Java庫特徵值浮點數

Question

嗨我有賈馬圖書館，但這個圖書館工作只與雙數..和它非常緩慢。對於Android應用程序..最後我不需要如此高的eig分辨率的精度..所以有一些JAva libaray與浮點數.....類似的語法與jama？ becouse ...我不想重新寫我的440行代碼謝謝。 EIG。轉置，逆等基本線性代數運算..

或存在相同的java庫特徵值。與線程？

Answer 1

或者你在找這樣的事嗎？

 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; 
} 
} 

如果這是你想要的，不客氣。

Answer 2

我知道一個庫叫la4j，你可能有興趣研究一下。我應該提到，一般來說，如果你打算做很多矩陣操作/計算（我自己已經嘗試過並且陷入死衚衕），我不認爲Java是一個好的選擇，但你可能會更好地研究Python （NumPy）或C++（Armadillo）。