ysa-signal


Nameysa-signal JSON
Version 1.2.15 PyPI version JSON
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home_pageNone
SummaryYSA Signal - Standalone signal analyzer for .brw/.h5 files
upload_time2025-10-09 16:43:49
maintainerNone
docs_urlNone
authorNone
requires_python>=3.6
licenseMIT
keywords signal processing neuroscience electrophysiology mea seizure detection
VCS
bugtrack_url
requirements numpy h5py pybind11 matplotlib
Travis-CI No Travis.
coveralls test coverage 
            # YSA Signal

[![Post-Release Integration Test](https://github.com/ParrishLab/ysa-signal/actions/workflows/post-release-test.yml/badge.svg)](https://github.com/ParrishLab/ysa-signal/actions/workflows/post-release-test.yml)
[![PyPI version](https://badge.fury.io/py/ysa-signal.svg)](https://badge.fury.io/py/ysa-signal)

**Standalone signal analyzer for downsampled .brw files**

YSA Signal processes MEA recordings from downsampled .brw files, detects seizures and status epilepticus events, and saves the results in a compact HDF5 format.

**Supported Platforms**: macOS (Intel & Apple Silicon) • Windows (x64)

## Installation

```bash
pip install ysa-signal
```

## Usage

### GUI Mode

To run the GUI, just run this command after installation:
```bash
ysa-signal
```

The GUI provides two tabs:

- **Process Files**: Select input files, optionally enable seizure analysis, and save processed data
- **View Signals**: Load processed files and view signals in an interactive 64x64 channel grid

### CLI Mode

```bash
# Process without analysis (faster)
ysa-signal input.brw output_processed.h5

# Process with seizure analysis
ysa-signal input.brw output_processed.h5 --do-analysis
```

### Python API

```python
from ysa_signal import process_and_store, save_processed_data, load_processed_data

# Read in downsampled .brw file, process it, and store the results in memory (not on disk on a file)
processed_data = process_and_store('/path/to/file.brw', do_analysis=True)

# Save the processed data to an h5 file (on disk on a file you specify)
save_processed_data(processed_data, '/path/to/file_processed.h5')

# With already processed data saved to an h5 file, you can load it back into memory
loaded_data = load_processed_data('/path/to/file_processed.h5')

# Example: Accessing data for a specific channel (row, col)
row = loaded_data.active_channels[0][0]
col = loaded_data.active_channels[0][1]

# Access the signal and seizure times for the specified channel
channel_data = loaded_data.data[row - 1, col - 1]
signal = channel_data['signal']
sz_times = channel_data['SzTimes']
```

### Batch Processing Example

```python
from ysa_signal import process_and_store, save_processed_data
import glob

for brw_file in glob.glob('data/*.brw'):
    output_file = brw_file.replace('.brw', '_processed.h5')
    processed_data = process_and_store(brw_file, do_analysis=True)
    save_processed_data(processed_data, output_file)
```

## Support

- GitHub: [github.com/ParrishLab/ysa-signal](https://github.com/ParrishLab/ysa-signal/issues)
- Email: jacobbcahoon@gmail.com
- Phone: (385) 307-9925

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    "description": "# YSA Signal\n\n[![Post-Release Integration Test](https://github.com/ParrishLab/ysa-signal/actions/workflows/post-release-test.yml/badge.svg)](https://github.com/ParrishLab/ysa-signal/actions/workflows/post-release-test.yml)\n[![PyPI version](https://badge.fury.io/py/ysa-signal.svg)](https://badge.fury.io/py/ysa-signal)\n\n**Standalone signal analyzer for downsampled .brw files**\n\nYSA Signal processes MEA recordings from downsampled .brw files, detects seizures and status epilepticus events, and saves the results in a compact HDF5 format.\n\n**Supported Platforms**: macOS (Intel & Apple Silicon) \u2022 Windows (x64)\n\n## Installation\n\n```bash\npip install ysa-signal\n```\n\n## Usage\n\n### GUI Mode\n\nTo run the GUI, just run this command after installation:\n```bash\nysa-signal\n```\n\nThe GUI provides two tabs:\n\n- **Process Files**: Select input files, optionally enable seizure analysis, and save processed data\n- **View Signals**: Load processed files and view signals in an interactive 64x64 channel grid\n\n### CLI Mode\n\n```bash\n# Process without analysis (faster)\nysa-signal input.brw output_processed.h5\n\n# Process with seizure analysis\nysa-signal input.brw output_processed.h5 --do-analysis\n```\n\n### Python API\n\n```python\nfrom ysa_signal import process_and_store, save_processed_data, load_processed_data\n\n# Read in downsampled .brw file, process it, and store the results in memory (not on disk on a file)\nprocessed_data = process_and_store('/path/to/file.brw', do_analysis=True)\n\n# Save the processed data to an h5 file (on disk on a file you specify)\nsave_processed_data(processed_data, '/path/to/file_processed.h5')\n\n# With already processed data saved to an h5 file, you can load it back into memory\nloaded_data = load_processed_data('/path/to/file_processed.h5')\n\n# Example: Accessing data for a specific channel (row, col)\nrow = loaded_data.active_channels[0][0]\ncol = loaded_data.active_channels[0][1]\n\n# Access the signal and seizure times for the specified channel\nchannel_data = loaded_data.data[row - 1, col - 1]\nsignal = channel_data['signal']\nsz_times = channel_data['SzTimes']\n```\n\n### Batch Processing Example\n\n```python\nfrom ysa_signal import process_and_store, save_processed_data\nimport glob\n\nfor brw_file in glob.glob('data/*.brw'):\n    output_file = brw_file.replace('.brw', '_processed.h5')\n    processed_data = process_and_store(brw_file, do_analysis=True)\n    save_processed_data(processed_data, output_file)\n```\n\n## Support\n\n- GitHub: [github.com/ParrishLab/ysa-signal](https://github.com/ParrishLab/ysa-signal/issues)\n- Email: jacobbcahoon@gmail.com\n- Phone: (385) 307-9925\n",
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