From ee48e30335db2a84b377ee9df12d925863a17692 Mon Sep 17 00:00:00 2001
From: Tim Mensinger <mensingertim@gmail.com>
Date: Mon, 23 Sep 2024 12:05:41 +0200
Subject: [PATCH] Allow general discrete grids (#90)

---
 .github/workflows/main.yml                    |   15 +-
 .pre-commit-config.yaml                       |    2 +-
 examples/long_running.py                      |   13 +-
 explanations/dispatchers.ipynb                |   12 +-
 explanations/function_representation.ipynb    |   10 +-
 pixi.lock                                     | 1562 +++++++++--------
 pyproject.toml                                |    6 +-
 src/lcm/entry_point.py                        |    7 +-
 src/lcm/grids.py                              |  140 +-
 src/lcm/input_processing/__init__.py          |    3 +-
 .../discrete_grid_conversion.py               |  280 +++
 src/lcm/input_processing/process_model.py     |   20 +-
 src/lcm/input_processing/util.py              |    2 +-
 src/lcm/interfaces.py                         |    4 +
 src/lcm/simulate.py                           |   29 +-
 src/lcm/solve_brute.py                        |    9 +-
 src/lcm/user_model.py                         |   37 +-
 tests/conftest.py                             |   18 +
 .../test_create_params_template.py            |    6 +-
 .../test_discrete_state_conversion.py         |  156 ++
 tests/input_processing/test_process_model.py  |   30 +-
 tests/test_entry_point.py                     |   58 +-
 tests/test_grids.py                           |  105 +-
 tests/test_model.py                           |   12 +-
 tests/test_model_functions.py                 |    1 +
 tests/test_models/deterministic.py            |   80 +-
 tests/test_models/stochastic.py               |   28 +-
 tests/test_next_state.py                      |    1 +
 tests/test_simulate.py                        |   33 +-
 tests/test_solution_on_toy_model.py           |   26 +-
 tests/test_solve_brute.py                     |    2 +
 tests/test_state_space.py                     |    3 +-
 32 files changed, 1729 insertions(+), 981 deletions(-)
 create mode 100644 src/lcm/input_processing/discrete_grid_conversion.py
 create mode 100644 tests/input_processing/test_discrete_state_conversion.py

diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index f0420fe4..82baa5a1 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -26,15 +26,16 @@ jobs:
           - '3.12'
     steps:
       - uses: actions/checkout@v4
-      - uses: prefix-dev/setup-pixi@v0.8.0
+      - uses: prefix-dev/setup-pixi@v0.8.1
         with:
           pixi-version: v0.29.0
           cache: true
           cache-write: ${{ github.event_name == 'push' && github.ref_name == 'main' }}
           environments: test-cpu
           activate-environment: true
+          frozen: true
       - name: Run pytest
-        shell: bash -l {0}
+        shell: bash {0}
         run: pixi run -e test-cpu tests
       - name: Upload coverage report
         if: runner.os == 'Linux' && matrix.python-version == '3.12'
@@ -46,26 +47,28 @@ jobs:
       fail-fast: false
     steps:
       - uses: actions/checkout@v4
-      - uses: prefix-dev/setup-pixi@v0.8.0
+      - uses: prefix-dev/setup-pixi@v0.8.1
         with:
           pixi-version: v0.29.0
           cache: true
           cache-write: ${{ github.event_name == 'push' && github.ref_name == 'main' }}
           environments: mypy
+          frozen: true
       - name: Run mypy
-        shell: bash -l {0}
+        shell: bash {0}
         run: pixi run mypy
   run-explanation-notebooks:
     name: Run explanation notebooks on Python 3.12
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: prefix-dev/setup-pixi@v0.8.0
+      - uses: prefix-dev/setup-pixi@v0.8.1
         with:
           pixi-version: v0.29.0
           cache: true
           cache-write: ${{ github.event_name == 'push' && github.ref_name == 'main' }}
           environments: test-cpu
+          frozen: true
       - name: Run explanation notebooks
-        shell: bash -l {0}
+        shell: bash {0}
         run: pixi run -e test-cpu explanation-notebooks
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 4912e6d8..c6c5559a 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -46,7 +46,7 @@ repos:
     hooks:
       - id: yamllint
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.4
+    rev: v0.6.5
     hooks:
       # Run the linter.
       - id: ruff
diff --git a/examples/long_running.py b/examples/long_running.py
index 9c54a5f0..992987a5 100644
--- a/examples/long_running.py
+++ b/examples/long_running.py
@@ -1,5 +1,7 @@
 """Example specification for a consumption-savings model with health and exercise."""
 
+from dataclasses import dataclass
+
 import jax.numpy as jnp
 
 from lcm import DiscreteGrid, LinspaceGrid, Model
@@ -9,6 +11,15 @@
 # ======================================================================================
 
