diff --git a/mbtrack2/utilities/read_impedance.py b/mbtrack2/utilities/read_impedance.py
index 3d1ba4b1617d4e13ee9015ae4caa2215609cf636..bd3fe6ee4f1e5e91a47414e62279a887e15d0c5a 100644
--- a/mbtrack2/utilities/read_impedance.py
+++ b/mbtrack2/utilities/read_impedance.py
@@ -412,39 +412,32 @@ def read_wakis(file, component_type='long', divide_by=None, imp=True):
                          comment="#",
                          header=None,
                          sep=r'\s+',
-                         names=["Frequency", "Z"])  # read as string 
-                         
+                         names=["Frequency","Z"])
         df["Frequency"] = df["Frequency"].apply(lambda x: complex(x.strip(
-            "()")))   # Convert both columns from strings to complex numbers
+            "()")))
         df["Z"] = df["Z"].apply(lambda x: complex(x.strip("()")))
         df["Frequency"] = df["Frequency"].apply( 
             lambda z: z.real
-        )   # Remove imaginary parts from frequency column (they're all 0j)
-        if divide_by is not None:  # Normalize if needed
+        )
+        if divide_by is not None:
             df["Z"] = df["Z"] / divide_by
         if component_type == 'long':
             df["Z"] = df["Z"].apply(lambda z: complex(abs(z.real), z.imag))
-
         df.set_index("Frequency", inplace=True)
-
         result = Impedance(variable=df.index,
                            function=df["Z"],
                            component_type=component_type)
     else:
-        
         df = pd.read_csv(file,
                          comment="#",
                          header=None,
                          sep=r'\s+',
-                         names=["Distance", "Wake"])
-                         
+                         names=["Distance", "Wake"])                    
         df["Time"] = df["Distance"] / c
         df["Wake"] = df["Wake"] * 1e12
         if divide_by is not None:
-            df["Wake"] = df["Wake"] / divide_by
-            
-        df.set_index("Time", inplace=True)
-        
+            df["Wake"] = df["Wake"] / divide_by            
+        df.set_index("Time", inplace=True)        
         result = WakeFunction(variable=df.index,
                               function=df["Wake"],
                               component_type=component_type)