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from pathlib import Path
import numpy as np
import pandas as pd
import plotly.colors as pcolors
import plotly.graph_objects as go
import streamlit as st
from ase.data import chemical_symbols
from plotly.subplots import make_subplots
from scipy.interpolate import CubicSpline
color_sequence = pcolors.qualitative.Plotly
st.markdown("# Homonuclear diatomics")
# button to toggle plots
container = st.container(border=True)
energy_plot = container.checkbox("Show energy curves", value=True)
force_plot = container.checkbox("Show force curves", value=False)
ncols = 2
DATA_DIR = Path("mlip_arena/tasks/diatomics")
mlips = ["MACE-MP", "CHGNet"]
dfs = [pd.read_json(DATA_DIR / mlip.lower() / "homonuclear-diatomics.json") for mlip in mlips]
df = pd.concat(dfs, ignore_index=True)
df.drop_duplicates(inplace=True, subset=["name", "method"])
for i, symbol in enumerate(chemical_symbols[1:]):
if i % ncols == 0:
cols = st.columns(ncols)
rows = df[df["name"] == symbol + symbol]
if rows.empty:
continue
# fig = go.Figure()
fig = make_subplots(specs=[[{"secondary_y": True}]])
ylo = float("inf")
for j, method in enumerate(rows["method"].unique()):
row = rows[rows["method"] == method].iloc[0]
rs = np.array(row["R"])
es = np.array(row["E"])
fs = np.array(row["F"])
rs = np.array(rs)
ind = np.argsort(rs)
es = np.array(es)
fs = np.array(fs)
rs = rs[ind]
es = es[ind]
es = es - es[-1]
fs = fs[ind]
xs = np.linspace(rs.min()*0.99, rs.max()*1.01, int(5e2))
if energy_plot:
cs = CubicSpline(rs, es)
ys = cs(xs)
ylo = min(ylo, ys.min()*1.2, -1)
fig.add_trace(
go.Scatter(
x=xs, y=ys,
mode="lines",
line=dict(
color=color_sequence[j % len(color_sequence)],
width=2,
),
name=method,
),
secondary_y=False,
)
if force_plot:
cs = CubicSpline(rs, fs)
ys = cs(xs)
fig.add_trace(
go.Scatter(
x=xs, y=ys,
mode="lines",
line=dict(
color=color_sequence[j % len(color_sequence)],
width=1,
dash="dot",
),
name=method,
showlegend=False if energy_plot else True,
),
secondary_y=True,
)
fig.update_layout(
showlegend=True,
title_text=f"{symbol}-{symbol}",
title_x=0.5,
# yaxis_range=[ylo, 2*(abs(ylo))],
)
# Set x-axis title
fig.update_xaxes(title_text="Bond length (Å)")
# Set y-axes titles
if energy_plot:
fig.update_yaxes(title_text="Energy [eV]", secondary_y=False)
if force_plot:
fig.update_yaxes(title_text="Force [eV/Å]", secondary_y=True)
# cols[i % ncols].title(f"{row['name']}")
cols[i % ncols].plotly_chart(fig, use_container_width=True, height=250)
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