API Reference — dna/layers/RBFBehavior


AutomaticRadius

Toggles whether an RBF target's radius of influence is computed automatically rather than set explicitly.

Why this exists

Manually tuning each RBF target's radius is tedious and error-prone across large pose sets; this flag lets a rig opt into automatic radius computation instead, falling back to explicit control only where needed.

Fields

Name Type Description
On enumerator Radius is computed automatically.
Off enumerator Radius must be set explicitly.

RBFDistanceMethod

Selects how the distance between an input and an RBF pose target is measured.

Why this exists

Raw Euclidean distance is not always the right metric for RBF inputs — rotational data behaves differently depending on whether it's treated as a full quaternion or decomposed into swing/twist about a specific axis. This type lets a pose target be evaluated with the distance metric that matches the kind of data driving it (n-dimensional, quaternion, swing, or twist).

Fields

Name Type Description
Euclidean enumerator Standard n-dimensional distance measure.
Quaternion enumerator Treats inputs as a quaternion.
SwingAngle enumerator Treats inputs as a quaternion and finds distance between rotated TwistAxis direction.
TwistAngle enumerator Treats inputs as a half quaternion and finds distance between rotations around the TwistAxis direction.

Relationships

  • TwistAxis — the axis used by SwingAngle and TwistAngle distance measures.
  • RBFSolverType — the solver that consumes this distance measure.

RBFFunctionType

Selects the radial falloff function applied to distance when computing an RBF target's contribution weight.

Why this exists

RBF solvers need a way to convert "distance from target" into "contribution weight," and different falloff shapes (Gaussian, exponential, linear, cubic, quintic) produce different blend characteristics. Exposing this as a type lets each RBF setup choose the falloff curve that best matches its desired responsiveness.

Fields

Name Type Description
Gaussian enumerator Bell-curve falloff.
Exponential enumerator Exponential decay falloff.
Linear enumerator Linear falloff.
Cubic enumerator Cubic falloff.
Quintic enumerator Quintic falloff.

Relationships

  • RBFSolverType — the solver algorithm that applies this falloff function.
  • RBFDistanceMethod — supplies the distance value this function is applied to.

RBFNormalizeMethod

Selects when contribution weights from an RBF solve are normalized to sum to a consistent total.

Why this exists

The additive RBFSolverType can produce weights that exceed the expected 0-100% range depending on how many targets contribute, so a normalization policy is needed to keep results well-behaved. This type lets that policy be chosen per setup — only normalize when weights exceed one, or always normalize.

Fields

Name Type Description
OnlyNormalizeAboveOne enumerator Normalize only when the summed weight exceeds one.
AlwaysNormalize enumerator Always normalize the summed weight.

Relationships

  • RBFSolverType — the additive solver is the primary consumer of this normalization policy.

RBFSolverType

Selects the algorithm used to combine RBF (radial basis function) pose target contributions into a final weight.

Why this exists

An RBF solver needs to be able to trade off speed for coverage: the additive solver sums contributions and is cheap but needs more targets and a normalization pass, while the interpolative solver blends by distance and gives smoother results with fewer targets at higher cost. Exposing this as a type lets a rig pick the right trade-off per solver instead of hard-coding one strategy.

Fields

Name Type Description
Additive enumerator Sums contributions from each target; faster, may need more targets and normalization for smooth results.
Interpolative enumerator Interpolates values from each target by distance; smoother with fewer targets, at higher computational cost.

Relationships

  • RBFFunctionType — the falloff function used to weight each target's contribution.
  • RBFDistanceMethod — how distance between input and target is measured for this solver.
  • RBFNormalizeMethod — whether/how results are normalized, most relevant to the additive solver.