# 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.
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