Interface TensorOverRing<T extends TensorOverRing<T,U,V,W>,U extends TensorOverRing<U,U,V,W>,V,W>

Type Parameters:
T - Type of this tensor.
U - Type of dense tensor equivalent to T. If T is dense, then this should be the same type as T. This parameter required because some ops between two sparse tensors may result in a dense tensor.
V - Storage for data of this tensor.
W - Type (or wrapper) of an element of this tensor. Should satisfy the axioms of a semiring as stated.
All Superinterfaces:
TensorOverSemiring<T,U,V,W>
All Known Subinterfaces:
FieldTensorMixin<T,U,V>, RingTensorMixin<T,U,V>, TensorOverField<T,U,V,W>
All Known Implementing Classes:
AbstractCooFieldMatrix, AbstractCooFieldTensor, AbstractCooFieldVector, AbstractCooRingMatrix, AbstractCooRingTensor, AbstractCooRingVector, AbstractCsrFieldMatrix, AbstractCsrRingMatrix, AbstractDenseDoubleTensor, AbstractDenseFieldMatrix, AbstractDenseFieldTensor, AbstractDenseFieldVector, AbstractDenseRingMatrix, AbstractDenseRingTensor, AbstractDenseRingVector, AbstractDoubleTensor, CMatrix, CooCMatrix, CooCTensor, CooCVector, CooFieldMatrix, CooFieldTensor, CooFieldVector, CooMatrix, CooRingMatrix, CooRingTensor, CooRingVector, CooTensor, CooVector, CsrCMatrix, CsrFieldMatrix, CsrMatrix, CsrRingMatrix, CTensor, CVector, FieldMatrix, FieldTensor, FieldVector, Matrix, RingMatrix, RingTensor, RingVector, Tensor, Vector
public interface TensorOverRing<T extends TensorOverRing<T,U,V,W>,U extends TensorOverRing<U,U,V,W>,V,W> extends TensorOverSemiring<T,U,V,W>
This interface specifies methods which any tensor whose data are elements of a ring should implement. This includes primitive values.

To allow for primitive types, the elements of this tensor do not necessarily have to implement Ring.

Formally, a ring is a set R with the binary ops addition (+) and multiplication (*) defined such that for elements a, b, c in R the following are satisfied:

  • Addition and multiplication are associative: a + (b + c) = (a + b) + c and a * (b * c) = (a * b) * c.
  • Addition is commutative: a + b = b + a
  • Existence of additive and multiplicative identities: There exists two distinct elements 0 and 1 in R such that a + 0 = 0 and a * 1 = 1 (called the additive and multiplicative identities respectively).
  • Distributivity of multiplication over addition: a * (b + c) = (a * b) + (a * c).
See Also:

  • Method Summary

    Modifier and Type
    Method
    Description
    TensorOverRing
    abs()
    Computes the element-wise absolute value of this tensor.
    int[]
    argmax()
    Finds the indices of the maximum value in this tensor.
    int[]
    argmaxAbs()
    Finds the indices of the maximum absolute value in this tensor.
    int[]
    argmin()
    Finds the indices of the minimum value in this tensor.
    int[]
    argminAbs()
    Finds the indices of the minimum absolute value in this tensor.
    T
    conj()
    Computes the element-wise conjugation of this tensor.
    default T
    H()
    Computes the conjugate transpose of a tensor by exchanging the first and last axes of this tensor and conjugating the exchanged values.
    T
    H(int... axes)
    Computes the conjugate transpose of this tensor.
    T
    H(int axis1, int axis2)
    Computes the conjugate transpose of a tensor by conjugating and exchanging axis1 and axis2.
    W
    max()
    Finds the maximum value in this tensor.
    double
    maxAbs()
    Finds the maximum absolute value in this tensor.
    W
    min()
    Finds the minimum value in this tensor.
    double
    minAbs()
    Finds the minimum value, in absolute value, in this tensor.
    T
    sub(T b)
    Computes the element-wise difference between two tensors of the same shape.
    T
    sub(W b)
    Subtracts a scalar value from each entry of this tensor.
    void
    subEq(W b)
    Subtracts a scalar value from each entry of this tensor and stores the result in this tensor.

