diff --git a/tests/population/multiprocessing_via_population_comparison.py b/tests/population/multiprocessing_via_population_comparison.py
index 2fca56d4ed3e27aec6b82f0cb067f53903bf53a3..5907236ea9ea748686a5fc99d97876e078454af7 100644
--- a/tests/population/multiprocessing_via_population_comparison.py
+++ b/tests/population/multiprocessing_via_population_comparison.py
@@ -3,6 +3,7 @@ import json
 import time
 import pickle
 import sys
+import numpy as np
 
 import matplotlib.pyplot as plt
 
@@ -76,26 +77,26 @@ def parse_function(self, output):
 
 ## Set values
 test_pop = Population()
-test_pop.set(
-    C_logging_code="""
-if(stardata->star[0].SN_type != SN_NONE)    
-{
-    if (stardata->model.time < stardata->model.max_evolution_time)
-    {
-        Printf("DAVID_SN %30.12e %g %g %g %d\\n",
-            // 
-            stardata->model.time, // 1
-            stardata->star[0].mass, //2
-            stardata->previous_stardata->star[0].mass, //3
-            stardata->star[0].pms_mass, //4
-            stardata->star[0].SN_type //5
-      );
-    };
-    /* Kill the simulation to save time */
-    stardata->model.max_evolution_time = stardata->model.time - stardata->model.dtm;
-};
-"""
-)
+# test_pop.set(
+#     C_logging_code="""
+# if(stardata->star[0].SN_type != SN_NONE)    
+# {
+#     if (stardata->model.time < stardata->model.max_evolution_time)
+#     {
+#         Printf("DAVID_SN %30.12e %g %g %g %d\\n",
+#             // 
+#             stardata->model.time, // 1
+#             stardata->star[0].mass, //2
+#             stardata->previous_stardata->star[0].mass, //3
+#             stardata->star[0].pms_mass, //4
+#             stardata->star[0].SN_type //5
+#       );
+#     };
+#     /* Kill the simulation to save time */
+#     stardata->model.max_evolution_time = stardata->model.time - stardata->model.dtm;
+# };
+# """
+# )
 
 test_pop.set(
     separation=1000000000,
@@ -116,7 +117,7 @@ with open("comparison_result.dat", "a") as f:
     f.write(str(res) + "\n")
 
 
-mass_distribution = np.arange(1, 200)
+# mass_distribution = np.arange(1, 200)
 
 
 # evolve_population_mp(parse_function, mass_distribution)