comments

src/WarrenCowleyParameters/__init__.py

@@ -7,14 +7,17 @@
 
 
 class WarrenCowleyParameters(ModifierInterface):
+    # List of integers representing the maximum number of atoms in shells
     nneigh = List(Int, value=[0, 12], label="Max atoms in shells", minlen=2)
 
     def validateInput(self):
+        # Check if the list of maximum atoms in shells is strictly increasing
         if not np.all(np.diff(self.nneigh) > 0):
             raise ValueError("'Max atoms in shells' must be strictly increasing.")
 
     @staticmethod
     def get_type_name(data, id):
+        # Get the name of a particle type by its ID
         ptype = data.particles["Particle Type"].type_by_id(id)
         name = ptype.name
         if name:
@@ -23,11 +26,13 @@ def get_type_name(data, id):
 
     @staticmethod
     def get_concentration(particle_types):
+        # Calculate the concentration of unique particle types
         unique_types, counts = np.unique(particle_types, return_counts=True)
         return unique_types, counts / len(particle_types)
 
     @staticmethod
     def get_central_atom_type_mask(unique_types, particles_types):
+        # Create a mask for central atom types
         central_atom_type_mask = []
         for atom_type in unique_types:
             central_atom_type_mask.append(np.where(particles_types == atom_type))
@@ -37,9 +42,9 @@ def get_central_atom_type_mask(unique_types, particles_types):
     def get_wc_from_neigh_in_shell_types(
         neigh_in_shell_types, central_atom_type_mask, c, unique_types
     ):
+        # Calculate Warren-Cowley parameters for atoms in shells
         ntypes = len(c)
         neight_in_shell = neigh_in_shell_types.shape[1]
-
         wc = np.zeros((ntypes, ntypes))
 
         for i in range(ntypes):
@@ -56,8 +61,9 @@ def modify(self, data: DataCollection, frame: int, **kwargs):
         self.validateInput()
         particles_types = np.array(data.particles.particle_type)
         ntypes = len(np.unique(particles_types))
-
         max_number_of_neigh = np.max(self.nneigh)
+
+        # Find nearest neighbors for each particle
         finder = NearestNeighborFinder(max_number_of_neigh, data)
         neigh_idx, _ = finder.find_all()
 
@@ -67,6 +73,7 @@ def modify(self, data: DataCollection, frame: int, **kwargs):
         nshells = len(self.nneigh) - 1
         wc_for_shells = np.zeros((nshells, ntypes, ntypes))
 
+        # Calculate Warren-Cowley parameters for each shell
         for m in range(nshells):
             neigh_idx_in_shell = neigh_idx[:, self.nneigh[m] : self.nneigh[m + 1]]
             neigh_in_shell_types = particles_types[neigh_idx_in_shell]
@@ -80,6 +87,8 @@ def modify(self, data: DataCollection, frame: int, **kwargs):
         labels = []
         warrenCowley = []
         idx = list(range(len(unique_types)))
+
+        # Get labels and values for Warren-Cowley parameters
         for m in range(nshells):
             labels.append([])
             warrenCowley.append([])
@@ -90,6 +99,7 @@ def modify(self, data: DataCollection, frame: int, **kwargs):
                 labels[-1].append(f"{namei}-{namej}")
                 warrenCowley[-1].append(wc_for_shells[m, i, j])
 
+        # Create DataTable objects for visualization
         for m in range(nshells):
             table = DataTable(
                 title=f"Warren-Cowley parameter: shell={m+1}", plot_mode=DataTable.PlotMode.BarChart