1

私はここにあるコードとアルゴリズムを実装しようとしています:

行列式 とここ: 行列式を計算する方法は?n*nまたは単に5*5

しかし、私はそれに固執しています。

私の最初の質問は、このアルゴリズムが実際にどのルールを使用するかです(数学には行列式を計算できるルールがいくつかあるので)-アルゴリズムが正しく適用されているかどうかを最初に確認したいと思います。

私の2番目の質問は、3x3と4x4の場合は正常に機能するように見えますが、5x5の場合はNaNが得られるため、私が間違ったこと(つまり、実装)またはアルゴリズム自体の問題です。結果は、いくつかのオンライン行列式計算機でチェックされ、5x5を除いて問題ありません。

これは私のコードです:

using System;

public class Matrix
{
    private int row_matrix; //number of rows for matrix
    private int column_matrix; //number of colums for matrix
    private double[,] matrix; //holds values of matrix itself

    //create r*c matrix and fill it with data passed to this constructor
    public Matrix(double[,] double_array)
    {
        matrix = double_array;
        row_matrix = matrix.GetLength(0);
        column_matrix = matrix.GetLength(1);
        Console.WriteLine("Contructor which sets matrix size {0}*{1} and fill it with initial data executed.", row_matrix, column_matrix);
    }

    //returns total number of rows
    public int countRows()
    {
        return row_matrix;
    }

    //returns total number of columns
    public int countColumns()
    {
        return column_matrix;
    }

    //returns value of an element for a given row and column of matrix
    public double readElement(int row, int column)
    {
        return matrix[row, column];
    }

    //sets value of an element for a given row and column of matrix
    public void setElement(double value, int row, int column)
    {
        matrix[row, column] = value;
    }

    public double deterMatrix()
    {
        double det = 0;
        double value = 0;
        int i, j, k;

        i = row_matrix;
        j = column_matrix;
        int n = i;

        if (i != j)
        {
            Console.WriteLine("determinant can be calculated only for sqaure matrix!");
            return det;
        }

        for (i = 0; i < n - 1; i++)
        {
            for (j = i + 1; j < n; j++)
            {
                det = (this.readElement(j, i) / this.readElement(i, i));

                //Console.WriteLine("readElement(j, i): " + this.readElement(j, i));
                //Console.WriteLine("readElement(i, i): " + this.readElement(i, i));
                //Console.WriteLine("det is" + det);
                for (k = i; k < n; k++)
                {
                    value = this.readElement(j, k) - det * this.readElement(i, k);

                    //Console.WriteLine("Set value is:" + value);
                    this.setElement(value, j, k);
                }
            }
        }
        det = 1;
        for (i = 0; i < n; i++)
            det = det * this.readElement(i, i);

        return det;
    }
}

internal class Program
{
    private static void Main(string[] args)
    {
        Matrix mat03 = new Matrix(new[,]
        {
            {1.0, 2.0, -1.0},
            {-2.0, -5.0, -1.0},
            {1.0, -1.0, -2.0},
        });

        Matrix mat04 = new Matrix(new[,]
        {
            {1.0, 2.0, 1.0, 3.0},
            {-2.0, -5.0, -2.0, 1.0},
            {1.0, -1.0, -3.0, 2.0},
            {4.0, -1.0, -3.0, 1.0},
        });

        Matrix mat05 = new Matrix(new[,]
        {
            {1.0, 2.0, 1.0, 2.0, 3.0},
            {2.0, 1.0, 2.0, 2.0, 1.0},
            {3.0, 1.0, 3.0, 1.0, 2.0},
            {1.0, 2.0, 4.0, 3.0, 2.0},
            {2.0, 2.0, 1.0, 2.0, 1.0},
        });

        double determinant = mat03.deterMatrix();
        Console.WriteLine("determinant is: {0}", determinant);

        determinant = mat04.deterMatrix();
        Console.WriteLine("determinant is: {0}", determinant);

        determinant = mat05.deterMatrix();
        Console.WriteLine("determinant is: {0}", determinant);
    }
}
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2 に答える 2

