Skip to main content

Efficient random sampling via linear interpolation.

Project description

lintsampler

Efficient random sampling via linear interpolation.

Test Coverage Status Documentation Status License: MIT

When you know densities on the 2 endpoints of 1D interval, or the 4 corners of a 2D rectangle, or generally the $2^k$ vertices of a $k$-dimensional hyperbox (or a series of such hyperboxes, e.g., the cells of a $k$-dimensional grid), linear interpolant sampling provides a technique to draw random samples within the hyperbox. lintsampler provides a Python implementation of this.

See the documentation or the linear interpolant sampling paper for further details.

Documentation

The documentation, including some example notebooks, is available at lintsampler.readthedocs.io/.

Installation

Three ways of installing lintsampler:

  • pip:
pip install lintsampler
  • conda:
conda install -c conda-forge lintsampler
  • Simply cloning this repository.

Attribution

If using lintsampler for a research publication, please cite our paper: link to come.

License

lintsampler is available under the MIT license. See the LICENSE file for specifics.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lintsampler-0.1.3.tar.gz (443.8 kB view hashes)

Uploaded Source

Built Distribution

lintsampler-0.1.3-py3-none-any.whl (13.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page