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add mlip diatomic curves
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,73 +1,127 @@ | ||
| from pathlib import Path | ||
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| import numpy as np | ||
| import numpy.linalg as LA | ||
| import plotly.express as px | ||
| 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 ase.io import read | ||
| from plotly.subplots import make_subplots | ||
| from scipy.interpolate import CubicSpline | ||
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| st.markdown("# Homonuclear diatomics") | ||
| color_sequence = pcolors.qualitative.Plotly | ||
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| DATA_DIR = Path("mlip_arena/tasks/diatomics") | ||
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| for i, symbol in enumerate(chemical_symbols[1:10]): | ||
| st.markdown("# Homonuclear diatomics") | ||
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| if i % 3 == 0: | ||
| cols = st.columns(3) | ||
| # 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) | ||
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| fpath = DATA_DIR / "gpaw" / f"{symbol+symbol}_AFM" / "traj.extxyz" | ||
| ncols = 2 | ||
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| if not fpath.exists(): | ||
| continue | ||
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| trj = read(fpath, index=":") | ||
| DATA_DIR = Path("mlip_arena/tasks/diatomics") | ||
| mlips = ["MACE-MP", "CHGNet"] | ||
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| rs, es, s2s = [], [], [] | ||
| dfs = [pd.read_json(DATA_DIR / mlip.lower() / "homonuclear-diatomics.json") for mlip in mlips] | ||
| df = pd.concat(dfs, ignore_index=True) | ||
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| 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()) | ||
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| rs = np.array(rs) | ||
| ind = np.argsort(rs) | ||
| es = np.array(es) | ||
| s2s = np.array(s2s) | ||
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| rs = rs[ind] | ||
| es = es[ind] | ||
| s2s = s2s[ind] | ||
| df.drop_duplicates(inplace=True, subset=["name", "method"]) | ||
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| es = es - es[-1] | ||
| for i, symbol in enumerate(chemical_symbols[1:]): | ||
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| xs = np.linspace(rs.min()*0.99, rs.max()*1.01, int(5e2)) | ||
| if i % ncols == 0: | ||
| cols = st.columns(ncols) | ||
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| cs = CubicSpline(rs, es) | ||
| ys = cs(xs) | ||
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| cs = CubicSpline(rs, s2s) | ||
| s2s = cs(xs) | ||
| rows = df[df["name"] == symbol + symbol] | ||
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| ylo = min(ys.min()*1.5, -1) | ||
| if rows.empty: | ||
| continue | ||
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| 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"}, | ||
| # fig = go.Figure() | ||
| fig = make_subplots(specs=[[{"secondary_y": True}]]) | ||
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| ylo = float("inf") | ||
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| for j, method in enumerate(rows["method"].unique()): | ||
| row = rows[rows["method"] == method].iloc[0] | ||
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| rs = np.array(row["R"]) | ||
| es = np.array(row["E"]) | ||
| fs = np.array(row["F"]) | ||
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| rs = np.array(rs) | ||
| ind = np.argsort(rs) | ||
| es = np.array(es) | ||
| fs = np.array(fs) | ||
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| rs = rs[ind] | ||
| es = es[ind] | ||
| es = es - es[-1] | ||
| fs = fs[ind] | ||
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| xs = np.linspace(rs.min()*0.99, rs.max()*1.01, int(5e2)) | ||
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| if energy_plot: | ||
| cs = CubicSpline(rs, es) | ||
| ys = cs(xs) | ||
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| ylo = min(ylo, ys.min()*1.2, -1) | ||
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| 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, | ||
| ) | ||
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| if force_plot: | ||
| cs = CubicSpline(rs, fs) | ||
| ys = cs(xs) | ||
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| 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, | ||
| ) | ||
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| fig.update_layout( | ||
| showlegend=True, | ||
| title_text=f"{symbol}-{symbol}", | ||
| title_x=0.5, | ||
| # yaxis_range=[ylo, 2*(abs(ylo))], | ||
| ) | ||
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| cols[i % 3].title(f"{symbol+symbol}") | ||
