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matrix/ai.dragonfly.math.matrix.decomposition/SV

SV

ai.dragonfly.math.matrix.decomposition.SV
See theSV companion object
class SV[M <: Int, N <: Int]

Construct the singular value decomposition Structure to access U, S and V.

Attributes

M

Rectangular matrix

Companion:
object
Source:
SV.scala
Graph
Supertypes
class Object
trait Matchable
class Any

Members list

Concise view

Value members

Concrete methods

inline def S: Matrix[N, N]

Return the diagonal matrix of singular values

Return the diagonal matrix of singular values

Attributes

Returns:

S

Source:
SV.scala
inline def S_inverse: Matrix[N, N]

Return the diagonal matrix of singular values

Return the diagonal matrix of singular values

https://en.wikipedia.org/wiki/Singular_value_decomposition#Pseudoinverse "where Σ† is the pseudoinverse of Σ, which is formed by replacing every non-zero diagonal entry by its reciprocal and transposing the resulting matrix."

Attributes

Returns:

S

Source:
SV.scala
def cond: Double

Two norm condition number

Two norm condition number

Attributes

Returns:

max(S)/min(S)

Source:
SV.scala
def norm2: Double

Two norm

Two norm

Attributes

Returns:

max(S)

Source:
SV.scala
def rank: Int

Effective numerical matrix rank

Effective numerical matrix rank

Attributes

Returns:

Number of nonnegligible singular values.

Source:
SV.scala

Concrete fields

val U: Matrix[M, N]

Attributes

Source:
SV.scala
val V: Matrix[N, N]

Attributes

Source:
SV.scala
val m: Int

Attributes

Source:
SV.scala
val n: Int

Attributes

Source:
SV.scala
val singularValues: Vec[N]

Attributes

Source:
SV.scala
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