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UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION MDAnalysis is structured around two fundamental classes: the Universe and the AtomGroup.Almost all code in MDAnalysis begins with Universe, which contains all the information describing a molecular dynamics system.. It has two key properties: atoms: an AtomGroup of the system’s atoms, providing access to important analysis methods(described below)
MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible through 4.2.3. DISTANCE ANALYSIS MDAnalysis.analysis.distances.distance_array (reference, configuration, box=None, result=None, backend='serial') ¶ Calculate all possible distances between a reference set and another configuration. If there are n positions in reference and m positions in configuration, a distance array of shape (n, m) will be computed.. If the optional argument box is supplied, the minimum image MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION MDAnalysis is structured around two fundamental classes: the Universe and the AtomGroup.Almost all code in MDAnalysis begins with Universe, which contains all the information describing a molecular dynamics system.. It has two key properties: atoms: an AtomGroup of the system’s atoms, providing access to important analysis methods(described below)
INSTALLATION QUICK START · MDANALYSIS Installation Quick Start. MDAnalysis offers two methods to install the released version. For most users we recommend the Conda installation method.. Conda. If you don’t have conda installed yet, follow the installation instructions for conda.. To install the lastest stable release with conda do:. conda config --add channels conda-forge condainstall mdanalysis
INSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
UNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. 4.7.3. RADIAL DISTRIBUTION FUNCTIONS 4.7.3.1. Average radial distribution function¶. InterRDF is a tool to calculate average radial distribution functions between two groups of atoms. Suppose we have two AtomGroups A and B. A contains atom A1, A2, and B contains B1, B2.Given A and B to InterRDF, the output will be the average of RDFs between A1 and B1, A1 and B2, A2 and B1, A2 and B2.A typical application is to calculate the RDF 11.1.1. CORE OBJECT: UNIVERSE 11.1.1.1. Classes¶ class MDAnalysis.core.universe.Universe (*args, **kwargs) ¶. The MDAnalysis Universe contains all the information describing the system. The system always requires a topology file — in the simplest case just a list of atoms. This can be a CHARMM/NAMD PSF file or a simple coordinate file with atom informations such as XYZ, PDB, Gromacs GRO, or CHARMM CRD. ATOM SELECTION LANGUAGE The select_atoms() method of a AtomGroup or a Universe returns an AtomGroup.These two methods have different behaviour: while Universe.select_atoms operates on all the atoms in the universe, AtomGroup.select_atoms only operates on the atoms within the original AtomGroup. A single selection phrase always returns an AtomGroup with atoms sorted according to their index in the topology.THE TOPOLOGY SYSTEM
Users will almost never interact directly with a Topology.Modifying atom containers or topology attributes is typically done through Universe.Methods for viewing containers or topology attributes, or for calculating topology object values, are accessed through AtomGroup. 6.21. XTC TRAJECTORY FILES class MDAnalysis.coordinates.XTC.XTCReader (filename, convert_units=True, sub=None, refresh_offsets=False, **kwargs) . Reader for the Gromacs XTC trajectory format. XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. 6.17. AMBER TRAJECTORIES 6.17. AMBER trajectories — MDAnalysis.coordinates.TRJ ¶ AMBER can write ASCII trajectories (“traj”) and binary trajectories (“netcdf”). MDAnalysis supports reading of 6.24. READING TRAJECTORIES FROM MEMORY 1. Overview over MDAnalysis; 2. The topology system; 3. Selection commands; 4. Analysis modules; 5. Topology modules; 6. Coordinates modules. 6.1. Trajectory Readers MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible throughINSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u 3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6UNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. ALL DISTANCES BETWEEN TWO SELECTIONS All distances between two selections¶. Here we use distances.distance_array to quantify the distances between each atom of a target set to each atom in a reference set, and show how we can extend that to calculating the distances between the centers-of-mass of residues.. Last executed: May 18, 2021 with MDAnalysis 1.1.1 Last updated: January 2020 Minimum version of MDAnalysis: 0.19.0 MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible throughINSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u 3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6UNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. ALL DISTANCES BETWEEN TWO SELECTIONS All distances between two selections¶. Here we use distances.distance_array to quantify the distances between each atom of a target set to each atom in a reference set, and show how we can extend that to calculating the distances between the centers-of-mass of residues.. Last executed: May 18, 2021 with MDAnalysis 1.1.1 Last updated: January 2020 Minimum version of MDAnalysis: 0.19.0 INSTALLATION QUICK START · MDANALYSIS Installation Quick Start. MDAnalysis offers two methods to install the released version. For most users we recommend the Conda installation method.. Conda. If you don’t have conda installed yet, follow the installation instructions for conda.. To install the lastest stable release with conda do:. conda config --add channels conda-forge condainstall mdanalysis
INSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
UNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. GUESSING — MDANALYSIS USER GUIDE DOCUMENTATION MDAnalysis can guess if bonds exist between two atoms, based on the distance between them. A bond is created if the 2 atoms are within. d < f ⋅ ( R 1 + R 2) of each other, where R 1 and R 2 are the VdW radii of the atoms and f is an ad-hoc fudge_factor. This is the same algorithm that VMD uses. Angles can be guessed from the bondconnectivity.
11.1.1. CORE OBJECT: UNIVERSE 11.1.1.1. Classes¶ class MDAnalysis.core.universe.Universe (*args, **kwargs) ¶. The MDAnalysis Universe contains all the information describing the system. The system always requires a topology file — in the simplest case just a list of atoms. This can be a CHARMM/NAMD PSF file or a simple coordinate file with atom informations such as XYZ, PDB, Gromacs GRO, or CHARMM CRD. ANALYSING PORE DIMENSIONS WITH HOLE This will create several outputs in your directory: hole1.out: the log file for HOLE.. hole1.sph: a PDB-like file containing the coordinates of the pore centers.. simple2.rad: file of Van der Waals’ radii. run_n/radii_n_m.dat.gz: the profile for each frame. tmp/pdb_name.pdb: the short name of a PDB file with your structure.As hole is a FORTRAN77 program, it is limited in how long of a 6.3. DCD TRAJECTORY I/O 6.3. DCD trajectory I/O — MDAnalysis.coordinates.DCD ¶. Classes to read and write DCD binary trajectories, the format used by CHARMM, NAMD, and also LAMMPS. Trajectories can be read regardless of system-endianness as this is auto-detected. Generally, DCD trajectories produced by any code can be read (with the DCDReader) although there can be 6.24. READING TRAJECTORIES FROM MEMORY 1. Overview over MDAnalysis; 2. The topology system; 3. Selection commands; 4. Analysis modules; 5. Topology modules; 6. Coordinates modules. 6.1. Trajectory Readers 6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. 6.17. AMBER TRAJECTORIES 6.17. AMBER trajectories — MDAnalysis.coordinates.TRJ ¶ AMBER can write ASCII trajectories (“traj”) and binary trajectories (“netcdf”). MDAnalysis supports reading of MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible throughINSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6 UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering.UNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. 6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible throughINSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. ATOM SELECTION LANGUAGE Atom selection language. AtomGroups can be created by selecting atoms using the MDAnalysis atom selection language: The select_atoms () method of a AtomGroup or a Universe returns an AtomGroup. These two methods have different behaviour: while Universe.select_atoms operates on all the atoms in the universe, AtomGroup.select_atoms only operates 6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. INSTALLATION QUICK START · MDANALYSIS Installation Quick Start. MDAnalysis offers two methods to install the released version. For most users we recommend the Conda installation method.. Conda. If you don’t have conda installed yet, follow the installation instructions for conda.. To install the lastest stable release with conda do:. conda config --add channels conda-forge condainstall mdanalysis
3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6INSTALLATION
Installation¶. The latest versions of MDAnalysis can be installed using conda or pip.Currently, the conda releases only support serial calculations. If you plan to use the parallel OpenMP algorithms, you need to install MDAnalysis with pip and have a working OpenMPinstallation.
UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) uUNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. 11.1.1. CORE OBJECT: UNIVERSE 11.1.1.1. Classes¶ class MDAnalysis.core.universe.Universe (*args, **kwargs) ¶. The MDAnalysis Universe contains all the information describing the system. The system always requires a topology file — in the simplest case just a list of atoms. This can be a CHARMM/NAMD PSF file or a simple coordinate file with atom informations such as XYZ, PDB, Gromacs GRO, or CHARMM CRD. EXAMPLES — MDANALYSIS USER GUIDE DOCUMENTATION Examples¶. MDAnalysis maintains a collection of Jupyter notebooks as examples of what the code can do. Each notebook can be downloaded from the source repository to run on your own computer, or viewed as an online tutorial on the user guide. ATOM SELECTION LANGUAGE Atom selection language. AtomGroups can be created by selecting atoms using the MDAnalysis atom selection language: The select_atoms () method of a AtomGroup or a Universe returns an AtomGroup. These two methods have different behaviour: while Universe.select_atoms operates on all the atoms in the universe, AtomGroup.select_atoms only operates 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None 6.24. READING TRAJECTORIES FROM MEMORY 1. Overview over MDAnalysis; 2. The topology system; 3. Selection commands; 4. Analysis modules; 5. Topology modules; 6. Coordinates modules. 6.1. Trajectory Readers MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible through MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6 UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. ATOM SELECTION LANGUAGE Atom selection language. AtomGroups can be created by selecting atoms using the MDAnalysis atom selection language: The select_atoms () method of a AtomGroup or a Universe returns an AtomGroup. These two methods have different behaviour: while Universe.select_atoms operates on all the atoms in the universe, AtomGroup.select_atoms only operates ALL DISTANCES BETWEEN TWO SELECTIONS All distances between two selections¶. Here we use distances.distance_array to quantify the distances between each atom of a target set to each atom in a reference set, and show how we can extend that to calculating the distances between the centers-of-mass of residues.. Last executed: May 18, 2021 with MDAnalysis 1.1.1 Last updated: January 2020 Minimum version of MDAnalysis: 0.19.0 6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB 6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible through MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6 UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. ATOM SELECTION LANGUAGE Atom selection language. AtomGroups can be created by selecting atoms using the MDAnalysis atom selection language: The select_atoms () method of a AtomGroup or a Universe returns an AtomGroup. These two methods have different behaviour: while Universe.select_atoms operates on all the atoms in the universe, AtomGroup.select_atoms only operates ALL DISTANCES BETWEEN TWO SELECTIONS All distances between two selections¶. Here we use distances.distance_array to quantify the distances between each atom of a target set to each atom in a reference set, and show how we can extend that to calculating the distances between the centers-of-mass of residues.. Last executed: May 18, 2021 with MDAnalysis 1.1.1 Last updated: January 2020 Minimum version of MDAnalysis: 0.19.0 6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. INSTALLATION QUICK START · MDANALYSIS Installation Quick Start. MDAnalysis offers two methods to install the released version. For most users we recommend the Conda installation method.. Conda. If you don’t have conda installed yet, follow the installation instructions for conda.. To install the lastest stable release with conda do:. conda config --add channels conda-forge condainstall mdanalysis
3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6UNITS AND CONSTANTS
