add a pipeline for arepo

galsec.py

@@ -113,24 +113,35 @@ def aggregate(
     assert weight_field in extensive_fields
 
     for field in weighted_fields:
+        # Multiply weighted field by the weight v*m
         grouped_data[field] *= grouped_data[weight_field]
 
+    # Compute the sum of all fields
     binned_data = grouped_data[extensive_fields + weighted_fields].groups.aggregate(
         np.add
     )
 
     for field in weighted_fields:
-        binned_data[field] /= binned_data[weight_field]  # weighted mean
+        # For weighted field, divided by the total mass
+        # We obtain the weighted mean vmean = 𝚺 (m*v) / 𝚺 m
+        binned_data[field] /= binned_data[weight_field]  
 
-        # Veocity dispersion
+        # We allso compute the weighted dispersion around the weighted mean
+        # Restart from the unweighted data v
         grouped_data[field] /= grouped_data[weight_field]
         for i in range(len(grouped_data.groups)):
+            # retrieve the indices of each group
             slice = grouped_data.groups.indices[i], grouped_data.groups.indices[i + 1]
+            # Compute the fluctuations wrt the weighted mean (v - vmean)
             grouped_data[slice[0] : slice[1]][field] -= binned_data[i][field]
+        
+        # Compute m * (v - vmean)^2
         grouped_data[field] = grouped_data[weight_field] * grouped_data[field] ** 2
+        # Compute 𝚺 m * (v - vmean)^2
         binned_data[f"sigma_{field}"] = grouped_data[field,].groups.aggregate(
             np.add
         )[field]
+        # Compute sigma = 𝚺 (m * (v - vmean)^2) / 𝚺 m
         binned_data[f"sigma_{field}"] = np.sqrt(
             binned_data[f"sigma_{field}"] / binned_data[weight_field]
         )
@@ -462,7 +473,7 @@ class Galsec:
         self,
         delta_r: Quantity[u.kpc] = u.kpc,
         rmin: Quantity[u.kpc] = 1 * u.kpc,
-        rmax: Quantity[u.kpc] = 12 * u.kpc,
+        rmax: Quantity[u.kpc] = 30 * u.kpc,
         zmin: Quantity[u.kpc] = -0.5 * u.kpc,
         zmax: Quantity[u.kpc] = 0.5 * u.kpc,
     ):
@@ -475,7 +486,7 @@ class Galsec:
         rmin : Quantity[u.kpc], optional
             filter out bin below that radius, by default 1*u.kpc
         rmax : Quantity[u.kpc], optional
-            filter out bin beyond that radius, by default 12*u.kpc
+            filter out bin beyond that radius, by default 30*u.kpc
         """
 
         self.ring_binning(delta_r)