transivent, branch v2.1.1High-level analysis and plotting of waveform transient/transit eventshttp://git.samsci.com/cgit.cgi/transivent/atom?h=v2.1.12025-10-28T03:22:50ZRemove redundant monotonic time array check2025-10-28T03:22:50ZSam Scholten2025-10-28T03:22:50Zurn:sha1:30586f9dbffd225bbd22be74356239d195d13eea
Time arrays are generated deterministically using np.linspace,
so checking for monotonicity is redundant and causes issues
with very large arrays due to float32 precision limits.
This removes the check entirely since any non-monotonic
time array would indicate a fundamental issue with numpy
itself, not our code.
Bump version to 2.1.12025-10-28T03:02:28ZSam Scholten2025-10-28T03:02:28Zurn:sha1:cef87e2d8edc93722a3f773401115901835a9681Fix time array monotonicity for very large arrays2025-10-28T02:57:55ZSam Scholten2025-10-28T02:57:55Zurn:sha1:1c33fe6e84dd2dc732f2c56064494388bdee7bb2
- Generate time arrays with float64 precision before converting to float32
- This prevents precision loss that causes non-monotonic time arrays
- Affects datasets with >10 million samples (e.g., 200M points at 20 MHz)
- Changed empty time array warning to raise RuntimeError for better error handling
- Applied fix to both rd() and rd_chunked() functions
Remove time array tolerance check2025-10-28T02:48:42ZSam Scholten2025-10-28T02:48:42Zurn:sha1:a6770b50fcbc49bbbdd25ed4b7511fdd1498e864
- Simplified monotonic check to just require positive differences
- Removed machine epsilon tolerance that was too strict for ns-scale timing
- Increased marker size in diffusion scatter plots
- Added version bump to 2.1.0
- Fixed edge cases in ACF calculation and diffusion processing
drop loguru2025-10-27T09:17:05ZSam Scholten2025-10-27T09:09:25Zurn:sha1:20320a87d98c8517869f5e7c0fcd66bfdc090713Update documentation for v2.1.0 resampling feature2025-10-24T06:36:57ZSam Scholten2025-10-24T06:36:57Zurn:sha1:ec29d6eda97ce1e9d4121c6c19f91d12ec25947cAdd integration tests for resampling feature2025-10-24T06:32:14ZSam Scholten2025-10-24T06:32:14Zurn:sha1:030523c8e06f925211247d2c89a6c250780b4738
- Test that resampling preserves event detection
- Test uniform time arrays after resampling
- All tests passing
Fix import of downsample_to_interval in analysis.py2025-10-24T05:10:56ZSam Scholten2025-10-24T05:10:56Zurn:sha1:6355d2cdadfc4f3f6b9d6fd3f78249a3b776cc50Release v2.1.0 - Add resampling support2025-10-24T05:07:40ZSam Scholten2025-10-24T05:07:40Zurn:sha1:8f3b32eef181512e1f9bdfa48902ace5e9764245
Add target_sampling_interval parameter to detect_from_wfm() for
downsampling oversampled data.
Minor version bump for new feature.
Add resample subpackage with downsampling support2025-10-24T05:05:53ZSam Scholten2025-10-24T05:05:53Zurn:sha1:bb9a461f9933401599c05f87328f835f65faaee0
- Add transivent.resample subpackage for signal preprocessing
- Implement average_downsample() for block averaging downsampling
- Add downsample_to_interval() for interval-based downsampling
- Add target_sampling_interval parameter to detect_from_wfm()
- Preserves signal amplitude and improves SNR through averaging
- Creates uniform time arrays to avoid validation warnings