cern.colt.matrix.impl
Class SparseDoubleMatrix2D

java.lang.Object
  cern.colt.PersistentObject
      cern.colt.matrix.impl.AbstractMatrix
          cern.colt.matrix.impl.AbstractMatrix2D
              cern.colt.matrix.DoubleMatrix2D
                  cern.colt.matrix.impl.SparseDoubleMatrix2D

All Implemented Interfaces:

Cloneable, Serializable

public class SparseDoubleMatrix2D

extends DoubleMatrix2D

Sparse hashed 2-d matrix holding double 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 OpenIntDoubleHashMap, which is a compact and performant hashing technique.

Memory requirements:

Cells that

• are never set to non-zero values do not use any memory.
• switch from zero to non-zero state do use memory.
• switch back from non-zero to zero state also do use memory. However, their memory is automatically reclaimed from time to time. It can also manually be reclaimed by calling trimToSize().

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 DenseDoubleMatrix2D. 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);
                }
        }

        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

See Also:

cern.colt.map, OpenIntDoubleHashMap, Serialized Form

SparseDoubleMatrix2D

public SparseDoubleMatrix2D(double[][] 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.

SparseDoubleMatrix2D

public SparseDoubleMatrix2D(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 || (double)columns*rows > Integer.MAX_VALUE.

SparseDoubleMatrix2D

public SparseDoubleMatrix2D(int rows,
                            int columns,
                            int initialCapacity,
                            double minLoadFactor,
                            double 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 OpenIntDoubleHashMap.

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 || (double)columns*rows > Integer.MAX_VALUE.

assign

public DoubleMatrix2D assign(double value)

Sets all cells to the state specified by value.

Overrides:

assign in class DoubleMatrix2D

Parameters:

value - the value to be filled into the cells.

Returns:

this (for convenience only).

assign

public DoubleMatrix2D assign(DoubleFunction 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 DoubleMatrix2D

Parameters:

function - a function object taking as argument the current cell's value.

Returns:

this (for convenience only).

See Also:

Functions

assign

public DoubleMatrix2D assign(DoubleMatrix2D 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 DoubleMatrix2D

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 DoubleMatrix2D assign(DoubleMatrix2D y,
                             DoubleDoubleFunction function)

Description copied from class: DoubleMatrix2D

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]y[row,col]
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 DoubleMatrix2D

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:

Functions

cardinality

public int cardinality()

Returns the number of cells having non-zero values.

Overrides:

cardinality in class DoubleMatrix2D

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 (non-null) cells.

forEachNonZero

public DoubleMatrix2D forEachNonZero(IntIntDoubleFunction function)

Description copied from class: DoubleMatrix2D

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 DoubleMatrix2D

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 double 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 DoubleMatrix2D

Parameters:

row - the index of the row-coordinate.

column - the index of the column-coordinate.

Returns:

the value at the specified coordinate.

like

public DoubleMatrix2D 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 DenseDoubleMatrix2D the new matrix must also be of type DenseDoubleMatrix2D, if the receiver is an instance of type SparseDoubleMatrix2D the new matrix must also be of type SparseDoubleMatrix2D, etc. In general, the new matrix should have internal parametrization as similar as possible.

Specified by:

like in class DoubleMatrix2D

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 DoubleMatrix1D 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 DenseDoubleMatrix2D the new matrix must be of type DenseDoubleMatrix1D, if the receiver is an instance of type SparseDoubleMatrix2D the new matrix must be of type SparseDoubleMatrix1D, etc.

Specified by:

like1D in class DoubleMatrix2D

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,
                     double 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 DoubleMatrix2D

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

• are never set to non-zero values do not use any memory.
• switch from zero to non-zero state do use memory.
• switch back from non-zero to zero state also do use memory. However, their memory can be reclaimed by calling trimToSize().

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

zMult

public DoubleMatrix1D zMult(DoubleMatrix1D y,
                            DoubleMatrix1D z,
                            double alpha,
                            double beta,
                            boolean transposeA)

Description copied from class: DoubleMatrix2D

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 DoubleMatrix2D

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 DoubleMatrix2D zMult(DoubleMatrix2D B,
                            DoubleMatrix2D C,
                            double alpha,
                            double beta,
                            boolean transposeA,
                            boolean transposeB)

Description copied from class: DoubleMatrix2D

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 DoubleMatrix2D

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).