Attributes
- Companion
- class
- Graph
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- Supertypes
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trait Producttrait Mirrorclass Objecttrait Matchableclass Any
- Self type
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StatisticalMeshModel.type
Members list
Type members
Inherited types
The names of the product elements
The names of the product elements
Attributes
- Inherited from:
- Mirror
The name of the type
The name of the type
Attributes
- Inherited from:
- Mirror
Value members
Concrete methods
creates a StatisticalMeshModel by discretizing the given Gaussian Process on the points of the reference mesh.
creates a StatisticalMeshModel by discretizing the given Gaussian Process on the points of the reference mesh.
Attributes
Adds a bias model to the given statistical shape model
Adds a bias model to the given statistical shape model
Attributes
Returns a PCA model with given reference mesh and a set of items in correspondence. All points of the reference mesh are considered for computing the PCA
Returns a PCA model with given reference mesh and a set of items in correspondence. All points of the reference mesh are considered for computing the PCA
Per default, the resulting mesh model will have rank (i.e. number of principal components) corresponding to the number of linearly independent fields. By providing an explicit stopping criterion, one can, however, compute only the leading principal components. See PivotedCholesky.StoppingCriterion for more details.
Attributes
Creates a new Statistical mesh model, with its mean and covariance matrix estimated from the given fields.
Creates a new Statistical mesh model, with its mean and covariance matrix estimated from the given fields.
Per default, the resulting mesh model will have rank (i.e. number of principal components) corresponding to the number of linearly independent fields. By providing an explicit stopping criterion, one can, however, compute only the leading principal components. See PivotedCholesky.StoppingCriterion for more details.