    Methods inherited from interface org.flag4j.arrays.backend.semiring_arrays.TensorOverSemiring

    add, add, addEq, elemMult, getData, getRank, getShape, isOnes, isZeros, makeLikeTensor, mult, multEq, prod, sum, tensorDot, tensorDot, tensorDot, tensorDot, tensorTr, tensorTr

  • Method Details

    • sub

      T sub(W b)
      Subtracts a scalar value from each entry of this tensor.
      Parameters:
      b - Scalar value in difference.
      Returns:
      The difference of this tensor and the scalar b.

    • subEq

      void subEq(W b)
      Subtracts a scalar value from each entry of this tensor and stores the result in this tensor.
      Parameters:
      b - Scalar value in difference.

    • sub

      T sub(T b)
      Computes the element-wise difference between two tensors of the same shape.
      Parameters:
      b - Second tensor in the element-wise difference.
      Returns:
      The difference of this tensor with b.
      Throws:
      TensorShapeException - If this tensor and b do not have the same shape.

    • abs

      TensorOverRing abs()
      Computes the element-wise absolute value of this tensor.
      Returns:
      The element-wise absolute value of this tensor.

    • conj

      T conj()
      Computes the element-wise conjugation of this tensor.
      Returns:
      The element-wise conjugation of this tensor.

    • H

      default T H()
      Computes the conjugate transpose of a tensor by exchanging the first and last axes of this tensor and conjugating the exchanged values.
      Returns:
      The conjugate transpose of this tensor.
      See Also:

    • H

      T H(int axis1, int axis2)
      Computes the conjugate transpose of a tensor by conjugating and exchanging axis1 and axis2.
      Parameters:
      axis1 - First axis to exchange and conjugate.
      axis2 - Second axis to exchange and conjugate.
      Returns:
      The conjugate transpose of this tensor according to the specified axes.
      Throws:
      IndexOutOfBoundsException - If either axis1 or axis2 are out of bounds for the rank of this tensor.
      See Also:

    • H

      T H(int... axes)
      Computes the conjugate transpose of this tensor. That is, conjugates and permutes the axes of this tensor so that it matches the permutation specified by axes.
      Parameters:
      axes - Permutation of tensor axis. If the tensor has rank N, then this must be an array of length N which is a permutation of {0, 1, 2, ..., N-1}.
      Returns:
      The conjugate transpose of this tensor with its axes permuted by the axes array.
      Throws:
      IndexOutOfBoundsException - If any element of axes is out of bounds for the rank of this tensor.
      IllegalArgumentException - If axes is not a permutation of {1, 2, 3, ... N-1}.
      See Also:

    • min

      W min()
      Finds the minimum value in this tensor.
      Returns:
      The minimum value in this tensor.

    • max

      W max()
      Finds the maximum value in this tensor.
      Returns:
      The maximum value in this tensor.

    • argmin

      int[] argmin()
      Finds the indices of the minimum value in this tensor.
      Returns:
      The indices of the minimum value in this tensor. If this value occurs multiple times, the indices of the first entry (in row-major ordering) are returned.

    • argmax

      int[] argmax()
      Finds the indices of the maximum value in this tensor.
      Returns:
      The indices of the maximum value in this tensor. If this value occurs multiple times, the indices of the first entry (in row-major ordering) are returned.

    • argminAbs

      int[] argminAbs()
      Finds the indices of the minimum absolute value in this tensor.
      Returns:
      The indices of the minimum absolute value in this tensor. If this value occurs multiple times, the indices of the first entry (in row-major ordering) are returned.

    • argmaxAbs

      int[] argmaxAbs()
      Finds the indices of the maximum absolute value in this tensor.
      Returns:
      The indices of the maximum absolute value in this tensor. If this value occurs multiple times, the indices of the first entry (in row-major ordering) are returned.

    • minAbs

      double minAbs()
      Finds the minimum value, in absolute value, in this tensor.
      Returns:
      The minimum value, in absolute value, in this tensor.

    • maxAbs

      double maxAbs()
      Finds the maximum absolute value in this tensor.
      Returns:
      The maximum absolute value in this tensor.