Finished implimenting all of the matrix math functions

Matrix.h

@@ -1,14 +1,22 @@
+#pragma once
+
 #include <cstdint>
 #include <array>
 #include <type_traits>
+#include <cstdlib>
 
 template <uint8_t rows, uint8_t columns>
 class Matrix{
     public:
+    Matrix();
+
+    Matrix(const std::array<float, columns> & array);
+
     /**
      * @brief Element-wise matrix addition
      * @param other the other matrix to add to this one
      * @param result A buffer to store the result into
+     * @note there is no problem if result == this
      */
     void Add(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const;
     
@@ -16,6 +24,7 @@ class Matrix{
      * @brief Element-wise subtract matrix
      * @param other the other matrix to subtract from this one
      * @param result A buffer to store the result into
+     * @note there is no problem if result == this
      */
     void Subtract(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const;
 
@@ -31,12 +40,14 @@ class Matrix{
      * @brief Multiply the matrix by a scalar
      * @param scalar the the scalar to multiply by
      * @param result A buffer to store the result into
+     * @note there is no problem if result == this
      */
     void Multiply(float scalar, Matrix<rows, columns> & result) const;
     
     /**
      * @brief Invert this matrix
      * @param result A buffer to store the result into
+     * @warning this is super slow! Only call it if you absolutely have to!!!
      */
     void Invert(Matrix<rows, columns> & result) const;
 
@@ -55,12 +66,19 @@ class Matrix{
     /**
      * @return Get the determinant of the matrix
      */
-    float Det();
+    float Det() const;
+
+    /**
+     * @brief Calculate the eigenvalues for a square matrix
+     * @param result a buffer to store the result into
+     */
+    void EigenValues(Matrix<rows, 1> & result) const;
 
     /**
      * @brief Element-wise multiply the two matrices
      * @param other the other matrix to multiply into this one
      * @param result A buffer to store the result into
+     * @note there is no problem if result == this
      */
     void ElementMultiply(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const;
 
@@ -68,6 +86,7 @@ class Matrix{
      * @brief Element-wise divide the two matrices
      * @param other the other matrix to multiply into this one
      * @param result A buffer to store the result into
+     * @note there is no problem if result == this
      */
     void ElementDivide(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const;
     
@@ -79,19 +98,26 @@ class Matrix{
      */
     float & Get(uint8_t row_index, uint8_t column_index) const;
 
+    /**
+     * @brief get the specified row of the matrix returned as a reference to the internal array
+     */
+    std::array<float, columns> & operator[](uint8_t row_index) const;
+
+    void operator=(Matrix<rows, columns> & other);
+
     /**
      * @brief Get a row from the matrix
      * @param row_index the row index to get
      * @param row a buffer to write the row into
      */
-    void GetRow(uint8_t row_index, Matrix<rows, 1> & row) const;
+    void GetRow(uint8_t row_index, Matrix<1, columns> & row) const;
 
     /**
      * @brief Get a row from the matrix
      * @param column_index the row index to get
      * @param column a buffer to write the row into
      */
-    void GetColumn(uint8_t column_index, Matrix<1, columns> & column) const;
+    void GetColumn(uint8_t column_index, Matrix<rows, 1> & column) const;
 
     /**
      * @brief Get the number of rows in this matrix
@@ -104,7 +130,6 @@ class Matrix{
     constexpr uint8_t GetColumnSize(){return columns;}
 
     private:
-
     /**
      * @brief take the dot product of the two vectors
      */
@@ -116,13 +141,42 @@ class Matrix{
      */
     void zeroMatrix();
 
-    void matrixOfMinors(const Matrix<rows, columns> & input, Matrix<rows, columns> & result) const;
+    void matrixOfMinors(Matrix<rows, columns> & result) const;
 
-    void adjugate(const Matrix<rows, columns> & input, Matrix<rows, columns> & result) const;
+    void minorMatrix(Matrix<rows-1, columns-1> & result, uint8_t row_idx, uint8_t column_idx) const;
 
+    void adjugate(Matrix<rows, columns> & result) const;
+
+    /**
+     * @brief reduce the matrix so the sum of its elements equal 1
+     * @param result a buffer to store the result into
+     */
+    void normalize(Matrix<rows, columns> & result) const;
+
+    constexpr bool isSquare(){return rows==columns;}
     std::array<std::array<float, columns>, rows> matrix;
 };
 
