info2Praktikum-NeuronalesNetz/matrix.c

#include "matrix.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

/*typedef struct {
    unsigned int rows;  //Zeilen
    unsigned int cols; //Spalten
    MatrixType *buffer; //Zeiger auf Speicherbereich Reihen*Spalten
} Matrix;*/

Matrix createMatrix(const unsigned int rows, const unsigned int cols) {
  if (cols == 0 || rows == 0) {
    Matrix errorMatrix = {0, 0, NULL};
    return errorMatrix;
  }
  MatrixType *buffer =
      malloc(rows * cols * sizeof(MatrixType)); // Speicher reservieren, malloc
                                                // liefert Zeiger auf Speicher
  Matrix newMatrix = {rows, cols, buffer};      // neue Matrix nach struct
  return newMatrix;
}
void clearMatrix(Matrix *matrix) {

  if (matrix->buffer != NULL) {
    free((*matrix).buffer);
    matrix->buffer = NULL;
  }
  matrix->rows = 0;
  matrix->cols = 0;
}

void setMatrixAt(const MatrixType value, Matrix matrix,
                 const unsigned int rowIdx, // Kopie der Matrix wird übergeben
                 const unsigned int colIdx) {

  if (rowIdx >= matrix.rows || colIdx >= matrix.cols) {
    // Speichergröße nicht überschreiten
    return;
  }
  matrix.buffer[rowIdx * matrix.cols + colIdx] = value;
  // rowIdx * matrix.cols -> Beginn der Zeile colIdx ->Spalte
  // innerhalb der Zeile
}
MatrixType
getMatrixAt(const Matrix matrix,
            const unsigned int rowIdx, // Kopie der Matrix wird übergeben
            const unsigned int colIdx) {
  if (rowIdx >= matrix.rows || colIdx >= matrix.cols ||
      matrix.buffer == NULL) { // Speichergröße nicht überschreiten
    return UNDEFINED_MATRIX_VALUE;
  }

  MatrixType value = matrix.buffer[rowIdx * matrix.cols + colIdx];

  return value;
}
Matrix broadCastCols(const Matrix matrix, const unsigned int cols) {
  Matrix copy1 = createMatrix(matrix.rows, cols);
  for (int r = 0; r < matrix.rows; r++) {
    MatrixType valueMatrix1 = getMatrixAt(matrix, r, 0);
    for (int c = 0; c < cols; c++) {
      setMatrixAt(valueMatrix1, copy1, r, c);
    }
  }
  return copy1;
}
Matrix broadCastRows(const Matrix matrix, const unsigned int rows) {
  Matrix copy1 = createMatrix(rows, matrix.cols);
  for (int c = 0; c < matrix.cols; c++) {
    MatrixType valueMatrix1 = getMatrixAt(matrix, 0, c);
    for (int r = 0; r < rows; r++) {
      setMatrixAt(valueMatrix1, copy1, r, c);
    }
  }
  return copy1;
}
Matrix add(const Matrix matrix1, const Matrix matrix2) {

  // Ergebnismatrix
  Matrix result;
  const int cols1 = matrix1.cols;
  const int rows1 = matrix1.rows;
  const int cols2 = matrix2.cols;
  const int rows2 = matrix2.rows;

  const int rowsEqual = (matrix1.rows == matrix2.rows) ? 1 : 0;
  const int colsEqual = (matrix1.cols == matrix2.cols) ? 1 : 0;

