cifkit 1.0.1

Python library for high-throuhgput .cif analysis

cifkit

The documentation is available here: https://bobleesj.github.io/cifkit

cifkit is designed to provide a set of well-organized and fully-tested utility functions for handling large datasets, on the order of tens of thousands, of .cif files.

The current codebase and documentation are actively being improved as of July 3, 2024.

Motivation

Since Summer 2023, I have been developing interactive tools that analyze .cif files. I have identified the following needs:

• Format files at once: .cif files parsed from databases often contain ill-formatted files. We need a tool to standardize, preprocess, and filter out bad files. I also need to copy, move, and sort .cif files based on specific attributes.
• Visualize coordination geometry: We are interested in determining the coordination geometry and the best site in the supercell for analysis in a high-throughput manner. We need to identify the best site for each site label.
• Visualize distribution of files: We want to easily identify and categorize a distribution of underlying .cif files based on supercell size, tags, coordination numbers, elements, etc.

Overview

Designed for individuals with minimal programming experience, cifkit provides two primary objects: Cif and CifEnsemble.

Cif

Cif is initialized with a .cif file path. It parses the .cif file, preprocesses ill-formatted files, generates supercells, and computes nearest neighbors. It also determines coordination numbers using four different methods and generates polyhedrons for each site.

from cifkit import Cif
from cifkit import Example

# Initalize with the example file provided
cif = Cif(Example.Er10Co9In20_file_path)

# Print attributes
print("File name:", cif.file_name)
print("Formula:", cif.formula)
print("Unique element:", cif.unique_elements)

CifEnsemble

CifEnsemble is initialized with a folder path containing .cif files. It identifies unique attributes, such as space groups and elements, across the .cif files, moves and copies files based on these attributes. It generates histograms for all attributes.

from cifkit import CifEnsemble
from cifkit import Example

# Initialize
ensemble = CifEnsemble(Example.ErCoIn_folder_path)

# Get unique attributes
ensemble.unique_formulas
ensemble.unique_structures
ensemble.unique_elements
ensemble.unique_space_group_names
ensemble.unique_space_group_numbers
ensemble.unique_tags
ensemble.minimum_distances
ensemble_test.supercell_atom_counts

Tutorial and documentation

I provide example .cif files that can be easily imported, and you can visit the documentation page here.

Installation

To install

pip install cifkit

You may need to download other dependencies:

pip install cifkit pyvista gemmi

gemmi is used for parsing .cif files. pyvista is used for plotting polyhedrons.

Visuals

Polyhedron

You can visualize the polyhedron generated from each atomic site based on the coordination number geoemtry. In our research, the goal is to map the structure and coordination number with the physical property.

from cifkit import Cif

# Example usage
cif = Cif("your_cif_file_path")
site_labels = cif.site_labels

# Loop through each site
for label in site_labels:
    # Dipslay each polyhedron, a file saved for each
    cif.plot_polyhedron(label, is_displayed=True)

Histograms

You can use CifEnsemble to visualize distributions of file counts based on specific attributes, etc. Learn all features from the documentation provided here.

By formulas:

By structures:

Project using cifkit

• CIF Bond Analyzer (CBA) - extract and visualize bonding patterns - DOI | GitHub

How to ask for help or contribute

cifkit is designed for experimental materials scientists and chemists. If you encounter any issues or have questions, please feel free to reach out via the email listed on my GitHub profile. My goal is to ensure that cifkit is accessible and easy to use for everyone.

Asking for feedback

If cifkit has been useful in your research, you could help me by taking 2-3 seconds to "star" this repository. This helps me identify whether this project is useful for the community and lets others make informed decision.

Contributors

cifkit is made possible with contributions and support from the following individuals:

• Anton Oliynyk: original ideation
• Alex Vtorov: polyhedron, testing
• Danila Shiryaev: testing, bug report
• Fabian Zills (@PythonFZ): Tooling recommendations
• Emil Jaffal (@EmilJaffal): original testing, bug report
• Nikhil Kumar Barua: initial development