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| from pathlib import Path | |
| import numpy as np | |
| import numpy.linalg as LA | |
| import plotly.express as px | |
| import streamlit as st | |
| from ase.data import chemical_symbols | |
| from ase.io import read | |
| from scipy.interpolate import CubicSpline | |
| st.markdown("# Homonuclear diatomics") | |
| DATA_DIR = Path("mlip_arena/tasks/diatomics") | |
| for i, symbol in enumerate(chemical_symbols[1:10]): | |
| if i % 3 == 0: | |
| cols = st.columns(3) | |
| fpath = DATA_DIR / "gpaw" / f"{symbol+symbol}_AFM" / "traj.extxyz" | |
| if not fpath.exists(): | |
| continue | |
| trj = read(fpath, index=":") | |
| rs, es, s2s = [], [], [] | |
| for atoms in trj: | |
| rs.append(LA.norm(atoms.positions[1] - atoms.positions[0])) | |
| es.append(atoms.get_potential_energy()) | |
| s2s.append(np.power(atoms.get_magnetic_moments(), 2).mean()) | |
| rs = np.array(rs) | |
| ind = np.argsort(rs) | |
| es = np.array(es) | |
| s2s = np.array(s2s) | |
| rs = rs[ind] | |
| es = es[ind] | |
| s2s = s2s[ind] | |
| es = es - es[-1] | |
| xs = np.linspace(rs.min()*0.99, rs.max()*1.01, int(5e2)) | |
| cs = CubicSpline(rs, es) | |
| ys = cs(xs) | |
| cs = CubicSpline(rs, s2s) | |
| s2s = cs(xs) | |
| ylo = min(ys.min()*1.5, -1) | |
| fig = px.scatter( | |
| x=xs, y=ys, | |
| render_mode="webgl", | |
| color=s2s, | |
| range_color=[0, s2s.max()], | |
| width=500, | |
| range_y=[ylo, 1.2*(abs(ylo))], | |
| # title=f"{atoms.get_chemical_formula()}", | |
| labels={"x": "Bond length (Å)", "y": "Energy", "color": "Magnetic moment"}, | |
| ) | |
| cols[i % 3].title(f"{symbol+symbol}") | |
| cols[i % 3].plotly_chart(fig, use_container_width=False) | |
| # st.latex(r"\frac{d^2E}{dr^2} = \frac{d^2E}{dr^2}") | |
| # st.components.v1.html(fig.to_html(include_mathjax='cdn'),height=500) | |