| cols[i % 3].plotly_chart(fig, use_container_width=False) | ||
| # Set x-axis title | ||
| fig.update_xaxes(title_text="Bond length (Å)") | ||
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| # st.latex(r"\frac{d^2E}{dr^2} = \frac{d^2E}{dr^2}") | ||
| # Set y-axes titles | ||
| if energy_plot: | ||
| fig.update_yaxes(title_text="Energy [eV]", secondary_y=False) | ||
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| # st.components.v1.html(fig.to_html(include_mathjax='cdn'),height=500) | ||
| if force_plot: | ||
| fig.update_yaxes(title_text="Force [eV/Å]", secondary_y=True) | ||
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| # cols[i % ncols].title(f"{row['name']}") | ||
| cols[i % ncols].plotly_chart(fig, use_container_width=True, height=250) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,92 @@ | ||
| import streamlit as st | ||
| from ase.data import chemical_symbols | ||
| from pymatgen.core import Element | ||
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| elements = [Element.from_Z(z) for z in range(1, 119)] | ||
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| # Define the number of rows and columns in the periodic table | ||
| rows = 9 # There are 7 rows in the conventional periodic table | ||
| columns = 18 | ||
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| # Define a function to display the periodic table | ||
| def display_periodic_table(): | ||
| # elements = [ | ||
| # (element, element) for element in chemical_symbols[1:] | ||
| # ] | ||
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| # cols = st.columns(18, gap='small', vertical_alignment='bottom') # Create 18 columns for the periodic table layout | ||
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| row = 0 | ||
| for element in elements: | ||
| symbol = element.symbol | ||
| atomic_number = element.Z | ||
| group = element.group | ||
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| if element.row > row: | ||
| cols = st.columns(columns, gap='small', vertical_alignment='bottom') | ||
| row = element.row | ||
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| if element.block == 'f': | ||
| continue | ||
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| with cols[group - 1]: | ||
| if st.button(symbol, use_container_width=True): | ||
| st.session_state.selected_element = symbol | ||
| st.session_state.selected_name = symbol | ||
| st.rerun() | ||
| # st.experimental_rerun() | ||
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| for element in elements: | ||
| symbol = element.symbol | ||
| atomic_number = element.Z | ||
| group = element.group | ||
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| if element.row > row: | ||
| cols = st.columns(columns, gap='small', vertical_alignment='bottom') | ||
| row = element.row | ||
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| if element.block == 'f': | ||
| noble = Element.from_row_and_group(row-1, 18) | ||
| row += 2 | ||
| group += atomic_number - noble.Z - 2 | ||
| else: | ||
| continue | ||
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| with cols[group - 1]: | ||
| if st.button(symbol, use_container_width=True): | ||
| st.session_state.selected_element = symbol | ||
| st.session_state.selected_name = symbol | ||
| st.rerun() | ||
| # st.experimental_rerun() | ||
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| # for idx, (symbol, name) in enumerate(elements): | ||
| # with cols[idx % 18]: # Place each element in the correct column | ||
| # if st.button(symbol, use_container_width=True): | ||
| # st.session_state.selected_element = symbol | ||
| # st.session_state.selected_name = name | ||
| # st.experimental_rerun() | ||
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| # Define a function to display the details of an element | ||
| def display_element_details(): | ||
| symbol = st.session_state.selected_element | ||
| name = st.session_state.selected_name | ||
| st.write(f"### {name} ({symbol})") | ||
| st.write(f"Details about {name} ({symbol}) will be displayed here.") | ||
| if st.button("Back to Periodic Table"): | ||
| st.session_state.selected_element = None | ||
| st.session_state.selected_name = None | ||
| st.experimental_rerun() | ||
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| st.title("Periodic Table") | ||
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| # st.balloons() | ||
| if 'selected_element' not in st.session_state: | ||
| st.session_state.selected_element = None | ||
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| if st.session_state.selected_element: | ||
| display_element_details() | ||
| else: | ||
| display_periodic_table() | ||
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