Parallel Colt 0.7.2

cern.colt.matrix.tfloat.impl
Class SparseFloatMatrix2D

java.lang.Object
  extended by cern.colt.PersistentObject
      extended by cern.colt.matrix.AbstractMatrix
          extended by cern.colt.matrix.AbstractMatrix2D
              extended by cern.colt.matrix.tfloat.FloatMatrix2D
                  extended by cern.colt.matrix.tfloat.impl.SparseFloatMatrix2D
All Implemented Interfaces:
Serializable, Cloneable

public class SparseFloatMatrix2D
extends FloatMatrix2D

Sparse hashed 2-d matrix holding float elements. First see the package summary and javadoc tree view to get the broad picture.

Implementation:

Note that this implementation is not synchronized. Uses a OpenIntFloatHashMap, which is a compact and performant hashing technique.

Memory requirements:

Cells that

worst case: memory [bytes] = (1/minLoadFactor) * nonZeros * 13.
best case: memory [bytes] = (1/maxLoadFactor) * nonZeros * 13.
Where nonZeros = cardinality() is the number of non-zero cells. Thus, a 1000 x 1000 matrix with minLoadFactor=0.25 and maxLoadFactor=0.5 and 1000000 non-zero cells consumes between 25 MB and 50 MB. The same 1000 x 1000 matrix with 1000 non-zero cells consumes between 25 and 50 KB.

Time complexity:

This class offers expected time complexity O(1) (i.e. constant time) for the basic operations get, getQuick, set, setQuick and size assuming the hash function disperses the elements properly among the buckets. Otherwise, pathological cases, although highly improbable, can occur, degrading performance to O(N) in the worst case. As such this sparse class is expected to have no worse time complexity than its dense counterpart DenseFloatMatrix2D. However, constant factors are considerably larger.

Cells are internally addressed in row-major. Performance sensitive applications can exploit this fact. Setting values in a loop row-by-row is quicker than column-by-column, because fewer hash collisions occur. Thus

 for (int row = 0; row < rows; row++) {
     for (int column = 0; column < columns; column++) {
         matrix.setQuick(row, column, someValue);
     }
 }
 
is quicker than
 for (int column = 0; column < columns; column++) {
     for (int row = 0; row < rows; row++) {
         matrix.setQuick(row, column, someValue);
     }
 }
 

Version:
1.0, 09/24/99, 1.1, 08/22/2007
Author:
wolfgang.hoschek@cern.ch, Piotr Wendykier (piotr.wendykier@gmail.com)
See Also:
cern.colt.map, OpenIntFloatHashMap, Serialized Form

Field Summary
 
Fields inherited from class cern.colt.PersistentObject
serialVersionUID
 
Constructor Summary
SparseFloatMatrix2D(float[][] values)
          Constructs a matrix with a copy of the given values.
SparseFloatMatrix2D(int rows, int columns)
          Constructs a matrix with a given number of rows and columns and default memory usage.
SparseFloatMatrix2D(int rows, int columns, int[] rowIndexes, int[] columnIndexes, float value)
          Constructs a matrix with a copy of the given indexes and value.
SparseFloatMatrix2D(int rows, int columns, int[] rowIndexes, int[] columnIndexes, float[] values)
          Constructs a matrix with a copy of the given indexes and values.
SparseFloatMatrix2D(int rows, int columns, int initialCapacity, float minLoadFactor, float maxLoadFactor)
          Constructs a matrix with a given number of rows and columns using memory as specified.
SparseFloatMatrix2D(MatrixVectorReader r)
          Constructs a matrix from MatrixVectorReader.
 
