Metadata-Version: 2.1
Name: mathmatrix
Version: 0.4
Summary: A package for Python that lets you create and perform various operations on Matrices sucjh as finding the adjoint, inverse, determinant of a matrix, etc..
Home-page: https://github.com/Nectres/mathmatrix.git
Author: Keerthi Vasan S A
Author-email: sakeerthi23@gmail.com
License: MIT
Download-URL: https://github.com/Nectres/mathmatrix/archive/refs/tags/Alpha.tar.gz
Description: Features
        ~~~~~~~~
        
        -  Addition, Multiplication, Division, Subraction operations supported
           between matrices and between a matrix and a int / float
        -  Calculates:
        
           -  Determinant
           -  Inverse
           -  Cofactor of a given element in the Matrix
           -  Adjoint
        
        Getting started
        ---------------
        
        Creating a Matrix
        ^^^^^^^^^^^^^^^^^
        
        To create a matrix, specify the order of the Matrix (mxn) where the
        first argument (m) is the number of rows in the matrix and the second
        argument (n) is the number of columns
        
        We can use a nested list to represent a Matrix during initialization of
        an object In a nested list, the length of the outer list would be ‘m’
        and the number of elements the inner lists have would be ‘n’
        
        .. code:: python
        
           from matrix import Matrix
        
           matrix_list = [
               [1, 2, 3],
               [4, 5, 6],
               [7, 8, 9]
           ]
        
           matrix1 = Matrix(3, 3, matrix_list)
        
           print(matrix1)
           #Prints:
           # [ 1, 2, 3
           #   4, 5, 6
           #   7, 8, 9 ]
        
        Operations on Matrices
        ======================
        
        Addition and Subraction
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        We can add and subract matrices extremely easily:
        
        .. code:: python
        
           matrix_list2 = [
               [0, 1, 3], 
               [5, 2, 7], 
               [7, 1, 9]
           ]
           matrix2 = Matrix(3, 3, matrix_list2)
           matrix3 = matrix1 + matrix2
           print(matrix3)
           #Prints:
           # [ 1, 3, 6
           #   9, 7, 13
           #   14, 9, 18 ]
        
        Adding an int / float to a matrix will perform the operation on all
        elements of the matrix and return a new matrix
        
        .. code:: python
        
           matrix4 = matrix1 + 5
           print(matrix4)
           #Prints:
           # [ 6, 7, 8
           #   9, 10, 11
           #   12, 13, 14 ]
           # Same way,
           print(matrix4 - matrix1)
           # [ 5, 5, 5
           #   5, 5, 5
           #   5, 5, 5 ]
           print(matrix1 - 3)
           #Prints:
           # [ -2, -1, 0
           #   1, 2, 3
           #   4, 5, 6 ]
        
        Multiplication and Division
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Matrix multiplication can only be implemented if the number of columns
        in the first matrix is equal to the number of rows in the other matrix.
        Basically: A ``m x n`` Matrix can only be multiplied with a ``n x l``
        Matrix .
        
        The order of the resultant Matrix will be ``m x l``
        
        Example:
        
        .. code:: python
        
           # m x n * n x l : Gives m x l
           # 2 x 3 * 3 x 2 : Gives 2 x 2
           # 2 x 3 * 4 x 2 : Cannot mutliply
        
        Internally, division is calculated by multiplying a matrix and the
        inverse of the other matrix therefore the same condition applies for
        division
        
        .. code:: python
        
           print(matrix1 * 5)
           # [ 5, 10, 15
           #   20, 25, 30
           #   35, 40, 45 ]
           print(matrix1 * matrix2)
           # [ 31, 8, 44
           #   67, 20, 101
           #   103, 32, 44 ]
        
        Comparing matrices
        ~~~~~~~~~~~~~~~~~~
        
        ``Matrix == Matrix | 0 -> bool``
        
        Matrices can be compared for equality to another matrix Zero is used as
        an alias for a zero matrix
        
        Functionalities
        ---------------
        
        ``mathmatrix`` provides many functionalities for matrices out of the
        box:
        