2

なぜ車輪の再発明をするのですか?行列を逆行列化するための確定ANDを取得するためのよく知られた方法は、LU分解を行うことです。実際、MSDNマガジンは最近、これを行う方法についてhttp://msdn.microsoft.com/en-us/magazine/jj863137.aspxC#に投稿しました。

サンプルコードは

行列式

手元にある行列分解法を使用すると、行列式を計算する方法を簡単にコーディングできます。

static double MatrixDeterminant(double[][] matrix)
{
  int[] perm;
  int toggle;
  double[][] lum = MatrixDecompose(matrix, out perm, out toggle);
  if (lum == null)
    throw new Exception("Unable to compute MatrixDeterminant");
  double result = toggle;
  for (int i = 0; i < lum.Length; ++i)
    result *= lum[i][i];
  return result;
}

行列式は、分解された行列の対角線と符号チェックの積から評価されます。詳細については、記事をお読みください。

lum[i][j]行列にはジャグ配列を使用しますが、に変換する独自の行列ストレージに置き換えることができることに注意してくださいlum[i,j]

于 2013-03-20T17:36:37.737 に答える
1

@ja72 ご指示ありがとうございます。n*n 行列式を計算するための最終的な解は次のようになります。

using System;

internal class MatrixDecompositionProgram
{
    private static void Main(string[] args)
    {
        float[,] m = MatrixCreate(4, 4);
        m[0, 0] = 3.0f; m[0, 1] = 7.0f; m[0, 2] = 2.0f; m[0, 3] = 5.0f;
        m[1, 0] = 1.0f; m[1, 1] = 8.0f; m[1, 2] = 4.0f; m[1, 3] = 2.0f;
        m[2, 0] = 2.0f; m[2, 1] = 1.0f; m[2, 2] = 9.0f; m[2, 3] = 3.0f;
        m[3, 0] = 5.0f; m[3, 1] = 4.0f; m[3, 2] = 7.0f; m[3, 3] = 1.0f;

        int[] perm;
        int toggle;

        float[,] luMatrix = MatrixDecompose(m, out perm, out toggle);

        float[,] lower = ExtractLower(luMatrix);
        float[,] upper = ExtractUpper(luMatrix);

        float det = MatrixDeterminant(m);

        Console.WriteLine("Determinant of m computed via decomposition = " + det.ToString("F1"));
    }

    // --------------------------------------------------------------------------------------------------------------
    private static float[,] MatrixCreate(int rows, int cols)
    {
        // allocates/creates a matrix initialized to all 0.0. assume rows and cols > 0
        // do error checking here
        float[,] result = new float[rows, cols];
        return result;
    }

    // --------------------------------------------------------------------------------------------------------------
    private static float[,] MatrixDecompose(float[,] matrix, out int[] perm, out int toggle)
    {
        // Doolittle LUP decomposition with partial pivoting.
        // rerturns: result is L (with 1s on diagonal) and U; perm holds row permutations; toggle is +1 or -1 (even or odd)
        int rows = matrix.GetLength(0);
        int cols = matrix.GetLength(1);

        //Check if matrix is square
        if (rows != cols)
            throw new Exception("Attempt to MatrixDecompose a non-square mattrix");

        float[,] result = MatrixDuplicate(matrix); // make a copy of the input matrix

        perm = new int[rows]; // set up row permutation result
        for (int i = 0; i < rows; ++i) { perm[i] = i; } // i are rows counter

        toggle = 1; // toggle tracks row swaps. +1 -> even, -1 -> odd. used by MatrixDeterminant

        for (int j = 0; j < rows - 1; ++j) // each column, j is counter for coulmns
        {
            float colMax = Math.Abs(result[j, j]); // find largest value in col j
            int pRow = j;
            for (int i = j + 1; i < rows; ++i)
            {
                if (result[i, j] > colMax)
                {
                    colMax = result[i, j];
                    pRow = i;
                }
            }

            if (pRow != j) // if largest value not on pivot, swap rows
            {
                float[] rowPtr = new float[result.GetLength(1)];

