first commit

latency/generate_graph.py

@@ -0,0 +1,60 @@
+import argparse
+import pandas as pd
+import matplotlib.pyplot as plt
+
+def shorten_title(title, max_len=12):
+    """Return a shortened title for plotting."""
+    return title if len(title) <= max_len else title[:max_len] + "..."
+
+def main():
+    parser = argparse.ArgumentParser(description="Generate latency graph from CSV.")
+    parser.add_argument("--input", required=True, help="Input CSV file")
+    parser.add_argument("--output", required=True, help="Output PNG path")
+    parser.add_argument("--user", required=True, help="Username for graph title")
+    args = parser.parse_args()
+
+    # Load CSV
+    df = pd.read_csv(args.input)
+
+    # Convert to float
+    df["Latency(s)"] = pd.to_numeric(df["Latency(s)"], errors="coerce")
+    df = df.dropna(subset=["Latency(s)"])
+
+    latencies = df["Latency(s)"].values
+    titles = df["Title"].values
+    short_titles = [shorten_title(t) for t in titles]
+
+    # Compute average
+    avg_latency = latencies.mean()
+
+    plt.figure(figsize=(14, 6))
+
+    # --- Bar chart ---
+    bars = plt.bar(short_titles, latencies)
+
+    # --- Average line ---
+    plt.axhline(y=avg_latency, linestyle="--")
+    plt.text(
+        -0.4, avg_latency,
+        f"Avg = {avg_latency:.3f}s",
+        va="bottom",
+        fontsize=10,
+        fontweight="bold"
+    )
+
+    # --- Label each bar with exact value ---
+    for i, value in enumerate(latencies):
+        plt.text(i, value, f"{value:.3f}", ha="center", va="bottom", fontsize=8)
+
+    plt.xticks(rotation=45, ha="right")
+    plt.xlabel("Name")
+    plt.ylabel("Latency (seconds)")
+    plt.title(f"Latency Performance of {args.user}")
+
+    plt.tight_layout()
+    plt.savefig(args.output)
+
+    print(f"Graph saved to: {args.output}")
+
+if __name__ == "__main__":
+    main()