Speed up wrfchem_icbc.fetch

By switching from xarray to netCDF4 for reading 'Times' in the boundary conditions file

pycif/plugins/datastreams/fields/wrfchem_icbc/fetch.py

 import os
 
-# import numpy as np
+import numpy as np
 # import pandas as pd
 import datetime as dtm
-import xarray as xr
+import netCDF4 as nc
 from pycif.utils import path
 
 # Copied from chimere_icbc, adapted to WRF
@@ -29,10 +29,11 @@ def fetch(
         filei = datei.strftime("{}/{}".format(ref_dir, ref_file))
         list_files = {datei: [filei]}
         # Get time intervals from file as datetime.datetime
-        ds = xr.open_dataset(filei)
-        times_bytestr = ds["Times"].data
-        ds.close()
-        times = [dtm.datetime.strptime(t.decode("utf-8"), "%Y-%m-%d_%H:%M:%S") for t in times_bytestr]
+        ncf = nc.Dataset(filei)
+        times_char = ncf["Times"][:].astype(str)
+        ncf.close()
+        times_str = np.apply_along_axis(lambda x:"".join(x), 1, times_char)
+        times = [dtm.datetime.strptime(t, "%Y-%m-%d_%H:%M:%S") for t in times_str]
         # Add one more timestep to cover the period of the last input
         # time. In the flux plugin, I added flux_freq to the config to
         # do this, but here, it's all in the same file and comes from