12 Dec 2024
We are thrilled to announce that MDAnalysis has been awarded a Small Development Grant by NumFocus to enhance scientific molecular rendering with MolecularNodes in 2025. This initiative is a collaborative effort between Yuxuan Zhuang and Brady Johnston.
MolecularNodes facilitates the seamless import and visualization of structural biology data within Blender, leveraging Blender’s industry-leading visualization and animation tools. Molecular Nodes has garnered widespread excitement among scientists for its ability to create stunning and informative molecular visualizations. The current version of Molecular Nodes has an under-developed scripting interface, inhibiting the potential for automated molecular rendering. Our project aims to address these limtiations by developing a robust API, enabling users to render molecular structures with straightforward and customizable code.
Project Overview
The development will proceed in three key stages:
-
API Development: We will create a stable API for Molecular Nodes, empowering users to automate molecular rendering with minimal effort.
-
Interactive Jupyter Integration: A Jupyter widget will be built to integrate with MDAnalysis, providing an interactive environment for controlling and rendering molecular objects directly within notebooks via Blender.
-
Advanced Visualization Tools: We will develop tools for visualizing basic geometric features and even complex analysis results from MDAnalysis.
Be Part of the Process!
We invite you to join our Discord channel to share your ideas and feedback as we build these tools. If you’d like to be a beta user, let us know—-your input will help shape the future of Molecular Nodes! Stay tuned for updates and sneak peeks of our progress.
Thank you to NumFocus for supporting this exciting project!
22 Nov 2024
We are happy to release version 2.8.0 of MDAnalysis!
This is a minor release of the MDAnalysis library, which means that it
contains enhancements, bug fixes, deprecations, and other
backwards-compatible changes.
However, in this case minor does not quite do justice to what is
happening in this release, given that we have (at least) three big
changes/additions:
- The license was changed to the GNU
Lesser General Public License so that MDAnalysis can be used by
packages under any license while keeping the source code itself
free and protected.
-
We introduce the Guesser API for
guessing missing topology attributes such as element or mass in a
context-dependent manner. Until release 3.0, you should not
notice any differences but under the hood we are getting ready to
make it easier to work with simulations in a different context
(e.g., with the MARTINI force field or experimental PDB
files). With consistent attributes, such as elements, it becomes a
lot easier to interface with tools like the cheminformatics RDKit
(via the converters).
The guessers are the GSoC 2022 project of @aya9aladdin with
help from @lilyminium, @IAlibay, and @jbarnoud.
-
We are introducing parallel analysis for tools in
MDAnalysis.analysis following the simple
split-apply-combine paradigm that we originally prototyped in
PMDA . What’s really exciting is that any analysis code
that is based on MDAnalysis.analysis.base.AnalysisBase can
enable parallelization with a few lines of extra code—all the
hard work is done behind the scenes in the base class (in a way
that is fully backwards compatible!).
This new feature is the work of @marinegor who brought his
GSoC 2023 project to completion, with great contributions by
@p-j-smith, @yuxuanzhuang and @RMeli .
Not all MDAnalysis analysis classes have parallelization enabled
yet but @talagayev has been working tirelessly on already updating
GNMAnalysis, BAT, Dihedral, Ramachandran, Janin, DSSP
(yes, MDAnalysis has finally got DSSP, based on pydssp, also
thanks to @marinegor), HydrogenBondAnalysis, in addition to
RMSD.
Read on for more details on the license change and the usual
information on supported environments,
upgrading your version of MDAnalysis, and a
summary of the most important changes.
License change to LGPL
This is the first release of MDAnalysis under the Lesser General
Public License. We have been working towards this license change for
the last 3 years; this release (almost) concludes the process that we
described in our licensing update blog post.
-
All code is now under LGPLv2.1
license
or any higher version.
- The package is under the LGPLv3
license or any higher
version. However, once we have removed dependencies that prevent
licensing under LGPLv2.1+ at the moment, we will also license the
package under the same LGPLv2.1+ as the code itself.
We would like to thank all our contributors who granted us permission to
change the license. We would also like to thank a number of
institutions who were especially supportive of our open source
efforts, namely Arizona State University, Australian National
University, Johns Hopkins University, and the Open Molecular Science
Foundation. We are also grateful to NumFOCUS for legal
support. The relicensing team was lead by @IAlibay and @orbeckst.
Supported environments
The minimum required NumPy version is 1.23.3; MDAnalysis now builds
against NumPy 2.0.
