Packages

object SVDecomp extends SVDecomp

The SVDecomp object provides several test matrices as well as methods for determining rank and test the SVD factorizations.

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Type Members

  1. type FactorType = (MatrixD, VectorD, MatrixD)

    Factor type contains 'u, s, v' which are the left orthogonal matrix, the diagonal matrix/vector containing singular values and the right orthogonal matrix.

    Factor type contains 'u, s, v' which are the left orthogonal matrix, the diagonal matrix/vector containing singular values and the right orthogonal matrix.

    Definition Classes
    SVDecomp
  2. type FactorTypeFull = (MatrixD, MatrixD, MatrixD)
    Definition Classes
    SVDecomp

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. val a1: MatrixD
  5. val a2: MatrixD
  6. val a3: MatrixD
  7. val a4: MatrixD
  8. val a5: MatrixD
  9. val a6: MatrixD
  10. val a7: MatrixD
  11. val a8: MatrixD
  12. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  13. def clone(): AnyRef
    Attributes
    protected[java.lang]
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    AnyRef
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    @throws( ... )
  14. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  16. def factor(): FactorType

    Factor/deflate the matrix by iteratively turning elements not in the main diagonal to zero.

    Factor/deflate the matrix by iteratively turning elements not in the main diagonal to zero. Then return the vector of singular values (i.e., the main diagonal), along with the left and right singular matrices.

    Definition Classes
    SVDecomp
  17. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  18. def flip(u: MatrixD, v: MatrixD): Unit

    Flip negative main diagonal elements in the singular vectors to positive.

    Flip negative main diagonal elements in the singular vectors to positive.

    u

    the left orthongonal matrix

    v

    the right orthongonal matrix

    Definition Classes
    SVDecomp
  19. def flip(u: MatrixD, s: VectorD): Unit

    Flip negative singular values to positive and set singular values close to zero to zero.

    Flip negative singular values to positive and set singular values close to zero to zero.

    u

    the left orthongonal matrix

    s

    the vector of singular values

    Definition Classes
    SVDecomp
  20. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  21. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  22. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  23. final def ne(arg0: AnyRef): Boolean
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    AnyRef
  24. final def notify(): Unit
    Definition Classes
    AnyRef
  25. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  26. def rank(s: VectorD): Int

    Determine the rank of a matrix by counting the number of non-zero singular values.

    Determine the rank of a matrix by counting the number of non-zero singular values. The implementation assumes zero singular values are last in the vector.

    s

    the vector of singular values for the matrix whose rank is sought

  27. def reorder(ft: FactorType): Unit

    Reorder the singular values to be in non-increasing order.

    Reorder the singular values to be in non-increasing order. Must swap singular vectors in lock step with singular values. To minimize the number of swaps, selection sort is used.

    ft

    the factored matrix (u, s, v)

    Definition Classes
    SVDecomp
  28. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  29. def test(a: MatrixD, u_s_v: FactorType, name: String): Unit

    Test the SVD Factorization algorithm on matrix 'a' by factoring the matrix into a left matrix u, a vector s, and a right matrix v.

    Test the SVD Factorization algorithm on matrix 'a' by factoring the matrix into a left matrix u, a vector s, and a right matrix v. Then multiply back to recover the original matrix 'u ** s * v.t'.

    a

    the orginal matrix

    u_s_v

    the given matrix a factored into three components

    name

    the name of the test case

  30. def toString(): String
    Definition Classes
    AnyRef → Any
  31. final def wait(): Unit
    Definition Classes
    AnyRef
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    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
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    @throws( ... )
  33. final def wait(arg0: Long): Unit
    Definition Classes
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    @throws( ... )

Inherited from SVDecomp

Inherited from AnyRef

Inherited from Any

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