Units and constants¶. The units of MDAnalysis trajectories are the Å (ångström) for length and ps (picosecond) for time.Regardless of how the original MD format stored the trajectory data, MDAnalysis converts it to MDAnalysis units when reading the data in, and converts back when writing the data out. 11.1.1. CORE OBJECT: UNIVERSE 11.1.1.1. Classes¶ class MDAnalysis.core.universe.Universe (*args, **kwargs) ¶. The MDAnalysis Universe contains all the information describing the system. The system always requires a topology file — in the simplest case just a list of atoms. This can be a CHARMM/NAMD PSF file or a simple coordinate file with atom informations such as XYZ, PDB, Gromacs GRO, or CHARMM CRD. INDEX — MDANALYSIS 1.1.1 DOCUMENTATION BackboneSelection (class in MDAnalysis.core.selection) BaseSelection (class in MDAnalysis.core.selection) bBox (MDAnalysis.topology.tpr.obj.TpxHeader attribute) ATOM SELECTION LANGUAGE Atom selection language. AtomGroups can be created by selecting atoms using the MDAnalysis atom selection language: The select_atoms () method of a AtomGroup or a Universe returns an AtomGroup. These two methods have different behaviour: while Universe.select_atoms operates on all the atoms in the universe, AtomGroup.select_atoms only operates EXAMPLES — MDANALYSIS USER GUIDE DOCUMENTATION Examples¶. MDAnalysis maintains a collection of Jupyter notebooks as examples of what the code can do. Each notebook can be downloaded from the source repository to run on your own computer, or viewed as an online tutorial on the user guide. 4.7.3. RADIAL DISTRIBUTION FUNCTIONS 4.7.3.1. Average radial distribution function¶. InterRDF is a tool to calculate average radial distribution functions between two groups of atoms. Suppose we have two AtomGroups A and B. A contains atom A1, A2, and B contains B1, B2.Given A and B to InterRDF, the output will be the average of RDFs between A1 and B1, A1 and B2, A2 and B1, A2 and B2.A typical application is to calculate the RDF 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None 6.24. READING TRAJECTORIES FROM MEMORY 1. Overview over MDAnalysis; 2. The topology system; 3. Selection commands; 4. Analysis modules; 5. Topology modules; 6. Coordinates modules. 6.1. Trajectory Readers MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB INSTALLATION QUICK START · MDANALYSIS Installation Quick Start. MDAnalysis offers two methods to install the released version. For most users we recommend the Conda installation method.. Conda. If you don’t have conda installed yet, follow the installation instructions for conda.. To install the lastest stable release with conda do:. conda config --add channels conda-forge condainstall mdanalysis
6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible through 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. GUESSING — MDANALYSIS USER GUIDE DOCUMENTATION MDAnalysis can guess if bonds exist between two atoms, based on the distance between them. A bond is created if the 2 atoms are within. d < f ⋅ ( R 1 + R 2) of each other, where R 1 and R 2 are the VdW radii of the atoms and f is an ad-hoc fudge_factor. This is the same algorithm that VMD uses. Angles can be guessed from the bondconnectivity.
EXAMPLES — MDANALYSIS USER GUIDE DOCUMENTATION Examples¶. MDAnalysis maintains a collection of Jupyter notebooks as examples of what the code can do. Each notebook can be downloaded from the source repository to run on your own computer, or viewed as an online tutorial on the user guide. MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITHRUN PYTHON IN JUPYTER NOTEBOOKRUN PYTHON IN JUPYTER NOTEBOOKJUPYTER NOTEBOOK PYTHON 3 8JUPYTER NOTEBOOK PYTHON DOWNLOADJUPYTER NOTEBOOK PYTHON DOWNLOADJUPYTER NOTEBOOK PYTHON TUTORIAL Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. MDANALYSIS · MDANALYSISUSER GUIDEINSTALLATION QUICK STARTUSED BYABOUT MDANALYSISCITATIONSBLOG MDAnalysis is an object-oriented Python library to analyze trajectories from molecular dynamics (MD) simulations in many popular formats.It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools.. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB INSTALLATION QUICK START · MDANALYSIS Installation Quick Start. MDAnalysis offers two methods to install the released version. For most users we recommend the Conda installation method.. Conda. If you don’t have conda installed yet, follow the installation instructions for conda.. To install the lastest stable release with conda do:. conda config --add channels conda-forge condainstall mdanalysis
