[CT420]: Finish Assignment 1

year4/semester2/CT420/assignments/assignment1/code/plot.py

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+#!/usr/bin/python3
+
+import pandas as pd
+import matplotlib.pyplot as plt
+from datetime import datetime
+
+# dictionary that maps IPs to server names for readability
+servers = {
+    "2a01:258:fffe:f": "Ireland",
+    "213.5.132.231": "UK",
+    "150.241.82.187": "Europe",
+    "2603:c020:0:836": "US",
+    "159.196.178.7": "Australia",
+    "202.65.114.202": "Asia",
+}
+
+df = pd.read_csv("results.tsv", sep="\t")
+
+df['time'] = df['timestamp'].apply(lambda x: datetime.utcfromtimestamp(x).strftime('%H:%M'))
+
+plt.figure(figsize=(10, 6))
+
+for remote in df['remote'].unique():
+    remote_data = df[df['remote'] == remote]
+    plt.plot(remote_data['time'], remote_data['jitter'], label=servers[remote], marker="o")
+
+plt.title('Jitter over Time by Remote')
+plt.xlabel('Time (UTC)')
+plt.ylabel('Jitter')
+plt.legend(title='Remote', loc='best')
+plt.xticks(rotation=45)
+plt.tight_layout()
+
+plt.show()
+
+plt.figure(figsize=(10, 6))
+
+for remote in df['remote'].unique():
+    remote_data = df[df['remote'] == remote]
+    plt.plot(remote_data['time'], remote_data['delay'], label=servers[remote], marker="o")
+
+plt.title('Delay over Time by Remote')
+plt.xlabel('Time (UTC)')
+plt.ylabel('Delay')
+plt.legend(title='Remote', loc='best')
+plt.xticks(rotation=45)
+plt.tight_layout()
+
+plt.show()
+
+
+plt.figure(figsize=(10, 6))
+
+for remote in df['remote'].unique():
+    remote_data = df[df['remote'] == remote]
+    plt.plot(remote_data['time'], remote_data['offset'], label=servers[remote], marker="o")
+
+plt.title('Offset over Time by Remote')
+plt.xlabel('Time (UTC)')
+plt.ylabel('Offset')
+plt.legend(title='Remote', loc='best')
+plt.xticks(rotation=45)
+plt.tight_layout()
+
+plt.show()
+
+
+
+df['server'] = df['remote'].map(servers)
+jitter_statistics = df.groupby('server')['jitter'].agg(['max', 'min', 'mean', 'std']).reset_index()
+
+print("Jitter stats:")
+print(jitter_statistics)
+
+delay_statistics = df.groupby('server')['delay'].agg(['max', 'min', 'mean', 'std']).reset_index()
+print("Delay stats:")
+print(delay_statistics)
+
+offset_statistics = df.groupby('server')['offset'].agg(['max', 'min', 'mean', 'std']).reset_index()
+print("Offset stats:")
+print(offset_statistics)