text: # Script to generate a netcdf file with the hourly time series of the TS, w,
  # ssh in the CODAR region
  
  import datetime
  import netCDF4 as nc
  import numpy as np
  
  from salishsea_tools import (tidetools)
  from nowcast import analyze
  
  import baroclinic
  
  NodalCorr = tidetools.CorrTides
  
  to = datetime.datetime(2014, 11, 26)
  tf = datetime.datetime(2015, 4, 26)
  nowcast_path = '/results/SalishSea/nowcast/'
  grid = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')
  lon_grid = grid.variables['nav_lon']
  lat_grid = grid.variables['nav_lat']
  jmin = 220
  jmax = 360
  imin = 100
  imax = 172
  jss = np.arange(jmin, jmax)
  iss = np.arange(imin, imax)
  ks = np.arange(0, 40)
  
  filest = analyze.get_filenames(to, tf, '1h', 'grid_T', nowcast_path)
  filesw = analyze.get_filenames(to, tf, '1h', 'grid_W', nowcast_path)
  Ts, times = analyze.combine_files(filest, 'votemper', ks, jss, iss)
  Ss, times = analyze.combine_files(filest, 'vosaline', ks, jss, iss)
  sshs, times = analyze.combine_files(filest, 'sossheig', 'None', jss, iss)
  Ws, times = analyze.combine_files(filesw, 'vovecrtz', ks, jss, iss)
  Ws = Ws.data
  
  tmp = nc.Dataset(filest[0])
  depthst = tmp.variables['deptht'][:]
  tmp = nc.Dataset(filesw[0])
  depthsw = tmp.variables['depthw'][:]
  
  lons = lon_grid[jss, iss]
  lats = lat_grid[jss, iss]
  
  reftime = NodalCorr['reftime']
  time = tidetools.convert_to_hours(times, reftime=reftime)
  
  baroclinic.save_netcdf_TS(time, Ts, Ss, Ws, sshs, depthst, depthsw,
                            'JuandeFuca', lons, lats, to, tf)
  print('Finished')
  