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import os | |
import crystal_toolkit.components as ctc | |
import dash | |
import dash_mp_components as dmp | |
from crystal_toolkit.settings import SETTINGS | |
from dash import dcc, html | |
from dash.dependencies import Input, Output, State | |
from datasets import load_dataset | |
from pymatgen.core import Structure | |
from pymatgen.ext.matproj import MPRester | |
HF_TOKEN = os.environ.get("HF_TOKEN") | |
# Load only the train split of the dataset | |
dataset = load_dataset( | |
"LeMaterial/leDataset", | |
token=HF_TOKEN, | |
split="train", | |
columns=[ | |
"lattice_vectors", | |
"species_at_sites", | |
"cartesian_site_positions", | |
"energy", | |
"energy_corrected", | |
"immutable_id", | |
"elements", | |
"functional", | |
"stress_tensor", | |
"magnetic_moments", | |
"forces", | |
"band_gap_direct", | |
"band_gap_indirect", | |
"dos_ef", | |
"charges", | |
"functional", | |
"chemical_formula_reduced", | |
"chemical_formula_descriptive", | |
"total_magnetization", | |
], | |
) | |
dataset = dataset.select(range(1000)) | |
# Convert the train split to a pandas DataFrame | |
train_df = dataset.to_pandas() | |
del dataset | |
# Initialize the Dash app | |
app = dash.Dash(__name__, assets_folder=SETTINGS.ASSETS_PATH) | |
server = app.server # Expose the server for deployment | |
# Define the app layout | |
layout = html.Div( | |
[ | |
html.H1("Interactive Crystal Viewer"), | |
html.Div( | |
[ | |
html.Div( | |
[ | |
html.H3("Search for materials by elements (eg. 'Ac,Cd,Ge')"), | |
dmp.MaterialsInput( | |
allowedInputTypes=["elements"], | |
hidePeriodicTable=False, | |
periodicTableMode="toggle", | |
showSubmitButton=True, | |
submitButtonText="Submit", | |
type="elements", | |
id="materials-input", | |
), | |
], | |
style={ | |
"width": "100%", | |
"display": "inline-block", | |
"verticalAlign": "top", | |
}, | |
), | |
], | |
style={"margin-bottom": "20px"}, | |
), | |
html.Div( | |
[ | |
html.Label("Select Material"), | |
dcc.Dropdown( | |
id="material-dropdown", | |
options=[], # Empty options initially | |
value=None, | |
), | |
], | |
style={"margin-bottom": "20px"}, | |
), | |
html.Button("Display Material", id="display-button", n_clicks=0), | |
html.Div( | |
[ | |
html.Div( | |
id="structure-container", | |
style={ | |
"width": "48%", | |
"display": "inline-block", | |
"verticalAlign": "top", | |
}, | |
), | |
html.Div( | |
id="properties-container", | |
style={ | |
"width": "48%", | |
"display": "inline-block", | |
"paddingLeft": "4%", | |
"verticalAlign": "top", | |
}, | |
), | |
], | |
style={"margin-top": "20px"}, | |
), | |
], | |
style={ | |
"margin-left": "10px", | |
"margin-right": "10px", | |
}, | |
) | |
def on_submit_materials_input(n_clicks, query): | |
if n_clicks is None or not query: | |
return [], None | |
options = search_materials(query) | |
if not options: | |
return [], None | |
return options, options[0]["value"] | |
# Function to search for materials | |
def search_materials(query): | |
element_list = [el.strip() for el in query.split(",")] | |
isubset = lambda x: set(x).issubset(element_list) | |
isintersection = lambda x: len(set(x).intersection(element_list)) > 0 | |
entries_df = train_df[ | |
[isintersection(l) and isubset(l) for l in train_df.elements.values.tolist()] | |
] | |
options = [ | |
{ | |
"label": f"{res.chemical_formula_reduced} ({res.immutable_id}) Calculated with {res.functional}", | |
"value": n, | |
} | |
for n, res in entries_df.iterrows() | |
] | |
del entries_df | |
return options | |
# # Callback to update the material dropdown based on search | |
# @app.callback( | |
# [Output("material-dropdown", "options"), Output("material-dropdown", "value")], | |
# Input("search-button", "n_clicks"), | |
# State("query-input", "value"), | |
# ) | |
# def update_material_dropdown(n_clicks, query): | |
# if n_clicks is None or not query: | |
# return [], None | |
# options = search_materials(query) | |
# if not options: | |
# return [], None | |
# return options, options[0]["value"] | |
# Callback to display the selected material | |
def display_material(n_clicks, material_id): | |
if n_clicks is None or not material_id: | |
return "", "" | |
row = train_df.iloc[material_id] | |
structure = Structure( | |
[x for y in row["lattice_vectors"] for x in y], | |
row["species_at_sites"], | |
row["cartesian_site_positions"], | |
coords_are_cartesian=True, | |
) | |
# Create the StructureMoleculeComponent | |
structure_component = ctc.StructureMoleculeComponent(structure) | |
# Extract key properties | |
properties = { | |
"Material ID": row.immutable_id, | |
"Formula": row.chemical_formula_descriptive, | |
"Energy per atom (eV/atom)": row.energy / len(row.species_at_sites), | |
"Band Gap (eV)": row.band_gap_direct or row.band_gap_indirect, | |
"Total Magnetization (μB/f.u.)": row.total_magnetization, | |
} | |
# Format properties as an HTML table | |
properties_html = html.Table( | |
[ | |
html.Tbody( | |
[ | |
html.Tr([html.Th(key), html.Td(str(value))]) | |
for key, value in properties.items() | |
] | |
) | |
], | |
style={ | |
"border": "1px solid black", | |
"width": "100%", | |
"borderCollapse": "collapse", | |
}, | |
) | |
return structure_component.layout(), properties_html | |
# Register crystal toolkit with the app | |
ctc.register_crystal_toolkit(app, layout) | |
if __name__ == "__main__": | |
app.run_server(debug=True, port=7860, host="0.0.0.0") | |