function for loading IRIS data into yt from xarray

IRIS_data_xr_to_yt.py

import xarray as xr
import yt
import os
import numpy as np
import cartopy.feature as cfeature
import cartopy.crs as ccrs

ddir = os.path.join(yt.config.ytcfg.get('yt','test_data_dir'), 'sample_nc')
      

# https://ds.iris.edu/files/products/emc/emc-files/GYPSUM_percent.nc : a global model
# https://ds.iris.edu/files/products/emc/emc-files/wUS-SH-2010_percent.nc : a non-global model covering the western US


datasets = {
    "internal_geographic_partial": os.path.join(ddir,'wUS-SH-2010_percent.nc'), 
    "internal_geographic_global": os.path.join(ddir,'GYPSUM_percent.nc'), 
}

def get_internal_IRIS(case):
    # both datasets have the same variables and dimension order
    
    fi = datasets[case]

    with xr.open_dataset(fi) as xr_ds:
        dvs = xr_ds.dvs.to_masked_array().data
        deprng = [xr_ds.depth.data.min(), xr_ds.depth.data.max()]
        lonrng=[xr_ds.longitude.data.min(), xr_ds.longitude.data.max()]
        latrng=[xr_ds.latitude.data.min(), xr_ds.latitude.data.max()]

    data = {'dvs': (dvs, "%")}
    
    bbox = np.array([
      deprng,   
      latrng,
      lonrng
    ])

    dims = ['depth', 'latitude', 'longitude']

    return yt.load_uniform_grid(data, data['dvs'][0].shape, 1.0, 
                                geometry=("internal_geographic", dims),
                                bbox=bbox)