 
+# --------------------------------------------------------------------------------------
+# Categorical variables
+# --------------------------------------------------------------------------------------
+@dataclass
+class WorkingStatus:
+    retired: int = 0
+    working: int = 1
+
+
 # --------------------------------------------------------------------------------------
 # Utility function
 # --------------------------------------------------------------------------------------
@@ -67,7 +78,7 @@ def consumption_constraint(consumption, wealth, labor_income):
         "age": age,
     },
     choices={
-        "working": DiscreteGrid([0, 1]),
+        "working": DiscreteGrid(WorkingStatus),
         "consumption": LinspaceGrid(
             start=1,
             stop=100,
diff --git a/explanations/dispatchers.ipynb b/explanations/dispatchers.ipynb
index 81aae290..cab40c16 100644
--- a/explanations/dispatchers.ipynb
+++ b/explanations/dispatchers.ipynb
@@ -16,6 +16,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from dataclasses import dataclass\n",
+    "\n",
     "import jax.numpy as jnp\n",
     "import pytest\n",
     "from jax import vmap\n",
@@ -277,6 +279,12 @@
     "from lcm import DiscreteGrid, LinspaceGrid, Model\n",
     "\n",
     "\n",
+    "@dataclass\n",
+    "class RetirementStatus:\n",
+    "    working: int = 0\n",
+    "    retired: int = 1\n",
+    "\n",
+    "\n",
     "def utility(consumption, retirement, lagged_retirement, wealth):\n",
     "    working = 1 - retirement\n",
     "    retirement_habit = lagged_retirement * wealth\n",
@@ -296,11 +304,11 @@
     "    },\n",
     "    n_periods=1,\n",
     "    choices={\n",
-    "        \"retirement\": DiscreteGrid([0, 1]),\n",
+    "        \"retirement\": DiscreteGrid(RetirementStatus),\n",
     "        \"consumption\": LinspaceGrid(start=1, stop=2, n_points=2),\n",
     "    },\n",
     "    states={\n",
-    "        \"lagged_retirement\": DiscreteGrid([0, 1]),\n",
+    "        \"lagged_retirement\": DiscreteGrid(RetirementStatus),\n",
     "        \"wealth\": LinspaceGrid(start=1, stop=4, n_points=4),\n",
     "    },\n",
     ")"
diff --git a/explanations/function_representation.ipynb b/explanations/function_representation.ipynb
index 0e89ddb5..82c4429b 100644
--- a/explanations/function_representation.ipynb
+++ b/explanations/function_representation.ipynb
@@ -76,11 +76,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from dataclasses import dataclass\n",
+    "\n",
     "import jax.numpy as jnp\n",
     "\n",
     "from lcm import DiscreteGrid, LinspaceGrid, Model\n",
     "\n",
     "\n",
+    "@dataclass\n",
+    "class RetirementStatus:\n",
+    "    working: int = 0\n",
+    "    retired: int = 1\n",
+    "\n",
+    "\n",
     "def utility(consumption, working, disutility_of_work):\n",
     "    return jnp.log(consumption) - disutility_of_work * working\n",
     "\n",
@@ -125,7 +133,7 @@
     "        \"age\": age,\n",
     "    },\n",
     "    choices={\n",
-    "        \"retirement\": DiscreteGrid([0, 1]),\n",
+    "        \"retirement\": DiscreteGrid(RetirementStatus),\n",
     "        \"consumption\": LinspaceGrid(start=1, stop=400, n_points=20),\n",
     "    },\n",
     "    states={\n",
diff --git a/pixi.lock b/pixi.lock
index 4f2c9a9f..ed084c55 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -20,7 +20,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/babel-2.14.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/beautifulsoup4-4.12.3-pyha770c72_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.40-ha1999f0_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.40-hb3c18ed_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.40-hb3c18ed_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/bleach-6.1.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py312h2ec8cdc_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h4bc722e_7.conda
@@ -63,23 +63,23 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.2.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/executing-2.1.0-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.16.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.16.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/fqdn-1.5.1-pyhd8ed1ab_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-13.3.0-hfea6d02_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-13.3.0-hc28eda2_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-13.3.0-hc28eda2_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-13.3.0-hdbfa832_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-13.3.0-h6834431_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-13.3.0-h6834431_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/h11-0.14.0-pyhd8ed1ab_0.tar.bz2
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       - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.5-pyhd8ed1ab_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.0.1-pyhd8ed1ab_0.tar.bz2
-      - conda: https://conda.anaconda.org/conda-forge/noarch/identify-2.6.0-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/idna-3.8-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-8.4.0-pyha770c72_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib_metadata-8.4.0-hd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib_resources-6.4.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/identify-2.6.1-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/idna-3.10-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-8.5.0-pyha770c72_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib_metadata-8.5.0-hd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/importlib_resources-6.4.5-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.29.5-pyh3099207_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ipython-8.27.0-pyh707e725_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/isoduration-20.11.0-pyhd8ed1ab_0.tar.bz2
@@ -93,7 +93,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.23.0-hd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.5-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.6.2-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.6.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.7.2-py312h7900ff3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.14.2-pyhd8ed1ab_0.conda
@@ -106,8 +106,8 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/linux-64/libabseil-20240116.2-cxx17_he02047a_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-23_linux64_openblas.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-23_linux64_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-24_linux64_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-24_linux64_openblas.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcublas-12.6.1.4-h5888daf_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcurand-10.3.7.68-h5888daf_0.conda
@@ -124,7 +124,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-14.1.0-h77fa898_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgrpc-1.62.2-h15f2491_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-23_linux64_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-24_linux64_openblas.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hd590300_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libnvjitlink-12.6.68-h5888daf_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.27-pthreads_hac2b453_1.conda
@@ -142,7 +142,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/mistune-3.0.2-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ml_dtypes-0.4.0-py312hf9745cd_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ml_dtypes-0.5.0-py312hf9745cd_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.10.0-pyhd8ed1ab_0.conda
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@@ -162,8 +162,8 @@ environments:
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-      - conda: https://conda.anaconda.org/conda-forge/noarch/plotly-5.24.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/platformdirs-4.3.6-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/plotly-5.24.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.8.0-pyha770c72_1.conda
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@@ -179,7 +179,7 @@ environments:
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-      - conda: https://conda.anaconda.org/conda-forge/noarch/pytz-2024.1-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytz-2024.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pyyaml-6.0.2-py312h66e93f0_1.conda
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@@ -191,7 +191,7 @@ environments:
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-      - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-73.0.1-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-74.1.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/six-1.16.0-pyh6c4a22f_0.tar.bz2
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@@ -212,8 +212,8 @@ environments:
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+  url: https://conda.anaconda.org/conda-forge/noarch/setuptools-74.1.2-pyhd8ed1ab_0.conda
+  sha256: 71a4603248167bacc0aa985697a93aff62f6bcf008edaece09e79e83e43a7e22
+  md5: 56c9c11d004428e81d02eeb730fc6336
   depends:
   - python >=3.8
   license: MIT
   license_family: MIT
   purls:
-  - pkg:pypi/setuptools?source=hash-mapping
-  size: 1460460
-  timestamp: 1725348602179
+  - pkg:pypi/setuptools?source=compressed-mapping
+  size: 784583
+  timestamp: 1726752322559
 - kind: conda
   name: six
   version: 1.16.0
@@ -12895,6 +12926,7 @@ packages:
   - vc >=14.2,<15
   - vc14_runtime >=14.29.30139
   license: Apache-2.0
+  license_family: APACHE
   purls: []
   size: 151494
   timestamp: 1725532984828
@@ -13209,20 +13241,20 @@ packages:
   timestamp: 1725623878468
 - kind: conda
   name: types-pytz
-  version: 2024.1.0.20240417
+  version: 2024.2.0.20240913
   build: pyhd8ed1ab_0
   subdir: noarch
   noarch: python
-  url: https://conda.anaconda.org/conda-forge/noarch/types-pytz-2024.1.0.20240417-pyhd8ed1ab_0.conda
-  sha256: cc3913a5504b867c748981ba302e82dbc2bda71837f4894d29db8f6cb490e25d
-  md5: 7b71ace1b99195041329427c435b8125
+  url: https://conda.anaconda.org/conda-forge/noarch/types-pytz-2024.2.0.20240913-pyhd8ed1ab_0.conda
+  sha256: c2af0198a110223effe3508e598ac9d3351a68740faaf5cb737ffaa51b108233
+  md5: fa0073139a0bde9a14637bbe1fe2f1d3
   depends:
   - python >=3.6
   license: Apache-2.0 AND MIT
   purls:
   - pkg:pypi/types-pytz?source=hash-mapping
-  size: 18725
-  timestamp: 1713337633292
+  size: 18599
+  timestamp: 1726210576932
 - kind: conda
   name: typing-extensions
   version: 4.12.2
@@ -13414,14 +13446,13 @@ packages:
   timestamp: 1688655976471
 - kind: conda
   name: urllib3
-  version: 2.2.2
-  build: pyhd8ed1ab_1
-  build_number: 1
+  version: 2.2.3
+  build: pyhd8ed1ab_0
   subdir: noarch
   noarch: python
-  url: https://conda.anaconda.org/conda-forge/noarch/urllib3-2.2.2-pyhd8ed1ab_1.conda
-  sha256: 00c47c602c03137e7396f904eccede8cc64cc6bad63ce1fc355125df8882a748
-  md5: e804c43f58255e977093a2298e442bb8
+  url: https://conda.anaconda.org/conda-forge/noarch/urllib3-2.2.3-pyhd8ed1ab_0.conda
+  sha256: b6bb34ce41cd93956ad6eeee275ed52390fb3788d6c75e753172ea7ac60b66e5
+  md5: 6b55867f385dd762ed99ea687af32a69
   depends:
   - brotli-python >=1.0.9
   - h2 >=4,<5
@@ -13432,17 +13463,17 @@ packages:
   license_family: MIT
   purls:
   - pkg:pypi/urllib3?source=hash-mapping
-  size: 95048
-  timestamp: 1719391384778
+  size: 98076
+  timestamp: 1726496531769
 - kind: conda
   name: vc
   version: '14.3'
-  build: h8a93ad2_20
-  build_number: 20
+  build: h8a93ad2_21
+  build_number: 21
   subdir: win-64
-  url: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h8a93ad2_20.conda
-  sha256: 23ac5feb15a9adf3ab2b8c4dcd63650f8b7ae860c5ceb073e49cf71d203eddef
-  md5: 8558f367e1d7700554f7cdb823c46faf
+  url: https://conda.anaconda.org/conda-forge/win-64/vc-14.3-h8a93ad2_21.conda
+  sha256: f14f5238c2e2516e292af43d91df88f212d769b4853eb46d03291793dcf00da9
+  md5: e632a9b865d4b653aa656c9fb4f4817c
   depends:
   - vc14_runtime >=14.40.33810
   track_features:
@@ -13450,61 +13481,62 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 17391
-  timestamp: 1717709040616
+  size: 17243
+  timestamp: 1725984095174
 - kind: conda
   name: vc14_runtime
   version: 14.40.33810
-  build: hcc2c482_20
-  build_number: 20
+  build: ha82c5b3_21
+  build_number: 21
   subdir: win-64
-  url: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.40.33810-hcc2c482_20.conda
-  sha256: bba8daa6f78b26b48fb7e1377eb52160e25495710bf53146c5f405bd50565982
-  md5: ad33c7cd933d69b9dee0f48317cdf137
+  url: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.40.33810-ha82c5b3_21.conda
+  sha256: c3bf51bff7db39ad7e890dbef1b1026df0af36975aea24dea7c5fe1e0b382c40
+  md5: b3ebb670caf046e32b835fbda056c4f9
   depends:
   - ucrt >=10.0.20348.0
   constrains:
-  - vs2015_runtime 14.40.33810.* *_20
+  - vs2015_runtime 14.40.33810.* *_21
   license: LicenseRef-ProprietaryMicrosoft
   license_family: Proprietary
   purls: []
-  size: 751028
-  timestamp: 1724712684919
+  size: 751757
+  timestamp: 1725984166774
 - kind: conda
   name: virtualenv
-  version: 20.26.4
+  version: 20.26.5
   build: pyhd8ed1ab_0
   subdir: noarch
   noarch: python
-  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.26.4-pyhd8ed1ab_0.conda
-  sha256: 6eeb4f9e541f2e5198185c44ab4f5a2bdf700ca395b18617e12a8e00cf176d05
-  md5: 14c15fa7def506fe7d1a0e3abdc212d6
+  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.26.5-pyhd8ed1ab_0.conda
+  sha256: 09ee54637f1979c8e9955a363ff9637454cbf63af509cf45a44f184a9ed27a15
+  md5: 949a6778521278cb96d7491bd99a5418
   depends:
   - distlib <1,>=0.3.7
   - filelock <4,>=3.12.2
   - platformdirs <5,>=3.9.1
   - python >=3.8
   license: MIT
+  license_family: MIT
   purls:
   - pkg:pypi/virtualenv?source=hash-mapping
-  size: 4886907
-  timestamp: 1725779361477
+  size: 4876524
+  timestamp: 1726642673644
 - kind: conda
   name: vs2015_runtime
   version: 14.40.33810
-  build: h3bf8584_20
-  build_number: 20
+  build: h3bf8584_21
+  build_number: 21
   subdir: win-64
-  url: https://conda.anaconda.org/conda-forge/win-64/vs2015_runtime-14.40.33810-h3bf8584_20.conda
-  sha256: 0c2803f7a788c51f28235a7228dc2ab3f107b4b16ab0845a3e595c8c51e50a7a
-  md5: c21f1b4a3a30bbc3ef35a50957578e0e
+  url: https://conda.anaconda.org/conda-forge/win-64/vs2015_runtime-14.40.33810-h3bf8584_21.conda
+  sha256: 472410455c381e406ec8c1d3e0342b48ee23122ef7ffb22a09d9763ca5df4d20
+  md5: b3f37db7b7ae1c22600fa26a63ed99b3
   depends:
   - vc14_runtime >=14.40.33810
   license: BSD-3-Clause
   license_family: BSD
   purls: []
-  size: 17395
-  timestamp: 1717709043353
+  size: 17241
+  timestamp: 1725984096440
 - kind: conda
   name: wayland
   version: 1.23.1
@@ -13645,15 +13677,15 @@ packages:
   timestamp: 1718843348208
 - kind: conda
   name: xcb-util-cursor
-  version: 0.1.4
-  build: h4ab18f5_2
-  build_number: 2
+  version: 0.1.5
+  build: hb9d3cd8_0
   subdir: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/xcb-util-cursor-0.1.4-h4ab18f5_2.conda
-  sha256: c72e58bae4a7972ca4dee5e850e82216222c06d53b3651e1ca7db8b5d2fc95fe
-  md5: 79e46d4a6ccecb7ee1912042958a8758
+  url: https://conda.anaconda.org/conda-forge/linux-64/xcb-util-cursor-0.1.5-hb9d3cd8_0.conda
+  sha256: c7b35db96f6e32a9e5346f97adc968ef2f33948e3d7084295baebc0e33abdd5b
+  md5: eb44b3b6deb1cab08d72cb61686fe64c
   depends:
-  - libgcc-ng >=12
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=13
   - libxcb >=1.13
   - libxcb >=1.16,<1.17.0a0
   - xcb-util-image >=0.4.0,<0.5.0a0
@@ -13661,8 +13693,8 @@ packages:
   license: MIT
   license_family: MIT
   purls: []
-  size: 20397
-  timestamp: 1718899451268
+  size: 20296
+  timestamp: 1726125844850
 - kind: conda
   name: xcb-util-image
   version: 0.4.0
@@ -14061,23 +14093,23 @@ packages:
 - kind: conda
   name: xorg-libxxf86vm
   version: 1.1.5
-  build: h4bc722e_1
-  build_number: 1
+  build: hb9d3cd8_2
+  build_number: 2
   subdir: linux-64
-  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxxf86vm-1.1.5-h4bc722e_1.conda
-  sha256: 109d6b1931d1482faa0bf6de83c7e6d9ca36bbf9d36a00a05df4f63b82fce5c3
-  md5: 0c90ad87101001080484b91bd9d2cdef
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxxf86vm-1.1.5-hb9d3cd8_2.conda
+  sha256: 449e39b31711325738434f5e6db0c51c9e84d96e4005ec0acd9d1f500c05e8e7
+  md5: 1bc52d70c5dc46b1792e039b4fa120a0
   depends:
   - __glibc >=2.17,<3.0.a0
-  - libgcc-ng >=12
+  - libgcc >=13
   - xorg-libx11 >=1.8.9,<2.0a0
   - xorg-libxext >=1.3.4,<2.0a0
   - xorg-xextproto >=7.3.0,<8.0a0
   license: MIT
   license_family: MIT
   purls: []
-  size: 18443
-  timestamp: 1722110433983
+  size: 18332
+  timestamp: 1726233001299
 - kind: conda
   name: xorg-recordproto
   version: 1.14.2
@@ -14336,21 +14368,21 @@ packages:
   timestamp: 1725430044838
 - kind: conda
   name: zipp
-  version: 3.20.1
+  version: 3.20.2
   build: pyhd8ed1ab_0
   subdir: noarch
   noarch: python
-  url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.20.1-pyhd8ed1ab_0.conda
-  sha256: 30762bd25b6fc8714d5520a223ccf20ad4a6792dc439c54b59bf44b60bf51e72
-  md5: 74a4befb4b38897e19a107693e49da20
+  url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.20.2-pyhd8ed1ab_0.conda
+  sha256: 1e84fcfa41e0afdd87ff41e6fbb719c96a0e098c1f79be342293ab0bd8dea322
+  md5: 4daaed111c05672ae669f7036ee5bba3
   depends:
   - python >=3.8
   license: MIT
   license_family: MIT
   purls:
   - pkg:pypi/zipp?source=hash-mapping
-  size: 21110
-  timestamp: 1724731063145
+  size: 21409
+  timestamp: 1726248679175
 - kind: conda
   name: zlib
   version: 1.3.1
diff --git a/pyproject.toml b/pyproject.toml
index d589ec9d..085dccff 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -227,11 +227,11 @@ extend-ignore = [
 