Method Summary
 FloatMatrix2D assign(float value)
          Sets all cells to the state specified by value.
 FloatMatrix2D assign(FloatFunction function)
          Assigns the result of a function to each cell; x[row,col] = function(x[row,col]).
 FloatMatrix2D assign(FloatMatrix2D source)
          Replaces all cell values of the receiver with the values of another matrix.
 FloatMatrix2D assign(FloatMatrix2D y, FloatFloatFunction function)
          Assigns the result of a function to each cell; x[row,col] = function(x[row,col],y[row,col]).
 SparseFloatMatrix2D assign(int[] rowIndexes, int[] columnIndexes, float[] values, FloatFloatFunction function)
           
 SparseFloatMatrix2D assign(int[] rowIndexes, int[] columnIndexes, float value, FloatFloatFunction function)
           
 int cardinality()
          Returns the number of cells having non-zero values.
 CCFloatMatrix2D convertToCCFloatMatrix2D()
           
 CCMFloatMatrix2D convertToCCMFloatMatrix2D()
           
 RCFloatMatrix2D convertToRCFloatMatrix2D()
           
 RCMFloatMatrix2D convertToRCMFloatMatrix2D()
           
 AbstractLongFloatMap elements()
          Returns the elements of this matrix.
 void ensureCapacity(int minCapacity)
          Ensures that the receiver can hold at least the specified number of non-zero cells without needing to allocate new internal memory.
 FloatMatrix2D forEachNonZero(IntIntFloatFunction function)
          Assigns the result of a function to each non-zero cell; x[row,col] = function(x[row,col]).
 float getQuick(int row, int column)
          Returns the matrix cell value at coordinate [row,column].
 long index(int row, int column)
          Returns the position of the given coordinate within the (virtual or non-virtual) internal 1-dimensional array.
 FloatMatrix2D like(int rows, int columns)
          Construct and returns a new empty matrix of the same dynamic type as the receiver, having the specified number of rows and columns.
 FloatMatrix1D like1D(int size)
          Construct and returns a new 1-d matrix of the corresponding dynamic type, entirelly independent of the receiver.
 void setQuick(int row, int column, float value)
          Sets the matrix cell at coordinate [row,column] to the specified value.
 void trimToSize()
          Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
 FloatMatrix1D vectorize()
          Returns a vector obtained by stacking the columns of the matrix on top of one another.
 FloatMatrix1D zMult(FloatMatrix1D y, FloatMatrix1D z, float alpha, float beta, boolean transposeA)
          Linear algebraic matrix-vector multiplication; z = alpha * A * y + beta*z.
 FloatMatrix2D zMult(FloatMatrix2D B, FloatMatrix2D C, float alpha, float beta, boolean transposeA, boolean transposeB)
          Linear algebraic matrix-matrix multiplication; C = alpha * A x B + beta*C.
 
Methods inherited from class cern.colt.matrix.tfloat.FloatMatrix2D
aggregate, aggregate, aggregate, aggregate, assign, assign, assign, assign, assign, copy, equals, equals, get, getMaxLocation, getMinLocation, getNegativeValues, getNonZeros, getPositiveValues, like, normalize, set, toArray, toString, viewColumn, viewColumnFlip, viewDice, viewPart, viewRow, viewRowFlip, viewSelection, viewSelection, viewSelection, viewSorted, viewStrides, zAssign8Neighbors, zMult, zMult, zSum
 
Methods inherited from class cern.colt.matrix.AbstractMatrix2D
checkShape, checkShape, columns, columnStride, rows, rowStride, size, toStringShort
 
Methods inherited from class cern.colt.matrix.AbstractMatrix
isView
 
Methods inherited from class cern.colt.PersistentObject
clone
 
Methods inherited from class java.lang.Object
getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Constructor Detail

SparseFloatMatrix2D

public SparseFloatMatrix2D(float[][] values)
Constructs a matrix with a copy of the given values. values is required to have the form values[row][column] and have exactly the same number of columns in every row.

The values are copied. So subsequent changes in values are not reflected in the matrix, and vice-versa.

Parameters:
values - The values to be filled into the new matrix.
Throws:
IllegalArgumentException - if for any 1 <= row < values.length: values[row].length != values[row-1].length .

