Getting started
The purpose of this guide is to illustrate some of the main features that
cifkit provides. It assumes a very basic knowledge of Python.
cifkit is an open source CIF library that supports supercell generation and
provide tools for high-throuhgput analysis. It also provides various tools for
determining coordination numbers, plotting polyhedrons from each site based on
the coordination numbers, bond fractions, move and copy .cif files based on a
set of attributes, and determine atomic mixing information in 2-3 lines of code.
Installation
Install cifkit via:
You may need to download other dependencies:
gemmi is used for parsing .cif files. pyvista is used for plotting
polyhedrons.
Start with CifEnsemble
cifkit offers a class called CifEnsemble which handles many .cif files in
a high-throuhgput way. You can initialize the object using the folder path
containing .cif files shown below.
from cifkit import CifEnsemble
# Initialize
ensemble = CifEnsemble("tests/data/cif/ensemble_test")
# Initialize including nested files
ensemble = CifEnsemble("tests/data/cif/ensemble_test", add_nested_files=True)
# Folder path
ensemble.cif_folder_path
# "tests/data/cif/ensemble_test"
If you do not have .cif files for testing, cifkit also provides a set of
.cif files accessible.
from cifkit import CifEnsemble, Example
from cifkit import Example
# Initalize with the file path
ensemble = CifEnsemble(Example.ErCoIn_big_folder_path)
Get unique attributes
Use the ensemble object to get unique attributes such as elements, formulas,
etc.
# Unique formulas
ensemble.unique_formulas
# {"EuIr2Ge2", "CeRu2Ge2", "LaRu2Ge2", "Mo"}
# Unique structures
ensemble.unique_structures
# {"CeAl2Ga2", "W"}
# Unique elements
ensemble.unique_elements
# {"La", "Ru", "Ge", "Ir", "Eu", "Ce", "Mo"}
# Unique space group names
ensemble.unique_space_group_names
# {"I4/mmm", "Im-3m"}
# Unique space group numbers
ensemble.unique_space_group_numbers
# {139, 229}
# Unique tags
ensemble.unique_tags
# {"hex", "rt", "rt_hex", ""}
Get distances and supercell size per file
The following computes the size of each supercell and the minimum distance per file.
# Get min distance per file
ensemble.minimum_distances
# [("tests/data/cif/ensemble_test/250709.cif", 2.725),
# ("tests/data/cif/ensemble_test/300171.cif", 2.383),
# ("tests/data/cif/ensemble_test/300170.cif", 2.28)]
# Get supercell size per file
ensemble_test.supercell_atom_counts
# [("tests/data/cif/ensemble_test/250709.cif", 54),
# ("tests/data/cif/ensemble_test/300171.cif", 360),
# ("tests/data/cif/ensemble_test/300170.cif", 360)]
Filter files by attributes
The following returns a set of file paths to each .cif file.
# By formulas
ensemble_test.filter_by_formulas(["LaRu2Ge2"])
ensemble_test.filter_by_formulas(["LaRu2Ge2", "Mo"])
# By structures
ensemble_test.filter_by_structures(["W"])
ensemble_test.filter_by_structures("CeAl2Ga2")
# By space group
ensemble_test.filter_by_space_group_names("Im-3m")
# By space group numbers
ensemble_test.filter_by_space_group_numbers([139])
Move and copy files
Now you have a set of file paths with example below, you can copy and move files to a specific directroy. For high-throuhgout analysis, you might be interested in separating files based on tags, elements, coordination numbers, etc.
file_paths = {
"tests/data/cif/ensemble_test/300169.cif",
"tests/data/cif/ensemble_test/300171.cif",
"tests/data/cif/ensemble_test/300170.cif",
}
# To move files
ensemble.move_cif_files(file_paths, dest_dir_path)
# To copy files
ensemble.copy_cif_files(file_paths, dest_dir_path)
Are you ready?
Now, if you are interested in working with individual .cif files and learn
more about all features in cifkit, let's visit the Example notebooks section
here!