 [tool.ruff.lint.per-file-ignores]
 "docs/source/conf.py" = ["E501", "ERA001", "DTZ005"]
-"tests/*" = ["PLR2004"]
-"examples/*" = ["INP001"]
+"tests/*" = ["PLR2004", "D101"]
+"examples/*" = ["INP001", "D101"]
 "explanations/*" = ["INP001", "B018", "T201", "E402", "PD008"]
 "scripts/*" = ["INP001", "D101", "RET503"]
-"**/*.ipynb" = ["FBT003", "E402"]
+"**/*.ipynb" = ["FBT003", "E402", "D101"]
 
 [tool.ruff.lint.pydocstyle]
 convention = "google"
diff --git a/src/lcm/entry_point.py b/src/lcm/entry_point.py
index 2ccf5148..f41c247f 100644
--- a/src/lcm/entry_point.py
+++ b/src/lcm/entry_point.py
@@ -66,7 +66,7 @@ def get_lcm_function(
     if targets not in {"solve", "simulate", "solve_and_simulate"}:
         raise NotImplementedError
 
-    _mod = process_model(model=model)
+    _mod = process_model(model)
     last_period = _mod.n_periods - 1
     interpolation_options = DefaultMapCoordinatesOptions | (interpolation_options or {})
 
@@ -170,6 +170,7 @@ 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,
     )
 
@@ -183,6 +184,7 @@ 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,
     )
 
@@ -193,7 +195,8 @@ def get_lcm_function(
     elif targets == "solve_and_simulate":
         _target = partial(simulate_model, solve_model=solve_model)
 
-    return cast(Callable, _target), _mod.params
+    user_params = _mod.discrete_grid_converter.internal_params_to_params(_mod.params)
+    return cast(Callable, _target), user_params
 
 
 def create_compute_conditional_continuation_value(
diff --git a/src/lcm/grids.py b/src/lcm/grids.py
index 15c89bce..9ea98432 100644
--- a/src/lcm/grids.py
+++ b/src/lcm/grids.py
@@ -1,8 +1,8 @@
 """Collection of classes that are used by the user to define the model and grids."""
 
 from abc import ABC, abstractmethod
-from collections.abc import Collection
-from dataclasses import dataclass
+from dataclasses import dataclass, fields, is_dataclass
+from typing import Any
 
 import jax.numpy as jnp
 from jax import Array
@@ -16,37 +16,56 @@ class Grid(ABC):
     """LCM Grid base class."""
 
     @abstractmethod
-    def to_jax(self) -> jnp.ndarray:
+    def to_jax(self) -> Array:
         """Convert the grid to a Jax array."""
 
 
-@dataclass(frozen=True)
 class DiscreteGrid(Grid):
-    """A grid of discrete values.
+    """A class representing a discrete grid.
+
+    Args:
+        category_class (type): The category class representing the grid categories. Must
+            be a dataclass with fields that have unique scalar int or float values.
 
     Attributes:
-        options: The options in the grid. Must be an iterable of scalar int or float
-            values.
+        categories: The list of category names.
+        codes: The list of category codes.
+
+    Raises:
+        GridInitializationError: If the `category_class` is not a dataclass with scalar
+            int or float fields.
 
     """
 
-    options: Collection[int | float]
+    def __init__(self, category_class: type) -> None:
+        """Initialize the DiscreteGrid.
 
-    def __post_init__(self) -> None:
-        if not isinstance(self.options, Collection):
-            raise GridInitializationError(
-                "options must be a collection of scalar int or float values, e.g., a ",
-                "list or tuple",
-            )
+        Args:
+            category_class (type): The category class representing the grid categories.
+                Must be a dataclass with fields that have unique scalar int or float
+                values.
+
+        """
+        _validate_discrete_grid(category_class)
+
+        names_and_values = _get_field_names_and_values(category_class)
 
-        errors = _validate_discrete_grid(self.options)
-        if errors:
-            msg = format_messages(errors)
-            raise GridInitializationError(msg)
+        self.__categories = tuple(names_and_values.keys())
+        self.__codes = tuple(names_and_values.values())
+
+    @property
+    def categories(self) -> tuple[str, ...]:
+        """Get the list of category names."""
+        return self.__categories
+
+    @property
+    def codes(self) -> tuple[int | float, ...]:
+        """Get the list of category codes."""
+        return self.__codes
 
     def to_jax(self) -> Array:
         """Convert the grid to a Jax array."""
-        return jnp.array(list(self.options))
+        return jnp.array(self.codes)
 
 
 @dataclass(frozen=True, kw_only=True)
@@ -58,14 +77,11 @@ class ContinuousGrid(Grid, ABC):
     n_points: int
 
     def __post_init__(self) -> None:
-        errors = _validate_continuous_grid(
+        _validate_continuous_grid(
             start=self.start,
             stop=self.stop,
             n_points=self.n_points,
         )
-        if errors:
-            msg = format_messages(errors)
-            raise GridInitializationError(msg)
 
     @abstractmethod
     def to_jax(self) -> Array:
@@ -131,40 +147,78 @@ def get_coordinate(self, value: Scalar) -> Scalar:
 # ======================================================================================
 
 
-def _validate_discrete_grid(options: Collection[int | float]) -> list[str]:
-    """Validate the discrete grid options.
+def _validate_discrete_grid(category_class: type) -> None:
+    """Validate the field names and values of the category_class passed to DiscreteGrid.
 
     Args:
-        options: The user options to validate.
+        category_class: The category class representing the grid categories. Must
+            be a dataclass with fields that have unique scalar int or float values.
 
-    Returns:
-        list[str]: A list of error messages.
+    Raises:
+        GridInitializationError: If the `category_class` is not a dataclass with scalar
+            int or float fields.
 
     """
-    error_messages = []
+    if not is_dataclass(category_class):
+        raise GridInitializationError(
+            "category_class must be a dataclass with scalar int or float fields, "
+            f"but is {category_class}."
+        )
 
-    if not len(options) > 0:
-        error_messages.append("options must contain at least one element")
+    names_and_values = _get_field_names_and_values(category_class)
 
-    if not all(isinstance(option, int | float) for option in options):
-        error_messages.append("options must contain only scalar int or float values")
+    error_messages = []
 
-    if len(options) != len(set(options)):
-        error_messages.append("options must contain unique values")
+    if not names_and_values:
+        error_messages.append(
+            "category_class passed to DiscreteGrid must have at least one field"
+        )
+
+    names_with_non_numerical_values = [
+        name
+        for name, value in names_and_values.items()
+        if not isinstance(value, int | float)
+    ]
+    if names_with_non_numerical_values:
+        error_messages.append(
+            "Field values of the category_class passed to DiscreteGrid can only be "
+            "scalar int or float values. The values to the following fields are not: "
+            f"{names_with_non_numerical_values}"
+        )
 
-    if list(options) != list(range(len(options))):
+    values = list(names_and_values.values())
+    duplicated_values = [v for v in values if values.count(v) > 1]
+    if duplicated_values:
         error_messages.append(
-            "options must be a list of consecutive integers starting from 0",
+            "Field values of the category_class passed to DiscreteGrid must be unique. "
+            "The following values are duplicated: "
+            f"{set(duplicated_values)}"
         )
 
-    return error_messages
+    if error_messages:
+        msg = format_messages(error_messages)
+        raise GridInitializationError(msg)
+
+
+def _get_field_names_and_values(dc: type) -> dict[str, Any]:
+    """Get the fields of a dataclass.
+
+    Args:
+        dc: The dataclass to get the fields of.
+
+    Returns:
+        A dictionary with the field names as keys and the field values as values. If
+        no value is provided for a field, the value is set to None.
+
+    """
+    return {field.name: getattr(dc, field.name, None) for field in fields(dc)}
 
 
 def _validate_continuous_grid(
     start: float,
     stop: float,
     n_points: int,
-) -> list[str]:
+) -> None:
     """Validate the continuous grid parameters.
 
     Args:
@@ -172,8 +226,8 @@ def _validate_continuous_grid(
         stop: The stop value of the grid.
         n_points: The number of points in the grid.
 
-    Returns:
-        list[str]: A list of error messages.
+    Raises:
+        GridInitializationError: If the grid parameters are invalid.
 
