# -*- coding: utf-8 -*-
"""
Created on Wed Mar 11 11:16:57 2020

example grid set up

@author: jdha
"""

import numpy as np
from netCDF4 import Dataset

def set_hgrid(dx, dy, jpi, jpj, zoffx, zoffy):
    # Set grid positions [km]
    latt = np.zeros((jpi, jpj))
    lont = np.zeros((jpi, jpj))
    lonu = np.zeros((jpi, jpj))
    latu = np.zeros((jpi, jpj))
    lonv = np.zeros((jpi, jpj))
    latv = np.zeros((jpi, jpj))
    lonf = np.zeros((jpi, jpj))
    latf = np.zeros((jpi, jpj))

    for i in range(0, jpi):
        lont[i, :] = zoffx * dx * 1.e-3 + dx * 1.e-3 * np.float(i)
        lonu[i, :] = zoffx * dx * 1.e-3 + dx * 1.e-3 * (np.float(i) + 0.5)

    for j in range(0, jpj):
        latt[:, j] = zoffy * dy * 1.e-3 + dy * 1.e-3 * float(j)
        latv[:, j] = zoffy * dy * 1.e-3 + dy * 1.e-3 * (float(j) + 0.5)

    lonv = lont
    lonf = lonu
    latu = latt
    latf = latv

    e1t = np.ones((jpi, jpj)) * dx
    e2t = np.ones((jpi, jpj)) * dy
    e1u = np.ones((jpi, jpj)) * dx
    e2u = np.ones((jpi, jpj)) * dy
    e1v = np.ones((jpi, jpj)) * dx
    e2v = np.ones((jpi, jpj)) * dy
    e1f = np.ones((jpi, jpj)) * dx
    e2f = np.ones((jpi, jpj)) * dy

    # Set bathymetry [m]:
    batt = 500. + 0.5 * 1500. * (1.0 + np.tanh((lont - 40.) / 7.))

    # Set surface mask:
    ktop = np.zeros((jpi, jpj))
    #ktop[1:jpi - 1, nghost + 1:jpj - nghost - 1] = 1
    #batt = np.where((ktop == 0.), 0., batt)

    # Set coriolis parameter:
    ff_t = np.zeros((jpi, jpj))
    ff_f = np.zeros((jpi, jpj))

    grid_h = {'lont':lont, 'latt':latt, 'lonu':lonu, 'latu':latu, 'lonv':lonv, 'latv':latv, 'lonf':lonf, 'latf':latf, \
           'e1t':e1t, 'e2t':e2t, 'e1u':e1u, 'e2u':e2u, 'e1v':e1v, 'e2v':e2v, 'e1f':e1f, 'e2f':e2f, 'batt':batt, \
              'ktop':ktop, 'ff_f':ff_f, 'ff_t':ff_t,'jpi':jpi,'jpj':jpj,'dy':dy,'dx':dx}

    return grid_h

def set_zgrid(grid_h,jpk,max_dep,min_dep,z_dim):

    jpi = grid_h['jpi']
    jpj = grid_h['jpj']

    dept_1d = np.linspace(min_dep,max_dep,jpk)
    e3t_1d = np.linspace(1.0,z_dim,jpk)
    e3w_1d = np.linspace(1.0,z_dim,jpk)

    e3t = np.zeros((jpi, jpj, len(e3t_1d)))
    e3u = np.zeros((jpi, jpj, len(e3t_1d)))
    e3v = np.zeros((jpi, jpj, len(e3t_1d)))
    e3w = np.zeros((jpi, jpj, len(e3w_1d)))
    e3f = np.zeros((jpi, jpj, len(e3t_1d)))
    e3uw = np.zeros((jpi, jpj, len(e3t_1d)))
    e3vw = np.zeros((jpi, jpj, len(e3t_1d)))

    e3t[:] = e3t_1d
    e3u[:] = e3t_1d
    e3v[:] = e3t_1d
    e3w[:] = e3w_1d
    e3f[:] = e3t_1d
    e3uw[:] = e3t_1d
    e3vw[:] = e3t_1d

    grid_z = {'dept_1d':dept_1d,'e3t_1d':e3t_1d,'e3w_1d':e3w_1d,'e3t':e3t,'e3u':e3u,'e3v':e3v,'e3w':e3w,'e3f':e3f, \
              'e3uw':e3uw,'e3vw':e3vw}

    return grid_z

def write_coord_H(fileout, grid_h):
    '''
    Writes out a NEMO formatted coordinates file.