+template <uint8_t rows, uint8_t columns>
+Matrix<rows, columns>::Matrix(){
+    this->zeroMatrix();
+}
+
+template <uint8_t rows, uint8_t columns>
+Matrix<rows, columns>::Matrix(const std::array<float, columns> & array){
+    for(uint8_t row_idx{0}; row_idx < rows; row_idx++){
+        for(uint8_t column_idx{0}; column_idx < columns; column_idx++){
+            uint16_t i = static_cast<uint16_t>(row_idx) + static_cast<uint16_t>(column_idx);
+            if(i < array.size()){
+                this->Get(row_idx, column_idx) = array[i];
+            }
+            else{
+                this->Get(row_idx, column_idx) = 0;
+            }
+        }
+    }
+}
+
 template <uint8_t rows, uint8_t columns>
 void Matrix<rows, columns>::Add(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const{
     for(uint8_t row{0}; row < rows; row++){
@@ -183,14 +237,15 @@ void Matrix<rows, columns>::Invert(Matrix<rows, columns> & result) const{
         return;
     }
 
+    // TODO: This algorithm is really inneficient because of the matrix of minors. We should make a different algorithm
     // how to calculate the inverse: https://www.mathsisfun.com/algebra/matrix-inverse-minors-cofactors-adjugate.html
 
     // calculate the matrix of minors
     Matrix<rows, columns> minors{};
-    this->matrixOfMinors(this, minors);
+    this->matrixOfMinors(minors);
 
     // now adjugate the matrix and save it in our output
-    this->adjugate(minors, result);
+    minors.adjugate(result);
     float determinant = this->Det();
 
     // scale the result by 1/determinant and we have our answer
@@ -199,5 +254,199 @@ void Matrix<rows, columns>::Invert(Matrix<rows, columns> & result) const{
 