     """
     error_messages = []
@@ -194,4 +248,6 @@ def _validate_continuous_grid(
     if valid_start_type and valid_stop_type and start >= stop:
         error_messages.append("start must be less than stop")
 
-    return error_messages
+    if error_messages:
+        msg = format_messages(error_messages)
+        raise GridInitializationError(msg)
diff --git a/src/lcm/input_processing/__init__.py b/src/lcm/input_processing/__init__.py
index 849cbdc9..546866d9 100644
--- a/src/lcm/input_processing/__init__.py
+++ b/src/lcm/input_processing/__init__.py
@@ -1,3 +1,4 @@
+from .discrete_grid_conversion import DiscreteGridConverter
 from .process_model import process_model
 
-__all__ = ["process_model"]
+__all__ = ["process_model", "DiscreteGridConverter"]
diff --git a/src/lcm/input_processing/discrete_grid_conversion.py b/src/lcm/input_processing/discrete_grid_conversion.py
new file mode 100644
index 00000000..a1084e26
--- /dev/null
+++ b/src/lcm/input_processing/discrete_grid_conversion.py
@@ -0,0 +1,280 @@
+import functools
+from collections.abc import Callable
+from dataclasses import dataclass, field, make_dataclass
+from typing import TypeVar, cast
+
+import jax.numpy as jnp
+from dags.signature import with_signature
+from jax import Array
+
+from lcm.functools import all_as_kwargs
+from lcm.grids import DiscreteGrid
+from lcm.input_processing.util import (
+    get_gridspecs,
+)
+from lcm.typing import ParamsDict
+from lcm.user_model import Model
+
+
+@dataclass(frozen=True, kw_only=True)
+class DiscreteGridConverter:
+    """Converts between representations of discrete variables and associated parameters.
+
+    While LCM supports general discrete grids, internally, these are converted to
+    array indices. This class provides functionality for converting between the internal
+    representation and the external representation of states, choices, and associated
+    parameters.
+
+    Attributes:
+        index_to_code: A dictionary of functions mapping from the internal index to the
+            code for each converted state. Keys correspond to the names of converted
+            discrete variables.
+        code_to_index: A dictionary of functions mapping from the code to the internal
+            index for each converted state. Keys correspond to the names of converted
+            discrete variables.
+
+    """
+
+    index_to_code: dict[str, Callable[[Array], Array]] = field(default_factory=dict)
+    code_to_index: dict[str, Callable[[Array], Array]] = field(default_factory=dict)
+
+    def __post_init__(self) -> None:
+        if set(self.index_to_code.keys()) != set(self.code_to_index.keys()):
+            raise ValueError(
+                "The keys of index_to_code and code_to_index must be the same."
+            )
+
+    def internal_params_to_params(self, internal: ParamsDict) -> ParamsDict:
+        """Convert parameters from internal to external representation.
+
+        If a state has been converted, the name of its corresponding next function must
+        be changed from `next___{var}_index__` to `next_{var}`.
+
+        """
+        params = internal.copy()
+        for var in self.index_to_code:
+            old_name = f"next___{var}_index__"
+            if old_name in params:
+                params[f"next_{var}"] = params.pop(old_name)
+        return params
+
+    def params_to_internal_params(self, params: ParamsDict) -> ParamsDict:
+        """Convert parameters from external to internal representation.
+
+        If a state has been converted, the name of its corresponding next function must
+        be changed from `next_{var}` to `next___{var}_index__`.
+
+        """
+        internal = params.copy()
+        for var in self.index_to_code:
+            old_name = f"next_{var}"
+            if old_name in internal:
+                internal[f"next___{var}_index__"] = internal.pop(old_name)
+        return internal
+
+    def internal_vars_to_vars(self, internal: dict[str, Array]) -> dict[str, Array]:
+        """Convert discrete variables from internal to external representation.
+
+        If a variable has been converted, the name of its corresponding index function
+        must be changed from `___{var}_index__` to `{var}`, and the values of the
+        variable must be converted from indices to codes.
+
+        """
+        variables = internal.copy()
+        for var, index_to_code in self.index_to_code.items():
+            old_name = f"__{var}_index__"
+            if old_name in internal:
+                variables[var] = index_to_code(variables.pop(old_name))
+        return variables
+
+    def vars_to_internal_vars(self, variables: dict[str, Array]) -> dict[str, Array]:
+        """Convert discrete variables from external to internal representation.
+
+        If a variable has been converted, the name of its corresponding index function
+        must be changed from `{var}` to `___{var}_index__`, and the values of the
+        variable must be converted from codes to indices.
+
+        """
+        internal = variables.copy()
+        for var, code_to_index in self.code_to_index.items():
+            if var in variables:
+                internal[f"__{var}_index__"] = code_to_index(internal.pop(var))
+        return internal
+
+
+def convert_arbitrary_codes_to_array_indices(
+    model: Model,
+) -> tuple[Model, DiscreteGridConverter]:
+    """Update the user model to ensure that discrete variables have index codes.
+
+    For each discrete variable with non-index codes, we:
+
+        1. Remove the variable from the states or choices dictionary
+        2. Replace it with a new state or choice with array index codes
+        3. Add updated next functions (if the variable was a state variable)
+        4. Add a function that maps the array index codes to the original codes
+
+    Args:
+        model: The model as provided by the user.
+
+    Returns:
+        - The model with all discrete variables having index codes.
+        - A converter that can be used to convert between the internal and external
+          representation of the model.
+
+    """
+    gridspecs = get_gridspecs(model)
+
+    non_index_discrete_vars = _get_discrete_vars_with_non_index_codes(model)
+
+    # fast path
+    if not non_index_discrete_vars:
+        return model, DiscreteGridConverter()
+
+    functions = model.functions.copy()
+    states = model.states.copy()
+    choices = model.choices.copy()
+
+    # Update grids
+    # ----------------------------------------------------------------------------------
+    for var in non_index_discrete_vars:
+        grid: DiscreteGrid = gridspecs[var]  # type: ignore[assignment]
+        index_category_class = make_dataclass(
+            grid.__str__(),
+            [(f"__{name}_index__", int, i) for i, name in enumerate(grid.categories)],
+        )
+        index_grid = DiscreteGrid(index_category_class)
+
+        if var in model.states:
+            states.pop(var)
+            states[f"__{var}_index__"] = index_grid
+        else:
+            choices.pop(var)
+            choices[f"__{var}_index__"] = index_grid
+
+    # Update next functions
+    # ----------------------------------------------------------------------------------
+    non_index_states = [s for s in model.states if s in non_index_discrete_vars]
+
+    for var in non_index_states:
+        functions[f"next___{var}_index__"] = _get_next_index_func(
+            functions.pop(f"next_{var}"),
+            codes_array=gridspecs[var].to_jax(),
+            name=var,
+        )
+
+    # Add index to code functions
+    # ----------------------------------------------------------------------------------
+    index_to_code_funcs = {
+        var: _get_index_to_code_func(gridspecs[var].to_jax(), name=var)
+        for var in non_index_discrete_vars
+    }
+    functions = functions | index_to_code_funcs
+
+    # Create code to index functions for converter
+    # ----------------------------------------------------------------------------------
+    code_to_index_funcs = {
+        var: _get_code_to_index_func(gridspecs[var].to_jax(), name=var)
+        for var in non_index_discrete_vars
+    }
+
+    discrete_grid_converter = DiscreteGridConverter(
+        index_to_code=index_to_code_funcs,
+        code_to_index=code_to_index_funcs,
+    )
+
+    new_model = model.replace(
+        states=states,
+        choices=choices,
+        functions=functions,
+    )
+    return new_model, discrete_grid_converter
+
+
+def _get_discrete_vars_with_non_index_codes(model: Model) -> list[str]:
+    """Get discrete variables with non-index codes.
+
+    Collect all discrete variables with codes that do not correspond to indices.
+
+    """
+    gridspecs = get_gridspecs(model)
+    discrete_vars = []
+    for name, spec in gridspecs.items():
+        if isinstance(spec, DiscreteGrid) and list(spec.codes) != list(
+            range(len(spec.codes))
+        ):
+            discrete_vars.append(name)
+    return discrete_vars
+
+
+F = TypeVar("F", bound=Callable[[tuple[Array, ...]], Array])
+
+
+def _get_next_index_func(next_func: F, codes_array: Array, name: str) -> F:
+    """Get next function for index state variable.
+
+    Args:
+        next_func: The next function for the state variable.
+        codes_array: An array of codes.
+        name: The name of the state variable.
+
+    Returns:
+        A next function corresponding to the index version of the state variable.
+
+    """
+    code_to_index = _get_code_to_index_func(codes_array, name)
+
+    @functools.wraps(next_func)
+    def next_index_func(*args, **kwargs) -> Array:
+        next_state = next_func(*args, **kwargs)
+        return code_to_index(next_state)
+
+    return cast(F, next_index_func)
+
+
+def _get_index_to_code_func(codes_array: Array, name: str) -> Callable[[Array], Array]:
+    """Get function mapping from index to code.
+
+    Args:
+        codes_array: An array of codes.
+        name: The name of resulting function argument.
+
+    Returns:
+        A function mapping an array with indices corresponding to codes_array to the
+        corresponding codes.
+
+    """
+    arg_name = f"__{name}_index__"
+
+    @with_signature(args=[arg_name])
+    def func(*args, **kwargs):
+        kwargs = all_as_kwargs(args, kwargs, arg_names=[arg_name])
+        index = kwargs[arg_name]
+        return codes_array[index]
+
+    return func
+
+
+def _get_code_to_index_func(codes_array: Array, name: str) -> Callable[[Array], Array]:
+    """Get function mapping from code to index.
+
+    Args:
+        codes_array: An array of codes.
+        name: The name of resulting function argument.
+
+    Returns:
+        A function mapping an array with values in codes_array to their corresponding
+        indices.
+
+    """
+    sorted_indices = jnp.argsort(codes_array)
+    sorted_codes = codes_array[sorted_indices]
+
+    @with_signature(args=[name])
+    def code_to_index(*args, **kwargs):
+        kwargs = all_as_kwargs(args, kwargs, arg_names=[name])
+        data = kwargs[name]
+        indices_in_sorted = jnp.searchsorted(sorted_codes, data)
+        return sorted_indices[indices_in_sorted]
+
+    return code_to_index
diff --git a/src/lcm/input_processing/process_model.py b/src/lcm/input_processing/process_model.py
index 179c6268..f67420d9 100644
--- a/src/lcm/input_processing/process_model.py
+++ b/src/lcm/input_processing/process_model.py
@@ -9,6 +9,9 @@
 
 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,
@@ -36,18 +39,21 @@ def process_model(model: Model) -> InternalModel:
         The processed model.
 
     """
-    params = create_params_template(model)
+    tmp_model, converter = convert_arbitrary_codes_to_array_indices(model)
+
+    params = create_params_template(tmp_model)
 
     return InternalModel(
-        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),
+        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),
         params=params,
+        discrete_grid_converter=converter,
         # currently no additive utility shocks are supported
         random_utility_shocks=ShockType.NONE,
-        n_periods=model.n_periods,
+        n_periods=tmp_model.n_periods,
     )
 
 
diff --git a/src/lcm/input_processing/util.py b/src/lcm/input_processing/util.py
index 70a1a304..5392c8a7 100644
--- a/src/lcm/input_processing/util.py
+++ b/src/lcm/input_processing/util.py
@@ -133,7 +133,7 @@ def get_gridspecs(
     Returns:
         dict: Dictionary containing all variables of the model. The keys are
             the names of the variables. The values describe which values the variable
-            can take. For discrete variables these are the options. For continuous
+            can take. For discrete variables these are the codes. For continuous
             variables this is information about how to build the grids.
 
     """
diff --git a/src/lcm/interfaces.py b/src/lcm/interfaces.py
index 9e71d810..69ecaf54 100644
--- a/src/lcm/interfaces.py
+++ b/src/lcm/interfaces.py
@@ -5,6 +5,7 @@
 from jax import Array
 
 from lcm.grids import ContinuousGrid, DiscreteGrid, Grid
+from lcm.input_processing import DiscreteGridConverter
 from lcm.typing import ParamsDict, ShockType
 
 
@@ -93,6 +94,8 @@ 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.
 