SparseFloatMatrix2D

public SparseFloatMatrix2D(int rows,
                           int columns)
Constructs a matrix with a given number of rows and columns and default memory usage. All entries are initially 0.

Parameters:
rows - the number of rows the matrix shall have.
columns - the number of columns the matrix shall have.
Throws:
IllegalArgumentException - if rows<0 || columns<0 || (float)columns*rows > Integer.MAX_VALUE .

SparseFloatMatrix2D

public SparseFloatMatrix2D(int rows,
                           int columns,
                           int initialCapacity,
                           float minLoadFactor,
                           float maxLoadFactor)
Constructs a matrix with a given number of rows and columns using memory as specified. All entries are initially 0. For details related to memory usage see OpenIntFloatHashMap.

Parameters:
rows - the number of rows the matrix shall have.
columns - the number of columns the matrix shall have.
initialCapacity - the initial capacity of the hash map. If not known, set initialCapacity=0 or small.
minLoadFactor - the minimum load factor of the hash map.
maxLoadFactor - the maximum load factor of the hash map.
Throws:
IllegalArgumentException - if initialCapacity < 0 || (minLoadFactor < 0.0 || minLoadFactor >= 1.0) || (maxLoadFactor <= 0.0 || maxLoadFactor >= 1.0) || (minLoadFactor >= maxLoadFactor) .
IllegalArgumentException - if rows<0 || columns<0 || (float)columns*rows > Integer.MAX_VALUE .

SparseFloatMatrix2D

public SparseFloatMatrix2D(int rows,
                           int columns,
                           int[] rowIndexes,
                           int[] columnIndexes,
                           float[] values)
Constructs a matrix with a copy of the given indexes and values.

Parameters:
rows -
columns -
rowIndexes -
columnIndexes -
values -

SparseFloatMatrix2D

public SparseFloatMatrix2D(int rows,
                           int columns,
                           int[] rowIndexes,
                           int[] columnIndexes,
                           float value)
Constructs a matrix with a copy of the given indexes and value.

Parameters:
rows -
columns -
rowIndexes -
columnIndexes -
value -

SparseFloatMatrix2D

public SparseFloatMatrix2D(MatrixVectorReader r)
                    throws IOException
Constructs a matrix from MatrixVectorReader.

Parameters:
r - matrix reader
Throws:
IOException
Method Detail

assign

public FloatMatrix2D assign(FloatFunction function)
Assigns the result of a function to each cell; x[row,col] = function(x[row,col]).

Example:

   matrix = 2 x 2 matrix
   0.5 1.5      
   2.5 3.5
 
   // change each cell to its sine
   matrix.assign(cern.jet.math.Functions.sin);
   -->
   2 x 2 matrix
   0.479426  0.997495 
   0.598472 -0.350783
 
 
For further examples, see the package doc.

Overrides:
assign in class FloatMatrix2D
Parameters:
function - a function object taking as argument the current cell's value.
Returns:
this (for convenience only).
See Also:
FloatFunctions

assign

public FloatMatrix2D assign(float value)
Sets all cells to the state specified by value.

Overrides:
assign in class FloatMatrix2D
Parameters:
value - the value to be filled into the cells.
Returns:
this (for convenience only).

assign

public FloatMatrix2D assign(FloatMatrix2D source)
Replaces all cell values of the receiver with the values of another matrix. Both matrices must have the same number of rows and columns. If both matrices share the same cells (as is the case if they are views derived from the same matrix) and intersect in an ambiguous way, then replaces as if using an intermediate auxiliary deep copy of other.

Overrides:
assign in class FloatMatrix2D
Parameters:
source - the source matrix to copy from (may be identical to the receiver).
Returns:
this (for convenience only).
Throws:
IllegalArgumentException - if columns() != source.columns() || rows() != source.rows()

assign

public FloatMatrix2D assign(FloatMatrix2D y,
                            FloatFloatFunction function)
Description copied from class: FloatMatrix2D
Assigns the result of a function to each cell; x[row,col] = function(x[row,col],y[row,col]).

