What’s New in playNano 0.1.0

Release date: 2025-09-17

Welcome to the first public release of playNano! This version introduces a complete workflow for loading, processing, exploring, exporting, and analyzing high-speed AFM (HS-AFM) video data— together with a reproducible provenance model, notebooks, and full documentation.

✨ Highlights

  • AFM data loading & playback from .h5-jpk and .asd files, and from folders containing .spm or .jpk files.

  • Processing pipeline with masks and complete provenance (stack.provenance), storing per-step outputs under keys like step_<n>_<name>.

  • Export & re-import: save to .h5 or .npz and reload later with all stages, masks, and provenance preserved.

  • GUI (PySide6) with manual/auto Z-range and annotations/overlays (timestamps, “RAW” label, scale bar).

  • Exports to OME-TIFF and GIF (optional scale bars) for sharing and presentations.

  • Analysis framework with built-in modules (LoG blobs, DBSCAN/K-Means/X-Means, particle tracking) and pluggable extensions.

  • Documentation & notebooks: Sphinx site (User Guide, API, CLI) and example notebooks.

🧪 Processing & Provenance

  • Sequential filters and masks (e.g., plane removal, row/median alignment, polynomial flattening, Gaussian smoothing).

  • Each step records parameters, timestamps, and environment info in stack.provenance.

  • Intermediate results are snapshotted and ordered as step_<n>_<name> for reliable comparison and debugging.

💾 Export & Re-import

  • Save current stack (data, stages, masks, provenance) to HDF5 (.h5) or NumPy (.npz) bundles.

  • Reload bundles to continue processing or run analyses with full history intact.

  • Export to OME-TIFF for interoperability and GIF for rapid previews.

🖥️ GUI (PySide6)

  • Real-time playback, frame seeking, and snapshot previews.

  • Z-range control: auto or manual min/max for consistent visual scaling across frames.

  • Annotations/overlays: timestamps, “RAW” label, and scale bar can be rendered on top of frames.

  • Dark theme stylesheet for high-contrast analysis.

📊 Analysis Framework

  • Build pipelines from built-in and pluggable modules.

  • Included modules: LoG blob detection, DBSCAN/K-Means/X-Means clustering, and particle tracking.

  • Outputs: labeled masks, per-feature properties (area, min/max/mean, bbox, centroid), and per-frame summaries— tracked in provenance.

🔧 CLI

Use the playnano command to run pipelines headless, export bundles, and create GIFs:

playnano process "path/to/jpk_folder" --channel height_trace \
    --processing-file processing.yaml --export tif,npz,h5 --make-gif