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1.  final def !=(arg0: Any): Boolean

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2.  final def ##: Int

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3.  final def ==(arg0: Any): Boolean

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4.  def apply[DDomain[D] <: DiscreteDomain[D]](items: Seq[DiscreteField[_3D, [D]MultiBodyObject[D, DDomain], ShapeAndPoseVector[_3D]]], logExpMapping: PoseExpLogMapping[DDomain])(implicit multibodyObjectWarper: DomainWarp[_3D, [D]MultiBodyObject[D, DDomain]], domainWarper: DomainWarp[_3D, DDomain], rng: Random): MultiBodyShapeAndPosePGA[DDomain]

   Creates a new MultiBodyShapeAndPosePGA, with its mean and covariance matrix estimated from the given fields.

   Creates a new MultiBodyShapeAndPosePGA, with its mean and covariance matrix estimated from the given fields.

   Per default, the resulting multi body model will have rank (i.e. number of principal geodesic) corresponding to the number of linear independent fields at the tangent space.

5.  def apply[DDomain[D] <: DiscreteDomain[D]](domain: MultiBodyObject[_3D, DDomain], meanVector: DenseVector[Double], variance: DenseVector[Double], basisMatrix: DenseMatrix[Double])(implicit warper: DomainWarp[_3D, [D]MultiBodyObject[D, DDomain]], warper2: DomainWarp[_3D, DDomain]): MultiBodyShapeAndPosePGA[DDomain]

   creates a MultiBodyShapeAndPosePGA from vector/matrix representation of the mean, variance and basis matrix.

   creates a MultiBodyShapeAndPosePGA from vector/matrix representation of the mean, variance and basis matrix.

   See also

   DenseVector[Double], DenseVector[Double], DenseMatrix[Double

6.  def apply[DDomain[D] <: DiscreteDomain[D]](dc: DataCollection[_3D, [D]MultiBodyObject[D, DDomain], ShapeAndPoseVector[_3D]])(implicit multiiBodyWarper: DomainWarp[_3D, [D]MultiBodyObject[D, DDomain]], innerWarper: DomainWarp[_3D, DDomain], rng: Random): MultiBodyShapeAndPosePGA[DDomain]

   Returns a MultiBodyShapeAndPosePGA with given a set of items in correspondence after logarithmic computation.

   Returns a MultiBodyShapeAndPosePGA with given a set of items in correspondence after logarithmic computation. All points of the reference domain are considered for computing the PGA

   Per default, the resulting multi body model will have rank (i.e. number of principal geodesic) corresponding to the number of linear independent fields at the tangent space.

7.  final def asInstanceOf[T0]: T0

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8.  def clone(): AnyRef

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9.  final def eq(arg0: AnyRef): Boolean

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10.  def equals(arg0: AnyRef): Boolean

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11.  def finalize(): Unit

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12.  final def getClass(): Class[_ <: AnyRef]

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13.  def hashCode(): Int

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14.  final def isInstanceOf[T0]: Boolean

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15.  final def ne(arg0: AnyRef): Boolean

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16.  final def notify(): Unit

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17.  final def notifyAll(): Unit

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18.  final def synchronized[T0](arg0: => T0): T0

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19.  def toString(): String

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20.  final def wait(): Unit

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

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22.  final def wait(arg0: Long): Unit

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