fix(merge conflicts)

README.md

@@ -45,6 +45,9 @@ For detailed instructions on how to use the project, please refer to the **[API
 3. **Simulate a trained model:**
    See [Simulation & Evaluation](docs/api/simulation.md).
 
+4. **Compare fault tolerance of models:**
+   See [Checkpoint & Model Evaluation](docs/api/evaluation.md)
+
 ## HPC
 
 See **[docs/HPC.md](docs/HPC.md)** for the full guide, including environment setup, cluster selection, interactive debugging, and job submission.

docs/README.md

@@ -1,6 +1,6 @@
 # Documentation
 
-## Design & architecture ([`/design`](./design/))
+## Design & architecture (`/design`)
 
 If you are interested in the "why did you do it like this?"
 
@@ -11,7 +11,7 @@ If you are interested in the "why did you do it like this?"
 - [Learning algorithm](./design/learning_algorithm.md): RL techniques, i.e. PPO.
 - [Reward function](./design/learning_algorithm.md): Goals, fitness tracking, and reward structures.
 
-## API reference ([`/api`](./api/))
+## API reference (`/api`)
 
 If you are interested in the "how do I use it?"
 
@@ -19,3 +19,5 @@ If you are interested in the "how do I use it?"
 - [Tracking & Monitoring](./api/tracking.md): Setting up WandB and TensorBoard to monitor runs.
 - [Simulation](./api/simulation.md): Visualizing and evaluating models.
 - [Environment](./api/environment.md): MuJoCo environment interaction and configuration.
+- [Analysis](./api/analysis.md): Comparing checkpoints and generating plots.
+- [Evaluation](./api/evaluation.md): Evaluating checkpoints and comparing fault tolerance.

docs/api/evaluation.md

@@ -15,7 +15,7 @@ python scripts/train.py evaluation.evaluate_checkpoints=true evaluation.eval_max
 
 Results are saved to `runs/<run_dir>/metrics/checkpoint_evaluation.csv` and synced to Weights & Biases if enabled.
 
-## Cross-Model & Defect Tolerance Analysis
+## Cross-Model & Fault Tolerance Analysis
 
 To measure how well different controllers handle damage (amputations), use `scripts/compare_models.py`. This script performs a grid search over models x morphologies.
 

scripts/plots/analyze_convergence.py

@@ -58,11 +58,10 @@ class Columns(str, Enum):
 # Maps architecture display names to the path of their evaluation CSV.
 # Update these paths once real evaluation data is available.
 FILE_MAPPING: dict[str, str] = {
-    "centralized 2 arms": "runs/dummy/dummy_centralized_2_arms.csv",
+    # "centralized 2 arms": "runs/dummy/dummy_centralized_2_arms.csv",
-    "centralized 5 arms": "runs/dummy/dummy_centralized_5_arms.csv",
+    "centralized 5 arms": "runs/final-v2-centralized/checkpoint_evaluation.csv",
-    "decentralized fully connected": "runs/dummy/dummy_decentralized_fully_connected.csv",
+    "decentralized fully connected": "runs/final-v2-fully-conn/checkpoint_evaluation.csv",
-    "decentralized ring-level": "runs/dummy/dummy_decentralized_ring-level.csv",
+    "decentralized ring-level": "runs/final-v2-ring/checkpoint_evaluation.csv",
-    "decentralized segment-level": "runs/dummy/dummy_decentralized_segment-level.csv",
 }
 
 # Architecture profiles for dummy data generation: (max_reward, max_velocity, sigmoid_speed)
@@ -137,6 +136,10 @@ def load_metrics(file_mapping: dict[str, str]) -> pd.DataFrame:
 
         df = df[required].copy()
         df[Columns.ARCH] = arch_name
+        df[Columns.VELOCITY] = (df[Columns.INITIAL_XY_DIST] - df[Columns.FINAL_XY_DIST]) / df[
+            Columns.EVAL_STEPS
+        ]
+
         dfs.append(df)
 
     return pd.concat(dfs, ignore_index=True) if dfs else pd.DataFrame()
@@ -333,6 +336,7 @@ def plot_results(df: pd.DataFrame, results: pd.DataFrame, output_dir: str, **kwa
 def obtain_data() -> pd.DataFrame:
     """Resolves the file mapping, falling back to generated dummy CSVs if needed."""
     global USING_DUMMY_DATA
+
     if not any(os.path.exists(p) for p in FILE_MAPPING.values()):
         logger.info("No real evaluation files found. Generating dummy CSVs at expected locations.")
         generate_dummy_csvs(FILE_MAPPING)