    Args:
        fileout         (string): filename
        lon[t/u/v/f](np.ndarray): longitude array at [t/u/v/f]-points (2D)
        lat[t/u/v/f](np.ndarray): latitude array at [t/u/v/f]-points (2D)
        e1[t/u/v/f] (np.ndarray): zonal scale factors at [t/u/v/f]-points
        e2[t/u/v/f] (np.ndarray): meridional scale factors at [t/u/v/f]-points

    Returns:
    '''

    # Open pointer to netcdf file
    dataset = Dataset(fileout, 'w', format='NETCDF4_CLASSIC')

    # Get input size and create appropriate dimensions
    # TODO: add some sort of error handling
    nx, ny = np.shape(grid_h['lont'])
    dataset.createDimension('x', nx)
    dataset.createDimension('y', ny)

    # Create Variables
    nav_lon = dataset.createVariable('nav_lon', np.float32, ('y', 'x'))
    nav_lat = dataset.createVariable('nav_lat', np.float32, ('y', 'x'))

    glamt = dataset.createVariable('glamt', np.float64, ('y', 'x'))
    glamu = dataset.createVariable('glamu', np.float64, ('y', 'x'))
    glamv = dataset.createVariable('glamv', np.float64, ('y', 'x'))
    glamf = dataset.createVariable('glamf', np.float64, ('y', 'x'))
    gphit = dataset.createVariable('gphit', np.float64, ('y', 'x'))
    gphiu = dataset.createVariable('gphiu', np.float64, ('y', 'x'))
    gphiv = dataset.createVariable('gphiv', np.float64, ('y', 'x'))
    gphif = dataset.createVariable('gphif', np.float64, ('y', 'x'))

    ge1t = dataset.createVariable('e1t', np.float64, ('y', 'x'))
    ge1u = dataset.createVariable('e1u', np.float64, ('y', 'x'))
    ge1v = dataset.createVariable('e1v', np.float64, ('y', 'x'))
    ge1f = dataset.createVariable('e1f', np.float64, ('y', 'x'))
    ge2t = dataset.createVariable('e2t', np.float64, ('y', 'x'))
    ge2u = dataset.createVariable('e2u', np.float64, ('y', 'x'))
    ge2v = dataset.createVariable('e2v', np.float64, ('y', 'x'))
    ge2f = dataset.createVariable('e2f', np.float64, ('y', 'x'))

    nav_lon.units, nav_lon.long_name = 'km', 'X'
    nav_lat.units, nav_lat.long_name = 'km', 'Y'

    # Populate file with input data
    # TODO: do we need to transpose?
    nav_lon[:, :] = grid_h['lont'].T
    nav_lat[:, :] = grid_h['latt'].T

    glamt[:, :] = grid_h['lont'].T
    glamu[:, :] = grid_h['lonu'].T
    glamv[:, :] = grid_h['lonv'].T
    glamf[:, :] = grid_h['lonf'].T
    gphit[:, :] = grid_h['latt'].T
    gphiu[:, :] = grid_h['latu'].T
    gphiv[:, :] = grid_h['latv'].T
    gphif[:, :] = grid_h['latf'].T

    ge1t[:, :] = grid_h['e1t'].T
    ge1u[:, :] = grid_h['e1u'].T
    ge1v[:, :] = grid_h['e1v'].T
    ge1f[:, :] = grid_h['e1f'].T
    ge2t[:, :] = grid_h['e2t'].T
    ge2u[:, :] = grid_h['e2u'].T
    ge2v[:, :] = grid_h['e2v'].T
    ge2f[:, :] = grid_h['e2f'].T

    # Close off pointer
    dataset.close()

    return 0

def write_coord_Z(fileout, grid_h,grid_z):
    '''
    Writes out a NEMO formatted coordinates file.

    Args:

    Returns:
    '''

    # Open pointer to netcdf file
    dataset = Dataset(fileout, 'w', format='NETCDF4_CLASSIC')

    # Get input size and create appropriate dimensions
    # TODO: add some sort of error handling
    nx, ny, nz = np.shape(grid_z['e3t'])
    dataset.createDimension('x', nx)
    dataset.createDimension('y', ny)
    dataset.createDimension('z', nz)


