diff --git a/tests/population/comparison_result_astro1.dat b/tests/population/comparison_result_astro1.dat
index a13e8c03bc5b1b37db80f253d974c1b789a1d96b..073379c0f24a5c04cd3ab30b004488e304e285bc 100644
--- a/tests/population/comparison_result_astro1.dat
+++ b/tests/population/comparison_result_astro1.dat
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diff --git a/tests/population/comparison_result_laptop.dat b/tests/population/comparison_result_laptop.dat
deleted file mode 100644
index 073379c0f24a5c04cd3ab30b004488e304e285bc..0000000000000000000000000000000000000000
--- a/tests/population/comparison_result_laptop.dat
+++ /dev/null
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-(32, 10000, 1051.2897226810455, 63.89476823806763, 16.453455449811013)
-(32, 10000, 1050.2103514671326, 63.592018842697144, 16.514813817516313)
-(32, 10000, 1012.8798322677612, 65.41985893249512, 15.482757816902708)
-(32, 10000, 1025.2572581768036, 64.88021302223206, 15.80231029490433)
diff --git a/tests/population/name_testcase.pdf b/tests/population/name_testcase.pdf
new file mode 100644
index 0000000000000000000000000000000000000000..e7f0d56f02432cf56e04889e6ed52c1e6e20b628
Binary files /dev/null and b/tests/population/name_testcase.pdf differ
diff --git a/tests/population/name_testcase.png b/tests/population/name_testcase.png
new file mode 100644
index 0000000000000000000000000000000000000000..1173cb0233aedb2dc3f0e3d110730265461364a4
Binary files /dev/null and b/tests/population/name_testcase.png differ
diff --git a/tests/population/plot_scaling.py b/tests/population/plot_scaling.py
index c819a207347dcb2263748cc14f42df932293caa7..fe5b04174343082ac19815c7ebf95784b5e73eaf 100644
--- a/tests/population/plot_scaling.py
+++ b/tests/population/plot_scaling.py
@@ -8,17 +8,22 @@ def calc_mean_and_std(arr):
# Readout
result_file = 'comparison_result.dat'
+result_file = 'comparison_result_astro1.dat'
+name_testcase = 'Astro1'
+
+
results = []
-name_testcase = 'laptop David'
with open(result_file, 'r') as f:
for line in f:
res = list(eval(line.strip()))
- res.append(res[-2]/res[-1])
+ if len(res)==6:
+ res.append(res[-2]/res[-1])
results.append(res)
# make dataframe
headers = ['cores', 'total_systems', 'total_time_sequentially', 'total_time_multiprocessing', 'ratio']
+
df = pd.DataFrame(results)
df.columns = headers
@@ -63,7 +68,9 @@ for i in unique_amt_cores:
# Plot
x_position_shift = 0
y_position_shift = -0.05
+max_speedup = 0
for amt_systems in unique_amt_systems:
+
cores = []
speedup = []
std = []
@@ -75,20 +82,26 @@ for amt_systems in unique_amt_systems:
speedup.append(el['mean_ratio'])
std.append(el['std_ratio'])
+ 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'])
plt.errorbar(cores, speedup, std, linestyle='None', marker='^', label='{} systems'.format(amt_systems))
- x_position_shift += 0.04
+ 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)")
-plt.legend()
-plt.show()
-
-
-
+plt.xlim(0, max(unique_amt_cores) + 4)
+plt.ylim(0, max_speedup + 2)
+plt.grid()
+plt.legend()
+plt.savefig('name_testcase'+'.png')
+plt.savefig('name_testcase'+'.pdf')
+plt.show()
\ No newline at end of file