EC-SBM community detection analysis: full pipeline and writeup

Implement community detection on 3 EC-SBM networks (polblogs, topology,
internet_as) using 5 methods (Leiden-Mod, Leiden-CPM at 0.1 and 0.01,
Infomap, graph-tool SBM). Compute AMI/ARI/NMI accuracy, cluster statistics,
and generate figures and LaTeX report.

1 files changed, 67 insertions, 0 deletions

diff --git a/scripts/run_all.py b/scripts/run_all.py
new file mode 100644
index 0000000..c98b9a2
--- /dev/null
+++ b/scripts/run_all.py
@@ -0,0 +1,67 @@
+"""Master orchestration script: run all methods, compute accuracy and stats, generate plots."""
+
+import sys
+import os
+import time
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from config import NETWORKS, METHODS
+
+
+def main():
+    start = time.time()
+
+    print("=" * 60)
+    print("EC-SBM Community Detection Analysis Pipeline")
+    print("=" * 60)
+
+    # Step 1: Run community detection methods
+    for net_name in NETWORKS:
+        for method in METHODS:
+            m_name = method["name"]
+            m_type = method["type"]
+
+            print(f"\n{'='*60}")
+            print(f"Running {m_name} on {net_name}")
+            print(f"{'='*60}")
+
+            if m_type == "leiden":
+                from run_leiden import run_leiden
+                run_leiden(net_name, m_name, method["quality"],
+                           method.get("resolution"))
+            elif m_type == "infomap":
+                from run_infomap import run_infomap
+                run_infomap(net_name)
+            elif m_type == "graphtool_sbm":
+                from run_graphtool_sbm import run_graphtool_sbm
+                run_graphtool_sbm(net_name)
+
+    # Step 2: Compute accuracy
+    print(f"\n{'='*60}")
+    print("Computing accuracy metrics")
+    print(f"{'='*60}")
+    from compute_accuracy import compute_all_accuracy
+    compute_all_accuracy()
+
+    # Step 3: Compute cluster stats
+    print(f"\n{'='*60}")
+    print("Computing cluster statistics")
+    print(f"{'='*60}")
+    from compute_stats import compute_all_stats
+    compute_all_stats()
+
+    # Step 4: Generate plots and tables
+    print(f"\n{'='*60}")
+    print("Generating plots and LaTeX tables")
+    print(f"{'='*60}")
+    from generate_plots import generate_all
+    generate_all()
+
+    elapsed = time.time() - start
+    print(f"\n{'='*60}")
+    print(f"Pipeline complete in {elapsed:.1f}s")
+    print(f"{'='*60}")
+
+
+if __name__ == "__main__":
+    main()