MatrixX

MatrixX is a Java library designed to provide a robust and intuitive API for matrix manipulation and algebra. Whether you are working on scientific computing, engineering, data analysis, or algorithm development, MatrixX delivers high-performance matrix operations and algebraic tools out of the box.

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Features

🟦 Matrix Creation

• Identity Matrix: Generate identity matrices of any size.
• Zero Matrix: Create zero matrices.
• From Array: Instantiate matrices directly from 2D arrays.

🖨️ Print / Display

• Easily print matrices in a readable format.

➕ Matrix Operations

• Addition: Element-wise matrix addition.
• Subtraction: Element-wise matrix subtraction.
• Multiplication: Standard matrix multiplication.

🔹 Utility Operations

• Transpose: Get the transpose of a matrix.
• Scalar Multiplication: Multiply a matrix by a scalar.
• Equality Check: Compare matrices for equality.
• Matrix Power (Aⁿ): Raise a matrix to an integer power.
• Determinant: Compute determinants (supports 2x2, 3x3, and recursive for larger matrices).
• Inverse: Calculate the inverse of a matrix (if it exists).

🔸 Algebraic Tools

• LU Decomposition: Decompose a matrix into lower and upper triangular matrices.
• Gauss-Jordan Elimination: Perform row reduction for solving systems or finding inverses.
• Rank of Matrix: Compute the rank.
• Reduced Row Echelon Form (RREF): Reduce matrices to their canonical form.

🔹 Special Matrix Types Support

• Diagonal Matrices
• Symmetric Matrices
• Identity Matrices
• Orthogonal Matrices

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Installation

Add MatrixX to your Java project (Maven/Gradle setup coming soon).
For now, clone the repository and include the source files in your project:

git clone https://github.com/ayoubMah/MatrixX.git

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Basic Usage

import matrixx.Matrix;

public class Example {
    public static void main(String[] args) {
        double[][] data = {
            {1, 2},
            {3, 4}
        };
        Matrix A = new Matrix(data);
        Matrix B = Matrix.identity(2);

        Matrix sum = A.add(B);
        sum.print(); // Display the resulting matrix
    }
}

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Roadmap

• Matrix creation and display
• Basic arithmetic operations
• Transpose, scalar multiplication, equality check
• Determinant and inverse (recursive algorithms)
• LU decomposition, Gauss-Jordan, RREF
• Special matrix type detection and optimizations

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Contributing

Pull requests, feature requests, and bug reports are welcome!
Please open an issue to discuss your ideas or questions.

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License

This project is licensed under the MIT License.

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Author

ayoubMah