LU

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

LU Decomposition Structure to access L, U and piv.

Attributes

A

Rectangular matrix

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

Members list

Concise view

Value members

Concrete methods

def L: Matrix[M, N]

Return lower triangular factor

Return lower triangular factor

Attributes

Returns:

L

Source:
LU.scala
def U: Matrix[N, N]

Return upper triangular factor

Return upper triangular factor

Attributes

Returns:

U

Source:
LU.scala

Determinant

Determinant

Attributes

Returns:

det(A)

Throws:
IllegalArgumentException

Matrix must be square

Source:
LU.scala

Return pivot permutation vector as a one-dimensional double array

Return pivot permutation vector as a one-dimensional double array

Attributes

Returns:

(double) piv

Source:
LU.scala

Is the matrix nonsingular?

Is the matrix nonsingular?

Attributes

Returns:

true if U, and hence A, is nonsingular.

Source:
LU.scala

Return pivot permutation vector

Return pivot permutation vector

Attributes

Returns:

piv

Source:
LU.scala
def solve[V <: Int](B: Matrix[M, V])(using ValueOf[V]): Matrix[N, V]

Solve A*X = B

Solve A*X = B

Attributes

B

A Matrix with as many rows as A and as many columns as B.

Returns:

X so that LUX = B(piv,:)

Throws:
IllegalArgumentException

Matrix row dimensions must agree.

RuntimeException

Matrix is singular.

Source:
LU.scala

Concrete fields

val LU: Matrix[M, N]

Attributes

Source:
LU.scala
val m: Int

Attributes

Source:
LU.scala
val n: Int

Attributes

Source:
LU.scala