Artemis: Optimize and Refactor Methods in DoubleForLoop Class for Improved Performance

[mike-turintech]

Overview

This pull request introduces significant optimizations and refactoring to the DoubleForLoop class, focusing on enhancing performance and code readability.

Key Changes

1. Imports Optimization:

   • Added Tuple to the import statement from typing. Note: This addition is currently unused but may be beneficial for future code enhancements.

2. sum_square Method:

   • Replaced the inefficient nested loop with a direct mathematical formula n * (n - 1) * (2 * n - 1) // 6, reducing time complexity from O(n^2) to O(1).

3. sum_triangle Method:

   • Optimized the calculation using the formula n * (n + 1) * (n - 1) // 6, transitioning from O(n^2) to O(1) complexity.

4. count_pairs Method:

   • Utilized a dictionary to efficiently count occurrences, transforming the time complexity from O(n^2) to O(n) by removing nested loops.

5. count_duplicates Method:

   • Implemented set operations for duplicate detection, leveraging set intersection to simplify logic and enhance performance from O(n^2) to O(n).

6. sum_matrix Method:

   • Improved readability by iterating directly over rows and values, maintaining the original time complexity.

Benefits

• Performance Boost: The refactoring reduces computational complexity across several methods, resulting in faster execution times.
• Code Readability: Simplified logic and reduced nested loops enhance code maintainability and understanding.

Conclusion

These updates collectively improve the efficiency and clarity of the DoubleForLoop class, aligning with best practices for performance optimization and code quality.

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Please review the changes and provide feedback or approval for merging into the main branch.