FloatMatrixDataDense.java
package org.djunits.value.vfloat.matrix.data;
import java.util.stream.IntStream;
import org.djunits.value.ValueRuntimeException;
import org.djunits.value.storage.StorageType;
import org.djunits.value.vfloat.function.FloatFunction;
import org.djunits.value.vfloat.function.FloatFunction2;
import org.djutils.exceptions.Throw;
/**
* Stores dense data for a FloatMatrix and carries out basic operations.
* <p>
* Copyright (c) 2013-2024 Delft University of Technology, PO Box 5, 2600 AA, Delft, the Netherlands. All rights reserved. <br>
* BSD-style license. See <a href="https://djunits.org/docs/license.html">DJUNITS License</a>.
* </p>
* @author <a href="https://www.tudelft.nl/averbraeck">Alexander Verbraeck</a>
* @author <a href="https://www.tudelft.nl/staff/p.knoppers/">Peter Knoppers</a>
*/
public class FloatMatrixDataDense extends FloatMatrixData
{
/** */
private static final long serialVersionUID = 1L;
/**
* Create a matrix with dense data.
* @param matrixSI float[]; the data to store
* @param rows int; the number of rows
* @param cols int; the number of columns
* @throws ValueRuntimeException in case <code>rows * cols != matrixSI.length</code>
*/
public FloatMatrixDataDense(final float[] matrixSI, final int rows, final int cols) throws ValueRuntimeException
{
super(StorageType.DENSE);
if (rows * cols != matrixSI.length)
{
throw new ValueRuntimeException("FloatMatrixDataDense constructor, rows * cols != matrixSI.length");
}
this.matrixSI = new float[matrixSI.length];
System.arraycopy(matrixSI, 0, this.matrixSI, 0, matrixSI.length);
this.rows = rows;
this.cols = cols;
}
/**
* 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].
* @param matrixSI float[][]; the data to store
* @throws NullPointerException when matrixSI is null
* @throws ValueRuntimeException in case matrix is ragged
*/
public FloatMatrixDataDense(final float[][] matrixSI) throws ValueRuntimeException
{
super(StorageType.DENSE);
Throw.whenNull(matrixSI, "DoubleMatrixDataDense constructor, matrixSI == null");
this.rows = matrixSI.length;
this.cols = this.rows == 0 ? 0 : matrixSI[0].length;
this.matrixSI = new float[this.rows * this.cols];
for (int r = 0; r < this.rows; r++)
{
float[] row = matrixSI[r];
if (row.length != this.cols)
{
throw new ValueRuntimeException("FloatMatrixDataDense constructor, ragged matrix");
}
System.arraycopy(row, 0, this.matrixSI, r * this.cols, row.length);
}
}
/** {@inheritDoc} */
@Override
public final int cardinality()
{
// this does not copy the data. See http://stackoverflow.com/questions/23106093/how-to-get-a-stream-from-a-float
return (int) IntStream.range(0, this.matrixSI.length).parallel().mapToDouble(i -> this.matrixSI[i])
.filter(d -> d != 0.0).count();
}
/** {@inheritDoc} */
@Override
public final FloatMatrixDataDense assign(final FloatFunction floatFunction)
{
IntStream.range(0, this.rows() * this.cols()).parallel()
.forEach(i -> this.matrixSI[i] = floatFunction.apply(this.matrixSI[i]));
return this;
}
/** {@inheritDoc} */
@Override
public final FloatMatrixDataDense assign(final FloatFunction2 floatFunction, final FloatMatrixData right)
{
if (right.isDense())
{
FloatMatrixDataDense rightDense = (FloatMatrixDataDense) right;
IntStream.range(0, this.rows() * this.cols()).parallel()
.forEach(i -> this.matrixSI[i] = floatFunction.apply(this.matrixSI[i], rightDense.matrixSI[i]));
}
else
{
IntStream.range(0, this.rows() * this.cols()).parallel().forEach(
i -> this.matrixSI[i] = floatFunction.apply(this.matrixSI[i], right.getSI(i / this.cols, i % this.cols)));
}
return this;
}
