Docstrings

tardis/simulation/convergence.py

@@ -1,8 +1,25 @@
 import numpy as np
+from numba import njit
+
+from tardis.montecarlo.montecarlo_numba import njit_dict_no_parallel
 
 
 class ConvergenceSolver:
     def __init__(self, strategy):
+        """_summary_
+
+        Parameters
+        ----------
+        strategy : _type_
+            Convergence strategy for the physical property
+
+        Raises
+        ------
+        NotImplementedError
+            Custom convergence type specified
+        ValueError
+            Unknown convergence type specified
+        """
         self.convergence_strategy = strategy
         self.damping_factor = self.convergence_strategy.damping_constant
         self.threshold = self.convergence_strategy.threshold
@@ -21,10 +38,41 @@ def __init__(self, strategy):
                 f"- input is {self.convergence_strategy.type}"
             )
 
+    @njit(**njit_dict_no_parallel)
     def damped_converge(self, value, estimated_value):
+        """Damped convergence solver
+
+        Parameters
+        ----------
+        value : np.float64
+            The current value of the physical property
+        estimated_value : np.float64
+            The estimated value of the physical property
+
+        Returns
+        -------
+        np.float64
+            The converged value
+        """
         return value + self.damping_factor * (estimated_value - value)
 
     def get_convergence_status(self, value, estimated_value, no_of_cells):
+        """Get the status of convergence for the physical property
+
+        Parameters
+        ----------
+        value : np.float64, Quantity
+            The current value of the physical property
+        estimated_value : np.float64, Quantity
+            The estimated value of the physical property
+        no_of_cells : np.int64
+            The number of cells to measure convergence over
+
+        Returns
+        -------
+        bool
+            True if convergence is reached
+        """
         convergence = abs(value - estimated_value) / estimated_value
 
         fraction_converged = (