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A fast and easy to use dense and sparse matrix linear algebra library written in Java.
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/*
* Copyright (c) 2023, 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.ops;
import javax.annotation.Generated;
import org.ejml.UtilEjml;
import org.ejml.data.FMatrix4;
import org.ejml.data.FMatrixRMaj;
import org.jetbrains.annotations.Nullable;
/**
* Converts 1D and 2D arrays to and from EJML data types
*
* @author Peter Abeles
*/
@Generated("org.ejml.ops.DConvertArrays")
public class FConvertArrays {
public static FMatrixRMaj convert( float[][] src, @Nullable FMatrixRMaj dst ) {
int rows = src.length;
if (rows == 0)
throw new IllegalArgumentException("Rows of src can't be zero");
int cols = src[0].length;
UtilEjml.checkTooLarge(rows, cols);
if (dst == null) {
dst = new FMatrixRMaj(rows, cols);
} else {
dst.reshape(rows, cols);
}
int pos = 0;
for (int i = 0; i < rows; i++) {
float[] row = src[i];
if (row.length != cols) {
throw new IllegalArgumentException("All rows must have the same length");
}
System.arraycopy(row, 0, dst.data, pos, cols);
pos += cols;
}
return dst;
}
/**
* Convert a {@link FMatrixRMaj} to a two-dimensional array,
* given FMatrixRMaj can take a float[][] as input to constructor
*
* @param src is an input FMatrixRMaj
* @return a 2D array contains the same elements as the input matrix
*/
public static float[][] convert( FMatrixRMaj src ) {
float[][] array = new float[src.numRows][src.numCols];
for (int row = 0; row < src.numRows; row++) {
for (int column = 0; column < src.numCols; column++) {
array[row][column] = src.unsafe_get(row, column);
}
}
return array;
}
// public static FMatrixSparseCSC convert(float[][]src , @Nullable FMatrixSparseCSC dst ) {
// int rows = src.length;
// if( rows == 0 )
// throw new IllegalArgumentException("Rows of src can't be zero");
// int cols = src[0].length;
//
// if( dst == null ) {
// dst = new FMatrixSparseCSC(rows,cols);
// } else {
// dst.reshape(rows,cols);
// }
//
// for (int col = 0; col < cols; col++) {
// for (int row = 0; row < rows; row++) {
// float v = src[row][col];
// if( v == 0 )
// continue;
// // make sure there's enoguh data to store the new element and a bit extra
// if( dst.nz_values.length <= dst.nz_length ) {
// dst.growMaxLength(dst.nz_values.length*2+2,true);
// }
// dst.nz_values[dst.nz_length] = v;
// dst.nz_rows[dst.nz_length++] = row;
// }
// dst.col_idx[col+1] = dst.nz_length;
// }
// dst.indicesSorted = true;
//
//
// return dst;
// }
public static FMatrix4 convert( float[][] src, @Nullable FMatrix4 dst ) {
if (dst == null)
dst = new FMatrix4();
if (src.length == 4) {
if (src[0].length == 1)
throw new IllegalArgumentException("Expected a vector");
dst.a1 = src[0][0];
dst.a2 = src[1][0];
dst.a3 = src[2][0];
dst.a4 = src[3][0];
} else if (src.length == 1 && src[0].length == 4) {
dst.a1 = src[0][0];
dst.a2 = src[0][1];
dst.a3 = src[0][2];
dst.a4 = src[0][3];
} else {
throw new IllegalArgumentException("Expected a 4x1 or 1x4 vector");
}
return dst;
}
}