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The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math3.linear;
import org.apache.commons.math3.Field;
import org.apache.commons.math3.FieldElement;
import org.apache.commons.math3.util.OpenIntToFieldHashMap;
/**
* Sparse matrix implementation based on an open addressed map.
*
*
* Caveat: This implementation assumes that, for any {@code x},
* the equality {@code x * 0d == 0d} holds. But it is is not true for
* {@code NaN}. Moreover, zero entries will lose their sign.
* Some operations (that involve {@code NaN} and/or infinities) may
* thus give incorrect results.
*
* @param the type of the field elements
* @since 2.0
*/
public class SparseFieldMatrix> extends AbstractFieldMatrix {
/** Storage for (sparse) matrix elements. */
private final OpenIntToFieldHashMap entries;
/** Row dimension. */
private final int rows;
/** Column dimension. */
private final int columns;
/**
* Create a matrix with no data.
*
* @param field Field to which the elements belong.
*/
public SparseFieldMatrix(final Field field) {
super(field);
rows = 0;
columns= 0;
entries = new OpenIntToFieldHashMap(field);
}
/**
* Create a new SparseFieldMatrix with the supplied row and column
* dimensions.
*
* @param field Field to which the elements belong.
* @param rowDimension Number of rows in the new matrix.
* @param columnDimension Number of columns in the new matrix.
* @throws org.apache.commons.math3.exception.NotStrictlyPositiveException
* if row or column dimension is not positive.
*/
public SparseFieldMatrix(final Field field,
final int rowDimension, final int columnDimension) {
super(field, rowDimension, columnDimension);
this.rows = rowDimension;
this.columns = columnDimension;
entries = new OpenIntToFieldHashMap(field);
}
/**
* Copy constructor.
*
* @param other Instance to copy.
*/
public SparseFieldMatrix(SparseFieldMatrix other) {
super(other.getField(), other.getRowDimension(), other.getColumnDimension());
rows = other.getRowDimension();
columns = other.getColumnDimension();
entries = new OpenIntToFieldHashMap(other.entries);
}
/**
* Generic copy constructor.
*
* @param other Instance to copy.
*/
public SparseFieldMatrix(FieldMatrix other){
super(other.getField(), other.getRowDimension(), other.getColumnDimension());
rows = other.getRowDimension();
columns = other.getColumnDimension();
entries = new OpenIntToFieldHashMap(getField());
for (int i = 0; i < rows; i++) {
for (int j = 0; j < columns; j++) {
setEntry(i, j, other.getEntry(i, j));
}
}
}
/** {@inheritDoc} */
@Override
public void addToEntry(int row, int column, T increment) {
checkRowIndex(row);
checkColumnIndex(column);
final int key = computeKey(row, column);
final T value = entries.get(key).add(increment);
if (getField().getZero().equals(value)) {
entries.remove(key);
} else {
entries.put(key, value);
}
}
/** {@inheritDoc} */
@Override
public FieldMatrix copy() {
return new SparseFieldMatrix(this);
}
/** {@inheritDoc} */
@Override
public FieldMatrix createMatrix(int rowDimension, int columnDimension) {
return new SparseFieldMatrix(getField(), rowDimension, columnDimension);
}
/** {@inheritDoc} */
@Override
public int getColumnDimension() {
return columns;
}
/** {@inheritDoc} */
@Override
public T getEntry(int row, int column) {
checkRowIndex(row);
checkColumnIndex(column);
return entries.get(computeKey(row, column));
}
/** {@inheritDoc} */
@Override
public int getRowDimension() {
return rows;
}
/** {@inheritDoc} */
@Override
public void multiplyEntry(int row, int column, T factor) {
checkRowIndex(row);
checkColumnIndex(column);
final int key = computeKey(row, column);
final T value = entries.get(key).multiply(factor);
if (getField().getZero().equals(value)) {
entries.remove(key);
} else {
entries.put(key, value);
}
}
/** {@inheritDoc} */
@Override
public void setEntry(int row, int column, T value) {
checkRowIndex(row);
checkColumnIndex(column);
if (getField().getZero().equals(value)) {
entries.remove(computeKey(row, column));
} else {
entries.put(computeKey(row, column), value);
}
}
/**
* Compute the key to access a matrix element.
*
* @param row Row index of the matrix element.
* @param column Column index of the matrix element.
* @return the key within the map to access the matrix element.
*/
private int computeKey(int row, int column) {
return row * columns + column;
}
}