Skip to main content

Approximate the structure factor of a stationary point process, test its hyperuniformity, and identify its class of hyperuniformity.

Project description

structure-factor

CI-tests codecov docs-build docs-page PyPi version Python >=3.7.1,<3.10 Open In Colab

Approximate the structure factor of a stationary point process, test its hyperuniformity, and identify its class of hyperuniformity.

Introduction

structure-factor is an open-source Python project which currently collects

  • various estimators of the structure factor
  • several diagnostics of hyperuniformity

for stationary and isotropic point processes.

Please checkout the documentation for more details.

Dependencies

Installation

structure-factor works with Python >=3.7.1,<3.10.

Once installed it can be called from

  • import structure_factor
  • from structure_factor import ...

Install the project as a dependency

  • Install the latest version published on PyPi version

    # activate your virtual environment an run
    poetry add structure-factor
    # poetry add structure-factor@latest to update if already present
    # pip install --upgrade structure-factor
    
  • Install from source (this may be broken)

    # activate your virtual environment and run
    poetry add git+https://github.com/For-a-few-DPPs-more/structure-factor.git
    # pip install git+https://github.com/For-a-few-DPPs-more/structure-factor.git
    

Install in editable mode and potentially contribute to the project

The package can be installed in editable mode using poetry.

To do this, clone the repository:

  • if you considered forking the repository

    git clone https://github.com/your_user_name/structure-factor.git
    
  • if you have not forked the repository

    git clone https://github.com/For-a-few-DPPs-more/structure-factor.git
    

and install the package in editable mode

cd structure-factor
poetry shell  # to create/activate local .venv (see poetry.toml)
poetry install
# poetry install --no-dev  # to avoid installing the development dependencies
# poetry add -E docs -E notebook  # to install extra dependencies

Documentation

The documentation docs-page is

Build the documentation

If you use poetry

  • install the documentation dependencies (see [tool.poetry.extras] in pyproject.toml)

    cd structure-factor
    poetry shell  # to create/activate local .venv (see poetry.toml)
    poetry install -E docs  # (see [tool.poetry.extras] in pyproject.toml)
    
  • and run

    # cd structure-factor
    # poetry shell  # to create/activate local .venv (see poetry.toml)
    poetry run sphinx-build -b html docs docs/_build/html
    open _build/html/index.html
    

Otherwise, if you don't use poetry

  • install the documentation dependencies (listed in [tool.poetry.extras] in pyproject.toml), and

  • run

    cd structure-factor
    # activate a virtual environment
    pip install '.[notebook]'  # (see [tool.poetry.extras] in pyproject.toml)
    sphinx-build -b html docs docs/_build/html
    open _build/html/index.html
    

Getting started

Documentation

See the documentation docs-page

Notebooks

Jupyter that showcase structure-factor are available in the ./notebooks folder.

How to cite this work

Companion paper

We wrote a companion paper to structure-factor,

On estimating the structure factor of a point process, with applications to hyperuniformity

where we provided rigorous mathematical derivations of the structure factor's estimators of a stationary point process and showcased structure-factor on different point processes. We also contribute a new asymptotically valid statistical test of hyperuniformity. Finally, we compared numerically the accuracy of the estimators.

Citation

If you use structure-factor, please consider citing it with this piece of BibTeX:

@article{HGBLR:22,
  arxivid = {2203.08749},
  journal = {arXiv preprint},
  author  = {Hawat, Diala and Gautier, Guillaume and Bardenet, R{\'{e}}mi and Lachi{\`{e}}ze-Rey, Rapha{\"{e}}l},
  note    = {arXiv: 2203.08749},
  title   = {On estimating the structure factor of a point process, with applications to hyperuniformity},
  year    = {2022},
}

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

structure_factor-2.2.1.tar.gz (3.0 MB view hashes)

Uploaded source

Built Distribution

structure_factor-2.2.1-py3-none-any.whl (3.0 MB view hashes)

Uploaded py3

Supported by

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