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structure-factor

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

Introduction

Hyperuniformity is the study of stationary point processes with a sub-Poisson variance of the number of points in a large window. To study the hyperuniformity of a given point process, a common practice in statistical physics is to estimate a spectral measure called the structure factor, the behavior of which around zero is a sign of hyperuniformity. The structure factor of a point process is defined via the Fourier transform of its total correlation function, and a point process is hyperuniform if its structure factor vanishes at zero. This Python toolbox gathers many estimators of the structure factor, along with a numerical test of effective hyperuniformity and a test for identifying the possible hyperuniformity class.


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

Dependencies

  • R programming language, since we call the spatstat R package to estimate the pair correlation function of point processes using spatstat-interface.

  • Python dependencies are listed in the pyproject.toml file. Note that they mostly correspond to the latest version.

    [tool.poetry.dependencies]
    python = ">=3.8,<3.10"
    
    numpy = "^1.20.3"
    scipy = "^1.6.3"
    matplotlib = "^3.4.2"
    pandas = "^1.2.4"
    spatstat-interface = "^0.1.0"
    # spatstat-interface https://github.com/For-a-few-DPPs-more/spatstat-interface requires rpy2 https://rpy2.github.io/
    

Installation

structure-factor works with Python 3.8+.

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
    # pip install 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
    sphinx-build -b html docs docs/_build/html
    open _build/html/index.html
    

Getting started

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

    • if you use poetry

      cd structure-factor
      poetry shell  # to create/activate local .venv (see poetry.toml)
      poetry install -E notebook  # (see [tool.poetry.extras] in pyproject.toml)
      # open a notebook within VSCode for example
      
  • See the documentation docs-page

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