.. Contains the formatted docstrings from the analysis modules located in 'mdanalysis/MDAnalysis/analysis', although in some cases the documentation imports functions and docstrings from other files which are also curated to reStructuredText markup. .. module:: MDAnalysis.analysis .. _analysis-label: **************** Analysis modules **************** The :mod:`MDAnalysis.analysis` module provides a wide collection of analysis tools for molecular dynamics trajectories. These modules build upon MDAnalysis core functionality (trajectory I/O, selections, etc.) and are designed both for reuse in research workflows and as examples of using the MDAnalysis API. Each module typically defines an analysis class that follows a standard interface. See the `User Guide Analysis section`_ for interactive examples and additional context. .. _User Guide Analysis section: https://userguide.mdanalysis.org/stable/examples/analysis/README.html Getting started with analysis ============================= General usage pattern --------------------- Most analysis tools are implemented as single classes and follow this usage pattern: #. Import the module (e.g., :mod:`MDAnalysis.analysis.rms`). #. Initialize the analysis class with the required arguments. #. Run the analysis with :meth:`~MDAnalysis.analysis.base.AnalysisBase.run`. #. Access results via the :attr:`~MDAnalysis.analysis.base.AnalysisBase.results` attribute. .. code-block:: python from MDAnalysis.analysis import ExampleAnalysisModule # (e.g. RMSD) analysis_obj = ExampleAnalysisModule.AnalysisClass(universe, ...) analysis_obj.run(start=start_frame, stop=stop_frame, step=step) print(analysis_obj.results) Please see the individual module documentation for any specific caveats and also read and cite the reference papers associated with these algorithms. Using parallelization for analysis tools ---------------------------------------- .. versionadded:: 2.8.0 Many analysis tools (based on :class:`~MDAnalysis.analysis.base.AnalysisBase`) can be :ref:`run in parallel ` using a simple split-apply-combine scheme whereby slices of the trajectory ("split") are analyzed in parallel ("apply" the analysis function) and the data from the parallel executions are "combined" at the end. MDAnalysis supports different :ref:`backends ` for the parallel execution such as :mod:`multiprocessing` or `dask`_ (see :mod:`MDAnalysis.analysis.backends`). As a special case, serial execution is handled by the default ``backend='serial'``, i.e., by default, none of the analysis tools run in parallel and one has to explicitly request parallel execution. Without any additionally installed dependencies, only one parallel backend is supported -- Python :mod:`multiprocessing` (which is available in the Python standard library), which processes each slice of a trajectory by running a separate *process* on a different core of a multi-core CPU. .. _dask: https://dask.org/ .. Note:: Not all analysis tools in MDAnalysis can be parallelized and others have not yet been updated to make use of the :ref:`parallelization framework `, which was introduced in release 2.8.0. MDAnalysis aims to have parallelization enabled for all analysis tools that support it by release 3.0. In order to use parallelization, add ``backend='multiprocessing'`` to the arguments of the :meth:`~MDAnalysis.analysis.base.AnalysisBase.run` method together with ``n_workers=N`` where ``N`` is the number of CPUs that you want to use for parallelization. (You can use ``multiprocessing.cpu_count()`` to get the maximum available number of CPUs on your machine but this may not always lead to the best performance because of computational overheads and the fact that parallel access to a single trajectory file is often a performance bottleneck.) As an example we show how to run an RMSD calculation in parallel: .. code-block:: python import multiprocessing import MDAnalysis as mda from MDAnalysisTests.datafiles import PSF, DCD from MDAnalysis.analysis.rms import RMSD from MDAnalysis.analysis.align import AverageStructure # initialize the universe u = mda.Universe(PSF, DCD) # calculate average structure for reference avg = AverageStructure(mobile=u).run() ref = avg.results.universe # initialize RMSD run rmsd = RMSD(u, ref, select='backbone') rmsd.run(backend='multiprocessing', n_workers=multiprocessing.cpu_count()) Be explicit and specify both ``backend`` and ``n_workers``. Choosing too many workers or using large trajectory frames may lead to an out-of-memory error. You can also implement your own backends -- see :mod:`MDAnalysis.analysis.backends`. .. SeeAlso:: :ref:`parallel-analysis` for technical details Additional dependencies ----------------------- Some of the modules in :mod:`MDAnalysis.analysis` require additional Python packages to enable full functionality. For example, :mod:`MDAnalysis.analysis.encore` provides more options if `scikit-learn`_ is installed. If you installed MDAnalysis with :program:`pip` (see :ref:`installation-instructions`) these packages are *not automatically installed* although one can add the ``[analysis]`` tag to the :program:`pip` command to force their installation. If you installed MDAnalysis with :program:`conda` then a *full set of dependencies* is automatically installed. Other modules require external programs. For instance, the :mod:`MDAnalysis.analysis.hole2` module requires an installation of the HOLE_ suite of programs. You will need to install these external dependencies by following their installation instructions before you can use the corresponding MDAnalysis module. .. _scikit-learn: http://scikit-learn.org/ .. _HOLE: http://www.holeprogram.org/ Building blocks for Analysis ============================ The building block for the analysis modules is :class:`MDAnalysis.analysis.base.AnalysisBase`. To build your own analysis class start by reading the documentation. .. toctree:: :maxdepth: 1 analysis/base analysis/backends analysis/results analysis/parallelization Distances and contacts ====================== .. toctree:: :maxdepth: 1 analysis/align analysis/contacts analysis/distances analysis/atomicdistances analysis/rms analysis/psa analysis/encore analysis/bat Hydrogen bonding ================ .. toctree:: :maxdepth: 1 analysis/hydrogenbonds analysis/hbond_autocorrel analysis/wbridge_analysis Deprecated modules: .. toctree:: :maxdepth: 1 analysis/hbond_autocorrel_deprecated Membranes and membrane proteins =============================== .. toctree:: :maxdepth: 1 analysis/hole2 analysis/leaflet Nucleic acids ============= .. toctree:: :maxdepth: 1 analysis/nuclinfo analysis/nucleicacids Polymers ======== .. toctree:: :maxdepth: 1 analysis/polymer Structure ========= Macromolecules -------------- .. toctree:: :maxdepth: 1 analysis/gnm analysis/helix_analysis analysis/dihedrals analysis/dssp Liquids ------- .. toctree:: :maxdepth: 1 analysis/rdf analysis/msd Volumetric analysis =================== .. toctree:: :maxdepth: 1 analysis/density analysis/lineardensity analysis/waterdynamics analysis/dielectric Dimensionality Reduction ======================== .. toctree:: :maxdepth: 1 analysis/diffusionmap analysis/pca Legacy analysis modules ======================= The :mod:`MDAnalysis.analysis.legacy` module contains code that for a range of reasons is not as well maintained and tested as the other analysis modules. *Use with care.* .. toctree:: :maxdepth: 1 analysis/legacy_modules Data ==== .. toctree:: :maxdepth: 1 analysis/data