diff --git a/tests/population/plot_scaling.py b/tests/population/plot_scaling.py
index f0594e227d43f032d44db91015e82b644373a474..b11d7fcd10b18c6743824f47248008920fe6ec89 100644
--- a/tests/population/plot_scaling.py
+++ b/tests/population/plot_scaling.py
@@ -1,3 +1,5 @@
+import matplotlib 
+import os
 import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
@@ -5,22 +7,17 @@ import numpy as np
 
 def calc_mean_and_std(arr):
     return np.mean(arr), np.std(arr)
-
+####
 
 
 # Configure
 result_file = 'comparison_result.dat'
 result_file = 'comparison_result_astro1.dat'
 name_testcase = 'Astro1'
+img_dir = 'scaling_plots'
 
-
-
-
-
-
-# 
+# Readout file
 results = []
-
 with open(result_file, 'r') as f:
     for line in f:
         res = list(eval(line.strip()))
@@ -71,16 +68,20 @@ for i in unique_amt_cores:
 
             calculated_results.append(res_dict)
 
-
-# Plot
+#############################################################################################################################
+# Plot speed up  and efficiency.
 x_position_shift = 0
 y_position_shift = -0.05
 max_speedup = 0
+# https://stackoverflow.com/questions/46323530/matplotlib-plot-two-x-axes-one-linear-and-one-with-logarithmic-ticks 
+fig, ax1 = plt.subplots()
+ax2 = ax1.twinx()
 for amt_systems in unique_amt_systems:
 
     cores = []
     speedup = []
     std = [] 
+    efficiency = []
 
     for el in calculated_results:
         if el['systems']==amt_systems:
@@ -88,29 +89,81 @@ for amt_systems in unique_amt_systems:
             cores.append(el['cores'] + x_position_shift)
             speedup.append(el['mean_ratio'])
             std.append(el['std_ratio'])
+            efficiency.append(el['mean_ratio']/el['cores'])
 
             if el['mean_ratio'] > max_speedup:
                 max_speedup = el['mean_ratio']
 
-
             # add number of runs its based on
-            plt.text(el['cores'] + x_position_shift+0.01, el['mean_ratio']+y_position_shift, el['total_runs'])
+            ax1.text(el['cores'] + x_position_shift+0.01, el['mean_ratio']+y_position_shift, el['total_runs'])
 
-    plt.errorbar(cores, speedup, std, linestyle='None', marker='^', label='{} systems'.format(amt_systems))
+    ax1.errorbar(cores, speedup, std, linestyle='None', marker='^', label='Speed up & efficiency of {} systems'.format(amt_systems))
+    ax2.plot(cores, efficiency, alpha=0.5)
     x_position_shift += 0.1
 
-plt.title("Speed up ratio vs amount of cores for different amounts of systems on {}".format(name_testcase))
-plt.xlabel("Amount of cores used")
-plt.ylabel("Speed up ratio (time_linear/time_parallel)")
+ax1.set_title("Speed up ratio vs amount of cores for different amounts of systems on {}".format(name_testcase))
+ax1.set_xlabel("Amount of cores used")
+ax1.set_ylabel("Speed up ratio (time_linear/time_parallel)")
+
+ax1.set_xlim(0, max(unique_amt_cores) + 4)
+ax1.set_ylim(0, max_speedup + 2)
+ax2.set_ylim(0, 1)
+
+ax1.grid()
+ax1.legend(loc=4)
+fig.savefig(os.path.join(img_dir, 'speedup_scaling_{}.{}'.format(name_testcase, 'png')))
+fig.savefig(os.path.join(img_dir, 'speedup_scaling_{}.{}'.format(name_testcase, 'pdf')))
+fig.savefig(os.path.join(img_dir, 'speedup_scaling_{}.{}'.format(name_testcase, 'eps')))
+plt.show()
+
+#####
+# Plot run time
+# fig = plt.figure()
+# ax = fig.add_subplot(111)
+
+# color_options = ['blue', 'green', 'red', 'black', 'yellow', 'magenta']
+
+# x_position_shift = 0
+# y_position_shift = -0.05
+
+# colors = [color_options[i] for i in range(len(unique_amt_systems))]
+# for i, amt_systems in enumerate(unique_amt_systems):
+
+#     cores = []
+
+#     mean_times_linear = []
+#     mean_times_multiprocessing = []
+#     std_linear = [] 
+#     std_mp = []
+
+#     for el in calculated_results:
+#         if el['systems']==amt_systems:
+#             cores.append(el['cores'] + x_position_shift)
+
+#             mean_times_linear.append(el['mean_time_sequential'])
+#             std_linear.append(el['std_sequential'])
+
+#             mean_times_multiprocessing.append(el['mean_time_multiprocessing'])
+#             std_mp.append(el['std_multiprocessing'])
+
+#             # # add number of runs its based on
+#             # plt.text(el['cores'] + x_position_shift+0.01, el['mean_ratio']+y_position_shift, el['total_runs'])
+
+#     ax.errorbar(cores, mean_times_linear, std_linear, color=colors[i], linewidth=1, marker='P', label='{} systems linear run'.format(amt_systems))
+#     ax.errorbar(cores, mean_times_multiprocessing, std_multiprocessing, linewidth=1, color=colors[i],  marker='d', label='{} systems MP run'.format(amt_systems))
+#     x_position_shift += 0.1
 
-plt.xlim(0, max(unique_amt_cores) + 4)
-plt.ylim(0, max_speedup + 2)
+# ax.set_title("Total time for sequential and MP for different amounts of systems on {}".format(name_testcase))
+# ax.set_xlabel("Amount of cores used")
+# ax.set_ylabel("Total time taken (s)")
 
-plt.grid()
-plt.legend()
+# ax.set_xlim(0, max(unique_amt_cores) + 20)
+# ax.set_yscale('log')
+# ax.grid()
+# ax.legend()
 
-plt.savefig('scaling_{}.png'+'.png')
-plt.savefig('scaling_{}.png'+'.pdf')
-plt.savefig('scaling_{}.svg'+'.pdf')
+# fig.savefig(os.path.join(img_dir, 'total_time_scaling_{}.{}'.format(name_testcase, 'png')))
+# fig.savefig(os.path.join(img_dir, 'total_time_scaling_{}.{}'.format(name_testcase, 'pdf')))
+# fig.savefig(os.path.join(img_dir, 'total_time_scaling_{}.{}'.format(name_testcase, 'eps')))
 
-plt.show()
\ No newline at end of file
+# plt.show()
\ No newline at end of file
diff --git a/tests/population/scaling_plots/speedup_scaling_Astro1.eps b/tests/population/scaling_plots/speedup_scaling_Astro1.eps
new file mode 100644
index 0000000000000000000000000000000000000000..49d71a3748813b299d696d1cea0655c904398558
--- /dev/null
+++ b/tests/population/scaling_plots/speedup_scaling_Astro1.eps
@@ -0,0 +1,2382 @@
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