Example:

   // assign x[row,col] = x[row,col]<sup>y[row,col]</sup>
   m1 = 2 x 2 matrix 
   0 1 
   2 3
 
   m2 = 2 x 2 matrix 
   0 2 
   4 6
 
   m1.assign(m2, cern.jet.math.Functions.pow);
   -->
   m1 == 2 x 2 matrix
   1   1 
   16 729
 
 
For further examples, see the package doc.

Overrides:
assign in class FloatMatrix2D
Parameters:
y - the secondary matrix to operate on.
function - a function object taking as first argument the current cell's value of this, and as second argument the current cell's value of y,
Returns:
this (for convenience only).
See Also:
FloatFunctions

assign

public SparseFloatMatrix2D assign(int[] rowIndexes,
                                  int[] columnIndexes,
                                  float[] values,
                                  FloatFloatFunction function)

assign

public SparseFloatMatrix2D assign(int[] rowIndexes,
                                  int[] columnIndexes,
                                  float value,
                                  FloatFloatFunction function)

cardinality

public int cardinality()
Returns the number of cells having non-zero values.

Overrides:
cardinality in class FloatMatrix2D
Returns:
cardinality

convertToRCFloatMatrix2D

public RCFloatMatrix2D convertToRCFloatMatrix2D()

convertToCCFloatMatrix2D

public CCFloatMatrix2D convertToCCFloatMatrix2D()

convertToRCMFloatMatrix2D

public RCMFloatMatrix2D convertToRCMFloatMatrix2D()

convertToCCMFloatMatrix2D

public CCMFloatMatrix2D convertToCCMFloatMatrix2D()

elements

public AbstractLongFloatMap elements()
Returns the elements of this matrix.

Specified by:
elements in class FloatMatrix2D
Returns:
the elements

ensureCapacity

public void ensureCapacity(int minCapacity)
Ensures that the receiver can hold at least the specified number of non-zero cells without needing to allocate new internal memory. If necessary, allocates new internal memory and increases the capacity of the receiver.

This method never need be called; it is for performance tuning only. Calling this method before tt>set()ing a large number of non-zero values boosts performance, because the receiver will grow only once instead of potentially many times and hash collisions get less probable.

Overrides:
ensureCapacity in class AbstractMatrix
Parameters:
minCapacity - the desired minimum number of non-zero cells.

forEachNonZero

public FloatMatrix2D forEachNonZero(IntIntFloatFunction function)
Description copied from class: FloatMatrix2D
Assigns the result of a function to each non-zero cell; x[row,col] = function(x[row,col]). Use this method for fast special-purpose iteration. If you want to modify another matrix instead of this (i.e. work in read-only mode), simply return the input value unchanged. Parameters to function are as follows: first==row, second==column, third==nonZeroValue.

Overrides:
forEachNonZero in class FloatMatrix2D
Parameters:
function - a function object taking as argument the current non-zero cell's row, column and value.
Returns:
this (for convenience only).

getQuick

public float getQuick(int row,
                      int column)
Returns the matrix cell value at coordinate [row,column].

Provided with invalid parameters this method may return invalid objects without throwing any exception. You should only use this method when you are absolutely sure that the coordinate is within bounds. Precondition (unchecked): 0 <= column < columns() && 0 <= row < rows().

Specified by:
getQuick in class FloatMatrix2D
Parameters:
row - the index of the row-coordinate.
column - the index of the column-coordinate.
Returns:
the value at the specified coordinate.

index

public long index(int row,
                  int column)
Returns the position of the given coordinate within the (virtual or non-virtual) internal 1-dimensional array.