Supported Python versions: 3.10, 3.11, 3.12, 3.13. Support for version
3.13 has been added in this release and support for 3.9 has been
dropped (following SPEC 0).
Please note that Python 3.13 is limited to PyPi for now, the conda-forge channel installs only provide support for Python 3.10 to 3.12.
Supported Operating Systems:
Upgrading to MDAnalysis version 2.8.0
To update with mamba (or conda) from the conda-forge channel run
mamba update -c conda-forge mdanalysis
To update from PyPi with pip run
python -m pip install --upgrade MDAnalysis
For more help with installation see the installation instructions in the User Guide.
Make sure you are using a Python version compatible with MDAnalysis
before upgrading (Python >= 3.10).
Notable changes
For a full list of changes, bugfixes and deprecations see the CHANGELOG.
Enhancements:
- Added
guess_TopologyAttrs() API to the Universe to handle attribute
guessing (PR #3753)
- Added the
DefaultGuesser class, which is a general-purpose guesser with
the same functionalities as the existing guesser.py methods (PR #3753)
- Introduce parallelization API to
AnalysisBase and to analysis.rms.RMSD class
(Issue #4158, PR #4304)
- Add
analysis.DSSP module for protein secondary structure assignment, based on pydssp
- Improved performance of PDBWriter (Issue #2785, PR #4472)
- Added parsing of arbitrary columns of the LAMMPS dump parser. (Issue #3504)
- Implement average structures with iterative algorithm from
DOI 10.1021/acs.jpcb.7b11988. (Issue #2039, PR #4524)
- Add support for TPR files produced by Gromacs 2024.1 (PR #4523)
Fixes:
- Fix Bohrium (Bh) atomic mass in tables.py (PR #3753)
- Catch higher dimensional indexing in GroupBase & ComponentBase (Issue #4647)
- Do not raise an Error reading H5MD files with datasets like
observables/<particle>/<property> (part of Issue #4598, PR #4615)
- Fix failure in double-serialization of TextIOPicklable file reader.
(Issue #3723, PR #3722)
- Fix failure to preserve modification of coordinates after serialization,
e.g. with transformations
(Issue #4633, PR #3722)
- Fix PSFParser error when encountering string-like resids
(Issue #2053, Issue #4189 PR #4582)
- Convert openmm Quantity to raw value for KE and PE in OpenMMSimulationReader.
- Atomname methods can handle empty groups (Issue #2879, PR #4529)
- Fix bug in PCA preventing use of
frames=... syntax (PR #4423)
- Fix
analysis/diffusionmap.py iteration through trajectory to iteration
over self._sliced_trajectory, hence supporting
DistanceMatrix.run(frames=...) (PR #4433)
Changes:
- Relicense code contributions from GPLv2+ to LGPLv2.1+
and the package from GPLv3+ to LGPLv3+ (PR #4794)
- only use distopia < 0.3.0 due to API changes (Issue #4739)
- The
fetch_mmtf method has been removed as the REST API service
for MMTF files has ceased to exist (Issue #4634)
- MDAnalysis now builds against numpy 2.0 rather than the
minimum supported numpy version (PR #4620)
Deprecations:
- Deprecations of old guessing functionality (in favor of the new
Guesser API)
-
MDAnalysis.topology.guessers is deprecated in favour of the new
Guessers API and will be removed in version 3.0 (PR #4752)
- The
guess_bonds, vdwradii, fudge_factor, and lower_bound
kwargs are deprecated for bond guessing during Universe
creation. Instead, pass ("bonds", "angles", "dihedrals") into
to_guess or force_guess during Universe creation, and the
associated vdwradii, fudge_factor, and lower_bound kwargs
into Guesser creation. Alternatively, if vdwradii,
fudge_factor, and lower_bound are passed into
Universe.guess_TopologyAttrs, they will override the previous
values of those kwargs. (Issue #4756, PR #4757)
-
MDAnalysis.topology.tables is deprecated in favour of
MDAnalysis.guesser.tables and will be removed in version 3.0 (PR #4752)
- Element guessing in the
ITPParser is deprecated and will be removed in version 3.0
(Issue #4698)
-
Unknown masses are still set to 0.0 for current version, this
will be changed in version 3.0.0 and replaced by
Masses “no_value_label” attribute (np.nan) (PR #3753)
-
A number of analysis modules have been moved into their own
MDAKits, following the 3.0 roadmap towards a trimmed down core
library. Until release 3.0, these modules are still
available through MDAnalysis.analysis (either as an import of the
MDAKit as an automatically installed dependency of the MDAnalysis
package or as the original code) but from 3.0 onwards, users must
install the MDAKit explicitly and then import it by themselves.
