Package org.djunits.value.vfloat.matrix.data

Class FloatMatrixDataDense

java.lang.Object

org.djunits.value.storage.AbstractStorage<FloatMatrixData>

org.djunits.value.vfloat.matrix.data.FloatMatrixData

org.djunits.value.vfloat.matrix.data.FloatMatrixDataDense

All Implemented Interfaces:

Serializable, Cloneable

public class FloatMatrixDataDense
extends FloatMatrixData

Stores dense data for a FloatMatrix and carries out basic operations.

Copyright (c) 2013-2023 Delft University of Technology, PO Box 5, 2600 AA, Delft, the Netherlands. All rights reserved.
BSD-style license. See DJUNITS License.

Author:

Alexander Verbraeck, Peter Knoppers

See Also:

Serialized Form

Field Summary

Fields inherited from class org.djunits.value.vfloat.matrix.data.FloatMatrixData

cols, matrixSI, rows

Constructor Summary

Constructors

Constructor	Description
FloatMatrixDataDense(float[][] matrixSI)	Create a matrix with dense data.
FloatMatrixDataDense(float[] matrixSI, int rows, int cols)	Create a matrix with dense data.

Method Summary

Modifier and Type	Method	Description
FloatMatrixDataDense	assign(FloatFunction floatFunction)	Apply an operation to each cell.
FloatMatrixDataDense	assign(FloatFunction2 floatFunction, FloatMatrixData right)	Apply a binary operation on a cell by cell basis.
int	cardinality()	Compute and return the number of non-zero cells in this indexed value.
FloatMatrixDataDense	copy()	Create and return a deep copy of the data.
FloatMatrixData	divide(FloatMatrixData right)	Divide two matrices on a cell-by-cell basis.
float[][]	getDenseMatrixSI()	Create and return a deep copy of the data in dense format.
double[][]	getDoubleDenseMatrixSI()	Create and return a deep copy of the data in dense format.
float	getSI(int row, int col)	Retrieve one value from this data.
FloatMatrixDataDense	minus(FloatMatrixData right)	Subtract two matrices on a cell-by-cell basis.
FloatMatrixData	plus(FloatMatrixData right)	Add two matrices on a cell-by-cell basis.
void	setSI(int row, int col, float valueSI)	Sets a value at the [row, col] point in the matrix.
FloatMatrixData	times(FloatMatrixData right)	Multiply two matrices on a cell-by-cell basis.
FloatMatrixDataDense	toDense()	Return the data of this matrix in dense storage format.
FloatMatrixDataSparse	toSparse()	Return the data of this matrix in sparse storage format.

Methods inherited from class org.djunits.value.vfloat.matrix.data.FloatMatrixData

checkRectangularAndNonNull, checkRectangularAndNonNull, checkSizes, cols, compareDenseMatrixWithSparseMatrix, decrementBy, divideBy, equals, hashCode, incrementBy, instantiate, instantiate, instantiate, multiplyBy, rows, toString, zSum

Methods inherited from class org.djunits.value.storage.AbstractStorage

getStorageType, isDense, isSparse

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

FloatMatrixDataDense

public FloatMatrixDataDense(float[] matrixSI,
                            int rows,
                            int cols)
                     throws ValueRuntimeException

Create a matrix with dense data.

Parameters:

matrixSI - float[]; the data to store

rows - int; the number of rows

cols - int; the number of columns

Throws:

ValueRuntimeException - in case rows * cols != matrixSI.length

FloatMatrixDataDense

public FloatMatrixDataDense(float[][] matrixSI)
                     throws ValueRuntimeException

Create a matrix with dense data. The float array is of the form d[rows][columns] so each value can be found with f[row][column].

Parameters:

matrixSI - float[][]; the data to store

Throws:

NullPointerException - when matrixSI is null

ValueRuntimeException - in case matrix is ragged

Method Detail

cardinality

public final int cardinality()

Compute and return the number of non-zero cells in this indexed value.

Specified by:

cardinality in class AbstractStorage<FloatMatrixData>

Returns:

int; the number of non-zero cells

assign

public final FloatMatrixDataDense assign(FloatFunction floatFunction)

Apply an operation to each cell.

