Initial commit

research/utils/plot_degree_distribution.py

@@ -0,0 +1,114 @@
+import argparse
+import matplotlib.pyplot as plt
+import numpy as np
+import os
+
+def plot_degree_distribution(degree_file_path: str, output_image_path: str):
+    """
+    Reads a file containing node degrees (one per line) and plots the
+    degree distribution as a histogram.
+
+    Args:
+        degree_file_path: Path to the file containing degrees.
+        output_image_path: Path to save the output plot image.
+    """
+    try:
+        # Read degrees from the file
+        degrees = np.loadtxt(degree_file_path, dtype=int)
+        print(f"[LOG] Read {len(degrees)} degrees from {degree_file_path}")
+
+        if len(degrees) == 0:
+            print("[WARN] Degree file is empty. No plot generated.")
+            return
+
+        # Calculate basic statistics
+        min_deg = np.min(degrees)
+        max_deg = np.max(degrees)
+        avg_deg = np.mean(degrees)
+        median_deg = np.median(degrees)
+
+        print(f"[LOG] Degree Stats: Min={min_deg}, Max={max_deg}, Avg={avg_deg:.2f}, Median={median_deg}")
+
+        # Plotting the distribution
+        plt.figure(figsize=(10, 6))
+        # Determine appropriate number of bins, maybe max_deg+1 if not too large
+        # Or use automatic binning like 'auto' or Sturges' rule etc.
+        # Using max_deg - min_deg + 1 bins can be too many if the range is large
+        # Let's try 'auto' binning first
+        n_bins = 'auto'
+        # If max_deg is reasonably small, we can use exact bins
+        if max_deg <= 1000: # Heuristic threshold
+             n_bins = max_deg - min_deg + 1
+
+        counts, bin_edges, patches = plt.hist(degrees, bins=n_bins, edgecolor='black', alpha=0.7)
+        plt.xlabel("Node Degree")
+        plt.ylabel("Number of Nodes")
+        plt.title(f"Degree Distribution (from {os.path.basename(degree_file_path)})")
+        plt.grid(axis='y', linestyle='--', alpha=0.7)
+
+        # Add text for statistics on the plot
+        stats_text = (
+            f"Total Nodes: {len(degrees)}\n"
+            f"Min Degree: {min_deg}\n"
+            f"Max Degree: {max_deg}\n"
+            f"Avg Degree: {avg_deg:.2f}\n"
+            f"Median Degree: {median_deg}"
+        )
+        # Position the text box; adjust as needed
+        plt.text(0.95, 0.95, stats_text, transform=plt.gca().transAxes,
+                 fontsize=9, verticalalignment='top', horizontalalignment='right',
+                 bbox=dict(boxstyle='round,pad=0.5', fc='wheat', alpha=0.5))
+
+
+        plt.tight_layout()
+        plt.savefig(output_image_path)
+        print(f"[LOG] Degree distribution plot saved to {output_image_path}")
+        # plt.show() # Uncomment if you want to display the plot interactively
+        
+        # Create weighted degree distribution plot
+        plt.figure(figsize=(10, 6))
+        # Calculate weighted distribution (degree * number of nodes)
+        unique_degrees, degree_counts = np.unique(degrees, return_counts=True)
+        weighted_counts = unique_degrees * degree_counts
+        
+        plt.bar(unique_degrees, weighted_counts, edgecolor='black', alpha=0.7)
+        plt.xlabel("Node Degree")
+        plt.ylabel("Degree × Number of Nodes")
+        plt.title(f"Weighted Degree Distribution (from {os.path.basename(degree_file_path)})")
+        plt.grid(axis='y', linestyle='--', alpha=0.7)
+        
+        # Add text for statistics on the plot
+        plt.text(0.95, 0.95, stats_text, transform=plt.gca().transAxes,
+                 fontsize=9, verticalalignment='top', horizontalalignment='right',
+                 bbox=dict(boxstyle='round,pad=0.5', fc='wheat', alpha=0.5))
+        
+        # Generate weighted output filename based on the original output path
+        weighted_output_path = os.path.splitext(output_image_path)[0] + "_weighted" + os.path.splitext(output_image_path)[1]
+        
+        plt.tight_layout()
+        plt.savefig(weighted_output_path)
+        print(f"[LOG] Weighted degree distribution plot saved to {weighted_output_path}")
+
+    except FileNotFoundError:
+        print(f"[ERROR] Degree file not found: {degree_file_path}")
+    except Exception as e:
+        print(f"[ERROR] An error occurred: {e}")
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Plot the degree distribution from a file containing node degrees."
+    )
+    parser.add_argument(
+        "degree_file",
+        type=str,
+        help="Path to the input file containing node degrees (one degree per line)."
+    )
+    parser.add_argument(
+        "-o", "--output",
+        type=str,
+        default="degree_distribution.png",
+        help="Path to save the output plot image (default: degree_distribution.png)."
+    )
+    args = parser.parse_args()
+
+    plot_degree_distribution(args.degree_file, args.output)