Source code for tad_mctc.batch.mask.triples

# This file is part of tad-mctc.
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# SPDX-Identifier: Apache-2.0
# Copyright (C) 2024 Grimme Group
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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"""
Batch Utility: Masks
====================

Functions for creating masks that discern between padding and actual values.
"""

from __future__ import annotations

import torch

from ...typing import Tensor
from .pairs import real_pairs

__all__ = ["real_triples"]




def real_triples(
    numbers: Tensor, mask_diagonal: bool = True, mask_self: bool = True
) -> Tensor:
    """
    Create a mask for triples from atomic numbers. Padding value is zero.

    Parameters
    ----------
    numbers : Tensor
        Atomic numbers for all atoms.
    mask_diagonal : bool, optional
        Flag for also masking the diagonal, i.e., all pairs with the same
        indices. Defaults to `True`, i.e., writing False to the diagonal.
    mask_self : bool, optional
        Flag for also masking all triples where at least two indices are
        identical. Defaults to `True`, i.e., writing `False`.

    Returns
    -------
    Tensor
        Mask for triples.
    """
    real = real_pairs(numbers, mask_diagonal=False)
    mask = real.unsqueeze(-3) * real.unsqueeze(-2) * real.unsqueeze(-1)

    if mask_diagonal is True:
        mask *= ~torch.diag_embed(torch.ones_like(real))

    if mask_self is True:
        ones = torch.ones_like(real)
        mask *= ~torch.diag_embed(ones, offset=0, dim1=-3, dim2=-2)
        mask *= ~torch.diag_embed(ones, offset=0, dim1=-3, dim2=-1)
        mask *= ~torch.diag_embed(ones, offset=0, dim1=-2, dim2=-1)

    return mask