def _get_hrt(self, *shapes): # noqa: D102
# normalize length of r
h, r, t = super()._get_hrt(*shapes)
rc = view_complex(r)
rl = (rc.abs()**2).sum(dim=-1).sqrt()
r = r / rl.unsqueeze(dim=-1)
return h, r, t
def _exp_score(self, h, r, t) -> torch.FloatTensor: # noqa: D102
h, r, t = [view_complex(x) for x in (h, r, t)]
return (h * r * torch.conj(t)).sum().real
def _exp_score(self, h, r, t) -> torch.FloatTensor: # noqa: D102
h, r, t = strip_dim(*(view_complex(x) for x in (h, r, t)))
# check for unit length
assert torch.allclose((r.abs()**2).sum(dim=-1).sqrt(), torch.ones(1))
d = h * r - t
return -(d.abs()**2).sum(dim=-1).sqrt()