feat: Add support for determinant calculation

[mitsuki31]

Overview

This pull request includes several feature updates and documentation improvements to enhance the functionality and usability of the JMatrix library, especially focusing on adding support for determinant calculation.

Key Changes

Determinant Calculation Methods

• Added a new class called MatrixDeterminant to calculate the determinant of a matrix with two algorithms: Laplace expansion and Gaussian elimination. This addition enables efficient calculation of determinants for matrices of varying sizes.
• Added three new determinant calculation methods to the matrix class:
  • determinant()

    public double determinant();

    Calculates the determinant of the matrix instance.
  • determinant(Matrix)

    public static double determinant(Matrix m);

    Calculates the determinant of a given matrix.
  • determinant(double[][])

    public static double determinant(double[][] a);

    Calculates the determinant of a matrix represented as a two-dimensional (2D) array.

Note

Those method will automatically chooses the best algorithm for calculating the determinant based on the size of the matrix that are given. The cofactor expansion or laplace expansion algorithm will be used if the matrix size is smaller than or equal to $4\times4$; otherwise, the Gauss elimination algorithm will be used for larger matrix.

Documentation Updates

• Added a version class to matrix checker classes where missing from previous changes (feat: Enhance matrix validation and exception handling #129).
• Added detailed Javadoc with usage, exceptions, and algorithm notes for the new determinant calculation methods, providing clear guidance for users.
• Improved comment region markers for constructors and special methods, enhancing code readability and maintainability.

Impact

• The new determinant calculation methods will enable users to efficiently calculate determinants for matrices of varying sizes, making it easier to perform tasks such as matrix inversion, solving systems of linear equations, and more.
• The new determinant calculation methods are designed to be efficient and scalable, minimizing performance impacts on large matrices.
• The detailed Javadoc and improved comment region markers will provide clear guidance for users, making it easier for them to understand and use the library's features.