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package org.nd4j.linalg.api.blas.impl;
import org.nd4j.linalg.api.blas.Lapack;
import org.nd4j.linalg.api.buffer.DataBuffer;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/**
* Base lapack define float and double versions.
*
* @author Adam Gibson
*/
public abstract class BaseLapack implements Lapack {
private static Logger logger = LoggerFactory.getLogger(BaseLapack.class);
@Override
public INDArray getrf( INDArray A ) {
int m = A.rows() ;
int n = A.columns() ;
INDArray INFO = Nd4j.createArrayFromShapeBuffer(Nd4j.getDataBufferFactory().createInt(1),
Nd4j.getShapeInfoProvider().createShapeInformation(new int[]{1, 1}));
int mn = Math.min( m, n ) ;
INDArray IPIV = Nd4j.createArrayFromShapeBuffer(Nd4j.getDataBufferFactory().createInt(mn),
Nd4j.getShapeInfoProvider().createShapeInformation(new int[]{1, mn}));
if(A.data().dataType() == DataBuffer.Type.DOUBLE)
dgetrf(m,n,A,IPIV,INFO) ;
else if (A.data().dataType() == DataBuffer.Type.FLOAT)
sgetrf(m,n,A,IPIV,INFO);
else
throw new UnsupportedOperationException() ;
if( INFO.getInt(0) < 0 ) {
throw new Error( "Parameter #" + INFO.getInt(0) + " to getrf() was not valid" ) ;
} else if ( INFO.getInt(0) > 0 ) {
logger.warn( "The matrix is singular - cannot be used for inverse op. Check L matrix at row " + INFO.getInt(0) ) ;
}
return IPIV ;
}
/**
* Float version of LU decomp.
* This is the official LAPACK interface (in case you want to call this directly)
* See getrf for full details on LU Decomp
*
* @param M the number of rows in the matrix A
* @param N the number of cols in the matrix A
* @param A the matrix to factorize - data must be in column order ( create with 'f' ordering )
* @param IPIV an output array for the permutations ( must be int based storage )
* @param INFO error details 1 int array, a positive number (i) implies row i cannot be factored, a negative value implies paramtere i is invalid
*/
public abstract void sgetrf(int M, int N, INDArray A, INDArray IPIV, INDArray INFO) ;
public abstract void dgetrf(int M, int N, INDArray A, INDArray IPIV, INDArray INFO) ;
@Override
public void sgesvd( INDArray A, INDArray S, INDArray U, INDArray VT ) {
int m = A.rows() ;
int n = A.columns() ;
byte jobu = (byte)( U==null ? 'N' : 'A' ) ;
byte jobvt = (byte)( VT==null ? 'N' : 'A' ) ;
INDArray INFO = Nd4j.createArrayFromShapeBuffer(Nd4j.getDataBufferFactory().createInt(1),
Nd4j.getShapeInfoProvider().createShapeInformation(new int[]{1, 1}));
if(A.data().dataType() == DataBuffer.Type.DOUBLE)
dgesvd( jobu, jobvt, m, n, A, S, U, VT, INFO ) ;
else if (A.data().dataType() == DataBuffer.Type.FLOAT)
sgesvd( jobu, jobvt, m, n, A, S, U, VT, INFO ) ;
else
throw new UnsupportedOperationException() ;
if( INFO.getInt(0) < 0 ) {
throw new Error( "Parameter #" + INFO.getInt(0) + " to gesvd() was not valid" ) ;
} else if ( INFO.getInt(0) > 0 ) {
logger.warn( "The matrix contains singular elements. Check S matrix at row " + INFO.getInt(0) ) ;
}
}
public abstract void sgesvd( byte jobu, byte jobvt, int M, int N, INDArray A, INDArray S, INDArray U, INDArray VT, INDArray INFO ) ;
public abstract void dgesvd( byte jobu, byte jobvt, int M, int N, INDArray A, INDArray S, INDArray U, INDArray VT, INDArray INFO ) ;
@Override
public INDArray getPFactor( int M, INDArray ipiv ) {
// The simplest permutation is the identity matrix
INDArray P = Nd4j.eye( M ) ; // result is a square matrix with given size
for( int i=0 ; i i ) { // don't reswap when we get lower down in the vector
INDArray v1 = P.getColumn(i).dup() ; // because of row vs col major order we'll ...
INDArray v2 = P.getColumn( pivot ) ; // ... make a transposed matrix immediately
P.putColumn( i, v2 ) ;
P.putColumn( pivot, v1 ) ; // note dup() above is required - getColumn() is a 'view'
}
}
return P ; // the permutation matrix - contains a single 1 in any row and column
}
/* TODO: consider doing this in place to save memory. This implies U is taken out first
L is the same shape as the input matrix. Just the lower triangular with a diagonal of 1s
*/
@Override
public INDArray getLFactor( INDArray A ) {
int m = A.rows() ;
int n = A.columns() ;
INDArray L = Nd4j.create( m,n ) ;
for( int r=0 ; rc && r
