#!/usr/bin/env python
# coding: utf-8

# # DFS2 - Export to NetCDF

# In[1]:


# pip install mikeio xarray netcdf4


# In[2]:


import mikeio
import xarray as xr
import numpy as np


# In[3]:


ds = mikeio.read("../tests/testdata/gebco_sound.dfs2")


# In[4]:


ds.Elevation.plot();


# The simplest approach is to use the `Dataset.to_xarray()` or `DataArray.to_xarray()` method, if no custom information is neeeded.

# In[5]:


xr_ds = ds.to_xarray()
xr_ds


# In[6]:


xr_da = ds.Elevation.to_xarray()
xr_da


# Save it as a NetCDF file:

# In[7]:


xr_da.to_netcdf("gebco_std.nc")


# ## Customized NetCDF

# 1. Time-invariant file -> remove time dimension
# 2. Rename y, x to lat, lon
# 3. Lowercase names
# 4. Add other metadata

# In[8]:


x = ds.geometry.x
y = ds.geometry.y


# In[9]:


res = {}

spdims = ["lat", "lon"]

if len(ds.time) > 1:
    dims = ["t"] + spdims
    coords = {"t": ds.time}
else:
    dims = spdims
    coords = {}
    
coords["lon"] = xr.DataArray(x, dims="lon", attrs={"standard_name" : "longitude", "units" : "degrees_east"})
coords["lat"] = xr.DataArray(y, dims="lat", attrs={"standard_name" : "latitude", "units" : "degrees_north"})

for da in ds:
    name = da.name.lower()
    res[name] = xr.DataArray(np.squeeze(da.to_numpy()), dims=dims, 
    attrs={'name': name,
            # TODO add standard name from https://cfconventions.org/standard-names.html
            'units': da.unit.name,
            'eumType' : da.type,
            'eumUnit' : da.unit})        

xr_ds = xr.Dataset(res, coords=coords, attrs={'title': 'Converted from Dfs2 by MIKE IO'})


# In[10]:


xr_ds


# In[11]:


xr_ds.elevation.plot();


# In[12]:


xr_ds.to_netcdf("gebco.nc")


# # Clean up

# In[13]:


import os
os.remove("gebco_std.nc")
os.remove("gebco.nc")