add combution rank file

serve/ranks/combustion.py

@@ -0,0 +1,49 @@
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+import streamlit as st
+
+from mlip_arena.models import REGISTRY as MODELS
+
+valid_models = [
+    model
+    for model, metadata in MODELS.items()
+    if Path(__file__).stem in metadata.get("gpu-tasks", [])
+]
+
+DATA_DIR = Path("mlip_arena/tasks/combustion")
+
+@st.cache_data
+def get_data(models):
+    families = [MODELS[str(model)]["family"] for model in models]
+    dfs = [
+        pd.read_json(DATA_DIR / family.lower() / "hydrogen.json") for family in families
+    ]
+    df = pd.concat(dfs, ignore_index=True)
+    df.drop_duplicates(inplace=True, subset=["formula", "method"])
+    return df
+
+df = get_data(valid_models)
+
+@st.cache_data
+def get_com_drifts(df):
+    df_exploded = df.explode(["timestep", "com_drifts"]).reset_index(drop=True)
+
+    # Convert the 'com_drifts' column (which are arrays) into separate columns for x, y, and z components
+    df_exploded[["com_drift_x", "com_drift_y", "com_drift_z"]] = pd.DataFrame(
+        df_exploded["com_drifts"].tolist(), index=df_exploded.index
+    )
+
+    # Drop the original 'com_drifts' column
+    df_flat = df_exploded.drop(columns=["com_drifts"])
+
+    df_flat["total_com_drift"] = np.sqrt(
+        df_flat["com_drift_x"] ** 2 + df_flat["com_drift_y"] ** 2 + df_flat["com_drift_z"] ** 2
+    )
+
+    return df_flat
+
+df_exploded = get_com_drifts(df)
+
+table = pd.DataFrame()