Overrides:
index in class AbstractMatrix2D
Parameters:
row - the index of the row-coordinate.
column - the index of the column-coordinate.

like

public FloatMatrix2D like(int rows,
                          int columns)
Construct and returns a new empty matrix of the same dynamic type as the receiver, having the specified number of rows and columns. For example, if the receiver is an instance of type DenseFloatMatrix2D the new matrix must also be of type DenseFloatMatrix2D, if the receiver is an instance of type SparseFloatMatrix2D the new matrix must also be of type SparseFloatMatrix2D, etc. In general, the new matrix should have internal parametrization as similar as possible.

Specified by:
like in class FloatMatrix2D
Parameters:
rows - the number of rows the matrix shall have.
columns - the number of columns the matrix shall have.
Returns:
a new empty matrix of the same dynamic type.

like1D

public FloatMatrix1D like1D(int size)
Construct and returns a new 1-d matrix of the corresponding dynamic type, entirelly independent of the receiver. For example, if the receiver is an instance of type DenseFloatMatrix2D the new matrix must be of type DenseFloatMatrix1D, if the receiver is an instance of type SparseFloatMatrix2D the new matrix must be of type SparseFloatMatrix1D, etc.

Specified by:
like1D in class FloatMatrix2D
Parameters:
size - the number of cells the matrix shall have.
Returns:
a new matrix of the corresponding dynamic type.

setQuick

public void setQuick(int row,
                     int column,
                     float value)
Sets the matrix cell at coordinate [row,column] to the specified value.

Provided with invalid parameters this method may access illegal indexes without throwing any exception. You should only use this method when you are absolutely sure that the coordinate is within bounds. Precondition (unchecked): 0 <= column < columns() && 0 <= row < rows().

Specified by:
setQuick in class FloatMatrix2D
Parameters:
row - the index of the row-coordinate.
column - the index of the column-coordinate.
value - the value to be filled into the specified cell.

trimToSize

public void trimToSize()
Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.

Background:

Cells that

A sequence like set(r,c,5); set(r,c,0); sets a cell to non-zero state and later back to zero state. Such as sequence generates obsolete memory that is automatically reclaimed from time to time or can manually be reclaimed by calling trimToSize(). Putting zeros into cells already containing zeros does not generate obsolete memory since no memory was allocated to them in the first place.

Overrides:
trimToSize in class AbstractMatrix

vectorize

public FloatMatrix1D vectorize()
Returns a vector obtained by stacking the columns of the matrix on top of one another.

Specified by:
vectorize in class FloatMatrix2D
Returns:
a vector obtained by stacking the columns of the matrix on top of one another

zMult

public FloatMatrix1D zMult(FloatMatrix1D y,
                           FloatMatrix1D z,
                           float alpha,
                           float beta,
                           boolean transposeA)
Description copied from class: FloatMatrix2D
Linear algebraic matrix-vector multiplication; z = alpha * A * y + beta*z. z[i] = alpha*Sum(A[i,j] * y[j]) + beta*z[i], i=0..A.rows()-1, j=0..y.size()-1 . Where A == this.
Note: Matrix shape conformance is checked after potential transpositions.

Overrides:
zMult in class FloatMatrix2D
Parameters:
y - the source vector.
z - the vector where results are to be stored. Set this parameter to null to indicate that a new result vector shall be constructed.
Returns:
z (for convenience only).

zMult

public FloatMatrix2D zMult(FloatMatrix2D B,
                           FloatMatrix2D C,
                           float alpha,
                           float beta,
                           boolean transposeA,
                           boolean transposeB)
Description copied from class: FloatMatrix2D
Linear algebraic matrix-matrix multiplication; C = alpha * A x B + beta*C. C[i,j] = alpha*Sum(A[i,k] * B[k,j]) + beta*C[i,j], k=0..n-1.
Matrix shapes: A(m x n), B(n x p), C(m x p).
Note: Matrix shape conformance is checked after potential transpositions.

Overrides:
zMult in class FloatMatrix2D
Parameters:
B - the second source matrix.
C - the matrix where results are to be stored. Set this parameter to null to indicate that a new result matrix shall be constructed.
Returns:
C (for convenience only).

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