Make in_4d and uses_ensemble non-public class attributes, user doesn't need them

Author: kysolvik

dabench/dacycler/_dacycler.py

@@ -32,14 +32,9 @@ class DACycler():
             If not provided will be calculated automatically.
         h: Optional observation operator as function. More flexible
             (allows for more complex observation operator). Default is None.
-    
-    Attributes:
-        in_4d: True for 4D data assimilation techniques (e.g. 4DVar).
-        ensemble: True for ensemble-based data assimilation techniques
-            (ETKF).
     """
-    in_4d = False
-    ensemble = False
+    _in_4d: bool = False
+    _uses_ensemble: bool = False
 
     def __init__(self,
                  system_dim: int,
@@ -229,7 +224,7 @@ def cycle(self,
 
         # If don't specify analysis_time_in_window, is assumed to be middle
         if analysis_time_in_window is None:
-            if self.in_4d:
+            if self._in_4d:
                 analysis_time_in_window = 0
             else:
                 analysis_time_in_window = self.analysis_window/2
@@ -256,7 +251,7 @@ def cycle(self,
             obs_times=jnp.array(obs_vector.time.values),
             analysis_times=all_times+_time_offset,
             start_inclusive=True,
-            end_inclusive=self.in_4d,
+            end_inclusive=self._in_4d,
             analysis_window=analysis_window
         )
         input_state = input_state.assign(_cur_time=start_time)
@@ -272,7 +267,7 @@ def cycle(self,
                 obs_vector[self._observed_vars].to_array().data)
             self._obs_vector=self._obs_vector.fillna(0)
 
-        if self.in_4d:
+        if self._in_4d:
             cur_state, all_values = jax.lax.scan(
                     self._cycle_and_forecast_4d,
                     xj.from_xarray(input_state),

dabench/dacycler/_etkf.py

@@ -38,8 +38,8 @@ class ETKF(dacycler.DACycler):
         multiplicative_inflation: Scaling factor by which to multiply ensemble
             deviation. Default is 1.0 (no inflation).
     """
-    in_4d = False
-    ensemble = True
+    _in_4d: bool = False
+    _uses_ensemble: bool = True
 
     def __init__(self,
                  system_dim: int,

dabench/dacycler/_var3d.py

@@ -33,8 +33,8 @@ class Var3D(dacycler.DACycler):
         h: Optional observation operator as function. More flexible
             (allows for more complex observation operator). Default is None.
         """
-    in_4d = False
-    ensemble = False
+    _in_4d: bool = False
+    _uses_ensemble: bool = False
 
     def __init__(self,
                  system_dim: int,

dabench/dacycler/_var4d.py

@@ -55,8 +55,8 @@ class Var4D(dacycler.DACycler):
             [0, 1, 2, 3, 4, 5]. If None (default), will calculate
             automatically.
     """
-    in_4d = True
-    ensemble = False
+    _in_4d: bool = True
+    _uses_ensemble: bool = False
 
     def __init__(self,
                  system_dim: int,

dabench/dacycler/_var4d_backprop.py

@@ -61,8 +61,8 @@ class Var4DBackprop(dacycler.DACycler):
             return an error. This prevents it from hanging indefinitely
             when loss grows exponentionally. Default is 10.
     """
-    in_4d = True
-    ensemble = False
+    _in_4d: bool = True
+    _uses_ensemble: bool = False
 
     def __init__(self,
                  system_dim: int,