Temporary solution: WOA for surface track

def woa_track_from_file(d, lat, lon, filename, varnames=None):
    """ Temporary solution: WOA for surface track
    """
    d = np.asanyarray(d)
    lat = np.asanyarray(lat)
    lon = np.asanyarray(lon)

    lon[lon < 0] += 360

    doy = np.array([int(dd.strftime('%j')) for dd in d])

    nc = netCDF4.Dataset(expanduser(filename), 'r')

    if varnames is None:
        varnames = {}
        for v in nc.variables.keys():
            if nc.variables[v].dimensions == \
                    (u'time', u'depth', u'lat', u'lon'):
                        varnames[v] = v

    output = {}
    for v in varnames:
        output[v] = []

    for d_n, lat_n, lon_n in zip(doy, lat, lon):
        # Get the nearest point. In the future interpolate.
        n_d = (np.abs(d_n - nc.variables['time'][:])).argmin()
        n_x = (np.abs(lon_n - nc.variables['lon'][:])).argmin()
        n_y = (np.abs(lat_n - nc.variables['lat'][:])).argmin()

        for v in varnames:
            output[v].append(nc.variables[varnames[v]][n_d, 0, n_y, n_x])

    for v in varnames:
        output[v] = ma.fix_invalid(output[v])

    return output