GaussianProcessTransformationSpace

Type Members

type JacobianImage = (Point[D]) ⇒ DenseMatrix[Float]

Definition Classes
TransformationSpace
type T = GaussianProcessTransformation[D]

Type of parametric transforms generated by this space
Type of parametric transforms generated by this space

Definition Classes
GaussianProcessTransformationSpace → DifferentiableTransforms → TransformationSpace

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
def identityTransformParameters: DenseVector[Float]

returns the parameters corresponding the identity transform in this space
returns the parameters corresponding the identity transform in this space

Definition Classes
GaussianProcessTransformationSpace → TransformationSpace
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def parametersDimensionality: Int

Definition Classes
GaussianProcessTransformationSpace → TransformationSpace
def product(that: TransformationSpace[D] with DifferentiableTransforms[D]): ProductTransformationSpace[D, Nothing, Nothing]

Produces a ProductTransformationSpace combining self with the space passed as argument
Produces a ProductTransformationSpace combining self with the space passed as argument

Definition Classes
DifferentiableTransforms
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def takeDerivativeWRTParameters(p: ParameterVector): (Point[D]) ⇒ DenseMatrix[Float]

returns a function providing the Jacobian at a requested point.
returns a function providing the Jacobian at a requested point. This is used when optimizing over the parameters, e.g. during registration

Definition Classes
GaussianProcessTransformationSpace → TransformationSpace
def toString(): String

Definition Classes
AnyRef → Any
def transformForParameters(p: ParameterVector): GaussianProcessTransformation[D]

returns a transformation corresponding the indicated parameters
returns a transformation corresponding the indicated parameters

Definition Classes
GaussianProcessTransformationSpace → TransformationSpace
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Docs: object GaussianProcessTransformationSpace | package registration

class GaussianProcessTransformationSpace[D <: Dim] extends TransformationSpace[D] with DifferentiableTransforms[D]

Type Members

type JacobianImage = (Point[D]) ⇒ DenseMatrix[Float]

type T = GaussianProcessTransformation[D]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

def identityTransformParameters: DenseVector[Float]

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def parametersDimensionality: Int

def product(that: TransformationSpace[D] with DifferentiableTransforms[D]): ProductTransformationSpace[D, Nothing, Nothing]

final def synchronized[T0](arg0: ⇒ T0): T0

def takeDerivativeWRTParameters(p: ParameterVector): (Point[D]) ⇒ DenseMatrix[Float]

def toString(): String

def transformForParameters(p: ParameterVector): GaussianProcessTransformation[D]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from DifferentiableTransforms[D]

Inherited from TransformationSpace[D]

Inherited from AnyRef

Inherited from Any

Ungrouped