name)


date = datetime(2015, 1, 1)
a, c = h.eddy_identification(
    'ssha_karin',  # Variables used for identification
    date, # Date of identification
    0.002, # step between two isolines of detection (m) 
    pixel_limit=(8, 1000), # Min and max pixel count for valid contour 
    shape_error=55, # Error max (%) between ratio of circle fit and contour
    )

from matplotlib import pyplot as plt
import cartopy.crs as ccrs

fig = plt.figure(figsize=(15,7))
ax = fig.add_axes([.03,.03,.94,.94])
ax = fig.add_subplot(1, 1, 1,projection=ccrs.PlateCarree())
ax.coastlines()
ax.set_title('Eddies detected -- Cyclonic(red) and Anticyclonic(blue)')
ax.set_ylim(-5,35)
ax.set_xlim(105,135)
ax.set_aspect('equal')
a.display(ax, label="Anticyclonic ({nb_obs} eddies)",color='b', linewidth=1)
c.display(ax, label="cyclonic ({nb_obs} eddies)",color='r', linewidth=1)
ax.legend(loc="upper left") 
ax.grid()
ax.gridlines(draw_labels=True, xlocs=[105,110,115,120,125,130,135])
plt.show()

print(a)
print(c)

import netCDF4 as nc

with nc.Dataset(date.strftime('X:/MasterStudent_HY/Some data/Simulated SWOT data/Anticyclonic_%Y%m%d.nc'), 'w') as h:
    a.to_netcdf(h)
with nc.Dataset(date.strftime('X:/MasterStudent_HY/Some data/Simulated SWOT data/Cyclonic_%Y%m%d.nc'), 'w') as h:
    c.to_netcdf(h)