CAMS working for interpolation

pycif/plugins/datastreams/fields/netcdf_cams/__init__.py

@@ -15,8 +15,9 @@ _fullname = "CAMS netcdf files"
 
 input_arguments={
     "aibi_name": {
-       "doc": "to choose ai bi vertical coordinate names"
-              " instead of hyam and hybm",
+       "doc": "To choose ai/bi vertical coordinate names"
+              " instead of hyam and hybm; this depends on the version of the CAMS "
+              "product to be read",
        "default": False,
        "accepted": bool
     },

pycif/plugins/datastreams/fields/netcdf_cams/get_domain.py

@@ -6,6 +6,7 @@ import xarray as xr
 from .....utils.classes.setup import Setup
 import copy
 
+
 def get_domain(ref_dir, ref_file, input_dates, target_dir, tracer=None):
     
     # Looking for a reference file to read lon/lat in
@@ -67,6 +68,7 @@ def get_domain(ref_dir, ref_file, input_dates, target_dir, tracer=None):
     else :
          sigma_a = nc["hyam"].values
          sigma_b = nc["hybm"].values
+        
     nlevs = sigma_a.size
 
     # Initializes domain

pycif/plugins/datastreams/fields/netcdf_cams/read.py

@@ -31,16 +31,16 @@ def read(
         comp_type: type of boundary conditions to generate
 
     """
-
+    
     if ddi is None:
         raise Exception("CAMS netCDF read function was called "
                         "without specifying ddi")
-
+    
     # Variable name to extract
     var2extract = name
     if varnames != "":
         var2extract = varnames
-        
+    
     # Reading fields for periods within the simulation window
     xout = []
     opened_file = ""
@@ -49,7 +49,7 @@ def read(
         if dd_file != opened_file:
             ds = xr.open_dataset(dd_file)
             opened_file = dd_file
-
+        
         ntimes = ds.dims["time"]
         
         freq = pd.DatetimeIndex([dd[0]]).days_in_month[0] * 24 / ntimes
@@ -59,13 +59,13 @@ def read(
         lat = ds['latitude']
         conc = ds[var2extract].values[date_index]
         
-       if lat[1] < lat[0] and conc.ndim==4:
+        if lat[1] < lat[0] and conc.ndim == 4:
             conc = conc[:, :, ::-1, :]
-       elif  lat[1] < lat[0] and conc.ndim==3:
-            conc = conc[ :, ::-1, :]
+        elif lat[1] < lat[0] and conc.ndim == 3:
+            conc = conc[:, ::-1, :]
         
         xout.append(conc)
-
+    
     xmod = xr.DataArray(
         np.array(xout),
         coords={"time": np.array(dates)[:, 0]},