1 RriResult

rri_metrics.types.RriResult(
    rri,
    pm_dist_before,
    pm_dist_after,
    pm_acc_before,
    pm_comp_before,
    pm_acc_after,
    pm_comp_after,
    fscore_tau=None,
)

Batch of per-candidate RRI outcomes and distance diagnostics.

Shapes follow the candidate batch dimension C produced by the caller. Scalars such as the reference-only distances are broadcast to (C,) so downstream code can remain shape-agnostic.

1.1 Attributes

Name	Description
rri	Tensor[“C”] Relative reconstruction improvement `(d_before - d_after) / d_before`.
pm_dist_before	Tensor[“C”] Bidirectional Chamfer-style distance between `P_t` and the GT mesh.
pm_dist_after	Tensor[“C”] Bidirectional distance between `P_t ∪ P_q` and the GT mesh.
pm_acc_before	Tensor[“C”] Point→mesh (accuracy) distance for `P_t` (broadcast).
pm_comp_before	Tensor[“C”] Mesh→point (completeness) distance for `P_t` (broadcast).
pm_acc_after	Tensor[“C”] Point→mesh distance for `P_t ∪ P_q`.
pm_comp_after	Tensor[“C”] Mesh→point distance for `P_t ∪ P_q`.
fscore_tau	Optional F-score values at configured distance thresholds.

1.2 Methods

Name	Description
to_serializable	Serialize this result into a cache-friendly CPU payload.
from_serializable	Reconstruct one result from a serialized payload.
to	Move all tensors in this result to the specified device.

1.2.1 to_serializable

rri_metrics.types.RriResult.to_serializable()

Serialize this result into a cache-friendly CPU payload.

1.2.2 from_serializable

rri_metrics.types.RriResult.from_serializable(payload, *, device)

Reconstruct one result from a serialized payload.

1.2.2.1 Parameters

Name	Type	Description	Default
payload	dict[str, Any]	Serialized payload produced by `to_serializable`.	required
device	torch.device	Destination device for tensors.	required

1.2.2.2 Returns

Name	Type	Description
	'RriResult'	Reconstructed RRI result.

1.2.3 to

rri_metrics.types.RriResult.to(device)

Move all tensors in this result to the specified device.

# RriResult { #aria_nbv.rri_metrics.types.RriResult } ```python rri_metrics.types.RriResult( rri, pm_dist_before, pm_dist_after, pm_acc_before, pm_comp_before, pm_acc_after, pm_comp_after, fscore_tau=None, ) ``` Batch of per-candidate RRI outcomes and distance diagnostics. Shapes follow the candidate batch dimension ``C`` produced by the caller. Scalars such as the reference-only distances are broadcast to ``(C,)`` so downstream code can remain shape-agnostic. ## Attributes | Name | Description | | --- | --- | | [rri](#aria_nbv.rri_metrics.types.RriResult.rri) | Tensor["C"] Relative reconstruction improvement ``(d_before - d_after) / d_before``. | | [pm_dist_before](#aria_nbv.rri_metrics.types.RriResult.pm_dist_before) | Tensor["C"] Bidirectional Chamfer-style distance between ``P_t`` and the GT mesh. | | [pm_dist_after](#aria_nbv.rri_metrics.types.RriResult.pm_dist_after) | Tensor["C"] Bidirectional distance between ``P_t ∪ P_q`` and the GT mesh. | | [pm_acc_before](#aria_nbv.rri_metrics.types.RriResult.pm_acc_before) | Tensor["C"] Point→mesh (accuracy) distance for ``P_t`` (broadcast). | | [pm_comp_before](#aria_nbv.rri_metrics.types.RriResult.pm_comp_before) | Tensor["C"] Mesh→point (completeness) distance for ``P_t`` (broadcast). | | [pm_acc_after](#aria_nbv.rri_metrics.types.RriResult.pm_acc_after) | Tensor["C"] Point→mesh distance for ``P_t ∪ P_q``. | | [pm_comp_after](#aria_nbv.rri_metrics.types.RriResult.pm_comp_after) | Tensor["C"] Mesh→point distance for ``P_t ∪ P_q``. | | [fscore_tau](#aria_nbv.rri_metrics.types.RriResult.fscore_tau) | Optional F-score values at configured distance thresholds. | ## Methods | Name | Description | | --- | --- | | [to_serializable](#aria_nbv.rri_metrics.types.RriResult.to_serializable) | Serialize this result into a cache-friendly CPU payload. | | [from_serializable](#aria_nbv.rri_metrics.types.RriResult.from_serializable) | Reconstruct one result from a serialized payload. | | [to](#aria_nbv.rri_metrics.types.RriResult.to) | Move all tensors in this result to the specified device. | ### to_serializable { #aria_nbv.rri_metrics.types.RriResult.to_serializable } ```python rri_metrics.types.RriResult.to_serializable() ``` Serialize this result into a cache-friendly CPU payload. ### from_serializable { #aria_nbv.rri_metrics.types.RriResult.from_serializable } ```python rri_metrics.types.RriResult.from_serializable(payload, *, device) ``` Reconstruct one result from a serialized payload. #### Parameters {.doc-section .doc-section-parameters} | Name | Type | Description | Default | |---------|------------------|---------------------------------------------------|------------| | payload | dict\[str, Any\] | Serialized payload produced by `to_serializable`. | _required_ | | device | torch.device | Destination device for tensors. | _required_ | #### Returns {.doc-section .doc-section-returns} | Name | Type | Description | |--------|---------------|---------------------------| | | \'RriResult\' | Reconstructed RRI result. | ### to { #aria_nbv.rri_metrics.types.RriResult.to } ```python rri_metrics.types.RriResult.to(device) ``` Move all tensors in this result to the specified device.