@@ -104,6 +107,7 @@ 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
diff --git a/src/lcm/simulate.py b/src/lcm/simulate.py
index b804d3f0..aab880bb 100644
--- a/src/lcm/simulate.py
+++ b/src/lcm/simulate.py
@@ -9,6 +9,7 @@
 
 from lcm.argmax import argmax, segment_argmax
 from lcm.dispatchers import spacemap, vmap_1d
+from lcm.input_processing import DiscreteGridConverter
 from lcm.interfaces import InternalModel, Space
 
 
@@ -20,6 +21,7 @@ def simulate(
     compute_ccv_policy_functions,
     model: InternalModel,
     next_state,
+    discrete_grid_converter: DiscreteGridConverter,
     logger,
     solve_model=None,
     vf_arr_list=None,
@@ -43,6 +45,8 @@ def simulate(
             state and choice variables. For stochastic variables, it returns a random
             draw from the distribution of the next state.
         model (Model): Model instance.
+        discrete_grid_converter (DiscreteGridConverter): Converter for discrete
+            variables and parameters between external and internal representation.
         logger (logging.Logger): Logger that logs to stdout.
         solve_model (callable): Function that solves the model. Is only required if
             vf_arr_list is not provided.
@@ -63,8 +67,12 @@ def simulate(
             raise ValueError(
                 "You need to provide either vf_arr_list or solve_model.",
             )
+        # We do not need to convert the params here, because the solve_model function
+        # will do it.
         vf_arr_list = solve_model(params)
 
+    internal_params = discrete_grid_converter.params_to_internal_params(params)
+
     logger.info("Starting simulation")
 
     # Update the vf_arr_list
@@ -89,7 +97,7 @@ def simulate(
     sparse_choice_variables = model.variable_info.query("is_choice & is_sparse").index
 
     # The following variables are updated during the forward simulation
-    states = initial_states
+    states = discrete_grid_converter.vars_to_internal_vars(initial_states)
     key = jax.random.PRNGKey(seed=seed)
 
     # Forward simulation
@@ -132,7 +140,7 @@ def simulate(
             continuous_choice_grids=continuous_choice_grids[period],
             vf_arr=vf_arr_list[period],
             state_indexers=state_indexers[period],
-            params=params,
+            params=internal_params,
         )
 
         # Get optimal discrete choice given the optimal conditional continuous choices
@@ -195,7 +203,7 @@ def simulate(
             **states,
             **choices,
             _period=jnp.repeat(period, n_initial_states),
-            params=params,
+            params=internal_params,
             keys=sim_keys,
         )
 
@@ -205,14 +213,14 @@ def simulate(
 
         logger.info("Period: %s", period)
 
-    processed = _process_simulated_data(_simulation_results)
+    processed = _process_simulated_data(_simulation_results, discrete_grid_converter)
 
     if additional_targets is not None:
         calculated_targets = _compute_targets(
             processed,
             targets=additional_targets,
             model_functions=model.functions,
-            params=params,
+            params=internal_params,
         )
         processed = {**processed, **calculated_targets}
 
@@ -331,19 +339,23 @@ def _compute_targets(processed_results, targets, model_functions, params):
     return target_func(params=params, **kwargs)
 
 
-def _process_simulated_data(results):
+def _process_simulated_data(results, discrete_grid_converter):
     """Process and flatten the simulation results.
 
     This function produces a dict of arrays for each var with dimension (n_periods *
     n_initial_states,). The arrays are flattened, so that the resulting dictionary has a
     one-dimensional array for each variable. The length of this array is the number of
     periods times the number of initial states. The order of array elements is given by
-    an outer level of periods and an inner level of initial states ids.
+    an outer level of periods and an inner level of initial states ids. Discrete
+    variables with an internal representation are converted to their external
+    representation.
+
 
     Args:
         results (list): List of dicts with simulation results. Each dict contains the
             value, choices, and states for one period. Choices and states are stored in
             a nested dictionary.
+        discrete_grid_converter (DiscreteGridConverter): Converter for discrete grids.
 
     Returns:
         dict: Dict with processed simulation results. The keys are the variable names
@@ -362,7 +374,8 @@ def _process_simulated_data(results):
     }
     out = {key: jnp.concatenate(values) for key, values in dict_of_lists.items()}
     out["_period"] = jnp.repeat(jnp.arange(n_periods), n_initial_states)
-    return out
+
+    return discrete_grid_converter.internal_vars_to_vars(out)
 
 
 # ======================================================================================
diff --git a/src/lcm/solve_brute.py b/src/lcm/solve_brute.py
index a7f1ab82..978627da 100644
--- a/src/lcm/solve_brute.py
+++ b/src/lcm/solve_brute.py
@@ -10,6 +10,7 @@ def solve(
     continuous_choice_grids,
     compute_ccv_functions,
     emax_calculators,
+    discrete_grid_converter,
     logger,
 ):
     """Solve a model by brute force.
@@ -42,12 +43,16 @@ def solve(
         emax_calculators (list): List of functions that take continuation
             values for combinations of states and discrete choices and calculate the
             expected maximum over all discrete choices of a given state.
+        discrete_grid_converter (DiscreteGridConverter): Converter for discrete
+            variables and parameters between external and internal representation.
         logger (logging.Logger): Logger that logs to stdout.
 
     Returns:
         list: List with one value function array per period.
 
     """
+    internal_params = discrete_grid_converter.params_to_internal_params(params)
+
     # extract information
     n_periods = len(state_choice_spaces)
     reversed_solution = []
@@ -64,12 +69,12 @@ def solve(
             continuous_choice_grids=continuous_choice_grids[period],
             vf_arr=vf_arr,
             state_indexers=state_indexers[period],
-            params=params,
+            params=internal_params,
         )
 
         # solve discrete problem by calculating expected maximum over discrete choices
         calculate_emax = emax_calculators[period]
-        vf_arr = calculate_emax(conditional_continuation_values, params=params)
+        vf_arr = calculate_emax(conditional_continuation_values, params=internal_params)
         reversed_solution.append(vf_arr)
 
         logger.info("Period: %s", period)
diff --git a/src/lcm/user_model.py b/src/lcm/user_model.py
index c2ba24e3..92c31c91 100644
--- a/src/lcm/user_model.py
+++ b/src/lcm/user_model.py
@@ -31,17 +31,8 @@ class Model:
     states: dict[str, Grid] = field(default_factory=dict)
 
     def __post_init__(self) -> None:
-        type_errors = _validate_attribute_types(self)
-
-        if type_errors:
-            msg = format_messages(type_errors)
-            raise ModelInitilizationError(msg)
-
-        logical_errors = _validate_logical_consistency(self)
-
-        if logical_errors:
-            msg = format_messages(logical_errors)
-            raise ModelInitilizationError(msg)
+        _validate_attribute_types(self)
+        _validate_logical_consistency(self)
 
     def replace(self, **kwargs) -> "Model":
         """Replace the attributes of the model.
@@ -56,7 +47,7 @@ def replace(self, **kwargs) -> "Model":
         return dc.replace(self, **kwargs)
 
 
-def _validate_attribute_types(model: Model) -> list[str]:
+def _validate_attribute_types(model: Model) -> None:  # noqa: C901
     """Validate the types of the model attributes."""
     error_messages = []
 
@@ -64,20 +55,18 @@ def _validate_attribute_types(model: Model) -> list[str]:
     # ----------------------------------------------------------------------------------
     for attr_name in ("choices", "states"):
         attr = getattr(model, attr_name)
-        if not isinstance(attr, dict):
-            error_messages.append(f"{attr_name} must be a dictionary.")
-        else:
+        if isinstance(attr, dict):
             for k, v in attr.items():
                 if not isinstance(k, str):
                     error_messages.append(f"{attr_name} key {k} must be a string.")
                 if not isinstance(v, Grid):
                     error_messages.append(f"{attr_name} value {v} must be an LCM grid.")
+        else:
+            error_messages.append(f"{attr_name} must be a dictionary.")
 
     # Validate types of functions
     # ----------------------------------------------------------------------------------
-    if not isinstance(model.functions, dict):
-        error_messages.append("functions must be a dictionary.")
-    else:
+    if isinstance(model.functions, dict):
         for k, v in model.functions.items():
             if not isinstance(k, str):
                 error_messages.append(f"function keys must be a strings, but is {k}.")
@@ -85,11 +74,15 @@ def _validate_attribute_types(model: Model) -> list[str]:
                 error_messages.append(
                     f"function values must be a callable, but is {v}."
                 )
+    else:
+        error_messages.append("functions must be a dictionary.")
 
-    return error_messages
+    if error_messages:
+        msg = format_messages(error_messages)
+        raise ModelInitilizationError(msg)
 
 
-def _validate_logical_consistency(model: Model) -> list[str]:
+def _validate_logical_consistency(model: Model) -> None:
     """Validate the logical consistency of the model."""
     error_messages = []
 
@@ -119,4 +112,6 @@ def _validate_logical_consistency(model: Model) -> list[str]:
             f"are used in both states and choices: {states_and_choices_overlap}.",
         )
 
-    return error_messages
+    if error_messages:
+        msg = format_messages(error_messages)
+        raise ModelInitilizationError(msg)
diff --git a/tests/conftest.py b/tests/conftest.py
index a7a9a731..695ef46d 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,5 +1,23 @@
+from dataclasses import make_dataclass
+
+import pytest
 from jax import config
 
 
 def pytest_sessionstart(session):  # noqa: ARG001
     config.update("jax_enable_x64", val=True)
+
+
+def _category_class_factory(values: list[int]):
+    init = [(f"cat{i}", int, value) for i, value in enumerate(values)]
+    return make_dataclass("CategoryClass", init)
+
+
+@pytest.fixture(scope="session")
+def category_class_factory():
+    return _category_class_factory
+
+
+@pytest.fixture(scope="session")
+def binary_category_class(category_class_factory):
+    return category_class_factory([0, 1])
diff --git a/tests/input_processing/test_create_params_template.py b/tests/input_processing/test_create_params_template.py
index e0b9c0d5..475831fc 100644
--- a/tests/input_processing/test_create_params_template.py
+++ b/tests/input_processing/test_create_params_template.py
@@ -29,17 +29,17 @@ class ModelMock:
     states: dict[str, Any] | None = None
 
