uniform_sampling_kind#

t3toolbox.backend.uniform_fitting.uniform_sampling_kind(name, x0_data, weight=None)#
def uniform_sampling_kind(
        name:     str,        # 'apply' / 'entries' / 'probe'
        x0_data:  typ.Tuple,  # UniformTuckerTensorTrain.data at the fixed rank
        weight:   typ.Optional[typ.Any] = None,  # per-mode weight ω (probe only); apply/entries take none
) -> bfit.SamplingKind:

Dispatch to the uniform uniform_apply_kind() / entries / probe by name. Only the vector-valued probe kind is weightable (per-mode ω); plain apply/entries have no mode axis and take no weight (a non-None weight for them is a structural error).

Parameters:

  • name (str)

  • x0_data (t3toolbox.backend.common.typ.Tuple)

  • weight (t3toolbox.backend.common.typ.Optional[t3toolbox.backend.common.typ.Any])

Return type:

SamplingKind