Fix plots

measurements/CPU/plotResourceUsageDuringThrouputTest.py

@@ -24,16 +24,17 @@
 df_plot = pd.DataFrame(data)
 
 # Create the grouped bar chart
-plt.figure(figsize=(8.27, 11.69))  # A4 size in inches (210mm x 297mm)
+plt.figure(figsize=(10, 7), dpi=100)  # Changed to 1000x700 pixels equivalent
 sns.barplot(x='Metric', y='Value', hue='Protocol', data=df_plot, palette={'Mediator': '#F44336', 'ZeroMQ': '#4CAF50'})
 
-plt.xlabel('Performance Metric', fontsize=14)
-plt.ylabel('Average Usage', fontsize=14)
-plt.legend(title='Protocol', fontsize=12, title_fontsize=12)
+plt.xlabel('Performance Metric', fontsize=18)
+plt.ylabel('Average Usage', fontsize=18)
+plt.xticks(fontsize=16)
+plt.legend(title='Protocol', fontsize=16, title_fontsize=16)
 plt.grid(axis='y', linestyle='--', alpha=0.7)
 
 plt.tight_layout()
 
 # Save to PDF
-plt.savefig("resource_utilization.pdf", format="pdf")
+plt.savefig("resource_utilization.pdf", format="pdf", dpi=100)
 plt.show()

measurements/Latency/latencyDistributionComparison.py

@@ -22,7 +22,7 @@ def generate_comparison_plot():
     df_combined = pd.concat([df_zmq, df_mediator], ignore_index=True)
 
     print("Generating plot...")
-    plt.figure(figsize=(8.27, 11.69))  # A4 size in inches
+    plt.figure(figsize=(10, 7), dpi=100)  # Changed to 1000x700 pixels equivalent
 
     sns.violinplot(
         x='Protocol', 
@@ -31,14 +31,14 @@ def generate_comparison_plot():
         palette={'ZeroMQ': '#4CAF50', 'Mediator': '#F44336'}
     )
 
-    plt.xlabel('Communication Protocol', fontsize=14)
-    plt.ylabel('Round-Trip Latency (ms)', fontsize=14)
-    plt.xticks(fontsize=12)
-    plt.yticks(fontsize=12)
+    plt.xlabel('Communication Protocol', fontsize=18)
+    plt.ylabel('Round-Trip Latency (ms)', fontsize=18)
+    plt.xticks(fontsize=16)
+    plt.yticks(fontsize=16)
     plt.grid(True, which='major', linestyle='--', linewidth=0.5, color='grey')
 
     plt.tight_layout()
-    plt.savefig('latency_comparison.pdf', format='pdf')
+    plt.savefig('latency_comparison.pdf', format='pdf', dpi=100)
     print("Plot saved as 'latency_comparison.pdf'")
 
     plt.show()

measurements/Latency/latencyDistributionOfZMQ.py

@@ -11,7 +11,7 @@
     exit()
 
 # Create the plot
-plt.figure(figsize=(8.27, 11.69))  # A4 size in inches
+plt.figure(figsize=(10, 7), dpi=100)  # 1000x700 px at 100 dpi
 
 sns.violinplot(
     x='Protocol',
@@ -22,15 +22,15 @@
 
 # Add details to the plot
 plt.xlabel('')
-plt.ylabel('Round-Trip Latency (ms)', fontsize=14)
+plt.ylabel('Round-Trip Latency (ms)', fontsize=16)
 plt.grid(True, linestyle='--', alpha=0.6)
-plt.xticks(fontsize=12)
-plt.yticks(fontsize=12)
+plt.xticks(fontsize=14)
+plt.yticks(fontsize=14)
 
 plt.tight_layout()
 
 # Save to PDF
-plt.savefig('zmq_latency.pdf', format='pdf')
+plt.savefig('zmq_latency.pdf', format='pdf', dpi=100)
 print("Plot saved as 'zmq_latency.pdf'")
 
 # Calculate and print stats for your paper

measurements/Throughput/maximumThroughputComaprison.py

@@ -1,25 +1,22 @@
 import matplotlib.pyplot as plt
 
-# --- Enter your collected data here ---
 throughput_mediator = 15.7     # messages/sec
 throughput_zmq = 25432.1       # messages/sec
-# -------------------------------------
 
 protocols = ['Mediator', 'ZeroMQ']
 values = [throughput_mediator, throughput_zmq]
 colors = ['#F44336', '#4CAF50']
 
-plt.figure(figsize=(8.27, 11.69))  # A4 size in inches
+# Match exact pixel size: 1000x700 with dpi=100
+plt.figure(figsize=(10, 7), dpi=100)
 
 bars = plt.bar(protocols, values, color=colors)
 
-# Add plot details
-plt.ylabel('Throughput (Messages/Second)', fontsize=14)
-plt.xticks(fontsize=12)
-plt.yscale('log')  # log scale for large differences
+plt.ylabel('Throughput (Messages/Second)', fontsize=18)
+plt.xticks(fontsize=16)
+plt.yscale('log')
 plt.grid(axis='y', linestyle='--', alpha=0.7)
 
-# Add text labels on top of the bars
 for bar in bars:
     yval = bar.get_height()
     plt.text(
@@ -28,13 +25,13 @@
         f'{yval:,.0f}',
         va='bottom',
         ha='center',
-        fontsize=12
+        fontsize=16
     )
 
 plt.tight_layout()
 
-# Save the figure as PDF
-plt.savefig('throughput_comparison.pdf', format='pdf')
+# Save with the same dimensions
+plt.savefig("throughput_comparison.pdf", format="pdf", dpi=100)
 print("Plot saved as 'throughput_comparison.pdf'")
 
 plt.show()