compute_tau_jets_trs

t3toolbox.backend.sampling_derivatives.compute_tau_jets_trs(var_tt_cores, left_tt_cores, down_tt_cores, xi_jets, dxi_jets, nu_jets, trs)

def compute_tau_jets_trs(
        var_tt_cores:   typ.Sequence[NDArray],  # dG. len=d, elm_shape=K+C+(rLi,nUi,rR(i+1))
        left_tt_cores:  typ.Sequence[NDArray],  # P.  len=d, elm_shape=C+(rLi,nUi,rL(i+1))
        down_tt_cores:  typ.Sequence[NDArray],  # O.  len=d, elm_shape=C+(rLi,nOi,rR(i+1))
        xi_jets:        typ.Sequence[NDArray],  # frame input jets, len=d, elm_shape=(2,)+W+C+(nUi,)
        dxi_jets:       typ.Sequence[NDArray],  # var  input jets, len=d, elm_shape=(2,)+W+K+C+(nOi,)
        nu_jets:        typ.Sequence[NDArray],  # frame right jets, len=d, elm_shape=(order+1,)+W+C+(rR(i+1),)
        trs:            NDArray,                # binomial tensor, shape=(order+1,order+1,order+1)
) -> typ.Tuple[NDArray, ...]:                   # tau_jets. len=d, elm_shape=(order+1,)+W+K+C+(rL(i+1),)

Variation-rightward edge-variable jets tau – the mirror of compute_sigma_jets_trs().

Reverse the train (P in the Q-slot, O and dG reversed), run the sigma sweep, reverse the result.

Parameters:

• var_tt_cores (t3toolbox.backend.common.typ.Sequence[NDArray])

• left_tt_cores (t3toolbox.backend.common.typ.Sequence[NDArray])

• down_tt_cores (t3toolbox.backend.common.typ.Sequence[NDArray])

• xi_jets (t3toolbox.backend.common.typ.Sequence[NDArray])

• dxi_jets (t3toolbox.backend.common.typ.Sequence[NDArray])

• nu_jets (t3toolbox.backend.common.typ.Sequence[NDArray])

• trs (NDArray)

Return type:

t3toolbox.backend.common.typ.Tuple[NDArray, Ellipsis]