diff --git a/jaxley/modules/base.py b/jaxley/modules/base.py
index 71435643..cf9392dd 100644
--- a/jaxley/modules/base.py
+++ b/jaxley/modules/base.py
@@ -724,6 +724,16 @@ def _gather_channels_from_constituents(self, constituents: List):
             self.base.nodes.loc[self.nodes[name].isna(), name] = False
 
     def _prepare_for_jax(self):
+        """Prepare the module for simulation with JAX.
+
+        This function has to be run inside or before `to_jax`. It's main purpose is to;
+        1. Prepare the lookup of indices of states, parameters and mechanisms.
+        2. Add index attributes to mechanisms (i.e. where was it inserted) and also keep
+           track of states / parameters that are also shared by other mechanisms.
+
+        Adds `_inds_of_state_param(key: str)` to the module and also adds `indices` and
+        `_jax_inds` to the mechanisms.
+        """
         # prepare lookup of indices of states, parameters and mechanisms
         global_params = ["radius", "length", "axial_resistivity", "capacitance"]
         global_states = ["v"]
@@ -1262,9 +1272,18 @@ def _get_state_names(self) -> Tuple[List, List]:
         )
 
     def _iter_states_params(
-        self, params=False, states=False, currents=False
+        self, params: bool = False, states: bool = False, currents: bool = False
     ) -> Tuple[str, np.ndarray]:  # type: ignore
-        # assert that either params or states is True
+        """Iterate over all states and parameters.
+
+        Args:
+            params: Whether to iterate over parameters.
+            states: Whether to iterate over states.
+            currents: Whether to iterate over currents.
+
+        Yields:
+            The key and the indices of the states / parameters.
+        """
         assert params or states or currents, "Select either params / states / currents."
         all_mechs = self.channels + self.synapses
 
@@ -1299,12 +1318,27 @@ def get_parameters(self) -> List[Dict[str, jnp.ndarray]]:
     def _get_all_states_params(
         self,
         pstate: List[Dict],
-        voltage_solver=None,
-        delta_t=None,
-        all_params=None,
-        params=False,
-        states=False,
+        voltage_solver: str = None,
+        delta_t: float = None,
+        all_params: Dict[str, jnp.ndarray] = None,
+        params: bool = False,
+        states: bool = False,
     ) -> Dict[str, jnp.ndarray]:
+        """Get all parameters and/or states of the module.
+
+        Common backbone of both `get_all_parameters()` and `get_all_states()`.
+
+        Args:
+            pstate: The state of the trainable parameters.
+            voltage_solver: The voltage solver that is used.
+            delta_t: The stepsize.
+            all_params: All parameters of the module.
+            params: Whether to get the parameters.
+            states: Whether to get the states.
+
+        Returns:
+            A dictionary of all parameters and/or states of the module.
+        """
         states_params = {}
         pkeys = {}
         for i, p in enumerate(pstate):