refactor: 将子模块转为普通目录，移除外部 git 依赖

- 移除 JEPA/lejepa-identifiability 子模块 gitlink
- 移除 research/multiply/MultiPLY 子模块 gitlink
- 删除 .gitmodules（不再有外部 URL 依赖）
- 两个目录内容作为普通文件纳入主仓库追踪
- 删除各自内部 .git 目录，消除嵌套 git 仓库

JEPA/lejepa-identifiability/experiments/analysis/aggregate.py

@@ -0,0 +1,63 @@
+"""
+Aggregate results from any experiment into a flat CSV.
+
+Usage:
+    python analysis/aggregate.py --results_dir results/2d/ --out results/2d/summary.csv
+    python analysis/aggregate.py --results_dir results/ --recursive --out results/all.csv
+"""
+
+import argparse, glob, json, os
+import pandas as pd
+
+
+SCALAR_KEYS = [
+    "experiment", "run_name", "mixing", "encoder", "mode", "source_dist",
+    "seed", "N", "lamb", "rho", "lr", "steps", "batch_size", "n_layers", "hidden",
+    "r2_zx", "r2_xz", "r2_zh", "r2_hz",
+    "orth_err", "orth_err_normalized",
+    "epsilon", "delta", "D_bound", "approx_bound",
+    "procrustes_mse", "L_h", "trace_cov",
+    "final_align", "final_sigreg", "final_whiten", "final_loss",
+]
+
+
+def load_results(results_dir, recursive=False):
+    pattern = os.path.join(results_dir, "**/*.json") if recursive else os.path.join(results_dir, "*.json")
+    files = sorted(glob.glob(pattern, recursive=recursive))
+    print(f"Found {len(files)} .json files")
+
+    rows = []
+    for path in files:
+        try:
+            with open(path) as f:
+                r = json.load(f)
+            row = {k: r.get(k) for k in SCALAR_KEYS}
+            row["file"] = os.path.relpath(path, results_dir)
+            rows.append(row)
+        except Exception as e:
+            print(f"  SKIP {path}: {e}")
+    return pd.DataFrame(rows)
+
+
+def main():
+    p = argparse.ArgumentParser()
+    p.add_argument("--results_dir", type=str, required=True)
+    p.add_argument("--out", type=str, default=None)
+    p.add_argument("--recursive", action="store_true")
+    args = p.parse_args()
+
+    df = load_results(args.results_dir, recursive=args.recursive)
+    if len(df) == 0:
+        print("No results found.")
+        return
+
+    print(f"\n{len(df)} runs loaded")
+    print(df.to_string(index=False))
+
+    out = args.out or os.path.join(args.results_dir, "summary.csv")
+    df.to_csv(out, index=False)
+    print(f"\nSaved {out}")
+
+
+if __name__ == "__main__":
+    main()