public class TensorEigenValues extends Object
| Constructor and Description |
|---|
TensorEigenValues() |
public static <T extends RealType<T>,U extends RealType<U>> RandomAccessibleInterval<U> calculateEigenValuesSymmetric(RandomAccessibleInterval<T> tensor, RandomAccessibleInterval<U> eigenvalues)
tensor - Input that holds linear representation of upper triangular
tensor in last dimension, i.e. if tensor (t) has n+1
dimensions, the last dimension must be of size n * ( n + 1 ) /
2, and the entries in the last dimension are arranged like
this: [t11, t12, ... , t1n, t22, t23, ... , tnn]eigenvalues - Target RandomAccessibleInterval for storing the
resulting tensor eigenvalues. Number of dimensions must be the
same as for input. For an n+1 dimensional input, the size of
the last dimension must be n.public static <T extends RealType<T>,U extends RealType<U>> RandomAccessibleInterval<U> calculateEigenValuesSymmetric(RandomAccessibleInterval<T> tensor, RandomAccessibleInterval<U> eigenvalues, int nTasks, ExecutorService es)
tensor - Input that holds linear representation of upper triangular
tensor in last dimension, i.e. if tensor (t) has n+1
dimensions, the last dimension must be of size n * ( n + 1 ) /
2, and the entries in the last dimension are arranged like
this: [t11, t12, ... , t1n, t22, t23, ... , tnn]eigenvalues - Target RandomAccessibleInterval for storing the
resulting tensor eigenvalues. Number of dimensions must be the
same as for input. For an n+1 dimensional input, the size of
the last dimension must be n.nTasks - Number of tasks used for parallel computation of eigenvalues.es - ExecutorService providing workers for parallel
computation. Service is managed (created, shutdown) by caller.public static <T extends RealType<T>,U extends ComplexType<U>> RandomAccessibleInterval<U> calculateEigenValuesSquare(RandomAccessibleInterval<T> tensor, RandomAccessibleInterval<U> eigenvalues)
tensor - Input that holds linear representation of tensor in last
dimension, i.e. if tensor (t) has n+1 dimensions, the last
dimension must be of size n * n, and the entries in the last
dimension are arranged like this: [t11, t12, ... , t1n, t21,
t22, t23, ... , tn1, ... , tnn]eigenvalues - Target RandomAccessibleInterval for storing the
resulting tensor eigenvalues. Number of dimensions must be the
same as for input. For an n+1 dimensional input, the size ofpublic static <T extends RealType<T>,U extends ComplexType<U>> RandomAccessibleInterval<U> calculateEigenValuesSquare(RandomAccessibleInterval<T> tensor, RandomAccessibleInterval<U> eigenvalues, int nTasks, ExecutorService es)
tensor - Input that holds linear representation of tensor in last
dimension, i.e. if tensor (t) has n+1 dimensions, the last
dimension must be of size n * n, and the entries in the last
dimension are arranged like this: [t11, t12, ... , t1n, t21,
t22, t23, ... , tn1, ... , tnn]eigenvalues - Target RandomAccessibleInterval for storing the
resulting tensor eigenvalues. Number of dimensions must be the
same as for input. For an n+1 dimensional input, the size of
the last dimension must be n.nTasks - Number of threads/workers used for parallel computation of
eigenvalues.es - ExecutorService providing workers for parallel
computation. Service is managed (created, shutdown) by caller.public static <T extends RealType<T>,U extends ComplexType<U>> RandomAccessibleInterval<U> calculateEigenValues(RandomAccessibleInterval<T> tensor, RandomAccessibleInterval<U> eigenvalues, EigenValues<T,U> ev)
tensor - Input that holds linear representation of tensor in last
dimension. Parameter ev specifies representation.eigenvalues - Target RandomAccessibleInterval for storing the
resulting tensor eigenvalues. Number of dimensions must be the
same as for input. For an n+1 dimensional input, the size of
the last dimension must be n.ev - Implementation that specifies how to calculate eigenvalues
from last dimension of input.public static <T extends RealType<T>,U extends ComplexType<U>> RandomAccessibleInterval<U> calculateEigenValues(RandomAccessibleInterval<T> tensor, RandomAccessibleInterval<U> eigenvalues, EigenValues<T,U> ev, int nTasks, ExecutorService es)
tensor - Input that holds linear representation of tensor in last
dimension. Parameter ev specifies representation.eigenvalues - Target RandomAccessibleInterval for storing the
resulting tensor eigenvalues. Number of dimensions must be the
same as for input. For an n+1 dimensional input, the size of
the last dimension must be n.ev - Implementation that specifies how to calculate eigenvalues
from last dimension of input.nTasks - Number of threads/workers used for parallel computation of
eigenvalues.es - ExecutorService providing workers for parallel
computation. Service is managed (created, shutdown) by caller.public static <T extends RealType<T>,U extends RealType<U>> Img<U> createAppropriateResultImg(RandomAccessibleInterval<T> tensor, ImgFactory<U> factory)
tensor - n+1 dimensional RandomAccessibleInterval.factory - ImgFactory used for creating the result image.Img with size n in the last dimension.@Deprecated public static <T extends RealType<T>,U extends RealType<U>> Img<U> createAppropriateResultImg(RandomAccessibleInterval<T> tensor, ImgFactory<U> factory, U u)
createAppropriateResultImg(RandomAccessibleInterval, ImgFactory) instead.Copyright © 2015–2022 ImgLib2. All rights reserved.