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IR.Cai

(c) Jonathan Goodman, Benji Rowlands
2021-2024
[email protected]
University of Cambridge

Overview

This repository contains an implementation of the IR.Cai algorithm described in the paper "Towards automatically verifying chemical structures: the powerful combination of 1H NMR and IR spectroscopy".

The script is contained in cai.py. An example input file, with parameters set to the values used to obtain the results in the paper, is contained in input.txt.

Requirements

  • Operating system: this software has been tested on macOS Sonoma 14.5. It should work on other operating systems, but has not been tested on them.
  • Python version: this software was developed using Python 3.12.

Installation

To run this software, ensure you have Python 3.12 installed along with the following package:

  • matplotlib (version 3.9.0)

To configure the environment correctly, follow the following steps:

  1. Install Python: Ensure you have Python 3.12 installed. You can download it from the official Python website.

  2. Create a virtual environment:

    python3.12 -m venv .venv
source .venv/bin/activate

  3. Activate the virtual environment and install the required package:

    source .venv/bin/activate
pip install matplotlib==3.9.0

Expected install time: less than 1 minute.

Usage

  1. Prepare your input file: The input file should contain sections for settings, experimental data files and calculation data files. Each section should be denoted by tags <Settings>, <Experiments> and <Calculations>, and each section should be closed with a tag of the form </Settings>.

  2. Run the script: Execute the script from the command line with your input file as an argument.

python /path/to/cai.py your_input_file.txt

Example Input File

<Settings>
print_csv spectra scaling_factor summary
minimum_wavenumber 1250
maximum_wavenumber 1600
defined_scaling_factor 0.98
min_scale_factor 0.95
temperature 300
max_scale_factor 1.0
optimise_scaling_factor False
boltzmann_cutoff 20.0
broadening 12
save_path /path/to/your/save/file.csv (optional)
</Settings>

<Experiments>
/path/to/your/experimental/data/file.txt
</Experiments>

<Calculations>
/path/to/your/dir/containing/calculation/files
</Calculations>

Output

The software generates the following outputs:

  • A .log file containing detailed logs of the process.
  • A .csv file with the experimental and calculated spectra data.
  • A graph in .pdf format showing the experimental and calculated spectra.
  • A summary output appended to a specified path.

Example data

Usage of the software can be demonstrated using the molecules from the test set in the paper. All of the necessary files are contained in the Apollo repository. This folder contains its own README detailing how to reproduce the IR.Cai scores from the paper in conjunction with the IR.Cai script. Using the data from this repository, the IR.Cai scores from the paper can be obtained in roughly 10 minutes.

Scripts to reproduce the SCC plots from the paper are also available on GitHub.

Separately, all code and data necessary to reproduce the DP4* results from the paper may also be found on GitHub

Contact

For any questions or issues, please contact Jonathan Goodman at [email protected].