ysa-signal 1.0.1

YSA Signal - Standalone signal analyzer for .brw/.h5 files

YSA Signal

Mac only for now - Windows support coming soon

Standalone signal analyzer for downsampled .brw files

YSA Signal is a simple application for processing and analyzing data from the lab's downsampled .brw files. It uses optimized C++ extensions with HDF5 to quickly process MEA recordings, detect seizures and status epilepticus events, and save the processed data in a compact format for later analysis. The data pipeline is as follows:

  Local Field Potentials recorded on MEA with BrainWave
        │
        ▼
  .brw (HDF5 format that is specific to BrainWave)
        │
        ▼
  ChannelExtract.py (done in the lab to downsample and reformat)
        │
        ▼
  Downsampled .brw (HDF5 format)
        │
        ▼
  YSA Signal (this application)
        │
        ▼
  Processed .h5 (custom HDF5 format with analysis results and mV signal)

Quick Start

0. Installation

Clone the repository and navigate to the directory:

git clone https://github.com/ParrishLab/ysa-signal.git
cd ysa-signal

1. Run the Setup Wizard

The first time you use YSA Signal, run the setup wizard to install dependencies and compile the C++ extensions:

python setup_wizard.py

The wizard will:

• Check your Python version (3.6+ required)
• Install required Python packages (numpy, h5py, pybind11)
• Detect or guide you to install HDF5
• Compile the C++ extensions
• Verify the installation

2. Run the Application

GUI Mode (recommended for most users)

Simply run the application without arguments:

python ysa_signal.py

This launches a graphical interface where you can:

• Select input files (Downsampled .brw)
• Choose whether to perform seizure analysis (default is off for speed)
• Save processed data
• View signals in an interactive plot viewer

CLI Mode (For advanced uses and automation)

Process a file from the command line:

# Process without analysis (default)
python ysa_signal.py input.brw output_processed.h5

# Process with analysis
python ysa_signal.py input.brw output_processed.h5 --do-analysis

Output Format

YSA Signal saves processed data in a custom HDF5 format:

output.h5
├── metadata/
│   ├── sampling_rate (in Hz)
│   ├── num_rec_frames
│   ├── recording_length (in seconds)
│   ├── time_vector (in seconds)
│   ├── active_channels (list of (row, col) tuples)
│   └── original/ (original metadata from .brw)
│       ├── NRecFrames
│       ├── SamplingRate
│       ├── SignalInversion
│       ├── MaxVolt
│       ├── MinVolt
│       └── ... (all original metadata)
└── channels/
    ├── c_1_1/ (row 1, col 1)
    │   ├── signal (raw signal in mV)
    │   ├── SzTimes
    │   ├── SETimes
    │   └── DischargeTimes
    ├── c_1_2/
    │   └── ...
    └── ...

Using in Python Scripts

You can also use YSA Signal's helper functions in your own Python scripts:

from helper_functions import process_and_store, save_processed_data, load_processed_data

# Process a file
processed_data = process_and_store('input.brw', do_analysis=True)

# Save the processed data
save_processed_data(processed_data, 'output_processed.h5')

# Later, load the processed data
loaded_data = load_processed_data('output_processed.h5')

# Access channel data
channel_data = loaded_data.data[row-1, col-1]
signal = channel_data['signal']
sz_times = channel_data['SzTimes']

Requirements

• Python 3.6 or higher
• macOS 12.0 or higher (Monterey or later)
• numpy
• h5py
• pybind11
• HDF5 C++ library

The setup wizard will help you install all of these and verify compatibility.

Testing

YSA Signal includes comprehensive unit tests to ensure reliability. To run the tests:

# Install test dependencies
pip install -r requirements-dev.txt

# Run all tests
pytest

# Run tests with coverage report
pytest --cov=. --cov-report=term

# Run specific test file
pytest tests/test_helper_functions.py -v

Continuous Integration

The project uses GitHub Actions to automatically run tests on every pull request. Tests must pass before merging to main. The CI pipeline:

• Tests on macOS 12 (minimum supported) and latest
• Tests with Python 3.10
• Verifies the setup wizard runs correctly
• Runs all unit tests with coverage reporting

HDF5 Installation

HDF5 is required for reading .brw/.h5 files. The setup wizard will try to detect it automatically, but if it can't find it, you can install it via:

macOS

# Via Homebrew (recommended for most users)
brew install hdf5

# Or via Conda (recommended if using older macOS version like 12.0)
conda install -c conda-forge hdf5

This can come in handy to view hdf5 files: https://myhdf5.hdfgroup.org/

Manual Installation

1. Download from https://github.com/HDFGroup/hdf5/releases
   • Choose the appropriate version for your OS
   • Download the tarball or zip file
2. Extract and install (you should now see an hdf5 directory with bin, include, lib, etc.)
3. Set HDF5_DIR environment variable to the installation path

export HDF5_DIR=/path/to/hdf5

Troubleshooting

"C++ extension not available"

• Run the setup wizard: python setup_wizard.py
• Make sure HDF5 is installed
• Check that pybind11 is installed: pip install pybind11

"Could not find HDF5 installation"

• Install HDF5 using one of the methods above
• Or set the HDF5_DIR environment variable: export HDF5_DIR=/path/to/hdf5
• Run the setup wizard again

Compilation errors

• Make sure you have a C++ compiler installed (gcc/clang on macOS, MSVC on Windows)
• Check that Python development headers are installed
• Try updating pybind11: pip install --upgrade pybind11

License

Copyright © 2025 Jake Cahoon

Support

For issues and questions, please contact [e-mail] or shoot me a text at [phone]