Python arrays without numpy!

Saad-coder · November 5, 2020, 7:10am

Can someone help me regarding the subtraction and multiplication of two matrices which I created using arrays (without numpy) and I am doing it using object oriented by making class and functions. I had created 2 matrices and print them by calling the class in objects and now I have to make a function in the same class which subtracts and another function which multiplies these 2 matrices.

Any help?

mukeshgurpude · November 5, 2020, 7:50am

Basically you’re talking about Operator Overloading,
In python we can implement __sub__ method for subtraction __add__ for addition __mul__ for multiplication etc…
Read more here

thirty_two · November 6, 2020, 5:24am

You can find a complete example here

github.com

TheAlgorithms/Python/blob/master/matrix/matrix_class.py

# An OOP approach to representing and manipulating matrices


class Matrix:
    """
    Matrix object generated from a 2D array where each element is an array representing
    a row.
    Rows can contain type int or float.
    Common operations and information available.
    >>> rows = [
    ...     [1, 2, 3],
    ...     [4, 5, 6],
    ...     [7, 8, 9]
    ... ]
    >>> matrix = Matrix(rows)
    >>> print(matrix)
    [[1. 2. 3.]
     [4. 5. 6.]
     [7. 8. 9.]]

This file has been truncated. show original

Basically, you want to overload the arithmetic operators, for example

    def __add__(self, other):
        if self.order != other.order:
            raise ValueError("Addition requires matrices of the same order")
        return Matrix(
            [
                [self.rows[i][j] + other.rows[i][j] for j in range(self.num_columns)]
                for i in range(self.num_rows)
            ]
        )

So, you can now do, assuming you have already implemented your basic Matrix class

>>> rows = [
    ...     [1, 2, 3],
    ...     [4, 5, 6],
    ...     [7, 8, 9]
    ... ]
 >>> matrix = Matrix(rows)
 >>> matrix2 = matrix * 3
 >>> print(matrix + matrix2)
    [[4. 8. 12.]
     [16. 20. 24.]
     [28. 32. 36.]]