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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 | |
|---|---|
Omega(long seed,
int kp)
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| Method Summary | |
|---|---|
protected void |
accumDots(int aIndex,
double aElement,
double[] yRow)
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protected void |
accumDots(int aIndex,
double aElement,
Vector yRow)
|
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)
|
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)
|
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public Omega(long seed,
int kp)
| Method Detail |
|---|
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 valseed - the seed to use
public static long murmur64(byte[] val,
int offset,
int len,
long seed)
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