spatstat-interface 0.1.2

Simple Python interface with the spatstat R package using rpy2

spatstat-interface

• spatstat-interface
  • Dependencies
  • Installation
    • Install the project as a dependency
    • Install in editable mode and potentially contribute to the project
      • Using poetry
      • Using pip
  • Documentation
    • Main resources
    • Notes about spatstat
    • Calling functions
      • Calling function.variant
      • Keyword arguments

Simple Python interface with the spatial statistics R package spatstat using rpy2.

Dependencies

• R (programming language),

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

  [tool.poetry.dependencies]
  python = "^3.7.1"
  
  matplotlib = "^3.4.2"
  numpy = "^1.20.3"
  pandas = "^1.2.4"
  rpy2 = "^3.4.5"
  

Installation

You may consider using poetry to manage your whole project as described here https://github.com/guilgautier/template-python-project.

Install the project as a dependency

• Install the latest version published on

  # activate your virtual environment an run
  poetry add spatstat-interface
  # pip install spatstat-interface
  

• Install from source (this may be broken)

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

Install in editable mode and potentially contribute to the project

You may consider forking the repository.

In any case, your can clone the repository

• if you have forked the repository

  git clone https://github.com/your_user_name/spatstat-interface.git
  

• if you have not forked the repository

  git clone https://github.com/For-a-few-DPPs-more/spatstat-interface.git
  

Using poetry

The package can be installed in editable mode along with

• main (non-optional) dependencies, see [tool.poetry.dependencies] in pyproject.toml
• development dependencies, [tool.poetry.dev-dependencies] in pyproject.toml

cd spatstat-interface
# activate your virtual environment or run
# poetry shell  # to create/activate local .venv (see poetry.toml)
poetry install
# poetry install --no-dev  # to avoid installing the development dependencies

Using pip

For now, packages defined only by a pyproject.toml file can't be installed editable mode directly using pip.

Alternatives

1. consider using poetry instead

2. otherwise, for your convenience, the pyproject.toml file was duplicated into a setup.cfg file to enable editable install using pip.

   • modify the [build-system] section in pyproject.toml to

     [build-system]
     requires = ["setuptools >= 40.9.0", "wheel"]
     build-backend = "setuptools.build_meta"
     

   • intstall the project in editable mode

     cd spatstat-interface
     # activate your virtual environment and run
     pip install -e .
     

Documentation

Main resources

• notebooks showcase detailed examples
• rpy2 documentation
• spatstat documentation

Notes about spatstat

The spatstat package has recently been split into multiple sub-packages and extensions.

Using spatstat-interface, sub-packages and extensions are accessible in the following way

from spatstat_interface.interface import SpatstatInterface

spatstat = SpatstatInterface(update=True)
# spatstat.core is None
# spatstat.geom is None

# load/import sub-packages or extensions
spatstat.import_package("core", "geom", update=True)
spatstat.core
spatstat.geom

Calling functions

Calling function.variant

To call the R function.variant

# R code pcf.ppp
spatstat.core::pcf.ppp(X)

Replace . by _ to call function_variant in Python

# Python code pcf_ppp
spatstat.core.pcf_ppp(X)

Keyword arguments

Consider using Python dictionaries to pass keyword arguments. Below are a few examples.

• dot keywords, for example passing var.approx keyword argument won't work in Python

  # R code
  spatstat.core::pcf.ppp(X, kernel="epanechnikov", var.approx=False)
  

  # Python code
  params = {"kernel": "epanechnikov", "var.approx": False}
  spatstat.core.pcf_pp(X, **params)
  

• reserved keywords, for example lambda is a reserved Python keyword; it can't be used as a keyword argument

  # R code
  spatstat.core::dppGauss(lambda=rho, alpha=alpha, d=d)
  

  # Python code
  params = {"lambda": rho, "alpha": alpha, "d": d}
  spatstat.core.dppGauss(**params)