Hi I have the Jama librarry, but this libraray work only with Double numbers..and its very slow. for Android app ..and finally i dont need so high precision of eig decomp..so is there some JAva libaray with float num.....similar in syntax with jama? becouse...I dont want to re-- write again my 440 rows code thanks. eig. Transpose, inverse and so basic Linear algebra operations..
or exist same java library eigenvalues. with threads?
I know of one library called la4j, you might be interested in looking into that. I should mention that, generally, I don't think Java is a good choice if you're planning on doing many matrix manipulations/calculations (I myself have tried and hit a dead-end), you might be better off looking into Python (NumPy) or C++ (Armadillo) for such projects.
Or are you looking for something like this?
import java.util.Arrays;
public class Matrix {
protected int rows;
protected int cols;
double[][] values;
public Matrix(int rows, int cols) {
this.rows = rows;
this.cols = cols;
values = new double[rows][cols];
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
values[i][j] = 0;
}
public Matrix(int[][] M) {
this.rows = M.length;
this.cols = M[0].length;
values = new double[rows][cols];
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
values[i][j] = M[i][j];
}
public Matrix(double[][] M) {
this.rows = M.length;
this.cols = M[0].length;
values = new double[rows][cols];
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
values[i][j] = M[i][j];
}
public void setToEye() {
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
values[i][j] = (i == j) ? 1 : 0;
}
public static int[] matrixSize(Matrix M) {
int[] size = new int[2];
size[0] = M.rows;
size[1] = M.cols;
return size;
}
public static double vectMul(double[] A, double[] B) {
double suma = 0;
for (int i = 0; i < A.length; i++)
suma += A[i] * B[i];
return suma;
}
public static Matrix matrixTranspose(Matrix M) {
int[] size = matrixSize(M);
double[][] Mt = new double[size[0]][size[1]];
for (int i = 0; i < size[0]; i++)
for (int j = 0; j < size[1]; j++)
Mt[i][j] = M.getValue(j, i);
return new Matrix(Mt);
}
public static Matrix matrixMul(Matrix A, Matrix B) {
int m1 = matrixSize(A)[0];
int n1 = matrixSize(A)[1];
int m2 = matrixSize(B)[0];
int n2 = matrixSize(B)[1];
double[][] rez;
if (n1 != m2) {
System.err.println("Inner matrix dimensions must agree!");
return null;
}
rez = new double[m1][n2];
for (int i = 0; i < m1; i++)
for (int j = 0; j < n2; j++)
rez[i][j] = vectMul(A.getRow(i), B.getColumn(j));
Matrix r = new Matrix(rez);
return r;
}
public static Matrix matrixMulWithMod(Matrix A, Matrix B, double mod) {
int m1 = matrixSize(A)[0];
int n1 = matrixSize(A)[1];
int m2 = matrixSize(B)[0];
int n2 = matrixSize(B)[1];
double[][] rez;
if (n1 != m2) {
System.err.println("Inner matrix dimensions must agree!");
return null;
}
rez = new double[m1][n2];
for (int i = 0; i < m1; i++)
for (int j = 0; j < n2; j++)
rez[i][j] = vectMul(A.getRow(i), B.getColumn(j)) % mod;
Matrix r = new Matrix(rez);
return r;
}
public String toString() {
StringBuilder sb = new StringBuilder();
for (int i = 0; i < this.rows; i++) {
sb.append(Arrays.toString(values[i]));
sb.append('\n');
}
String str = sb.toString();
return str;
}
public double[][] getValues() {
return values;
}
public void setValues(double[][] values) {
this.values = values;
}
public void setValues(int[][] values) {
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
this.values[i][j] = (double) values[i][j];
}
public double getValue(int row, int col) {
return values[row][col];
}
public void setValue(int row, int col, double value) {
values[row][col] = value;
}
public double[] getRow(int row) {
double[] temp = new double[cols];
for (int i = 0; i < temp.length; i++)
temp[i] = values[row][i];
return temp;
}
public double[] getColumn(int col) {
double[] temp = new double[rows];
for (int i = 0; i < temp.length; i++)
temp[i] = values[i][col];
return temp;
}
public double[] toDoubleArray() {
double[] temp = new double[rows * cols];
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
temp[i * (rows + 1) + j] = values[i][j];
return temp;
}
public int[] toIntArray() {
int[] temp = new int[rows * cols];
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
temp[i * (rows + 1) + j] = (int) values[i][j];
return temp;
}
public int getRowCount() {
return this.rows;
}
public int getColumnsCount() {
return this.cols;
}
public static double getMatrixDet(Matrix M) {
int m = M.getRowCount();
int n = M.getColumnsCount();
double D = 0;
if (m != n) {
System.err.println("Matrix must be square!");
System.exit(0);
}
if (n > 1) {
Matrix I = new Matrix(m - 1, n - 1);
for (int i = 1; i < m; i++)
for (int j = 1; j < n; j++)
I.setValue(i - 1, j - 1, M.getValue(i, j));
D = M.getValue(0, 0) * getMatrixDet(I);
} else
D = M.getValue(0, 0);
// za niz , kopira iz niza a elemente 0:i-1 i+1:n sredi za matrcu
Matrix I = new Matrix(m - 1, n - 1);
for (int i = 1; i < n; i++) {
I = M.withoutIthRowAndJthCol(i, 0);
D = D + Math.pow((-1), i) * M.getValue(i, 0) * getMatrixDet(I);
}
return D;
}
public Matrix transpose() {
Matrix temp = new Matrix(this.values);
for (int i = 0; i < this.rows; i++)
for (int j = 0; j < this.cols; j++)
this.values[i][j] = temp.getValue(j, i);
return this;
}
private Matrix withoutIthRowAndJthCol(int row, int col) {
Matrix temp = new Matrix(this.rows - 1, this.cols - 1);
int k = 0, l = 0;
for (int i = 0; i < this.getRowCount(); i++) {
if (i == row)
continue;
for (int j = 0; j < this.getColumnsCount(); j++) {
if (j == col)
continue;
temp.setValue(k, l, this.values[i][j]);
l++;
}
l %= 2;
k++;
}
return temp;
}
public static Matrix getMatrixAdj(Matrix M) {
int m = M.getRowCount();
int n = M.getColumnsCount();
Matrix A = new Matrix(m, n);
if (m != n) {
System.err.println("Matrix must be square!");
System.exit(0);
}
for (int i = 0; i < m; i++)
for (int j = 0; j < n; j++) {
A.setValue(i, j, Math.pow((-1), i + j)
* getMatrixDet(M.withoutIthRowAndJthCol(i, j)));
}
A.transpose();
return A;
}
public static Matrix matrixDiv(Matrix M, double n) {
Matrix temp = M;
for (int i = 0; i < M.getRowCount(); i++)
for (int j = 0; j < M.getColumnsCount(); j++)
temp.setValue(i, j, (M.getValue(i, j) / n));
return temp;
}
public static Matrix getMatrixInv(Matrix M) {
Matrix I = new Matrix(M.getRowCount(), M.getColumnsCount());
if (M.getRowCount() != M.getColumnsCount()) {
System.err.println("Matrix must be square!");
System.exit(0);
}
if (getMatrixDet(M) == 0) {
System.err.println("Matrix is singular!");
System.exit(0);
}
I = matrixDiv(getMatrixAdj(M), getMatrixDet(M));
return I;
}
}
if this is what you wanted, you're welcome.
