ipi 3.3.1

# i-PI: a Universal Force Engine

A Python interface for ab initio path integral molecular dynamics simulations (and more). i-PI is a Python server (that does not need to be compiled and only requires a relatively recent version of Python and Numpy) that applies an algorithm to update the positions of the nuclei. One of many compatible external codes acts as client, and computes the electronic energy and forces.

This is typically a patched version of an electronic structure code, but a simple self-contained Fortran driver that implements several simple interatomic potentials is included for test purposes.

i-PI was originally developed to simulate the quantum mechanical nature of light nuclei by performing path integral molecular dynamics simulations, and it implements most of the state-of-the-art methods to accelerate this kind of calculations. It has since grown to also provide all sorts of simulation strategies, from replica exchange to geometry optimization.

If you use i-PI in your research, please cite the accompanying publication: for version 3, the relevant paper is [Litman et al., _J. Chem. Phys._ 161, 062504 (2024)](https://doi.org/10.1063/5.0215869)

` @article{litman2024ipi, title={i-PI 3.0: a flexible and efficient framework for advanced atomistic simulations}, author={Yair Litman and Venkat Kapil and Yotam M. Y. Feldman and Davide Tisi and Tomislav Begušić and Karen Fidanyan and Guillaume Fraux and Jacob Higer and Matthias Kellner and Tao E. Li and Eszter S. Pós and Elia Stocco and George Trenins and Barak Hirshberg and Mariana Rossi and Michele Ceriotti}, journal = {J. Chem. Phys.}, pages = {062505}, volume = {161}, year = {2024} } `

## Quick Setup

To use i-PI with an existing driver, install and update using pip:

Last version:

`bash python -m pip install git+https://github.com/i-pi/i-pi.git `

Last Release:

`bash pip install -U ipi `

## Documentation

You can find the online documentation at [https://docs.ipi-code.org](https://docs.ipi-code.org/). Alternatively, you can build it locally by following instructions in the docs/README.md file.

## Source installation

To develop i-PI or test it with the self-contained driver, follow these instructions. It is assumed that i-PI will be run from a Linux environment, with a recent version of Python, Numpy and gfortran, and that the terminal is initially in the i-pi package directory (the directory containing this file), which you can obtain by cloning the repository

`bash git clone https://github.com/i-pi/i-pi.git `

Source the environment settings file env.sh as source env.sh or . env.sh. It is useful to put this in your .bashrc or other settings file if you always want to have i-PI available.

## Compile the driver code

The built-in driver requires a FORTRAN compiler, and can be built as

`bash cd drivers/f90 make cd ../.. `

There is also a Python driver available in drivers/py, which however has limited functionalities.

## Examples and demos

The examples and demos folders contain inputs for many different types of calculations based on i-PI. Examples are typically minimal use-cases of specific features, while demos are more structured, tutorial-like examples that show how to realize more complex setups, and also provide a brief discussion of the underlying algorithms.

To run these examples, you should typically start i-PI, redirecting the output to a log file, and then run a couple of instances of the driver code. The progress of the wrapper is followed by monitoring the log file with the tail Linux command.

Optionally, you can make a copy of the directory with the example somewhere else if you want to keep the i-PI directory clean. For example, after sourcing the env.sh file,

`bash cd demos/para-h2-tutorial/tutorial-1/ i-pi tutorial-1.xml > log & i-pi-driver -a localhost -p 31415 -m sg -o 15 & i-pi-driver -a localhost -p 31415 -m sg -o 15 & tail -f log `

The monitoring can be interrupted with CTRL+C when the run has finished (5000 steps).

## Tutorials and online resources

The i-PI [documentation](https://docs.ipi-code.org/onlinereso.html) has a list of available tutorials, recipes and other useful online resources.

## Run the automatic test suite

The automatic test suite is driven by [tox](https://tox.wiki/), a Python automation tool that creates clean, isolated environments to make running tests ad build tasks more reproducible. You can install it with pip install tox). From the repository root, run any of:

` tox -e unit # unit tests tox -e regtests # regression tests (compiles and uses the fortran driver) tox -e examples # smoke-test all input examples `

tox builds a clean environment, installs i-PI plus the required test dependencies, and runs the suite. Run tox list to see all available environments.

See more details in the README file inside the ipi_tests folder.

## Contributing

If you have new features you want to implement into i-PI, your contributions are much welcome. See CONTRIBUTING.md for a brief set of style guidelines and best practices. Before embarking into a substantial project, it might be good to get in touch with the developers, e.g. by opening a wishlist issue.