/* * 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. * * <p> * 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. * </p> * @param <T> the type of the field elements * @since 2.0 */ public class SparseFieldMatrix<T extends FieldElement<T>> extends AbstractFieldMatrix<T> { /** Storage for (sparse) matrix elements. */ private final OpenIntToFieldHashMap<T> 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<T> field) { super(field); rows = 0; columns= 0; entries = new OpenIntToFieldHashMap<T>(field); } /** * Create a new SparseFieldMatrix<T> 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<T> field, final int rowDimension, final int columnDimension) { super(field, rowDimension, columnDimension); this.rows = rowDimension; this.columns = columnDimension; entries = new OpenIntToFieldHashMap<T>(field); } /** * Copy constructor. * * @param other Instance to copy. */ public SparseFieldMatrix(SparseFieldMatrix<T> other) { super(other.getField(), other.getRowDimension(), other.getColumnDimension()); rows = other.getRowDimension(); columns = other.getColumnDimension(); entries = new OpenIntToFieldHashMap<T>(other.entries); } /** * Generic copy constructor. * * @param other Instance to copy. */ public SparseFieldMatrix(FieldMatrix<T> other){ super(other.getField(), other.getRowDimension(), other.getColumnDimension()); rows = other.getRowDimension(); columns = other.getColumnDimension(); entries = new OpenIntToFieldHashMap<T>(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<T> copy() { return new SparseFieldMatrix<T>(this); } /** {@inheritDoc} */ @Override public FieldMatrix<T> createMatrix(int rowDimension, int columnDimension) { return new SparseFieldMatrix<T>(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; } }