1697ad9a5cb50f61583735f8e442f80fc72a473c,torch_geometric/transform/polar.py,Polar,__call__,#Polar#Any#,9

Before Change

        phi = torch.acos(direction[:, 2]) / PI
        spherical = torch.stack([theta, phi], dim=1)

        if data.weight is None:
            data.weight = spherical
        else:
            data.weight = torch.cat(
                [spherical, data.weight.unsqueeze(1)], dim=1)

        return data

After Change

        assert pos.dim() == 2

        cart = pos[col] - pos[row]
        rho = torch.norm(cart, p=2, dim=-1)
        rho /= rho.max()
        theta = torch.atan2(cart[..., 1], cart[..., 0]) / (2 * PI)
        theta += (theta < 0).type_as(theta)
        polar = torch.stack([rho, theta], dim=1)

        if pseudo is not None and self.cat:
            pseudo = pseudo.view(-1, 1) if pseudo.dim() == 1 else pseudo
            data.weight = torch.cat([pseudo, cart.type_as(polar)], dim=-1)
        else:
            data.weight = polar

        return data

Instances