 
-def test_create_params_without_shocks():
+def test_create_params_without_shocks(binary_category_class):
     model = ModelMock(
         functions={
             "f": lambda a, b, c: None,  # noqa: ARG005
             "next_b": lambda b: b,
         },
         choices={
-            "a": DiscreteGrid([0, 1]),
+            "a": DiscreteGrid(binary_category_class),
         },
         states={
-            "b": DiscreteGrid([0, 1]),
+            "b": DiscreteGrid(binary_category_class),
         },
         n_periods=None,
     )
diff --git a/tests/input_processing/test_discrete_state_conversion.py b/tests/input_processing/test_discrete_state_conversion.py
new file mode 100644
index 00000000..30d01337
--- /dev/null
+++ b/tests/input_processing/test_discrete_state_conversion.py
@@ -0,0 +1,156 @@
+from dataclasses import dataclass
+from typing import Any
+
+import jax.numpy as jnp
+import pytest
+from numpy.testing import assert_array_equal
+
+from lcm import DiscreteGrid
+from lcm.input_processing.discrete_grid_conversion import (
+    DiscreteGridConverter,
+    _get_code_to_index_func,
+    _get_discrete_vars_with_non_index_codes,
+    _get_index_to_code_func,
+    _get_next_index_func,
+    convert_arbitrary_codes_to_array_indices,
+)
+
+
+@dataclass
+class ModelMock:
+    """A model mock for testing the process_model function.
+
+    This dataclass has the same attributes as the Model dataclass, but does not perform
+    any checks, which helps us to test the process_model function in isolation.
+
+    """
+
+    n_periods: int
+    functions: dict[str, Any]
+    choices: dict[str, Any]
+    states: dict[str, Any]
+
+
+@pytest.fixture
+def model(category_class_factory):
+    def next_c(a, b):
+        return a + b
+
+    return ModelMock(
+        n_periods=2,
+        functions={
+            "next_c": next_c,
+        },
+        choices={
+            "a": DiscreteGrid(category_class_factory([0, 1])),
+        },
+        states={
+            # unsorted indices cannot be treated as indices
+            "c": DiscreteGrid(category_class_factory([1, 0])),
+        },
+    )
+
+
+@pytest.fixture
+def discrete_state_converter_kwargs():
+    return {
+        "index_to_code": {"c": _get_index_to_code_func(jnp.array([1, 0]), name="c")},
+        "code_to_index": {"c": _get_code_to_index_func(jnp.array([1, 0]), name="c")},
+    }
+
+
+def test_discrete_state_converter_internal_to_params(discrete_state_converter_kwargs):
+    expected = {
+        "next_c": 1,
+    }
+    internal_params = {
+        "next___c_index__": 1,
+    }
+    converter = DiscreteGridConverter(**discrete_state_converter_kwargs)
+    assert converter.internal_params_to_params(internal_params) == expected
+
+
+def test_discrete_state_converter_params_to_internal(discrete_state_converter_kwargs):
+    expected = {
+        "next___c_index__": 1,
+    }
+    params = {
+        "next_c": 1,
+    }
+    converter = DiscreteGridConverter(**discrete_state_converter_kwargs)
+    assert converter.params_to_internal_params(params) == expected
+
+
+def test_discrete_state_converter_internal_to_discrete_vars(
+    discrete_state_converter_kwargs,
+):
+    expected = jnp.array([1, 0])
+    internal_states = {
+        "__c_index__": jnp.array([0, 1]),
+    }
+    converter = DiscreteGridConverter(**discrete_state_converter_kwargs)
+    assert_array_equal(converter.internal_vars_to_vars(internal_states)["c"], expected)
+
+
+def test_discrete_state_converter_discrete_vars_to_internal(
+    discrete_state_converter_kwargs,
+):
+    expected = jnp.array([0, 1])
+    states = {
+        "c": jnp.array([1, 0]),
+    }
+    converter = DiscreteGridConverter(**discrete_state_converter_kwargs)
+    assert_array_equal(converter.vars_to_internal_vars(states)["__c_index__"], expected)
+
+
+def test_discrete_state_converter_raises_error_if_keys_dont_match():
+    index_to_code = {"a": 0}
+    code_to_index = {"b": 0}
+    with pytest.raises(
+        ValueError,
+        match="The keys of index_to_code and code_to_index must be the same.",
+    ):
+        DiscreteGridConverter(index_to_code=index_to_code, code_to_index=code_to_index)
+
+
+def test_get_index_to_label_func():
+    codes_array = jnp.array([1, 0])
+    got = _get_index_to_code_func(codes_array, name="foo")
+    assert got(__foo_index__=0) == 1
+    assert got(1) == 0
+
+
+def test_get_code_to_index_func():
+    codes_array = jnp.array([1, 0])
+    got = _get_code_to_index_func(codes_array, name="foo")
+    assert_array_equal(got(foo=codes_array), jnp.arange(2))
+
+
+def test_get_discrete_vars_with_non_index_codes(model):
+    got = _get_discrete_vars_with_non_index_codes(model)
+    assert got == ["c"]
+
+
+def test_convert_discrete_codes_to_indices(model):
+    # add replace method to model mock
+    model.replace = lambda **kwargs: ModelMock(**kwargs, n_periods=model.n_periods)
+
+    got, _ = convert_arbitrary_codes_to_array_indices(model)
+
+    assert "c" not in got.states
+    assert "__c_index__" in got.states
+    assert "c" in got.functions
+    assert got.states["__c_index__"].categories == ("__cat0_index__", "__cat1_index__")
+    assert got.states["__c_index__"].codes == (0, 1)
+    assert got.functions["c"](0) == 1
+    assert got.functions["c"](1) == 0
+
+
+def test_get_next_index_func():
+    got_func = _get_next_index_func(
+        next_func=lambda wealth, working: jnp.clip(wealth + working, 1, 3),
+        codes_array=jnp.array([1, 2, 3]),
+        name="wealth",
+    )
+    got = got_func(wealth=jnp.array([1, 2]), working=jnp.array([0, 1]))
+    assert_array_equal(got, jnp.array([0, 2]))
diff --git a/tests/input_processing/test_process_model.py b/tests/input_processing/test_process_model.py
index 61a459f7..821a1f33 100644
--- a/tests/input_processing/test_process_model.py
+++ b/tests/input_processing/test_process_model.py
@@ -39,7 +39,7 @@ class ModelMock:
 
 
 @pytest.fixture
-def model():
+def model(category_class_factory):
     def next_c(a, b):
         return a + b
 
@@ -49,10 +49,10 @@ def next_c(a, b):
             "next_c": next_c,
         },
         choices={
-            "a": DiscreteGrid([0, 1]),
+            "a": DiscreteGrid(category_class_factory([0, 1])),
         },
         states={
-            "c": DiscreteGrid([0, 1]),
+            "c": DiscreteGrid(category_class_factory([1, 10])),
         },
     )
 
@@ -91,14 +91,19 @@ def test_get_variable_info(model):
 
 def test_get_gridspecs(model):
     got = get_gridspecs(model)
-    assert got["a"] == DiscreteGrid([0, 1])
-    assert got["c"] == DiscreteGrid([0, 1])
+    assert isinstance(got["a"], DiscreteGrid)
+    assert got["a"].categories == ("cat0", "cat1")
+    assert got["a"].codes == (0, 1)
+
+    assert isinstance(got["c"], DiscreteGrid)
+    assert got["c"].categories == ("cat0", "cat1")
+    assert got["c"].codes == (1, 10)
 
 
 def test_get_grids(model):
     got = get_grids(model)
     assert_array_equal(got["a"], jnp.array([0, 1]))
-    assert_array_equal(got["c"], jnp.array([0, 1]))
+    assert_array_equal(got["c"], jnp.array([1, 10]))
 
 
 def test_process_model_iskhakov_et_al_2017():
@@ -137,8 +142,13 @@ def test_process_model_iskhakov_et_al_2017():
     )
     assert model.gridspecs["consumption"] == consumption_grid
 
-    assert model.gridspecs["retirement"] == DiscreteGrid([0, 1])
-    assert model.gridspecs["lagged_retirement"] == DiscreteGrid([0, 1])
+    assert isinstance(model.gridspecs["retirement"], DiscreteGrid)
+    assert model.gridspecs["retirement"].categories == ("working", "retired")
+    assert model.gridspecs["retirement"].codes == (0, 1)
+
+    assert isinstance(model.gridspecs["lagged_retirement"], DiscreteGrid)
+    assert model.gridspecs["lagged_retirement"].categories == ("working", "retired")
+    assert model.gridspecs["lagged_retirement"].codes == (0, 1)
 
     # Grids
     expected = grid_helpers.linspace(**model_config.choices["consumption"].__dict__)
@@ -195,7 +205,9 @@ def test_process_model():
     )
     assert model.gridspecs["consumption"] == consumption_specs
 
-    assert model.gridspecs["retirement"] == DiscreteGrid([0, 1])
+    assert isinstance(model.gridspecs["retirement"], DiscreteGrid)
+    assert model.gridspecs["retirement"].categories == ("working", "retired")
+    assert model.gridspecs["retirement"].codes == (0, 1)
 
     # Grids
     expected = grid_helpers.linspace(**model_config.choices["consumption"].__dict__)
diff --git a/tests/test_entry_point.py b/tests/test_entry_point.py
index d93dddab..b0c33622 100644
--- a/tests/test_entry_point.py
+++ b/tests/test_entry_point.py
@@ -29,15 +29,17 @@
 # ======================================================================================
 
 
-@pytest.mark.parametrize(
-    "model",
-    [
-        get_model_config(name, n_periods=3)
-        for name in ["iskhakov_et_al_2017", *STRIPPED_DOWN_AND_FULLY_DISCRETE_MODELS]
-    ],
-    ids=["iskhakov_et_al_2017", *STRIPPED_DOWN_AND_FULLY_DISCRETE_MODELS],
-)
-def test_get_lcm_function_with_solve_target(model):
+def test_get_lcm_function_with_solve_target_stripped_down():
+    model = get_model_config("iskhakov_et_al_2017_stripped_down", n_periods=3)
+    solve_model, params_template = get_lcm_function(model=model)
+
+    params = tree_map(lambda _: 0.2, params_template)
+
+    solve_model(params)
+
+
+def test_get_lcm_function_with_solve_target_fully_discrete():
+    model = get_model_config("iskhakov_et_al_2017_fully_discrete", n_periods=3)
     solve_model, params_template = get_lcm_function(model=model)
 
     params = tree_map(lambda _: 0.2, params_template)
@@ -50,15 +52,27 @@ def test_get_lcm_function_with_solve_target(model):
 # ======================================================================================
 
 
-@pytest.mark.parametrize(
-    "model",
-    [
-        get_model_config(name, n_periods=3)
-        for name in STRIPPED_DOWN_AND_FULLY_DISCRETE_MODELS
-    ],
-    ids=STRIPPED_DOWN_AND_FULLY_DISCRETE_MODELS,
-)
-def test_get_lcm_function_with_simulation_target_simple(model):
+def test_get_lcm_function_with_simulation_target_simple_stripped_down():
+    model = get_model_config("iskhakov_et_al_2017_stripped_down", n_periods=3)
+
+    simulate, params_template = get_lcm_function(
+        model=model,
+        targets="solve_and_simulate",
+    )
+    params = tree_map(lambda _: 0.2, params_template)
+
+    simulate(
+        params,
+        initial_states={
+            "wealth": jnp.array([0.0, 10.0, 50.0]),
+        },
+        additional_targets=["age"] if "age" in model.functions else None,
+    )
+
+
+def test_get_lcm_function_with_simulation_target_simple_fully_discrete():
+    model = get_model_config("iskhakov_et_al_2017_fully_discrete", n_periods=3)
+
     simulate, params_template = get_lcm_function(
         model=model,
         targets="solve_and_simulate",
@@ -234,9 +248,9 @@ def test_create_compute_conditional_continuation_value_with_discrete_model():
     )
 
     val = compute_ccv(
-        consumption_index=jnp.array([0, 1]),
+        __consumption_index__=jnp.array([0, 1]),
         retirement=1,
-        wealth=2,
+        __wealth_index__=2,
         params=params,
         vf_arr=None,
     )
@@ -338,9 +352,9 @@ def test_create_compute_conditional_continuation_policy_with_discrete_model():
     )
 
     policy, val = compute_ccv_policy(
-        consumption_index=jnp.array([0, 1]),
+        __consumption_index__=jnp.array([0, 1]),
         retirement=1,
-        wealth=2,
+        __wealth_index__=2,
         params=params,
         vf_arr=None,
     )
diff --git a/tests/test_grids.py b/tests/test_grids.py
index aad98b5b..1d23126c 100644
--- a/tests/test_grids.py
+++ b/tests/test_grids.py
@@ -1,3 +1,6 @@
+import re
+from dataclasses import make_dataclass
+
 import numpy as np
 import pytest
 
