from typing import Optional, Tuple
import torch
from torch_geometric.data import Data
from torch_geometric.data.datapipes import functional_transform
from torch_geometric.transforms import BaseTransform
[docs]@functional_transform('cartesian')
class Cartesian(BaseTransform):
r"""Saves the relative Cartesian coordinates of linked nodes in its edge
attributes (functional name: :obj:`cartesian`). Each coordinate gets
globally normalized to a specified interval (:math:`[0, 1]` by default).
Args:
norm (bool, optional): If set to :obj:`False`, the output will not be
normalized. (default: :obj:`True`)
max_value (float, optional): If set and :obj:`norm=True`, normalization
will be performed based on this value instead of the maximum value
found in the data. (default: :obj:`None`)
cat (bool, optional): If set to :obj:`False`, all existing edge
attributes will be replaced. (default: :obj:`True`)
interval ((float, float), optional): A tuple specifying the lower and
upper bound for normalization. (default: :obj:`(0.0, 1.0)`)
"""
def __init__(
self,
norm: bool = True,
max_value: Optional[float] = None,
cat: bool = True,
interval: Tuple[float, float] = (0.0, 1.0),
):
self.norm = norm
self.max = max_value
self.cat = cat
self.interval = interval
def forward(self, data: Data) -> Data:
assert data.pos is not None
assert data.edge_index is not None
(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
if self.norm and cart.numel() > 0:
max_val = float(cart.abs().max()) if self.max is None else self.max
length = self.interval[1] - self.interval[0]
center = (self.interval[0] + self.interval[1]) / 2
cart = length * cart / (2 * max_val) + center
if pseudo is not None and self.cat:
pseudo = pseudo.view(-1, 1) if pseudo.dim() == 1 else pseudo
data.edge_attr = torch.cat([pseudo, cart.type_as(pseudo)], dim=-1)
else:
data.edge_attr = cart
return data
def __repr__(self) -> str:
return (f'{self.__class__.__name__}(norm={self.norm}, '
f'max_value={self.max})')