Geometry Principal Components Node¶
The Geometry Principal Components node performs a Principal Component Analysis (PCA) on a field of positions.
PCA analyzes how the positions are distributed, finding the center of the data along with the orthogonal axes that best describe its orientation and shape. The resulting axes are ordered by how much the data varies along each direction, from greatest to least.
This is useful for determining the dominant orientation of geometry, aligning objects to point clouds, generating local coordinate systems, or measuring the extent of a distribution.
Inputs¶
- Geometry
Geometry containing the points to analyze.
All geometry component types except volumes are supported.
- Position
Position values used in the analysis.
Outputs¶
- Group Center
Center of the analyzed group.
- Rotation
Rotation whose local axes correspond to the principal axes of the data.
- Principal Components
Variance of the data along each principal axis.
Larger values indicate greater spread along the corresponding axis.
Principal Axes¶
- Longest Axis
Unit vector corresponding to the direction of greatest variance.
- Intermediate Axis
Unit vector corresponding to the direction of intermediate variance.
Together with the other axes, it forms a right-handed orthogonal basis.
- Shortest Axis
Unit vector corresponding to the direction of least variance.