@@ -6,61 +9,97 @@
     DiscreteGrid,
     LinspaceGrid,
     LogspaceGrid,
+    _get_field_names_and_values,
     _validate_continuous_grid,
     _validate_discrete_grid,
 )
 
 
 def test_validate_discrete_grid_empty():
-    assert _validate_discrete_grid([]) == ["options must contain at least one element"]
+    category_class = make_dataclass("Category", [])
+    error_msg = "category_class passed to DiscreteGrid must have at least one field"
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_discrete_grid(category_class)
 
 
 def test_validate_discrete_grid_non_scalar_input():
-    assert _validate_discrete_grid([1, "a"]) == [
-        "options must contain only scalar int or float values",
-        "options must be a list of consecutive integers starting from 0",
-    ]
+    category_class = make_dataclass("Category", [("a", int, 1), ("b", str, "s")])
+    error_msg = (
+        "Field values of the category_class passed to DiscreteGrid can only be "
+        "scalar int or float values. The values to the following fields are not: ['b']"
+    )
+    with pytest.raises(GridInitializationError, match=re.escape(error_msg)):
+        _validate_discrete_grid(category_class)
+
+
+def test_validate_discrete_grid_none_input():
+    category_class = make_dataclass("Category", [("a", int), ("b", int, 1)])
+    error_msg = (
+        "Field values of the category_class passed to DiscreteGrid can only be "
+        "scalar int or float values. The values to the following fields are not: ['a']"
+    )
+    with pytest.raises(GridInitializationError, match=re.escape(error_msg)):
+        _validate_discrete_grid(category_class)
 
 
 def test_validate_discrete_grid_non_unique():
-    assert _validate_discrete_grid([1, 2, 2]) == [
-        "options must contain unique values",
-        "options must be a list of consecutive integers starting from 0",
-    ]
+    category_class = make_dataclass("Category", [("a", int, 1), ("b", int, 1)])
+    error_msg = (
+        "Field values of the category_class passed to DiscreteGrid must be unique. "
+        "The following values are duplicated: {1}"
+    )
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_discrete_grid(category_class)
+
+
+def test_get_fields_with_defaults():
+    category_class = make_dataclass("Category", [("a", int, 1), ("b", int, 2)])
+    assert _get_field_names_and_values(category_class) == {"a": 1, "b": 2}
+
+
+def test_get_fields_no_defaults():
+    category_class = make_dataclass("Category", [("a", int), ("b", int)])
+    assert _get_field_names_and_values(category_class) == {"a": None, "b": None}
+
+
+def test_get_fields_instance():
+    category_class = make_dataclass("Category", [("a", int), ("b", int)])
+    assert _get_field_names_and_values(category_class(a=1, b=2)) == {"a": 1, "b": 2}
 
 
-def test_validate_discrete_grid_non_consecutive():
-    assert _validate_discrete_grid([1, 3, 2]) == [
-        "options must be a list of consecutive integers starting from 0"
-    ]
+def test_get_fields_empty():
+    category_class = make_dataclass("Category", [])
+    assert _get_field_names_and_values(category_class) == {}
 
 
 def test_validate_continuous_grid_invalid_start():
-    assert _validate_continuous_grid("a", 1, 10) == [
-        "start must be a scalar int or float value"
-    ]
+    error_msg = "start must be a scalar int or float value"
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_continuous_grid("a", 1, 10)
 
 
 def test_validate_continuous_grid_invalid_stop():
-    assert _validate_continuous_grid(1, "a", 10) == [
-        "stop must be a scalar int or float value"
-    ]
+    error_msg = "stop must be a scalar int or float value"
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_continuous_grid(1, "a", 10)
 
 
 def test_validate_continuous_grid_invalid_n_points():
-    assert _validate_continuous_grid(1, 2, "a") == [
-        "n_points must be an int greater than 0 but is a"
-    ]
+    error_msg = "n_points must be an int greater than 0 but is a"
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_continuous_grid(1, 2, "a")
 
 
 def test_validate_continuous_grid_negative_n_points():
-    assert _validate_continuous_grid(1, 2, -1) == [
-        "n_points must be an int greater than 0 but is -1"
-    ]
+    error_msg = "n_points must be an int greater than 0 but is -1"
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_continuous_grid(1, 2, -1)
 
 
 def test_validate_continuous_grid_start_greater_than_stop():
-    assert _validate_continuous_grid(2, 1, 10) == ["start must be less than stop"]
+    error_msg = "start must be less than stop"
+    with pytest.raises(GridInitializationError, match=error_msg):
+        _validate_continuous_grid(2, 1, 10)
 
 
 def test_linspace_grid_creation():
@@ -74,7 +113,10 @@ def test_logspace_grid_creation():
 
 
 def test_discrete_grid_creation():
-    grid = DiscreteGrid(options=[0, 1, 2])
+    category_class = make_dataclass(
+        "Category", [("a", int, 0), ("b", int, 1), ("c", int, 2)]
+    )
+    grid = DiscreteGrid(category_class)
     assert np.allclose(grid.to_jax(), np.arange(3))
 
 
@@ -88,9 +130,12 @@ def test_logspace_grid_invalid_start():
         LogspaceGrid(start=1, stop=0, n_points=10)
 
 
-def test_discrete_grid_invalid_options():
+def test_discrete_grid_invalid_category_class():
+    category_class = make_dataclass(
+        "Category", [("a", int, 1), ("b", str, "wrong_type")]
+    )
     with pytest.raises(
         GridInitializationError,
-        match="options must contain only scalar int or float values",
+        match="Field values of the category_class passed to DiscreteGrid can only be",
     ):
-        DiscreteGrid(options=[1, "a"])
+        DiscreteGrid(category_class)
diff --git a/tests/test_model.py b/tests/test_model.py
index 547a7762..4536946b 100644
--- a/tests/test_model.py
+++ b/tests/test_model.py
@@ -95,15 +95,15 @@ def test_model_invalid_n_periods():
         )
 
 
-def test_model_missing_next_func():
+def test_model_missing_next_func(binary_category_class):
     with pytest.raises(
         ModelInitilizationError,
         match="Each state must have a corresponding next state function.",
     ):
         Model(
             n_periods=2,
-            states={"health": DiscreteGrid([0, 1])},
-            choices={"exercise": DiscreteGrid([0, 1])},
+            states={"health": DiscreteGrid(binary_category_class)},
+            choices={"exercise": DiscreteGrid(binary_category_class)},
             functions={"utility": lambda: 0},
         )
 
@@ -121,14 +121,14 @@ def test_model_missing_utility():
         )
 
 
-def test_model_overlapping_states_choices():
+def test_model_overlapping_states_choices(binary_category_class):
     with pytest.raises(
         ModelInitilizationError,
         match="States and choices cannot have overlapping names.",
     ):
         Model(
             n_periods=2,
-            states={"health": DiscreteGrid([0, 1])},
-            choices={"health": DiscreteGrid([0, 1])},
+            states={"health": DiscreteGrid(binary_category_class)},
+            choices={"health": DiscreteGrid(binary_category_class)},
             functions={"utility": lambda: 0},
         )
diff --git a/tests/test_model_functions.py b/tests/test_model_functions.py
index bd9a933d..ad1b1ce3 100644
--- a/tests/test_model_functions.py
+++ b/tests/test_model_functions.py
@@ -34,6 +34,7 @@ def h():
         functions={"f": f, "g": g, "h": h},
         function_info=function_info,
         params=None,
+        discrete_grid_converter=None,
         random_utility_shocks=None,
         n_periods=None,
     )
diff --git a/tests/test_models/deterministic.py b/tests/test_models/deterministic.py
index 0c103e9c..f8dc7bb7 100644
--- a/tests/test_models/deterministic.py
+++ b/tests/test_models/deterministic.py
@@ -8,6 +8,7 @@
 """
 
 from copy import deepcopy
+from dataclasses import dataclass, make_dataclass
 
 import jax.numpy as jnp
 
@@ -18,6 +19,15 @@
 # ======================================================================================
 
 
+# --------------------------------------------------------------------------------------
+# Categorical variables
+# --------------------------------------------------------------------------------------
+@dataclass
+class RetirementStatus:
+    working: int = 0
+    retired: int = 1
+
+
 # --------------------------------------------------------------------------------------
 # Utility functions
 # --------------------------------------------------------------------------------------
@@ -35,20 +45,7 @@ def utility_with_filter(
     # https://github.com/OpenSourceEconomics/lcm/issues/30
     lagged_retirement,  # noqa: ARG001
 ):
-    return utility(consumption, working=working, disutility_of_work=disutility_of_work)
-
-
-def utility_fully_discrete(
-    consumption,
-    working,
-    disutility_of_work,
-    # Temporary workaround for bug described in issue #30, which requires us to pass
-    # all state variables to the utility function.
-    # TODO(@timmens): Remove function once #30 is fixed (re-use "utility").
-    # https://github.com/OpenSourceEconomics/lcm/issues/30
-    consumption_index,  # noqa: ARG001
-):
-    return utility(consumption, working=working, disutility_of_work=disutility_of_work)
+    return utility(consumption, working, disutility_of_work)
 
 
 # --------------------------------------------------------------------------------------
@@ -70,15 +67,6 @@ def age(_period):
     return _period + 18
 
 
-# Temporary workaround until option labels are supported that do not coincide with
-# the indices of the options.
-# TODO(@timmens): Remove this once #82 is closed.
-# https://github.com/OpenSourceEconomics/lcm/issues/82
-def consumption(consumption_index):
-    _consumption_values = jnp.array([1, 2])
-    return _consumption_values[consumption_index]
-
-
 # --------------------------------------------------------------------------------------
 # State transitions
 # --------------------------------------------------------------------------------------
@@ -86,6 +74,13 @@ def next_wealth(wealth, consumption, labor_income, interest_rate):
     return (1 + interest_rate) * (wealth - consumption) + labor_income
 