    # Create Variables
    nav_lon = dataset.createVariable('nav_lon', np.float32, ('y', 'x'))
    nav_lat = dataset.createVariable('nav_lat', np.float32, ('y', 'x'))
    nav_lev = dataset.createVariable('nav_lev', np.float32, 'z')

    ge3t1d = dataset.createVariable('e3t_1d', np.float64, 'z')
    ge3w1d = dataset.createVariable('e3w_1d', np.float64, 'z')
    gbat = dataset.createVariable('mbathy', np.float64, ('y', 'x'))
    ge3t = dataset.createVariable('e3t', np.float64, ('z','y', 'x'))
    ge3u = dataset.createVariable('e3u', np.float64, ('z','y', 'x'))
    ge3v = dataset.createVariable('e3v', np.float64, ('z','y', 'x'))
    ge3f = dataset.createVariable('e3f', np.float64, ('z','y', 'x'))
    ge3uw = dataset.createVariable('e3uw', np.float64, ('z', 'y', 'x'))
    ge3vw = dataset.createVariable('e3vw', np.float64, ('z', 'y', 'x'))

    nav_lon.units, nav_lon.long_name = 'km', 'X'
    nav_lat.units, nav_lat.long_name = 'km', 'Y'
    nav_lev.units, nav_lev.long_name = 'm', 'Z'

    # Populate file with input data
    # TODO: do we need to transpose?
    nav_lon[:, :] = grid_h['lont'].T
    nav_lat[:, :] = grid_h['latt'].T
    nav_lev[:] = grid_z['dept_1d']

    ge3t[:, :, :] = grid_z['e3t'].T
    ge3u[:, :, :] = grid_z['e3u'].T
    ge3v[:, :, :] = grid_z['e3v'].T
    ge3f[:, :, :] = grid_z['e3f'].T
    ge3uw[:, :, :] = grid_z['e3uw'].T
    ge3vw[:, :, :] = grid_z['e3vw'].T

    ge3t1d[:] = grid_z['e3t_1d']
    ge3w1d[:] = grid_z['e3w_1d']
    gbat[:,:] = grid_h['batt'].T


    # Close off pointer
    dataset.close()

    return 0

def write_domcfg(fileout, ln_zco, ln_zps, ln_sco, ln_isfcav, jperio, bat,
                 lont, latt, lonu, latu, lonv, latv, lonf, latf,
                 e1t, e2t, e1u, e2u, e1v, e2v, e1f, e2f, ff_f, ff_t,
                 dept_1d, e3t_1d, e3w_1d, e3t, e3u, e3v, e3f, e3w, e3uw, e3vw,
                 ktop, kbot):
    '''
    Writes out a NEMO formatted domcfg file.

    Args:
        fileout         (string): filename
        ln_zco         (logical): vertical coordinate flag [z-level]
        ln_zps         (logical): vertical coordinate flag [z-partial-step]
        ln_sco         (logical): vertical coordinate flag [sigma]
        ln_isfcav      (logical): ice cavity flag
        jperio             (int): domain type
        bat         (np.ndarray): bathymetry array at t-points (2D)
        lon[t/u/v/f](np.ndarray): longitude array at [t/u/v/f]-points (2D)
        lat[t/u/v/f](np.ndarray): latitude array at [t/u/v/f]-points (2D)
        e1[t/u/v/f] (np.ndarray): zonal scale factors at [t/u/v/f]-points
        e2[t/u/v/f] (np.ndarray): meridional scale factors at [t/u/v/f]-points
        ff_[f/t]    (np.ndarray): coriolis parameter at [t/f]-points
        dept_1d     (np.ndarray): 1D depth levels at t-points
        e3[t/w]_1d  (np.ndarray): 1D vertical scale factors at [t/w]-points
        e3[t/u/v/f] (np.ndarray): vertcal scale factors at [t/u/v/f]-points
        e3[w/uw/vw] (np.ndarray): vertcal scale factors at [w/uw/vw]-points
        ktop        (np.ndarray): upper most wet point
        kbot        (np.ndarray): lower most wet point

    Returns:
    '''

    # Open pointer to netcdf file
    dataset = Dataset(fileout, 'w', format='NETCDF4_CLASSIC')

    # Get input size and create appropriate dimensions
    # TODO: add some sort of error handling
    nx, ny, nz = np.shape(e3t)
    dataset.createDimension('x', nx)
    dataset.createDimension('y', ny)
    dataset.createDimension('z', nz)

    # create Variables
    nav_lon = dataset.createVariable('nav_lon', np.float32, ('y', 'x'))
    nav_lat = dataset.createVariable('nav_lat', np.float32, ('y', 'x'))
    nav_lev = dataset.createVariable('nav_lev', np.float32, 'z')

    giglo = dataset.createVariable('jpiglo', "i4")
    gjglo = dataset.createVariable('jpjglo', "i4")
    gkglo = dataset.createVariable('jpkglo', "i4")

    gperio = dataset.createVariable('jperio', "i4")

    gzco = dataset.createVariable('ln_zco', "i4")
    gzps = dataset.createVariable('ln_zps', "i4")
    gsco = dataset.createVariable('ln_sco', "i4")
    gcav = dataset.createVariable('ln_isfcav', "i4")

