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72b14da
jarvis-dft example completed
allaffa Sep 21, 2024
97dede1
added energy and energy_per_atom in jarvis-dft PyG objetcs
allaffa Jan 8, 2026
0b09f1c
added charge and spin as graph attributes
allaffa Jan 8, 2026
863e9ab
fixed formatting
allaffa Jan 8, 2026
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12 changes: 12 additions & 0 deletions examples/jarvis_dft/download_dataset.sh
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#!/bin/bash

# URL to download the zip file from
URL="https://figshare.com/ndownloader/articles/6815699/versions/10"

# Directory where the file will be saved
OUTPUT_DIR="dataset/JARVIS-DFT"

mkdir -p "$OUTPUT_DIR"

# Use curl to follow redirects and download the file
curl -L -o "$OUTPUT_DIR/6815699.zip" "$URL"
250 changes: 250 additions & 0 deletions examples/jarvis_dft/generate_dictionaries_pure_elements.py
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def generate_dictionary_bulk_energies():

energy_bulk_metal = {
"H": 0.0,
"He": 0.0,
"Li": 0.0,
"Be": 0.0,
"B": 0.0,
"C": 0.0,
"N": 0.0,
"O": 0.0,
"F": 0.0,
"Ne": 0.0,
"Na": 0.0,
"Mg": 0.0,
"Al": 0.0,
"Si": 0.0,
"P": 0.0,
"S": 0.0,
"Cl": 0.0,
"Ar": 0.0,
"K": 0.0,
"Ca": 0.0,
"Sc": 0.0,
"Ti": 0.0,
"V": 0.0,
"Cr": 0.0,
"Mn": 0.0,
"Fe": 0.0,
"Co": 0.0,
"Ni": 0.0,
"Cu": 0.0,
"Zn": 0.0,
"Ga": 0.0,
"Ge": 0.0,
"As": 0.0,
"Se": 0.0,
"Br": 0.0,
"Kr": 0.0,
"Rb": 0.0,
"Sr": 0.0,
"Y": 0.0,
"Zr": 0.0,
"Nb": 0.0,
"Mo": 0.0,
"Tc": 0.0,
"Ru": 0.0,
"Rh": 0.0,
"Pd": 0.0,
"Ag": 0.0,
"Cd": 0.0,
"In": 0.0,
"Sn": 0.0,
"Sb": 0.0,
"Te": 0.0,
"I": 0.0,
"Xe": 0.0,
"Cs": 0.0,
"Ba": 0.0,
"La": 0.0,
"Ce": 0.0,
"Pr": 0.0,
"Nd": 0.0,
"Pm": 0.0,
"Sm": 0.0,
"Eu": 0.0,
"Gd": 0.0,
"Tb": 0.0,
"Dy": 0.0,
"Ho": 0.0,
"Er": 0.0,
"Tm": 0.0,
"Yb": 0.0,
"Lu": 0.0,
"Hf": 0.0,
"Ta": 0.0,
"W": 0.0,
"Re": 0.0,
"Os": 0.0,
"Ir": 0.0,
"Pt": 0.0,
"Au": 0.0,
"Hg": 0.0,
"Tl": 0.0,
"Pb": 0.0,
"Bi": 0.0,
"Po": 0.0,
"At": 0.0,
"Rn": 0.0,
"Fr": 0.0,
"Ra": 0.0,
"Ac": 0.0,
"Th": 0.0,
"Pa": 0.0,
"U": 0.0,
"Np": 0.0,
"Pu": 0.0,
"Am": 0.0,
"Cm": 0.0,
"Bk": 0.0,
"Cf": 0.0,
"Es": 0.0,
"Fm": 0.0,
"Md": 0.0,
"No": 0.0,
"Lr": 0.0,
"Rf": 0.0,
"Db": 0.0,
"Sg": 0.0,
"Bh": 0.0,
"Hs": 0.0,
"Mt": 0.0,
"Ds": 0.0,
"Rg": 0.0,
"Cn": 0.0,
"Nh": 0.0,
"Fl": 0.0,
"Mc": 0.0,
"Lv": 0.0,
"Ts": 0.0,
"Og": 0.0,
}