 
+# For discrete state variables, we need to assure that the next state also belongs to
+# the grid. We therefore round the result of the continuous state transition function.
+def next_wealth_discrete(wealth, consumption, labor_income, interest_rate):
+    next_wealth_cont = next_wealth(wealth, consumption, labor_income, interest_rate)
+    return jnp.clip(jnp.rint(next_wealth_cont).astype(jnp.int32), 1, 400)
+
+
 # --------------------------------------------------------------------------------------
 # Constraints
 # --------------------------------------------------------------------------------------
@@ -97,7 +92,10 @@ def consumption_constraint(consumption, wealth):
 # Filters
 # --------------------------------------------------------------------------------------
 def absorbing_retirement_filter(retirement, lagged_retirement):
-    return jnp.logical_or(retirement == 1, lagged_retirement == 0)
+    return jnp.logical_or(
+        retirement == RetirementStatus.retired,
+        lagged_retirement == RetirementStatus.working,
+    )
 
 
 # ======================================================================================
@@ -121,7 +119,7 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
         "working": working,
     },
     choices={
-        "retirement": DiscreteGrid([0, 1]),
+        "retirement": DiscreteGrid(RetirementStatus),
         "consumption": LinspaceGrid(
             start=1,
             stop=400,
@@ -134,7 +132,7 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
             stop=400,
             n_points=100,
         ),
-        "lagged_retirement": DiscreteGrid([0, 1]),
+        "lagged_retirement": DiscreteGrid(RetirementStatus),
     },
 )
 
@@ -155,7 +153,7 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
         "age": age,
     },
     choices={
-        "retirement": DiscreteGrid([0, 1]),
+        "retirement": DiscreteGrid(RetirementStatus),
         "consumption": LinspaceGrid(
             start=1,
             stop=400,
@@ -172,30 +170,36 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
 )
 
 
+@dataclass
+class DiscreteConsumptionStatus:
+    low: int = 1
+    high: int = 2
+
+
+DiscreteWealthStatus = make_dataclass(
+    "DiscreteWealthStatus", [(f"level_{w}", int, w) for w in range(1, 401)]
+)
+
+
 ISKHAKOV_ET_AL_2017_FULLY_DISCRETE = Model(
     description=(
         "Starts from Iskhakov et al. (2017), removes filters and the lagged_retirement "
-        "state, and makes the consumption decision discrete."
+        "state, and makes the consumption decision and the wealth state discrete."
     ),
     n_periods=3,
     functions={
-        "utility": utility_fully_discrete,
-        "next_wealth": next_wealth,
+        "utility": utility,
+        "next_wealth": next_wealth_discrete,
         "consumption_constraint": consumption_constraint,
         "labor_income": labor_income,
         "working": working,
-        "consumption": consumption,
     },
     choices={
-        "retirement": DiscreteGrid([0, 1]),
-        "consumption_index": DiscreteGrid([0, 1]),
+        "retirement": DiscreteGrid(RetirementStatus),
+        "consumption": DiscreteGrid(DiscreteConsumptionStatus),
     },
     states={
-        "wealth": LinspaceGrid(
-            start=1,
-            stop=400,
-            n_points=100,
-        ),
+        "wealth": DiscreteGrid(DiscreteWealthStatus),
     },
 )
 
diff --git a/tests/test_models/stochastic.py b/tests/test_models/stochastic.py
index e5e96005..d31e592a 100644
--- a/tests/test_models/stochastic.py
+++ b/tests/test_models/stochastic.py
@@ -10,6 +10,7 @@
 """
 
 from copy import deepcopy
+from dataclasses import dataclass
 
 import jax.numpy as jnp
 
@@ -21,6 +22,27 @@
 # ======================================================================================
 
 
+# --------------------------------------------------------------------------------------
+# Categorical variables
+# --------------------------------------------------------------------------------------
+@dataclass
+class HealthStatus:
+    bad: int = 0
+    good: int = 1
+
+
+@dataclass
+class PartnerStatus:
+    single: int = 0
+    partnered: int = 1
+
+
+@dataclass
+class WorkingStatus:
+    retired: int = 0
+    working: int = 1
+
+
 # --------------------------------------------------------------------------------------
 # Utility function
 # --------------------------------------------------------------------------------------
@@ -91,7 +113,7 @@ def consumption_constraint(consumption, wealth):
         "labor_income": labor_income,
     },
     choices={
-        "working": DiscreteGrid([0, 1]),
+        "working": DiscreteGrid(WorkingStatus),
         "consumption": LinspaceGrid(
             start=1,
             stop=100,
@@ -99,8 +121,8 @@ def consumption_constraint(consumption, wealth):
         ),
     },
     states={
-        "health": DiscreteGrid([0, 1]),
-        "partner": DiscreteGrid([0, 1]),
+        "health": DiscreteGrid(HealthStatus),
+        "partner": DiscreteGrid(PartnerStatus),
         "wealth": LinspaceGrid(
             start=1,
             stop=100,
diff --git a/tests/test_next_state.py b/tests/test_next_state.py
index 7bdcbb27..416c6394 100644
--- a/tests/test_next_state.py
+++ b/tests/test_next_state.py
@@ -68,6 +68,7 @@ def f_weight_b(state):  # noqa: ARG001
         gridspecs=None,
         variable_info=None,
         params=None,
+        discrete_grid_converter=None,
         random_utility_shocks=None,
         n_periods=1,
     )
diff --git a/tests/test_simulate.py b/tests/test_simulate.py
index a9ab723c..05215b9d 100644
--- a/tests/test_simulate.py
+++ b/tests/test_simulate.py
@@ -9,7 +9,7 @@
     create_compute_conditional_continuation_policy,
     get_lcm_function,
 )
-from lcm.input_processing import process_model
+from lcm.input_processing import DiscreteGridConverter, process_model
 from lcm.logging import get_logger
 from lcm.model_functions import get_utility_and_feasibility_function
 from lcm.next_state import _get_next_state_function_simulation
@@ -75,6 +75,7 @@ def simulate_inputs():
         "compute_ccv_policy_functions": compute_ccv_policy_functions,
         "model": model,
         "next_state": _get_next_state_function_simulation(model),
+        "discrete_grid_converter": DiscreteGridConverter(),
     }
 
 
@@ -168,6 +169,32 @@ def test_simulate_using_get_lcm_function(
         assert (res.loc[period]["value"].diff()[1:] >= 0).all()
 
 
+# ======================================================================================
+# Test simulation works correctly with discrete grid conversion
+# ======================================================================================
+
+
+def test_simulate_with_discrete_grid_conversion():
+    """Test that the simulation works correctly with discrete grid conversion."""
+    model = get_model_config("iskhakov_et_al_2017_fully_discrete", n_periods=2)
+    params = get_params(wage=2)
+
+    simulate_model, _ = get_lcm_function(model=model, targets="solve_and_simulate")
+
+    res = simulate_model(
+        params,
+        initial_states={"wealth": jnp.array([1, 4])},
+        additional_targets=["labor_income", "working"],
+    )
+
+    assert "__consumption_index__" not in res.columns
+    assert "__wealth_index__" not in res.columns
+
+    assert_array_equal(res["retirement"], jnp.array([0, 1, 1, 1]))
+    assert_array_equal(res["consumption"], jnp.array([1, 2, 2, 2]))
+    assert_array_equal(res["wealth"], jnp.array([1, 4, 2, 2]))
+
+
 # ======================================================================================
 # Testing effects of parameters
 # ======================================================================================
@@ -353,7 +380,9 @@ def test_process_simulated_data():
         "b": jnp.array([-1, -2, -3, -4]),
     }
 
-    got = _process_simulated_data(simulated)
+    got = _process_simulated_data(
+        simulated, discrete_grid_converter=DiscreteGridConverter()
+    )
     assert tree_equal(expected, got)
 
 
diff --git a/tests/test_solution_on_toy_model.py b/tests/test_solution_on_toy_model.py
index 3da3b008..dc21258e 100644
--- a/tests/test_solution_on_toy_model.py
+++ b/tests/test_solution_on_toy_model.py
@@ -1,7 +1,7 @@
 """Test analytical solution and simulation with only discrete choices."""
 
 from copy import deepcopy
-from dataclasses import replace
+from dataclasses import dataclass, replace
 
 import jax.numpy as jnp
 import numpy as np
@@ -18,6 +18,24 @@
 # ======================================================================================
 # Model specification
 # ======================================================================================
+@dataclass
+class ConsumptionChoice:
+    low: int = 0
+    high: int = 1
+
+
+@dataclass
+class WorkingStatus:
+    retired: int = 0
+    working: int = 1
+
+
+@dataclass
+class HealthStatus:
+    bad: int = 0
+    good: int = 1
+
+
 def utility(consumption, working, wealth, health):  # noqa: ARG001
     return jnp.log(1 + health * consumption) - 0.5 * working
 
@@ -38,8 +56,8 @@ def consumption_constraint(consumption, wealth):
     },
     n_periods=2,
     choices={
-        "consumption": DiscreteGrid([0, 1]),
-        "working": DiscreteGrid([0, 1]),
+        "consumption": DiscreteGrid(ConsumptionChoice),
+        "working": DiscreteGrid(WorkingStatus),
     },
     states={
         "wealth": LinspaceGrid(
@@ -58,7 +76,7 @@ def next_health(health):
 
 STOCHASTIC_MODEL = deepcopy(DETERMINISTIC_MODEL)
 STOCHASTIC_MODEL.functions["next_health"] = next_health
-STOCHASTIC_MODEL.states["health"] = DiscreteGrid([0, 1])
+STOCHASTIC_MODEL.states["health"] = DiscreteGrid(HealthStatus)
 
 
 # ======================================================================================
diff --git a/tests/test_solve_brute.py b/tests/test_solve_brute.py
index 7fc11f2c..1cff2ec1 100644
--- a/tests/test_solve_brute.py
+++ b/tests/test_solve_brute.py
@@ -4,6 +4,7 @@
 from numpy.testing import assert_array_almost_equal as aaae
 
 from lcm.entry_point import create_compute_conditional_continuation_value
+from lcm.input_processing import DiscreteGridConverter
 from lcm.interfaces import Space
 from lcm.logging import get_logger
 from lcm.solve_brute import solve, solve_continuous_problem
@@ -112,6 +113,7 @@ def calculate_emax(values, params):  # noqa: ARG001
         continuous_choice_grids=continuous_choice_grids,
         compute_ccv_functions=utility_and_feasibility_functions,
         emax_calculators=emax_calculators,
+        discrete_grid_converter=DiscreteGridConverter(),
         logger=get_logger(debug_mode=False),
     )
 
diff --git a/tests/test_state_space.py b/tests/test_state_space.py
index c5d9384c..8449e76c 100644
--- a/tests/test_state_space.py
+++ b/tests/test_state_space.py
@@ -68,9 +68,10 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
         variable_info=None,
         functions=functions,
         function_info=function_info,
+        params=None,
+        discrete_grid_converter=None,
         random_utility_shocks=None,
         n_periods=100,
-        params={},
     )