tmmc-lnpy 0.1.5

Analysis of lnPi results from TMMC simulation

Package to analyze \(\ln \Pi(N)\) data from Transition Matrix Monte Carlo simulation.

Links

• Github repo

• Documentation

Installation

From Source

# * From pip
pip install tmmc-lnpy

# * From conda/mamba
conda install -c wpk-nist tmmc-lnpy

# * From Source
git clone {repo}
cd {repo}

# create needed environment
conda env create -n {optional-name] -f environment.yaml

# activate environment
conda activate {optional-name/lnpy-env (default)}

# install in development mode
pip install -e . --no-deps

# Optionally run tests.  This requires pytest
conda install pytest

pytest -x -v

Quick Intro

Take a look at the basic usage notebook for a quick introduction.

Note that the distribution name tmmc-lnpy is different than the package name lnpy, due to name conflicts on pypi. To load the package in python, do the following:

import lnpy
import lnpy.examples

ref = lnpy.examples("lj_sup")

Credits

This package was created with Cookiecutter and the wpk-nist-gov/cookiecutter-pypackage Project template forked from audreyr/cookiecutter-pypackage.

History

0.1.1 (2022-09-12)

• First release on PyPI.

This software was developed by employees of the National Institute of Standards and Technology (NIST), an agency of the Federal Government. Pursuant to title 17 United States Code Section 105, works of NIST employees are not subject to copyright protection in the United States and are considered to be in the public domain. Permission to freely use, copy, modify, and distribute this software and its documentation without fee is hereby granted, provided that this notice and disclaimer of warranty appears in all copies.

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