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A fast and easy to use dense and sparse matrix linear algebra library written in Java.
The newest version!
/*
* Copyright (c) 2022, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* Licensed 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.ejml.masks;
import javax.annotation.Generated;
import org.ejml.data.FMatrixSparseCSC;
import org.ejml.data.IGrowArray;
import org.jetbrains.annotations.Nullable;
import static org.ejml.UtilEjml.adjust;
/**
* Mask implementation which checks if the entry is assigned in the sparse matrix.
* The actual stored values are disregarded.
*/
@Generated("org.ejml.masks.DMaskSparseStructural")
public class FMaskSparseStructural extends Mask {
// TODO use a data-type-independent MatrixSparseCSC class
private final FMatrixSparseCSC matrix;
// Corresponding column to rowIndicesInIndexedColumn
private int indexedColumn = -1;
// int[] instead of boolean[] to avoid clearing on multiple setActiveColumns()
// If the row entry is non-zero in indexed column -> rowIndicesInIndexedColumn[row] == col
private int[] rowIndicesInIndexedColumn;
public FMaskSparseStructural( FMatrixSparseCSC matrix, boolean negated, @Nullable IGrowArray gw, boolean indexFirstColumn ) {
super(negated);
this.matrix = matrix;
this.rowIndicesInIndexedColumn = adjust(gw, matrix.numRows);
if (indexFirstColumn) {
setIndexColumn(0);
}
}
@Override
public boolean isSet( int row, int col ) {
if (col != indexedColumn) {
return negated ^ matrix.isAssigned(row, col);
} else {
return negated ^ (rowIndicesInIndexedColumn[row] - 1 == col);
}
}
@Override
public boolean isSet( int idx ) {
// assuming a column vector
return isSet(idx, 0);
}
@Override
public int getNumCols() {
return matrix.getNumCols();
}
@Override
public int getNumRows() {
return matrix.getNumRows();
}
@Override
public void setIndexColumn( int col ) {
if (indexedColumn != col) {
this.indexedColumn = col;
for (int i = matrix.col_idx[col]; i < matrix.col_idx[col + 1]; i++) {
rowIndicesInIndexedColumn[matrix.nz_rows[i]] = col + 1;
}
}
}
@Override
public int maxMaskedEntries() {
if (negated) {
return matrix.getNumCols()*matrix.getNumRows() - matrix.nz_length;
} else {
return matrix.nz_length;
}
}
/**
* Utility class to build {@link FMaskSparseStructural}
*/
public static class Builder extends MaskBuilder {
private FMatrixSparseCSC matrix;
private boolean indexFirstColumn;
private @Nullable IGrowArray gw;
public Builder( FMatrixSparseCSC matrix ) {
this.matrix = matrix;
}
/**
* @param indexFirstColumn Whether the first column should be indexed on mask construction
*/
public Builder withIndexFirstColumn( boolean indexFirstColumn ) {
this.indexFirstColumn = indexFirstColumn;
return this;
}
/**
* @param gw (Optional) Storage for internal workspace. Can be null.
*/
public Builder withWorkArray( IGrowArray gw ) {
this.gw = gw;
return this;
}
@Override
public FMaskSparseStructural build() {
return new FMaskSparseStructural(matrix, negated, gw, indexFirstColumn);
}
}
}