        Let’s create a sample matrix ``matrix`` to perform the operations on
        
        .. code:: python
        
           from mathmatrix import Matrix
        
           matrix = Matrix(3,3,[[1,2,3],[4,5,6],[7,8,9]])
        
        Transposing a matrix
        ~~~~~~~~~~~~~~~~~~~~
        
        ``Matrix.transpose() -> Matrix``
        
        After creating a matrix, you can transpose a Matrix using the
        ``transpose()`` method of Matrix
        
        .. code:: python
        
           print(matrix.transpose())
           # [ 1, 4, 7
           #   2, 5, 8
           #   3, 6, 7 ]
        
        Adjoint of a Matrix
        ~~~~~~~~~~~~~~~~~~~
        
        ``Matrix.adjoint() -> Matrix``
        
        Adjoint of a matrix is calculated as the transpose of cofactor matrix of
        a Matrix It can be calculated using the ``adjoint()`` method
        
        .. code:: python
        
           print(matrix.adjoint())
           # [ -3, 6, -3
           #   6, -12, 6
           #  -3, 6, -3 ]
        
        Determinant of a Matrix
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        ``Matrix.determinant() -> int | float``
        
        .. code:: python
        
           print(matrix.determinant())
           # 0
        
        Inverse of a Matrix
        ~~~~~~~~~~~~~~~~~~~
        
        ``Matrix.inverse() -> Matrix``
        
        Inverse of a matrix only exists for non-singular matrices ( Determinant
        of the Matrix should not be zero )
        
        .. code:: python
        
           print(matrix.determinant())
           # 0
           # Since determinant is zero, if we try to calculate Inverse it will throw the error:
           # ZeroDivisionError: Determinant of Matrix is zero, inverse of the matrix does not exist
        
        Cofactor of an element
        ~~~~~~~~~~~~~~~~~~~~~~
        
        ``Matrix.cofactor(m:int, n:int) -> int | float``
        
        Specify the position of the desired element in row number (m) and column
        number (n) to calculate it’s corresponding cofactor
        
        Chaining functions
        ~~~~~~~~~~~~~~~~~~
        
        Since functions return a new Matrix, you can chain many functions to get
        the desired output For example:
        
        .. code:: python
        
           matrix.transpose().adjoint().determinant()
           (matrix.determinant() * matrix.adjoint()).transpose()
        
        are all completely valid
        
        Additional Functions
        --------------------
        
        Generating a zero matrix
        ~~~~~~~~~~~~~~~~~~~~~~~~
        
        ``gen_zero_matrix(m:int, n:int) -> Matrix``
        
        You can use the ``gen_zero_matrix`` function to create a zero matrix of
        a given order For example,
        
        .. code:: python
        
           from mathmatrix import gen_zero_matrix, Matrix
           zero3 = gen_zero_matrix(3,3) 
           print(zero3)
           # [ 0, 0, 0
           #   0, 0, 0
           #   0, 0, 0 ]
           print(zero3 == 0)
           # True
        
        Generating an identity matrix
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        ``gen_zero_matrix(m:int, n:int) -> Matrix``
        
        You can use the ``gen_zero_matrix`` function to create a zero matrix of
        a given order For example,
        
        .. code:: python
        
           from mathmatrix import gen_zero_matrix, Matrix
           zero3 = gen_zero_matrix(3,3) 
           print(zero3)
           # [ 0, 0, 0
           #   0, 0, 0
           #   0, 0, 0 ]
           print(zero3 == 0)
           # True
        
        Note: For any Matrix ``matrix``,
        
        .. code:: python
        
           print(matrix * matrix.inverse() == gen_identity_matrix(matrix.m, matrix.n))
           # Always true (Inverse cannot be calculated for singular matrices so error is thrown in that case)
           print((matrix - matrix) == gen_zero_matrix(matrix.m,matrix.n))
           # Always true
        
Keywords: matrix,math,mathmatrix,matrices,matrix inverse,determinant
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/x-rst
