tsdistances 0.0.4

tsdistances is a Python library (with Rust backend) for computing various pairwise distances between sets of time series data. It provides efficient implementations of elastic distance measures such as Dynamic Time Warping (DTW), Longest Common Subsequence (LCSS), and Time Warping Edit (TWE). The library is designed to be fast and scalable, leveraging parallel computation for improved performance.

tsdistances

tsdistances is a Python library (with Rust backend) for computing various pairwise distances between sets of time series data. It provides efficient implementations of elastic distance measures such as Dynamic Time Warping (DTW), Longest Common Subsequence (LCSS), and Time Warping Edit (TWE), etc. The library is designed to be fast and scalable, leveraging parallel computation for improved performance.

Installation

Source

You can install tsdistances from source:

$ git clone https://github.com/albertoazzari/tsdistances/
$ cd tsdistances
$ python -m venv .venv
$ source .venv/bin/activate
$ pip install maturin
$ maturin develop --release

PIP

If you use pip, you can install tsdistances with:

pip install tsdistances

Usage

import numpy as np
import tsdistances

# Example usage of computing DTW distance
x1 = np.array([
    [1.0, 2.0, 3.0],
    [4.0, 5.0, 6.0]
])

x2 = np.array([
    [7.0, 8.0, 9.0],
    [10.0, 11.0, 12.0]
])

# Compute DTW distance
result = tsdistances.dtw(x1, x2, n_jobs=4)
print(result)