  // Broadcasting nur bei Vektor und Matrix, Fehlermeldung bei zwei unpassender
  // Matrix
  if (rowsEqual == 1 && colsEqual == 1) {
    Matrix result = createMatrix(matrix1.rows, matrix1.cols);
    if (result.buffer == NULL) {
      return (Matrix){0, 0, NULL};
    }
    for (int i = 0; i < rows1; i++) {
      for (int j = 0; j < cols1; j++) {
        int valueM1 = getMatrixAt(matrix1, i, j);
        int valueM2 = getMatrixAt(matrix2, i, j);
        int sum = valueM1 + valueM2;
        setMatrixAt(sum, result, i, j);
      }
    }
    return result;
  } else if (rowsEqual == 1 && (cols1 == 1 || cols2 == 1)) {
    if (cols1 == 1) { // broadcasting von vektor 1 zu matrix 1, add
      Matrix newMatrix = broadCastCols(matrix1, cols2);
      // add
      Matrix result = createMatrix(newMatrix.rows, newMatrix.cols);
      if (result.buffer == NULL) {
        return (Matrix){0, 0, NULL};
      }
      for (int i = 0; i < rows1; i++) {
        for (int j = 0; j < cols2; j++) {
          int valueM1 = getMatrixAt(newMatrix, i, j);
          int valueM2 = getMatrixAt(matrix2, i, j);
          int sum = valueM1 + valueM2;
          setMatrixAt(sum, result, i, j);
        }
      }
      clearMatrix(&newMatrix);
      return result;
    } else {
      Matrix newMatrix2 = broadCastCols(matrix2, cols1);
      // add
      Matrix result = createMatrix(newMatrix2.rows, newMatrix2.cols);
      if (result.buffer == NULL) {
        return (Matrix){0, 0, NULL};
      }
      for (int i = 0; i < rows1; i++) {
        for (int j = 0; j < cols1; j++) {
          int valueM1 = getMatrixAt(matrix1, i, j);
          int valueM2 = getMatrixAt(newMatrix2, i, j);
          int sum = valueM1 + valueM2;
          setMatrixAt(sum, result, i, j);
        }
      }

      return result;
    }
  }

  else if ((rows1 == 1 || rows2 == 1) && colsEqual == 1) {
    if (rows1 == 1) {
      Matrix newMatrix = broadCastRows(matrix1, rows2);
      // add
      Matrix result = createMatrix(newMatrix.rows, newMatrix.cols);
      if (result.buffer == NULL) {
        return (Matrix){0, 0, NULL};
      }
      for (int i = 0; i < rows2; i++) {
        for (int j = 0; j < cols1; j++) {
          int valueM1 = getMatrixAt(newMatrix, i, j);
          int valueM2 = getMatrixAt(matrix2, i, j);
          int sum = valueM1 + valueM2;
          setMatrixAt(sum, result, i, j);
        }
      }
      return result;
    } else {
      Matrix newMatrix2 = broadCastRows(matrix2, rows1);
      // add
      Matrix result = createMatrix(newMatrix2.rows, newMatrix2.cols);
      if (result.buffer == NULL) {
        return (Matrix){0, 0, NULL};
      }
      for (int i = 0; i < rows1; i++) {
        for (int j = 0; j < cols1; j++) {
          int valueM1 = getMatrixAt(matrix1, i, j);
          int valueM2 = getMatrixAt(newMatrix2, i, j);
          int sum = valueM1 + valueM2;
          setMatrixAt(sum, result, i, j);
        }
      }
      clearMatrix(&newMatrix2);
      return result;
    }
  } else {
    // kein add möglich
    Matrix errorMatrix = {0, 0, NULL};
    return errorMatrix;
  }
  return result;
}
Matrix multiply(const Matrix matrix1, const Matrix matrix2) {
  // Spalten1 müssen gleich zeilen2 sein! dann multiplizieren
  if (matrix1.cols == matrix2.rows) {
    Matrix multMatrix = createMatrix(matrix1.rows, matrix2.cols);
    // durch neue matrix iterieren
    for (int r = 0; r < matrix1.rows; r++) {
      for (int c = 0; c < matrix2.cols; c++) {
        MatrixType sum = 0.0;
        // skalarprodukte berechnen, k damit die ganze zeile mal die ganze
        // spalte genommen wird quasi
        for (int k = 0; k < matrix1.cols; k++) {
          // sum+=
          // matrix1.buffer[r*matrix1.cols+k]*matrix2.buffer[k*matrix2.cols+c];
          sum += getMatrixAt(matrix1, r, k) * getMatrixAt(matrix2, k, c);
        }
        // Ergebnisse in neue matrix speichern
        setMatrixAt(sum, multMatrix, r, c);
      }
    }
    return multMatrix;
  }
  // sonst fehler, kein multiply möglich
  else {
    Matrix errorMatrix = {0, 0, NULL};
    return errorMatrix;
  }
}