 template <uint8_t rows, uint8_t columns>
 void Matrix<rows, columns>::Transpose(Matrix<columns, rows> & result) const{
-
+    for(uint8_t column_idx{0}; column_idx < rows; column_idx++){
+        for(uint8_t row_idx{0}; row_idx < columns; row_idx++){
+            result.Get(row_idx, column_idx) = this->Get(column_idx, row_idx);
+        }
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::Square(Matrix<rows, columns> & result) const{
+    static_assert(this->isSquare(), "You can't square an non-square matrix.");
+    
+    this->Multiply(this, result);
+}
+
+template <uint8_t rows, uint8_t columns>
+float Matrix<rows, columns>::Det() const{
+    static_assert(this->isSquare(), "You can't take the determinant of a non-square matrix.");
+    Matrix<1, columns> eigenValues{};
+    this->EigenValues(eigenValues);
+
+    float determinant{1};
+    for(uint8_t i{0}; i < columns; i++){
+        determinant *= eigenValues.Get(0, i);
+    }
+
+    return determinant;
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::EigenValues(Matrix<rows, 1> & eigenvalues) const{
+    static_assert(rows == columns, "Eigenvalues can only be computed for square matrices.");
+    // I got this code from: https://www.quora.com/What-is-the-C-code-for-finding-eigenvalues
+    Matrix<rows, 1> v{};
+    Matrix<rows, 1> Av{};
+    Matrix<rows, 1> z{};
+
+    float d = 0.0, d_old = 0.0; 
+    constexpr float convergence_value{1e-6};
+    constexpr uint16_t max_iterations{500};
+ 
+    // Initialize v as a random vector
+    for (int i = 0; i < rows; i++) { 
+        v[0][i] = rand() / RAND_MAX; 
+    } 
+ 
+    // run this loop until the eigenvalues converge or we give up
+    for (uint16_t k{0}; k < max_iterations; k++) { 
+        /* Multiply A by v */ 
+        for (int i = 0; i < rows; i++) { 
+            Av[0][i] = 0.0; 
+            for (int j = 0; j < rows; j++) { 
+                Av[0][i] += this->Get(0, i * rows + j) * v[0][j]; 
+            } 
+        } 
+ 
+        // Calculate the eigenvalue and update v
+        d_old = d; 
+        d = dot_product(v, Av, rows); 
+        for (int i = 0; i < rows; i++) { 
+            z[0][i] = Av[0][i] - d * v[0][i]; 
+        } 
+
+        z.normalize(z);
+        
+        for (int i = 0; i < rows; i++) { 
+            v[0][i] = z[0][i]; 
+        } 
+ 
+        /* Check for convergence */ 
+        if (fabs(d - d_old) < convergence_value) { 
+            eigenvalues[0][k] = d; 
+            k++; 
+            d = 0.0; 
+            for (int i = 0; i < rows; i++) { 
+                v[0][i] = rand() / RAND_MAX; 
+            } 
+        } 
+    } 
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::ElementMultiply(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const{
+    for(uint8_t row_idx{0}; row_idx < rows; row_idx++){
+        for(uint8_t column_idx{0}; column_idx < columns; column_idx++){
+            result.Get(row_idx, column_idx) = this->Get(row_idx, column_idx) * other.Get(row_idx, column_idx);
+        }
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::ElementDivide(const Matrix<rows, columns> & other, Matrix<rows, columns> & result) const{
+    for(uint8_t row_idx{0}; row_idx < rows; row_idx++){
+        for(uint8_t column_idx{0}; column_idx < columns; column_idx++){
+            result.Get(row_idx, column_idx) = this->Get(row_idx, column_idx) / other.Get(row_idx, column_idx);
+        }
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+float & Matrix<rows, columns>::Get(uint8_t row_index, uint8_t column_index) const{
+    return this->matrix[row_index][column_index];
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::GetRow(uint8_t row_index, Matrix<1, columns> & row) const{
+    row = Matrix<1, columns>(this->matrix[row_index]);
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::GetColumn(uint8_t column_index, Matrix<rows, 1> & column) const{
+    for(uint8_t row_idx{0}; row_idx < rows; row_idx++){
+        column.Get(0, column_index) = this->Get(row_idx, column_index);
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+template <uint8_t vector_size>
+float Matrix<rows, columns>::dotProduct(const Matrix<vector_size, 1> & vec1, const Matrix<vector_size, 1> & vec2){
+    float sum{0};
+    for(uint8_t i{0}; i < vector_size; i++){
+        sum += vec1.Get(i, 0) * vec2.Get(i, 0);
+    }
+
+    return sum;
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::zeroMatrix(){
+    for(uint8_t row_idx{0}; row_idx < rows; row_idx++){
+        for(uint8_t column_idx{0}; column_idx < columns; column_idx++){
+            this->matrix[row_idx][column_idx] = 0;
+        }
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::matrixOfMinors(Matrix<rows, columns> & result) const{
+    Matrix<rows-1, columns-1> minorMatrix{};
+
+    for(uint8_t row_idx{0}; row_idx < rows; row_idx++){
+        for(uint8_t column_idx{0}; column_idx < columns; column_idx++){
+            this->minorMatrix(minorMatrix, row_idx, column_idx);
+            result.Get(row_idx, column_idx) = minorMatrix.Det();
+        }
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::minorMatrix(Matrix<rows-1, columns-1> & result, uint8_t row_idx, uint8_t column_idx) const{
+    std::array<float, (rows-1)*(columns-1)> subArray{};
+    
+    for(uint8_t row_iter{0}; row_iter < rows; row_iter++){
+        for(uint8_t column_iter{0}; column_iter < columns; column_iter++){
+            uint16_t i = static_cast<uint16_t>(row_iter) + static_cast<uint16_t>(column_iter);
+            if(row_iter == row_idx || column_iter == column_idx){
+                continue;
+            }
+            subArray[i] = this->Get(row_iter, column_iter);
+        }
+    }
+
+    result = Matrix<rows-1, columns-1>{subArray};
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::adjugate(Matrix<rows, columns> & result) const{
+    for(uint8_t row_iter{0}; row_iter < rows; row_iter++){
+        for(uint8_t column_iter{0}; column_iter < columns; column_iter++){
+            float sign = ((row_iter + 1) % 2) ? -1 : 1;
+            sign *= ((column_iter + 1) % 2) ? -1 : 1;
+            result.Get(row_iter, column_iter) = this->Get(row_iter, column_iter) * sign;
+        }
+    }
+}
+
+template <uint8_t rows, uint8_t columns>
+void Matrix<rows, columns>::normalize(Matrix<rows, columns> & result) const{
+    float sum{0};
+    for(uint8_t column_idx{0}; column_idx < rows; column_idx++){
+        for(uint8_t row_idx{0}; row_idx < columns; row_idx++){
+            sum += this->Get(row_idx, column_idx);
+        }
+    }
+
+    if(sum == 0){
+        // this wouldn't do anything anyways
+        result.zeroMatrix();
+        return;
+    }
+
+    for(uint8_t column_idx{0}; column_idx < rows; column_idx++){
+        for(uint8_t row_idx{0}; row_idx < columns; row_idx++){
+            result.Get(row_idx, column_idx) = this->Get(row_idx, column_idx) / sum;
+        }
+    }
 }