    ge3t1d = dataset.createVariable('e3t_1d', np.float64, 'z')
    ge3w1d = dataset.createVariable('e3w_1d', np.float64, 'z')
    gitop = dataset.createVariable('top_level', "i4", ('y', 'x'))
    gibot = dataset.createVariable('bottom_level', "i4", ('y', 'x'))
    gbat = dataset.createVariable('Bathymetry', np.float64, ('y', 'x'))
    glamt = dataset.createVariable('glamt', np.float64, ('y', 'x'))
    glamu = dataset.createVariable('glamu', np.float64, ('y', 'x'))
    glamv = dataset.createVariable('glamv', np.float64, ('y', 'x'))
    glamf = dataset.createVariable('glamf', np.float64, ('y', 'x'))
    gphit = dataset.createVariable('gphit', np.float64, ('y', 'x'))
    gphiu = dataset.createVariable('gphiu', np.float64, ('y', 'x'))
    gphiv = dataset.createVariable('gphiv', np.float64, ('y', 'x'))
    gphif = dataset.createVariable('gphif', np.float64, ('y', 'x'))
    ge1t = dataset.createVariable('e1t', np.float64, ('y', 'x'))
    ge1u = dataset.createVariable('e1u', np.float64, ('y', 'x'))
    ge1v = dataset.createVariable('e1v', np.float64, ('y', 'x'))
    ge1f = dataset.createVariable('e1f', np.float64, ('y', 'x'))
    ge2t = dataset.createVariable('e2t', np.float64, ('y', 'x'))
    ge2u = dataset.createVariable('e2u', np.float64, ('y', 'x'))
    ge2v = dataset.createVariable('e2v', np.float64, ('y', 'x'))
    ge2f = dataset.createVariable('e2f', np.float64, ('y', 'x'))
    gfff = dataset.createVariable('ff_f', np.float64, ('y', 'x'))
    gfft = dataset.createVariable('ff_t', np.float64, ('y', 'x'))
    ge3t = dataset.createVariable('e3t_0', np.float64, ('z', 'y', 'x'))
    ge3w = dataset.createVariable('e3w_0', np.float64, ('z', 'y', 'x'))
    ge3u = dataset.createVariable('e3u_0', np.float64, ('z', 'y', 'x'))
    ge3v = dataset.createVariable('e3v_0', np.float64, ('z', 'y', 'x'))
    ge3f = dataset.createVariable('e3f_0', np.float64, ('z', 'y', 'x'))
    ge3uw = dataset.createVariable('e3uw_0', np.float64, ('z', 'y', 'x'))
    ge3vw = dataset.createVariable('e3vw_0', np.float64, ('z', 'y', 'x'))

    nav_lon.units, nav_lon.long_name = 'km', 'X'
    nav_lat.units, nav_lat.long_name = 'km', 'Y'

    # Populate file with input data
    giglo[:] = nx
    gjglo[:] = ny
    gkglo[:] = nz

    gzco[:] = ln_zco
    gzps[:] = ln_zps
    gsco[:] = ln_sco
    gcav[:] = ln_isfcav

    gperio[:] = jperio

    # TODO: do we need to transpose?
    nav_lon[:, :] = lont.T
    nav_lat[:, :] = latt.T
    nav_lev[:] = dept_1d

    ge3t1d[:] = e3t_1d
    ge3w1d[:] = e3w_1d

    gitop[:, :] = ktop.T
    gibot[:, :] = kbot.T

    gbat[:, :] = bat.T

    glamt[:, :] = lont.T
    glamu[:, :] = lonu.T
    glamv[:, :] = lonv.T
    glamf[:, :] = lonf.T
    gphit[:, :] = latt.T
    gphiu[:, :] = latu.T
    gphiv[:, :] = latv.T
    gphif[:, :] = latf.T

    ge1t[:, :] = e1t.T
    ge1u[:, :] = e1u.T
    ge1v[:, :] = e1v.T
    ge1f[:, :] = e1f.T
    ge2t[:, :] = e2t.T
    ge2u[:, :] = e2u.T
    ge2v[:, :] = e2v.T
    ge2f[:, :] = e2f.T
    gfff[:, :] = ff_f.T
    gfft[:, :] = ff_t.T

    ge3t[:, :, :] = e3t.T
    ge3w[:, :, :] = e3w.T
    ge3u[:, :, :] = e3u.T
    ge3v[:, :, :] = e3v.T
    ge3f[:, :, :] = e3f.T
    ge3uw[:, :, :] = e3uw.T
    ge3vw[:, :, :] = e3vw.T

    # Close off pointer
    dataset.close()