Welcome to Atomap’s documentation! — Atomap 0.4.3.dev1 documentation

2025-1-18: Atomap has moved to GitHub
The development of Atomap has moved from https://gitlab.com/atomap/atomap to https://github.com/atomap-dev/atomap. While GitLab has been a good home for Atomap, most of the HyperSpy community is on GitHub. So this move will make collaboration with the rest of the community easier.
2025-1-5: Atomap 0.4.2 released
This is a small release which greatly improves the performance of remove_atoms_from_image_using_2d_gaussian, making it easier to work with large images with multiple sublattices. It also includes several minor style and linting fixes.
Atomap is a Python library for analysing atomic resolution scanning transmission electron microscopy images. It relies in fitting 2-D Gaussian functions to every atomic column in an image, and automatically find all major symmetry axes. The full procedure is explained in the article Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting.
The easiest way to try Atomap is via Binder: introductory Jupyter Notebook. To install Atomap on your own computer, see the install instructions.
Measuring the ellipticity of atomic columns. More info
Mapping the variation in distance between oxygen columns. More information
Atomap is under development and still in alpha, so bugs and errors can be expected. Bug reports and feature requests are welcome on the issue tracker. Contributors are welcome too!
If you publish scientific articles using Atomap, please consider citing the article Atomap: a new software tool for the automated analysis of atomic resolution images using two-dimensional Gaussian fitting. (M. Nord et al, Advanced Structural and Chemical Imaging 2017 3:9)
Atomap is available under the GNU GPL v3 license. The source code is found in the GitHub repository.
2024-10-20: Atomap 0.4.1 released
This is a maintenance release, making Atomap work with NumPy 2.0. It also updates Atomap to use pyproject.toml instead of setup.py.
2024-02-17: Atomap 0.4.0 released
This release is the first to work with the new 2.0.0 version of HyperSpy. The major change is a large improvement in plotting speed, for example sublattice.plot() or sublattice.plot_planes(), thanks to a reimplementation of HyperSpy’s marker functionality. Thanks to Carter Francis for the merge request! There has also been some minor updates of the install instructions, and fixes for deprecation warnings.
2023-11-18: Atomap 0.3.4 released
This release has a large performance improvement for the 2D Gaussian refinement, which is especially noticeable for large images with many atoms. A new parameter, nearest_neighbors, has been added to sublattice.construct_zone_axes: increasing it will give more atomic planes. Note: due to a new API-breaking version of HyperSpy (2.0.0), this Atomap release will be the last which will work with the older HyperSpy versions (1.x.x). Thus, the next releases will only work with HyperSpy 2.0.0 or higher, most users should not notice any differences.
2023-5-17: Atomap 0.3.3 released
This is a small maintenance release, fixing some deprecation warning, style issues, and fixing a plotting bug when visualizing vectors.
2022-4-28: Atomap 0.3.2 released
This is a maintenance release, updating Atomap to work with the newly released HyperSpy 1.7.
2021-6-11: Atomap 0.3.1 released!
This is a small release, with one bug fix from Tom Slater, and two performance improvements from Niels Cautaerts. The latter are related to finding the initial atomic column positions, and will especially improve the processing time for large images.
2021-4-23: Try Atomap without having to install anything, via Binder
Introductory Jupyter Notebook
2021-1-30: Atomap 0.3.0 released!
Information about the 3D structure of Sublattices can now be added, allowing for 3D atomic models to be “converted” into an Atom_Lattice via the Atomic Simulation Environment, and vice versa. This 3D information can be set manually, or via the intensity for homogeneous structures see statistical method and working with atomic models for more info. Thanks to Tom Slater and Eoghan O’Connell for implementing this!
The performance of atomic column integration has been greatly improved, atomap.integrate and Atom_Lattice.integrate_column_intensity will be much faster now. Thanks to Thomas Aarholt!
set_scale() method in Atom_Lattice and Sublattice has been added for easily setting the scale and unit.
Better support for visualizing Atom_Lattice and Sublattice objects with scaled units. Thanks to Eoghan O’Connell for adding this.
2020-1-29: Atomap 0.2.1 released!
New method for getting a pair distribution function, see the documentation for more info. Thanks to Tom Slater for implementing this!
Add a method for getting the local, often high frequency, scanning distortions utilizing the shape of the atomic columns: Quantify scan distortions.
Improved the progressbar when using Atomap in Jupyter Notebooks. Thanks to Alexander Skorikov!
2019-10-17: Atomap 0.2.0 released!
Greatly improved documentation, notebook and several new functions for analysing images with dumbbell features, like Si or GaAs.
New GUI tool for selection a subset of atom positions, making it easier to work on images with several phases.
Statistical quantification using Gaussian mixture model. Thanks to Tom Slater for implementing this!
Functions in the Atom_Position class: calculate_max_intensity() and calculate_min_intensity(). Thanks to Eoghan O’Connell for implementing this!
2019-03-05: Atomap 0.1.4 released!