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java.lang.Objectorg.apache.mahout.math.hadoop.stochasticsvd.Omega
public class Omega
simplistic implementation for Omega matrix in Stochastic SVD method
Constructor Summary | |
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Omega(long seed,
int kp)
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Method Summary | |
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protected void |
accumDots(int aIndex,
double aElement,
double[] yRow)
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protected void |
accumDots(int aIndex,
double aElement,
Vector yRow)
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void |
computeYRow(Vector aRow,
double[] yRow)
Deprecated. |
void |
computeYRow(Vector aRow,
Vector yRowOut)
A version to compute yRow as a sparse vector in case of extremely sparse matrices |
double |
getQuick(int row,
int column)
Get omega element at (x,y) uniformly distributed within [-1...1) |
static long |
murmur64(byte[] val,
int offset,
int len,
long seed)
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static long |
murmur64(long val,
int len,
long seed)
Shortened version for data < 8 bytes packed into len lowest bytes
of val . |
Vector |
mutlithreadedTRightMultiply(Vector v)
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Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public Omega(long seed, int kp)
Method Detail |
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public double getQuick(int row, int column)
row
- omega rowcolumn
- omega column@Deprecated public void computeYRow(Vector aRow, double[] yRow)
aRow
- row of matrix A (size n)yRow
- row of matrix Y (result) must be pre-allocated to size of (k+p)public void computeYRow(Vector aRow, Vector yRowOut)
aRow
- yRowOut
- public Vector mutlithreadedTRightMultiply(Vector v)
protected void accumDots(int aIndex, double aElement, double[] yRow)
protected void accumDots(int aIndex, double aElement, Vector yRow)
public static long murmur64(long val, int len, long seed)
len
lowest bytes
of val
.
val
- the valuelen
- the length of data packed into this many low bytes of val
seed
- the seed to use
public static long murmur64(byte[] val, int offset, int len, long seed)
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