Specified by:

assign in class FloatMatrixData

Parameters:

floatFunction - FloatFunction; the operation to apply

Returns:

FloatMatrixData; this (modified) double vector data object

assign

public final FloatMatrixDataDense assign(FloatFunction2 floatFunction,
                                         FloatMatrixData right)

Apply a binary operation on a cell by cell basis.

Specified by:

assign in class FloatMatrixData

Parameters:

floatFunction - FloatFunction2; the binary operation to apply

right - FloatMatrixData; the right operand for the binary operation

Returns:

FloatMatrixData; this (modified) double matrix data object

toDense

public final FloatMatrixDataDense toDense()

Return the data of this matrix in dense storage format.

Specified by:

toDense in class FloatMatrixData

Returns:

FloatMatrixDataDense; the dense transformation of this data

toSparse

public final FloatMatrixDataSparse toSparse()

Return the data of this matrix in sparse storage format.

Specified by:

toSparse in class FloatMatrixData

Returns:

FloatMatrixDataSparse; the sparse transformation of this data

getSI

public final float getSI(int row,
                         int col)

Retrieve one value from this data.

Specified by:

getSI in class FloatMatrixData

Parameters:

row - int; the row number to get the value for

col - int; the column number to get the value for

Returns:

the value at the [row, col] point

setSI

public final void setSI(int row,
                        int col,
                        float valueSI)

Sets a value at the [row, col] point in the matrix.

Specified by:

setSI in class FloatMatrixData

Parameters:

row - int; the row number to set the value for

col - int; the column number to set the value for

valueSI - float; the value at the index

getDenseMatrixSI

public final float[][] getDenseMatrixSI()

Create and return a deep copy of the data in dense format. The float array is of the form f[rows][columns] so each value can be found with f[row][column].

Specified by:

getDenseMatrixSI in class FloatMatrixData

Returns:

float[][]; a safe, dense copy of matrixSI as a matrix

getDoubleDenseMatrixSI

public final double[][] getDoubleDenseMatrixSI()

Create and return a deep copy of the data in dense format. The double array is of the form d[rows][columns] so each value can be found with d[row][column].

Specified by:

getDoubleDenseMatrixSI in class FloatMatrixData

Returns:

double[][]; a safe, dense copy of matrixSI as a matrix

copy

public final FloatMatrixDataDense copy()

Create and return a deep copy of the data.

Specified by:

copy in class AbstractStorage<FloatMatrixData>

Returns:

T; a deep copy of the data

plus

public FloatMatrixData plus(FloatMatrixData right)
                     throws ValueRuntimeException

Add two matrices on a cell-by-cell basis. If both matrices are sparse, a sparse matrix is returned, otherwise a dense matrix is returned.

Specified by:

plus in class FloatMatrixData

Parameters:

right - FloatMatrixData; the other data object to add

Returns:

the sum of this data object and the other data object

Throws:

ValueRuntimeException - if matrices have different lengths

minus

public final FloatMatrixDataDense minus(FloatMatrixData right)

Subtract two matrices on a cell-by-cell basis. If both matrices are sparse, a sparse matrix is returned, otherwise a dense matrix is returned.

Specified by:

minus in class FloatMatrixData

Parameters:

right - FloatMatrixData; the other data object to subtract

Returns:

the sum of this data object and the other data object

times

public FloatMatrixData times(FloatMatrixData right)
                      throws ValueRuntimeException

Multiply two matrices on a cell-by-cell basis. If both matrices are dense, a dense matrix is returned, otherwise a sparse matrix is returned.

Specified by:

times in class FloatMatrixData

Parameters:

right - FloatMatrixData; the other data object to multiply with

Returns:

FloatMatrixData; a new double matrix data store holding the result of the multiplications

Throws:

ValueRuntimeException - if matrices have different sizes

divide

public FloatMatrixData divide(FloatMatrixData right)
                       throws ValueRuntimeException

Divide two matrices on a cell-by-cell basis. If both matrices are dense, a dense matrix is returned, otherwise a sparse matrix is returned.

Specified by:

divide in class FloatMatrixData

Parameters:

right - FloatMatrixData; the other data object to divide by

Returns:

the sum of this data object and the other data object

Throws:

ValueRuntimeException - if matrices have different sizes