Use KMeans++ For ColorScape Generation #3164
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…ment - Implemented caching using ConcurrentDictionary to store normalized results - Added cache lookup before normalization to improve performance on repeated calls - Changed ToLower() to ToLowerInvariant() for culture-insensitive lowercase conversion - Removed unnecessary string.Empty parameter in Trim() call Performance improvements: - Mean execution time reduced from 231.819 μs to 16.711 μs - Memory allocation reduced from 65019 B to 32 B - GC pressure eliminated (Gen0 collections reduced from 20.5078 to 0) - Passed Unit Tests
- Implemented K-means++ for better initial centroid selection - Parallelize point assignment to nearest centroids - Added early termination when centroids converge - Optimized distance calculations using squared distances - Created benchmark to compare original and optimized versions Benchmark results: - Execution time: 3.58 ms (down from 56.85 ms, 15.86x faster) - Memory allocation: 532.07 KB (down from 97,486.85 KB, 99% reduction) - GC Gen0 collections: 175.7 (down from 31777.7, 99% reduction) Test Cases showed matching results for the optimized function
majora2007
reviewed
Sep 14, 2024
… improvement" This reverts commit 9d52e2c.
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I'll take a look at your enhancements with K means++ clustering, but unfortunately it's too late to include with the initial release of the colorscape system as we have just wrapped up all the testing for the next stable. |
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That's fine, I appreciate you taking a look at least |
majora2007
changed the title
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I tested this and the colors it comes out with is a bit questionable. I've made a lot of tweaks recently wrt Colorscapes so I may need to revisit this and play with the grouping. |
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Changed
Implemented K-means++ for improved initial centroid selection
Parallelized point assignment to nearest centroids
Added early termination when centroids converge
Optimized distance calculations using squared distances
Performance Improvements
Execution time: 15.86x faster (3.58 ms, down from 56.85 ms)
Memory allocation: 99% reduction (532.07 KB, down from 97,486.85 KB)
GC Gen0 collections: 99% reduction (175.7, down from 31777.7)
This Optimizing has passed test cases and returns the same values as the original function ensuring maintained functionality alongside the performance gains.
This enhancements significantly improve the efficiency of parsing through different series, reducing resource usage and improving overall system performance.