Metadata-Version: 2.1
Name: spiketraindist
Version: 0.0.1
Summary: Calculate spike train distances
License: Unlicense
Keywords: temporal coding,metric space,dynamic programming,neuroscience,Spike train
Author: matrix-reloaded-zen
Author-email: zen@example.com
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: numba (>=0.60.0,<0.61.0)
Requires-Dist: numpy (>=1.26.0,<2.0.0)
Description-Content-Type: text/markdown

# SpikeTrainDist

SpikeTrainDist is a Python package for calculating spike train distances.
This tool is designed for neuroscientists and researchers working with temporal coding and spike train analysis.

## Features

- Efficient implementation of the Victor-Purpura distance algorithm
- Utilizes [Numba](https://numba.pydata.org/) for performance optimization
- Supports various cost parameters, including special cases for spike count and infinite cost

## Installation

You can install SpikeTrainDist using pip:

```bash
pip install spiketraindist
```

## Usage

Here's a quick example of how to use the Victor-Purpura distance function:

```python
import numpy as np
from spiketraindist import victor_purpura_distance

spike_train_a = np.array([0.1, 0.3, 0.5])
spike_train_b = np.array([0.2, 0.4, 0.6])

distance = victor_purpura_distance(spike_train_a, spike_train_b, cost=1.0)
print(f"The Victor-Purpura distance is: {distance}")
```

## API Reference

### `victor_purpura_distance(spike_train_a, spike_train_b, cost=1.0)`

Computes the Victor-Purpura distance between two spike trains.

Parameters:

- `spike_train_a` (np.ndarray): The first spike train, represented as a 1D numpy array of spike times.
- `spike_train_b` (np.ndarray): The second spike train, represented as a 1D numpy array of spike times.
- `cost` (float, optional): The cost of shifting a spike in time. Default is 1.0.

Returns:

- `distance` (float): The Victor-Purpura distance between the two spike trains.

## Development

To set up the development environment:

1. Clone the repository
2. Install Poetry if you haven't already: `pip install poetry`
3. Install dependencies: `poetry install`
4. Activate the virtual environment: `poetry shell`

### Running Tests

To run the tests, use pytest:

```bash
pytest .
```

### Code Style

This project uses Ruff for code linting. To check your code, run:

```bash
ruff check .
```

## License

This project is licensed under the Unlicense - see the [LICENSE](LICENSE) file for details.

## References

1. J. D. Victor and K. P. Purpura, "Nature and precision of temporal coding in visual cortex: a metric-space analysis," Journal of Neurophysiology, vol. 76, no. 2. American Physiological Society, pp. 1310–1326, Aug. 01, 1996. doi: 10.1152/jn.1996.76.2.1310.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request or open an issue.

