Package org.apache.spark.mllib.linalg
Class BLAS
Object
org.apache.spark.mllib.linalg.BLAS
BLAS routines for MLlib's vectors and matrices.
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Constructor Summary
Constructors - 
Method Summary
Modifier and TypeMethodDescriptionstatic voidy += a * xstatic voidy = xstatic doubledot(x, y)static voidgemm(double alpha, Matrix A, DenseMatrix B, double beta, DenseMatrix C) C := alpha * A * B + beta * Cstatic voidgemv(double alpha, Matrix A, Vector x, double beta, DenseVector y) y := alpha * A * x + beta * ystatic org.slf4j.Loggerstatic voidorg$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1) static voidx = a * xstatic voidAdds alpha * v * v.t to a matrix in-place.static voidspr(double alpha, Vector v, DenseVector U) Adds alpha * v * v.t to a matrix in-place.static voidsyr(double alpha, Vector x, DenseMatrix A) A := alpha * x * x^T^ + A 
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Constructor Details
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BLAS
public BLAS() 
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Method Details
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axpy
y += a * x- Parameters:
 a- (undocumented)x- (undocumented)y- (undocumented)
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dot
dot(x, y)- Parameters:
 x- (undocumented)y- (undocumented)- Returns:
 - (undocumented)
 
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copy
y = x- Parameters:
 x- (undocumented)y- (undocumented)
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scal
x = a * x- Parameters:
 a- (undocumented)x- (undocumented)
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spr
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 aDenseVector(column major)alpha- (undocumented)v- (undocumented)
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spr
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)
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syr
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.
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gemm
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.
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gemv
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.
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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)  
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