adding a matrix equalization algorithm

[meg-1]

Describe your change:

Adding a matrix equalization algorithm, which equalizes all elements of the input vector to a common value, by making the minimal number of "updates" under the constraint of a step size (k).

• [x] Add an algorithm?
• [ ] Fix a bug or typo in an existing algorithm?
• [ ] Add or change doctests? -- Note: Please avoid changing both code and tests in a single pull request.
• [ ] Documentation change?

Checklist:

• [x] I have read CONTRIBUTING.md.
• [x] This pull request is all my own work -- I have not plagiarized.
• [x] I know that pull requests will not be merged if they fail the automated tests.
• [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
• [x] All new Python files are placed inside an existing directory.
• [x] All filenames are in all lowercase characters with no spaces or dashes.
• [x] All functions and variable names follow Python naming conventions.
• [x] All function parameters and return values are annotated with Python type hints.
• [x] All functions have doctests that pass the automated testing.
• [x] All new algorithms include at least one URL that points to Wikipedia or another similar explanation.
• [x] If this pull request resolves one or more open issues then the description above includes the issue number(s) with a closing keyword: "Fixes #ISSUE-NUMBER".

[meg-1]

Nice Add On!

Thank you, Sanko! @cclauss, if possible, could you please check this pr out and approve a merge? Would be much appreciated :))

[cclauss]

Please add a URL to a Wikipedia article or other source that explains what the algorithm does and why it is useful.

• https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md

[meg-1]

Please add a URL to a Wikipedia article or other source that explains what the algorithm does and why it is useful.

• https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md

Thank you, @cclauss, just did that!

[cclauss]

OK... Now that I know what the algorithm does, why would anyone ever want to use it?

[meg-1]

OK... Now that I know what the algorithm does, why would anyone ever want to use it?

Just added an explanation in the description of this commit:

This algorithm has practical use in scenarios where you need to achieve uniformity across elements of an array under specific constraints and with minimal changes. For example:

resource allocation (this algorithm provides a way to complete the task efficiently) game theory (this algorithm may help in devising fair strategies using minimal moves) signal processing (the algorithm might be applied where signal adjustments are constrained by step size).

And thank you very much for the review, @cclauss , just implemented all recommendations suggested :))