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ABF Analytics

A desktop application for analyzing ABF (Axon Binary Format) electrophysiology data files. Built with Rust and the Iced GUI framework.

Features

  • Raw Signal Visualization — View multi-channel voltage/current recordings with pan and zoom controls
  • Peak Detection — Detect and highlight signal peaks with adjustable sensitivity
  • Fourier Transform (FFT) Analysis — Frequency-domain analysis with optional smoothing and peak-only mode
  • Custom Sine Wave Overlay — Overlay user-defined sine waves (frequency, amplitude, phase) on the FFT view for comparison
  • Signal Reconstruction — Reconstruct signals from selected sine wave components with an adjustable vertical offset
  • Channel Selection — Toggle individual channels on/off during viewing and analysis

Requirements

  • Rust 1.85 or later (edition 2024 used by the abf_reader sub-crate)
  • A GPU with Vulkan, Metal, or DX12 support (required by the wgpu backend of Iced)

Building

git clone https://github.com/Ciwiruk/abf_analytics.git
cd abf_analytics
cargo build --release

The compiled binary will be placed in target/release/abf_analytics.

Usage

Run the application:

cargo run --release
  1. On the start screen, type the path to your .abf file (or use the Open File button) and click Load.
  2. Select which channels to display and click Confirm.
  3. Use the View screen to browse the raw signal; pan left/right, adjust the time window, and change the graph height.
  4. Switch to the Analytics screen to run peak detection or FFT analysis on the selected channels.

Project Structure

abf_analytics/
├── src/
│   └── main.rs          # GUI application (Iced)
├── abf_reader/
│   └── src/lib.rs       # ABF v1 file format parser
├── Cargo.toml           # Workspace / application manifest
└── Cargo.lock

License

This project is licensed under the MIT License. See LICENSE for details.