Remove discrete grid converter

src/lcm/entry_point.py

@@ -170,7 +170,6 @@ def get_lcm_function(
         continuous_choice_grids=continuous_choice_grids,
         compute_ccv_functions=compute_ccv_functions,
         emax_calculators=emax_calculators,
-        discrete_grid_converter=_mod.discrete_grid_converter,
         logger=logger,
     )
 
@@ -184,7 +183,6 @@ def get_lcm_function(
         compute_ccv_policy_functions=compute_ccv_policy_functions,
         model=_mod,
         next_state=jax.jit(_next_state_simulate),
-        discrete_grid_converter=_mod.discrete_grid_converter,
         logger=logger,
     )
 
@@ -195,8 +193,7 @@ def get_lcm_function(
     elif targets == "solve_and_simulate":
         _target = partial(simulate_model, solve_model=solve_model)
 
-    user_params = _mod.discrete_grid_converter.internal_params_to_params(_mod.params)
-    return cast(Callable, _target), user_params
+    return cast(Callable, _target), _mod.params
 
 
 def create_compute_conditional_continuation_value(

src/lcm/input_processing/__init__.py

@@ -1,4 +1,3 @@
-from .discrete_grid_conversion import DiscreteGridConverter
 from .process_model import process_model
 
-__all__ = ["process_model", "DiscreteGridConverter"]
+__all__ = ["process_model"]

src/lcm/input_processing/process_model.py

@@ -9,9 +9,6 @@
 
 from lcm.functools import all_as_args, all_as_kwargs
 from lcm.input_processing.create_params_template import create_params_template
-from lcm.input_processing.discrete_grid_conversion import (
-    convert_arbitrary_codes_to_array_indices,
-)
 from lcm.input_processing.util import (
     get_function_info,
     get_grids,
@@ -39,21 +36,18 @@ def process_model(model: Model) -> InternalModel:
         The processed model.
 
     """
-    tmp_model, converter = convert_arbitrary_codes_to_array_indices(model)
-
-    params = create_params_template(tmp_model)
+    params = create_params_template(model)
 
     return InternalModel(
-        grids=get_grids(tmp_model),
-        gridspecs=get_gridspecs(tmp_model),
-        variable_info=get_variable_info(tmp_model),
-        functions=_get_internal_functions(tmp_model, params=params),
-        function_info=get_function_info(tmp_model),
+        grids=get_grids(model),
+        gridspecs=get_gridspecs(model),
+        variable_info=get_variable_info(model),
+        functions=_get_internal_functions(model, params=params),
+        function_info=get_function_info(model),
         params=params,
-        discrete_grid_converter=converter,
         # currently no additive utility shocks are supported
         random_utility_shocks=ShockType.NONE,
-        n_periods=tmp_model.n_periods,
+        n_periods=model.n_periods,
     )
 
 

src/lcm/interfaces.py

@@ -5,7 +5,6 @@
 from jax import Array
 
 from lcm.grids import ContinuousGrid, DiscreteGrid, Grid
-from lcm.input_processing import DiscreteGridConverter
 from lcm.typing import ParamsDict, ShockType
 
 
@@ -94,8 +93,6 @@ class InternalModel:
             True if the function has the corresponding property. The columns are:
             is_filter, is_constraint, is_next.
         params: Dict of model parameters.
-        discrete_grid_converter: Helps with converting between internal and external
-            representations of model variables and associated parameters.
         n_periods: Number of periods.
         random_utility_shocks: Type of random utility shocks.
 
@@ -107,7 +104,6 @@ class InternalModel:
     functions: dict[str, Callable]
     function_info: pd.DataFrame
     params: ParamsDict
-    discrete_grid_converter: DiscreteGridConverter
     n_periods: int
     # Not properly processed yet
     random_utility_shocks: ShockType