return energy_bulk_metal


def generate_dictionary_elements():

periodic_table_atomic_numbers = {
1: "H",
2: "He",
3: "Li",
4: "Be",
5: "B",
6: "C",
7: "N",
8: "O",
9: "F",
10: "Ne",
11: "Na",
12: "Mg",
13: "Al",
14: "Si",
15: "P",
16: "S",
17: "Cl",
18: "Ar",
19: "K",
20: "Ca",
21: "Sc",
22: "Ti",
23: "V",
24: "Cr",
25: "Mn",
26: "Fe",
27: "Co",
28: "Ni",
29: "Cu",
30: "Zn",
31: "Ga",
32: "Ge",
33: "As",
34: "Se",
35: "Br",
36: "Kr",
37: "Rb",
38: "Sr",
39: "Y",
40: "Zr",
41: "Nb",
42: "Mo",
43: "Tc",
44: "Ru",
45: "Rh",
46: "Pd",
47: "Ag",
48: "Cd",
49: "In",
50: "Sn",
51: "Sb",
52: "Te",
53: "I",
54: "Xe",
55: "Cs",
56: "Ba",
57: "La",
58: "Ce",
59: "Pr",
60: "Nd",
61: "Pm",
62: "Sm",
63: "Eu",
64: "Gd",
65: "Tb",
66: "Dy",
67: "Ho",
68: "Er",
69: "Tm",
70: "Yb",
71: "Lu",
72: "Hf",
73: "Ta",
74: "W",
75: "Re",
76: "Os",
77: "Ir",
78: "Pt",
79: "Au",
80: "Hg",
81: "Tl",
82: "Pb",
83: "Bi",
84: "Po",
85: "At",
86: "Rn",
87: "Fr",
88: "Ra",
89: "Ac",
90: "Th",
91: "Pa",
92: "U",
93: "Np",
94: "Pu",
95: "Am",
96: "Cm",
97: "Bk",
98: "Cf",
99: "Es",
100: "Fm",
101: "Md",
102: "No",
103: "Lr",
104: "Rf",
105: "Db",
106: "Sg",
107: "Bh",
108: "Hs",
109: "Mt",
110: "Ds",
111: "Rg",
112: "Cn",
113: "Nh",
114: "Fl",
115: "Mc",
116: "Lv",
117: "Ts",
118: "Og",
}

return periodic_table_atomic_numbers
58 changes: 58 additions & 0 deletions examples/jarvis_dft/jarvis_energy.json
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{
"Verbosity": {
"level": 2
},
"NeuralNetwork": {
"Architecture": {
"model_type": "EGNN",
"equivariance": true,
"radius": 5.0,
"max_neighbours": 100000,
"num_gaussians": 50,
"envelope_exponent": 5,
"int_emb_size": 64,
"basis_emb_size": 8,
"out_emb_size": 128,
"num_after_skip": 2,
"num_before_skip": 1,
"num_radial": 6,
"num_spherical": 7,
"num_filters": 126,
"edge_features": ["length"],
"hidden_dim": 50,
"num_conv_layers": 3,
"output_heads": {
"graph":{
"num_sharedlayers": 2,
"dim_sharedlayers": 50,
"num_headlayers": 2,
"dim_headlayers": [50,25]
}
},
"task_weights": [1.0]
},
"Variables_of_interest": {
"input_node_features": [0, 1, 2, 3],
"output_names": ["energy"],
"output_index": [0],
"output_dim": [1],
"type": ["graph"]
},
"Training": {
"num_epoch": 50,
"perc_train": 0.8,
"loss_function_type": "mae",
"batch_size": 32,
"continue": 0,
"Optimizer": {
"type": "AdamW",
"learning_rate": 1e-3
}
}
},
"Visualization": {
"plot_init_solution": true,
"plot_hist_solution": false,
"create_plots": true
}
}
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