                //in order to preserve value of j new variable k for counter is declared
                //rowPtr[] is a 1D array that contains all the elements on a single row of the matrix
                //there has to be a loop over the columns to transfer the values
                //from the 2D array to the 1D rowPtr array.
                //----tranfer 2D array to 1D array BEGIN

                for (int k = 0; k < result.GetLength(1); k++)
                {
                    rowPtr[k] = result[pRow, k];
                }

                for (int k = 0; k < result.GetLength(1); k++)
                {
                    result[pRow, k] = result[j, k];
                }

                for (int k = 0; k < result.GetLength(1); k++)
                {
                    result[j, k] = rowPtr[k];
                }

                //----tranfer 2D array to 1D array END

                int tmp = perm[pRow]; // and swap perm info
                perm[pRow] = perm[j];
                perm[j] = tmp;

                toggle = -toggle; // adjust the row-swap toggle
            }

            if (Math.Abs(result[j, j]) < 1.0E-20) // if diagonal after swap is zero . . .
                return null; // consider a throw

            for (int i = j + 1; i < rows; ++i)
            {
                result[i, j] /= result[j, j];
                for (int k = j + 1; k < rows; ++k)
                {
                    result[i, k] -= result[i, j] * result[j, k];
                }
            }
        } // main j column loop

        return result;
    } // MatrixDecompose

    // --------------------------------------------------------------------------------------------------------------
    private static float MatrixDeterminant(float[,] matrix)
    {
        int[] perm;
        int toggle;
        float[,] lum = MatrixDecompose(matrix, out perm, out toggle);
        if (lum == null)
            throw new Exception("Unable to compute MatrixDeterminant");
        float result = toggle;
        for (int i = 0; i < lum.GetLength(0); ++i)
            result *= lum[i, i];

        return result;
    }

    // --------------------------------------------------------------------------------------------------------------
    private static float[,] MatrixDuplicate(float[,] matrix)
    {
        // allocates/creates a duplicate of a matrix. assumes matrix is not null.
        float[,] result = MatrixCreate(matrix.GetLength(0), matrix.GetLength(1));
        for (int i = 0; i < matrix.GetLength(0); ++i) // copy the values
            for (int j = 0; j < matrix.GetLength(1); ++j)
                result[i, j] = matrix[i, j];
        return result;
    }

    // --------------------------------------------------------------------------------------------------------------
    private static float[,] ExtractLower(float[,] matrix)
    {
        // lower part of a Doolittle decomposition (1.0s on diagonal, 0.0s in upper)
        int rows = matrix.GetLength(0); int cols = matrix.GetLength(1);
        float[,] result = MatrixCreate(rows, cols);
        for (int i = 0; i < rows; ++i)
        {
            for (int j = 0; j < cols; ++j)
            {
                if (i == j)
                    result[i, j] = 1.0f;
                else if (i > j)
                    result[i, j] = matrix[i, j];
            }
        }
        return result;
    }

    // --------------------------------------------------------------------------------------------------------------
    private static float[,] ExtractUpper(float[,] matrix)
    {
        // upper part of a Doolittle decomposition (0.0s in the strictly lower part)
        int rows = matrix.GetLength(0); int cols = matrix.GetLength(1);
        float[,] result = MatrixCreate(rows, cols);
        for (int i = 0; i < rows; ++i)
        {
            for (int j = 0; j < cols; ++j)
            {
                if (i <= j)
                    result[i, j] = matrix[i, j];
            }
        }
        return result;
    }
}
于 2013-03-25T12:28:46.747 に答える