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Releases: BelloneLab/pyBer

v0.21

07 Apr 16:53

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Full Changelog: v0.20...v0.21

v0.20

12 Mar 18:17
21c3433

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What's Changed

New Contributors

Full Changelog: fiber_photometry...v0.20

pyBer v0.15 - update

26 Feb 08:53
056e59c

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  • Better stability and new UI design
  • Spatial heatmap

Latest Build

12 Mar 18:08
056e59c

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Latest Build Pre-release
Pre-release

Full Changelog: neuroscience...latest

pyBer v0.1.2 - update

04 Feb 12:00
0b5e8fc

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pyBer is a desktop GUI for fiber photometry processing with a deterministic core pipeline and an interactive QC workflow.

Highlights

  • Supports raw data in .doric, .h5, or .csv
  • Artifact detection with global or adaptive MAD and optional padding, plus manual masking
  • Zero‑phase low‑pass filtering and joint resampling to a target sampling rate
  • Baseline estimation with pybaselines (asls, arpls, airpls)
  • Seven output modes including motion‑corrected dFF and z‑score variants
  • Fitted‑reference motion correction using OLS, Lasso, or robust RLM
  • Export processed traces to CSV or HDF5 with metadata
  • Post‑processing: DIO/behavior alignment, PSTH + heatmap, metrics, group mode

Quick start

conda env create -f environment.yml
python main.py

pyBer v0.1.1 - first public release

23 Jan 14:49
1cef096

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pyBer is a desktop GUI for fiber photometry processing with a deterministic core pipeline and an interactive QC workflow.

Highlights

  • Supports raw data in .doric, .h5 or .csv.
  • Artifact detection with global or adaptive MAD and optional padding, plus manual masking
  • Zero-phase low-pass filtering and joint resampling to a target sampling rate
  • Baseline estimation with pybaselines (asls, arpls, airpls)
  • Seven output modes including motion-corrected dFF and z-score variants
  • Fitted-reference motion correction using OLS, Lasso, or robust RLM
  • Export processed traces to CSV or HDF5 with metadata
  • Post-processing: DIO/behavior alignment, PSTH + heatmap, metrics, group mode

Quick start

conda env create -f environment.yml
python main.py