/** {@inheritDoc} */
@Override
public final FloatMatrixDataDense toDense()
{
return this;
}
/** {@inheritDoc} */
@Override
public final FloatMatrixDataSparse toSparse()
{
int length = cardinality();
float[] sparseSI = new float[length];
long[] indices = new long[length];
int count = 0;
for (int r = 0; r < this.rows; r++)
{
for (int c = 0; c < this.cols; c++)
{
int index = r * this.cols + c;
if (this.matrixSI[index] != 0.0)
{
sparseSI[count] = this.matrixSI[index];
indices[count] = index;
count++;
}
}
}
return new FloatMatrixDataSparse(sparseSI, indices, this.rows, this.cols);
}
/** {@inheritDoc} */
@Override
public final float getSI(final int row, final int col)
{
return this.matrixSI[row * this.cols + col];
}
/** {@inheritDoc} */
@Override
public final void setSI(final int row, final int col, final float valueSI)
{
this.matrixSI[row * this.cols + col] = valueSI;
}
/** {@inheritDoc} */
@Override
public final float[][] getDenseMatrixSI()
{
float[][] matrix = new float[this.rows][];
for (int r = 0; r < this.rows; r++)
{
float[] row = new float[this.cols];
System.arraycopy(this.matrixSI, r * this.cols, row, 0, row.length);
matrix[r] = row;
}
return matrix;
}
/** {@inheritDoc} */
@Override
public final double[][] getDoubleDenseMatrixSI()
{
double[][] matrix = new double[this.rows][];
for (int r = 0; r < this.rows; r++)
{
double[] row = new double[this.cols];
int offset = r * this.cols;
for (int c = 0; c < this.cols; c++)
{
row[c] = this.matrixSI[offset++];
}
matrix[r] = row;
}
return matrix;
}
/** {@inheritDoc} */
@Override
public final FloatMatrixDataDense copy()
{
try
{
return new FloatMatrixDataDense(getDenseMatrixSI());
}
catch (ValueRuntimeException exception)
{
throw new RuntimeException(exception); // should not happen -- original is not ragged...
}
}
/** {@inheritDoc} */
@Override
public FloatMatrixData plus(final FloatMatrixData right) throws ValueRuntimeException
{
checkSizes(right);
float[] fm = new float[this.rows * this.cols];
if (right.isDense())
{
IntStream.range(0, this.rows).parallel().forEach(r -> IntStream.range(0, this.cols).forEach(
c -> fm[r * this.cols + c] = this.matrixSI[r * this.cols + c] + right.matrixSI[r * this.cols + c]));
}
else
{ // right is sparse
IntStream.range(0, this.rows).parallel().forEach(r -> IntStream.range(0, this.cols)
.forEach(c -> fm[r * this.cols + c] = this.matrixSI[r * this.cols + c] + right.getSI(r, c)));
}
return new FloatMatrixDataDense(fm, this.rows, this.cols);
}
/** {@inheritDoc} */
@Override
public final FloatMatrixDataDense minus(final FloatMatrixData right)
{
checkSizes(right);
float[] fm = new float[this.rows * this.cols];
if (right.isDense())
{
IntStream.range(0, this.rows).parallel().forEach(r -> IntStream.range(0, this.cols).forEach(
c -> fm[r * this.cols + c] = this.matrixSI[r * this.cols + c] - right.matrixSI[r * this.cols + c]));
}
else
{ // right is sparse
IntStream.range(0, this.rows).parallel().forEach(r -> IntStream.range(0, this.cols)
.forEach(c -> fm[r * this.cols + c] = this.matrixSI[r * this.cols + c] - right.getSI(r, c)));
}
return new FloatMatrixDataDense(fm, this.rows, this.cols);
}
/** {@inheritDoc} */
@Override
public FloatMatrixData times(final FloatMatrixData right) throws ValueRuntimeException
{
if (right.isSparse())
{
// result shall be sparse
return right.times(this);
}
// Both are dense
checkSizes(right);
return this.copy().multiplyBy(right);
}
/** {@inheritDoc} */
@Override
public FloatMatrixData divide(final FloatMatrixData right) throws ValueRuntimeException
{
checkSizes(right);
return this.copy().divideBy(right);
}
}