SLAP2 Viewer GUI

The pySLAP2Viewer is a graphical user interface bundled with slap2-utils that allows interactive inspection and analysis of SLAP2 .dat files and reference stacks.

Overview

The viewer is intended to streamline SLAP2 data inspection and ROI-based trace extraction. Features include:

  • Browse and load .dat files and their associated .meta files

  • Load and overlay 2D or 3D reference stacks (.tif)

  • View ROIs overlaid on reference images

  • Interactively plot calcium or voltage activity traces

  • Inspect ROIs in 3D

Note

CuPy is used to accelerate ΔF/F calculations during trace extraction. SLAP2 acquisitions can exceed 10 kHz sampling rates, and GPU support ensures timely computation of fluorescence signals.

Usage

Once installed via pip, the viewer can be launched from the command line:

pySLAP2Viewer

Alternatively, it can be run manually from within Python:

from slap2_utils.dataviewer.cli import main
main()

Or directly launched if the GitHub repository is cloned:

python slap2_utils/dataviewer/mainWindow.py

Required Inputs

Required:

  • A SLAP2 .dat file (binary data)

  • The associated .meta file in the same directory of the .dat file

Optional:

  • A 2D or 3D reference stack .tif (for ROI overlays)

  • A stimulus log .h5 file (for marking stimulus-aligned traces)

Main Interface

Main GUI interface of SLAP2 viewer

This window provides access to:

  • File selection and metadata display

  • 2D or 3D ROI stack overlay

  • ROI index selection and label display

  • Trace extraction and plotting area

Trace Visualization

Traces of ROI activity
  • Traces are extracted using the ROI geometry stored in the metadata

  • ΔF/F is computed for each trace, with GPU acceleration using CuPy

3D ROI Visualization

3D rendering of ROIs without a reference stack

The 3D ROI viewer allows volumetric inspection of SLAP2-defined ROIs without requiring a reference stack.

Key features:

  • ROIs are rendered as labeled structures in 3D space

  • Useful for evaluating the spatial layout and depth distribution of active regions

  • Mouse interaction allows for zoom, pan, and rotation

  • Visualizes dendritic morphology and branching patterns when ROI geometry is detailed

Note

When no reference stack is provided, ROIs are visualized using only metadata coordinates. This is sufficient for spatial inspection, but anatomical alignment is not available.

Requirements

  • Python 3.9+

  • PyQt6

  • matplotlib

  • vispy

  • numpy

  • CuPy

  • Currently tested only on NVIDIA GPUs with CuPy using pyNeuroTrace

  • Reference stack must match ROI geometry