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| 1 | +# Performance Optimization Summary |
| 2 | + |
| 3 | +## Quick Summary |
| 4 | + |
| 5 | +This PR implements performance optimizations across the OpenPIV codebase to reduce execution time and memory usage. |
| 6 | + |
| 7 | +## Files Changed |
| 8 | + |
| 9 | +- `openpiv/pyprocess.py` - Vectorized array operations, reduced copies |
| 10 | +- `openpiv/validation.py` - Eliminated unnecessary masked array copies |
| 11 | +- `openpiv/filters.py` - Conditional masked array creation |
| 12 | +- `openpiv/test/test_performance.py` - New performance validation tests (NEW) |
| 13 | +- `PERFORMANCE_IMPROVEMENTS.md` - Detailed documentation (NEW) |
| 14 | + |
| 15 | +## Key Optimizations |
| 16 | + |
| 17 | +1. **Vectorized Operations**: Replaced Python loops and list comprehensions with NumPy operations |
| 18 | +2. **Reduced Array Copies**: Eliminated unnecessary copy operations, especially with masked arrays |
| 19 | +3. **Conditional Conversions**: Only convert dtypes when necessary |
| 20 | +4. **Optimized Border Checking**: Use np.maximum/np.minimum instead of array indexing |
| 21 | + |
| 22 | +## Performance Gains |
| 23 | + |
| 24 | +- `find_all_first_peaks`: Fully vectorized, < 10ms for 100 windows |
| 25 | +- `normalize_intensity`: Conditional conversion, < 50ms for 50 windows |
| 26 | +- `global_std`: No copies for non-masked input, < 10ms for 100x100 arrays |
| 27 | +- `replace_outliers`: Conditional masking, < 100ms for 50x50 arrays |
| 28 | + |
| 29 | +## Testing |
| 30 | + |
| 31 | +✅ All 198 existing tests pass |
| 32 | +✅ 5 new performance tests added |
| 33 | +✅ Total: 203 tests pass in ~8 seconds |
| 34 | +✅ Tutorial scripts verified working |
| 35 | + |
| 36 | +## Backward Compatibility |
| 37 | + |
| 38 | +✅ 100% backward compatible |
| 39 | +- Function signatures unchanged |
| 40 | +- Return types unchanged |
| 41 | +- Numerical results unchanged |
| 42 | + |
| 43 | +## Documentation |
| 44 | + |
| 45 | +See `PERFORMANCE_IMPROVEMENTS.md` for: |
| 46 | +- Detailed before/after code comparisons |
| 47 | +- Performance metrics |
| 48 | +- Future optimization opportunities |
| 49 | +- General optimization principles |
| 50 | + |
| 51 | +## Impact |
| 52 | + |
| 53 | +These optimizations particularly benefit: |
| 54 | +- Large PIV analysis with many interrogation windows |
| 55 | +- Iterative refinement algorithms |
| 56 | +- High-resolution image processing |
| 57 | +- Batch processing workflows |
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