scripts/tools/download_wandb_project.py

@@ -0,0 +1,142 @@
+from pathlib import Path
+from concurrent.futures import ThreadPoolExecutor, as_completed
+import threading
+import wandb
+import argparse
+
+# tune these depending on network / W&B limits
+MAX_RUN_WORKERS = 8
+MAX_FILE_WORKERS = 16
+MAX_ARTIFACT_WORKERS = 8
+
+api = wandb.Api()
+
+print_lock = threading.Lock()
+
+
+def safe_print(*args, **kwargs):
+    with print_lock:
+        print(*args, **kwargs)
+
+
+def download_file(file, run_dir):
+    target = run_dir / file.name
+
+    try:
+        # skip existing files
+        if target.exists():
+            return f"SKIP FILE {target}"
+
+        target.parent.mkdir(parents=True, exist_ok=True)
+
+        file.download(root=run_dir, replace=False)
+
+        return f"DONE FILE {target}"
+
+    except Exception as e:
+        return f"FAIL FILE {target}: {e}"
+
+
+def sanitize_artifact_name(name: str):
+    return name.replace(":", "_")
+
+
+def download_artifact(artifact, artifact_root):
+    try:
+        artifact_name = sanitize_artifact_name(artifact.name)
+        artifact_dir = artifact_root / artifact_name
+
+        if artifact_dir.exists() and any(artifact_dir.iterdir()):
+            return f"SKIP ARTIFACT {artifact.name}"
+
+        artifact_dir.mkdir(parents=True, exist_ok=True)
+
+        artifact.download(root=artifact_dir)
+
+        return f"DONE ARTIFACT {artifact.name}"
+
+    except Exception as e:
+        return f"FAIL ARTIFACT {artifact.name}: {e}"
+
+
+def download_run(run, root):
+    run_dir = root / f"{run.name}"
+    run_dir.mkdir(parents=True, exist_ok=True)
+
+    safe_print(f"\n=== {run.name} ({run.id}) ===")
+
+    # -------------------------
+    # Download regular run files
+    # -------------------------
+    files = list(run.files())
+
+    with ThreadPoolExecutor(max_workers=MAX_FILE_WORKERS) as executor:
+        futures = [executor.submit(download_file, file, run_dir) for file in files]
+
+        for future in as_completed(futures):
+            safe_print(future.result())
+
+    # -------------------------
+    # Download logged artifacts
+    # -------------------------
+    artifact_root = run_dir / "artifacts"
+
+    try:
+        artifacts = list(run.logged_artifacts())
+        safe_print(f"Found {len(artifacts)} artifacts for {run.name}")
+
+        with ThreadPoolExecutor(max_workers=MAX_ARTIFACT_WORKERS) as executor:
+            futures = [
+                executor.submit(download_artifact, artifact, artifact_root)
+                for artifact in artifacts
+            ]
+
+            for future in as_completed(futures):
+                safe_print(future.result())
+
+    except Exception as e:
+        safe_print(f"Artifact download failed for {run.name}: {e}")
+
+    # -------------------------
+    # OPTIONAL: download used/input artifacts
+    # -------------------------
+    # try:
+    #     used_artifacts = list(run.used_artifacts())
+    #     used_root = run_dir / "used_artifacts"
+    #
+    #     for artifact in used_artifacts:
+    #         download_artifact(artifact, used_root)
+    # except Exception as e:
+    #     safe_print(f"Used artifact download failed: {e}")
+
+    safe_print(f"Finished {run.name}")
+
+
+def main(entity: str, project: str, root: Path):
+    root.mkdir(exist_ok=True)
+
+    runs = list(api.runs(f"{entity}/{project}"))
+
+    safe_print(f"Found {len(runs)} runs")
+
+    with ThreadPoolExecutor(max_workers=MAX_RUN_WORKERS) as executor:
+        futures = [executor.submit(download_run, run, root) for run in runs]
+
+        for future in as_completed(futures):
+            try:
+                future.result()
+            except Exception as e:
+                safe_print("RUN FAILED:", e)
+
+    safe_print("\nAll downloads complete.")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--entity", type=str, default="SEL3-2026-Groep-4")
+    parser.add_argument("--project", type=str, required=True)
+    parser.add_argument("--root", type=str, default="runs")
+    args = parser.parse_args()
+
+    root = Path(args.root)
+    main(entity=args.entity, project=args.project, root=root)