- The
MDAnalysis.analysis.encore module has been deprecated in
favour of the mdaencore MDAKit and will be removed in version
3.0.0 (PR #4737)
- The
MDAnalysis.analysis.waterdynamics module has been deprecated in favour
of the waterdynamics MDAKit and will be removed in version 3.0.0 (PR #4404)
- The
MDAnalysis.analysis.psa module has been deprecated in favour of
the PathSimAnalysis MDAKit and will be removed in version 3.0.0
(PR #4403)
- The MMTF Reader is deprecated and will be removed in version 3.0 as
the MMTF format is no longer supported (Issue #4634).
Author statistics
This release was the work of 22 contributors, 10 of which are new contributors.
Our new contributors are:
Acknowledgements
MDAnalysis thanks NumFOCUS for its continued support as our fiscal sponsor and
the Chan Zuckerberg Initiative for supporting MDAnalysis under EOSS4 and EOSS5 awards.
— @IAlibay (release manager) on behalf of the MDAnalysis Team
03 Nov 2024
Have you ever wanted to analyze sub-picosecond dynamics in your trajectories? Trajectory file sizes too large? Want to sync up your analysis and trajectory production? Lucky for you MDAnalysis, in conjunction with Arizona State University (ASU) and with the support of a CSSI Elements grant from the National Science Foundation, is holding a free, online developer workshop focused on streaming and inline analysis of molecular simulations on December 4th 2024.
The general idea of streaming, just like with Netflix, is to transfer data piece-by-piece as needed instead of transferring entire files. In our case, the data generated during a running simulation is transmitted to MDAnalysis for processing without ever being stored on disk.
Our streaming interface is built on top of the TCP/IP socket protocol and can transmit data between distinct processes: A) on the same computer; B) on different computers in a local network; C) via the internet.
This allows analyzing MD simulation trajectories live while they are being generated. As a result, the streaming interface allows analyzing data at femtosecond-scale time intervals which would create massive trajectories and slow down the simulation engine if written to disk.
This online workshop is intended to introduce participants to streaming of trajectories directly from simulation engines, inline analysis
of simulations, and all the awesome science you can do with streaming. This workshop is suitable for students, developers, and researchers in the broad area of computational (bio)chemistry, materials science, and chemical engineering. It is designed for those who have some familiarity with MDAnalysis and are comfortable working with Python, Jupyter
Notebooks and a molecular simulation engine such as LAMMPS, GROMACS or NAMD.
Workshop Overview
The program will run from 8:00 am to 12:00 pm Pacific time on Wednesday, December 4th.
In the workshop, we will focus on contextualizing MD streaming, showing you some of its use cases from working as basic connective tissue to advanced, high-time-resolution analyses, and getting your hands dirty with streaming in a live-coding activity in an easy-to-use workshop environment.
| Topic |
Duration |
| 👋 Welcome |
5 min |
| 📦 MDAnalysis mission & ecosystem |
15 min |
| 🖼️ Streaming: big picture |
15 min |
| 👀 Streaming: first look |
10 min |
| ❓ Q&A: Streaming overview |
5 min |
| 📦Streaming: MD packages, IMDClient |
15 min |
| 👀 Demo: Multiple analyses on NAMD simulation stream |
10 min |
| 💤 Break |
10 min |
| 🎯Activity: Write your own stream analysis |
40 min |
| 📦 Streaming: MDAnalysis functionality |
10 min |
| ❓Q&A: Streaming with MDAnalysis |
5 min |
| 👀 Application: Velocity correlation functions and 2PT |
10 min |
| 👀 Application: Ion channel permeation |
10 min |
| ❓ Q&A: Applications |
5 min |
| 🔮 Future direction |
5 min |
| 📖 Open Forum |
20 min |
| 🚪 Closing |
5 min |
Registration
Attendance at this workshop will be free, and we encourage anyone with an interest in attending to register below.
Register
Workshop materials
All materials are made available in the github.com/MDAnalysis/imd-workshop-2024 repository.
Prepare for the interactive workshop activities by following the set-up instructions.
If you have any questions or special requests related to this workshop, you may contact the organizing committee.