Package org.apache.spark.mllib.linalg

Class BLAS

Object

org.apache.spark.mllib.linalg.BLAS

public class BLAS
extends Object

BLAS routines for MLlib's vectors and matrices.

Constructor Summary

Constructors

Constructor	Description
BLAS()

Method Summary

Modifier and Type	Method	Description
static void	axpy(double a, Vector x, Vector y)	y += a * x
static void	copy(Vector x, Vector y)	y = x
static double	dot(Vector x, Vector y)	dot(x, y)
static void	gemm(double alpha, Matrix A, DenseMatrix B, double beta, DenseMatrix C)	C := alpha * A * B + beta * C
static void	gemv(double alpha, Matrix A, Vector x, double beta, DenseVector y)	y := alpha * A * x + beta * y
static org.apache.spark.internal.Logging.LogStringContext	LogStringContext(scala.StringContext sc)
static org.slf4j.Logger	org$apache$spark$internal$Logging$$log_()
static void	org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1)
static void	scal(double a, Vector x)	x = a * x
static void	spr(double alpha, Vector v, double[] U)	Adds alpha * v * v.t to a matrix in-place.
static void	spr(double alpha, Vector v, DenseVector U)	Adds alpha * v * v.t to a matrix in-place.
static void	syr(double alpha, Vector x, DenseMatrix A)	A := alpha * x * x^T^ + A

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

BLAS

public BLAS()

Method Details

axpy

public static void axpy(double a,
 Vector x,
 Vector y)

y += a * x

Parameters:

a - (undocumented)

x - (undocumented)

y - (undocumented)

dot

public static double dot(Vector x,
 Vector y)

dot(x, y)

Parameters:

x - (undocumented)

y - (undocumented)

Returns:

(undocumented)

copy

public static void copy(Vector x,
 Vector y)

y = x

Parameters:

x - (undocumented)

y - (undocumented)

scal

public static void scal(double a,
 Vector x)

x = a * x

Parameters:

a - (undocumented)

x - (undocumented)

spr

public static void spr(double alpha,
 Vector v,
 DenseVector U)

Adds alpha * v * v.t to a matrix in-place. This is the same as BLAS's ?SPR.

Parameters:

U - the upper triangular part of the matrix in a DenseVector(column major)

alpha - (undocumented)

v - (undocumented)

spr

public static void spr(double alpha,
 Vector v,
 double[] U)

Adds alpha * v * v.t to a matrix in-place. This is the same as BLAS's ?SPR.

Parameters:

U - the upper triangular part of the matrix packed in an array (column major)

alpha - (undocumented)

v - (undocumented)

syr

public static void syr(double alpha,
 Vector x,
 DenseMatrix A)

A := alpha * x * x^T^ + A

Parameters:

alpha - a real scalar that will be multiplied to x * x^T^.

x - the vector x that contains the n elements.

A - the symmetric matrix A. Size of n x n.

gemm

public static void gemm(double alpha,
 Matrix A,
 DenseMatrix B,
 double beta,
 DenseMatrix C)

C := alpha * A * B + beta * C

Parameters:

alpha - a scalar to scale the multiplication A * B.

A - the matrix A that will be left multiplied to B. Size of m x k.

B - the matrix B that will be left multiplied by A. Size of k x n.

beta - a scalar that can be used to scale matrix C.

C - the resulting matrix C. Size of m x n. C.isTransposed must be false.

gemv

public static void gemv(double alpha,
 Matrix A,
 Vector x,
 double beta,
 DenseVector y)

y := alpha * A * x + beta * y

Parameters:

alpha - a scalar to scale the multiplication A * x.

A - the matrix A that will be left multiplied to x. Size of m x n.

x - the vector x that will be left multiplied by A. Size of n x 1.

beta - a scalar that can be used to scale vector y.

y - the resulting vector y. Size of m x 1.

org$apache$spark$internal$Logging$$log_

public static org.slf4j.Logger org$apache$spark$internal$Logging$$log_()

org$apache$spark$internal$Logging$$log__$eq

public static void org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1)

LogStringContext

public static org.apache.spark.internal.Logging.LogStringContext LogStringContext(scala.StringContext sc)