kim-convergence 0.0.2

kim-convergence designed to help in automatic equilibration detection & run length control.

kim-convergence utility module

How do you automatically estimate the length of the simulation required?

It is desirable to simulate the minimum amount of time necessary to reach an acceptable amount of uncertainty in the quantity of interest.

How do you automatically estimate the length of the warm-up period required?

Welcome to kim-convergence module!

The kim-convergence package is designed to help in automatic equilibration detection & run length control.

Document

!WORK IN PROGRESS!

Installing kim-convergence

Requirements

You need Python 3.7 or later to run kim-convergence. You can have multiple Python versions (2.x and 3.x) installed on the same system without problems.

To install Python 3 for different Linux flavors, macOS and Windows, packages are available at
https://www.python.org/getit/

Using pip

pip is the most popular tool for installing Python packages, and the one included with modern versions of Python.

kim-convergence can be installed with pip:

pip install kim-convergence

Note:

Depending on your Python installation, you may need to use pip3 instead of pip.

pip3 install kim-convergence

Depending on your configuration, you may have to run pip like this:

python3 -m pip install kim-convergence

Using pip (GIT Support)

pip currently supports cloning over git

pip install git+https://github.com/openkim/kim-convergence.git

For more information and examples, see the pip install reference.

Using conda

conda is the package management tool for Anaconda Python installations.

Installing kim-convergence from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge

Once the conda-forge channel has been enabled, kim-convergence can be installed with:

conda install kim-convergence

It is possible to list all of the versions of kim-convergence available on your platform with:

conda search kim-convergence --channel conda-forge

Basic Usage

Copyright

Copyright (c) 2021, Regents of the University of Minnesota.
All Rights Reserved

Contributing

Contributors:
      Yaser Afshar