# iacta

**Repository Path**: wuping4321/iacta

## Basic Information

- **Project Name**: iacta
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-01-09
- **Last Updated**: 2026-01-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Automatic Discovery of Chemical Reactions Using Imposed Activation
This repository contains code for the paper: [Automatic Discovery of Chemical Reactions Using Imposed Activation](https://doi.org/10.26434/chemrxiv.13008500.v2). 

Original authors: Cyrille Lavigne, Gabe Gomes, Robert Pollice, Alán Aspuru-Guzik

<img align="center" src="https://github.com/aspuru-guzik-group/iacta/blob/master/repo/TOC.png"/>

## Prerequsites: 

`iacta` needs [`python >= 3.7`](https://www.python.org/downloads/). Before being able to use the repository, you will need to install a few additional programs and packages. First, common packages that are required are `numpy` and `pandas`.

Second, you will need to install [`xtb version >= 6.3.0`](https://xtb-docs.readthedocs.io/en/latest/contents.html). Importantly, by default the `xtb` and `crest` binaries are assumed to be in `$PATH`. If they are not, the path to xtb has to be defined when running `iacta` with the appropriate option.

Third, you will need to install [`openbabel version >= 3.1.1`](https://open-babel.readthedocs.io/en/latest/Installation/install.html) and the associated python bindings. The easiest is to do this is via conda:

```
conda install -c conda-forge openbabel
```

Finally, you also need to install `yaml` and `pyaml`, again easiest to do via conda:

```
conda install -c conda-forge pyyaml
```

Afterwards, simply clone the GitHub repository and installation is complete. 

It is also recommended to define the environment variable `LOCALSCRATCH` before running. This variable should point to a directory to be used for temporary folders and files generated by `iacta`. Since `iacta` generates a lot of them, it is recommended to use a location with fast I/O.


## How to run: 

There are two ways to run `iacta`. The easiest is via `yaml` input files. There are a few example input files for the case studies shown in the paper in the subdirectories of the `test-set` and `other-examples` directories. These input files are used with `rsearch-restart.py` for `iacta` simulations as follows:

```
python3 /path/to/iacta/rsearch-restart.py /path/to/user.yaml -o path/to/output/
```

The second possibility is to use `rsearch.py`. There is one XYZ file in the example input files for the case studies shown in the paper. It can be found in the subdirectory `test-set/Sn2MeI`. The `iacta` search can be initiated as follows:

```
python3 /path/to/iacta/rsearch.py /path/to/initial.xyz 1 2 6.0 -o path/to/output/
```

For more detailed control over the input, please consult the help options `-h` for the `rsearch.py` and `rsearch-restart.py` scripts.


## Analyze output

We also implemented convenient tools to analyze the results generated by `iacta`. They are used as follows:

```
python3 /path/to/iacta/read_reactions.py /path/to/output/
```

This script provides some summary of the reactions discovered and also generates the files `parsed_reactions.csv` and `parsed_species.csv` which provide the most important reactions and species discovered in a comma-separated table together with the path to the directories that contain the corresponding reaction trajectories.


## Questions or Problems?
Please make a GitHub issue and be as clear and descriptive as possible. Feel free to reach out to: gabegomes[AT]cmu[DOT]edu and r[DOT]pollice[AT]rug[DOT]nl.


## License

The contents of the `iacta` repository are provided under the MIT license.


[![DOI](https://zenodo.org/badge/249187129.svg)](https://zenodo.org/badge/latestdoi/249187129)