Source code for torch_geometric.transforms.local_cartesian

import torch
from torch_scatter import scatter_max

from torch_geometric.transforms import BaseTransform

[docs]class LocalCartesian(BaseTransform): r"""Saves the relative Cartesian coordinates of linked nodes in its edge attributes. Each coordinate gets *neighborhood-normalized* to the interval :math:`{[0, 1]}^D`. Args: norm (bool, optional): If set to :obj:`False`, the output will not be normalized to the interval :math:`{[0, 1]}^D`. (default: :obj:`True`) cat (bool, optional): If set to :obj:`False`, all existing edge attributes will be replaced. (default: :obj:`True`) """ def __init__(self, norm=True, cat=True): self.norm = norm = cat def __call__(self, data): (row, col), pos, pseudo = data.edge_index, data.pos, data.edge_attr cart = pos[row] - pos[col] cart = cart.view(-1, 1) if cart.dim() == 1 else cart max_value, _ = scatter_max(cart.abs(), col, 0, dim_size=pos.size(0)) max_value = max_value.max(dim=-1, keepdim=True)[0] if self.norm: cart = cart / (2 * max_value[col]) + 0.5 else: cart = cart / max_value[col] if pseudo is not None and pseudo = pseudo.view(-1, 1) if pseudo.dim() == 1 else pseudo data.edge_attr =[pseudo, cart.type_as(pseudo)], dim=-1) else: data.edge_attr = cart return data