spiketraindist 0.0.1

Calculate spike train distances

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 for performance optimization
• Supports various cost parameters, including special cases for spike count and infinite cost

Installation

You can install SpikeTrainDist using pip:

pip install spiketraindist

Usage

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

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:

pytest .

Code Style

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

ruff check .

License

This project is licensed under the Unlicense - see the 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.