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from pathlib import Path
import pandas as pd
import streamlit as st
from mlip_arena.models import REGISTRY
DATA_DIR = Path("mlip_arena/tasks/diatomics")
methods = ["MACE-MP", "Equiformer", "CHGNet", "MACE-OFF", "eSCN", "ALIGNN"]
dfs = [pd.read_json(DATA_DIR / method.lower() / "homonuclear-diatomics.json") for method in methods]
df = pd.concat(dfs, ignore_index=True)
table = pd.DataFrame(columns=[
"Model",
"No. of supported elements",
"No. of reversed forces",
"Energy-consistent forces",
"Last updated",
"Code",
"Paper"
])
for method in df["method"].unique():
rows = df[df["method"] == method]
metadata = REGISTRY.get(method, None)
new_row = {
"Model": method,
"No. of supported elements": len(rows["name"].unique()),
"No. of reversed forces": None, # Replace with actual logic if available
"Energy-consistent forces": None, # Replace with actual logic if available
"Code": metadata.get("github", None) if metadata else None,
"Paper": metadata.get("doi", None) if metadata else None,
}
table = pd.concat([table, pd.DataFrame([new_row])], ignore_index=True)
table.set_index("Model", inplace=True)
s = table.style.background_gradient(
cmap="PuRd",
subset=["No. of supported elements"],
vmin=0, vmax=120
)
st.markdown("# MLIP Arena Leaderboard")
st.dataframe(
s,
use_container_width=True,
column_config={
"Code": st.column_config.LinkColumn(
# "GitHub",
# help="The top trending Streamlit apps",
# validate="^https://[a-z]+\.streamlit\.app$",
max_chars=100,
display_text="GitHub",
),
"Paper": st.column_config.LinkColumn(
# validate="^https://[a-z]+\.streamlit\.app$",
max_chars=100,
display_text="arXiv",
),
},
)
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