6.1. TRAJECTORY READERS AND WRITERS 6.1.1. Readers¶. All Readers are based on a ProtoReader class that defines a common Trajectory API and allows other code to interface with all trajectory formats in the same way, independent of the details of the trajectory format itself.. The Universe contains the API entry point attribute Universe.trajectory that points to the actual ProtoReader object; all Readers are accessible through 4.2.3. DISTANCE ANALYSIS 4.2.3. Distance analysis — MDAnalysis.analysis.distances ¶. This module provides functions to rapidly compute distances between atoms or groups of atoms. dist () and between () can take atom groups that do not even have to be from the same Universe. MDAnalysis.analysis.distances.distance_array(reference, configuration, box=None, result=None UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u MDANALYSIS.ANALYSIS.DISTANCES def dist (A, B, offset = 0, box = None): """Return distance between atoms in two atom groups. The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the `offset` keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering. GUESSING — MDANALYSIS USER GUIDE DOCUMENTATION MDAnalysis can guess if bonds exist between two atoms, based on the distance between them. A bond is created if the 2 atoms are within. d < f ⋅ ( R 1 + R 2) of each other, where R 1 and R 2 are the VdW radii of the atoms and f is an ad-hoc fudge_factor. This is the same algorithm that VMD uses. Angles can be guessed from the bondconnectivity.
EXAMPLES — MDANALYSIS USER GUIDE DOCUMENTATION Examples¶. MDAnalysis maintains a collection of Jupyter notebooks as examples of what the code can do. Each notebook can be downloaded from the source repository to run on your own computer, or viewed as an online tutorial on the user guide. MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITHRUN PYTHON IN JUPYTER NOTEBOOKRUN PYTHON IN JUPYTER NOTEBOOKJUPYTER NOTEBOOK PYTHON 3 8JUPYTER NOTEBOOK PYTHON DOWNLOADJUPYTER NOTEBOOK PYTHON DOWNLOADJUPYTER NOTEBOOK PYTHON TUTORIAL Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
6.21. XTC TRAJECTORY FILES XTC is a compressed trajectory format from Gromacs. The trajectory is saved with reduced precision (3 decimal places) compared to other lossless formarts like TRR and DCD. The main advantage of XTC files is that they require significantly less disk space and the loss of precision is usually not a problem. Notes. 3. SELECTION COMMANDS 3.1.4. Geometric¶ around distance selection selects all atoms a certain cutoff away from another selection, e.g. around 3.5 protein selects all atoms not belonging to protein that are within 3.5 Angstroms from the protein sphlayer innerRadius externalRadius selection selects all atoms within a spherical layer centered in the center of geometry (COG) of a given selection, e.g., sphlayer 2.4 6 4.2.3. DISTANCE ANALYSIS MDAnalysis.analysis.distances.distance_array (reference, configuration, box=None, result=None, backend='serial') ¶ Calculate all possible distances between a reference set and another configuration. If there are n positions in reference and m positions in configuration, a distance array of shape (n, m) will be computed.. If the optional argument box is supplied, the minimum image UNIVERSE — MDANALYSIS USER GUIDE DOCUMENTATION A Universe is typically created from a “topology” file, with optional “trajectory” file/s. Trajectory files must have the coordinates in the same order as atoms in the topology. See Formats for the topology and trajectory formats supported by MDAnalysis, and how to load each specific format. u = Universe(topology, trajectory) u INDEX — MDANALYSIS 1.1.1 DOCUMENTATION BackboneSelection (class in MDAnalysis.core.selection) BaseSelection (class in MDAnalysis.core.selection) bBox (MDAnalysis.topology.tpr.obj.TpxHeader attribute) 11.1.1. CORE OBJECT: UNIVERSE 11.1.1.1. Classes¶ class MDAnalysis.core.universe.Universe (*args, **kwargs) ¶. The MDAnalysis Universe contains all the information describing the system. The system always requires a topology file — in the simplest case just a list of atoms. This can be a CHARMM/NAMD PSF file or a simple coordinate file with atom informations such as XYZ, PDB, Gromacs GRO, or CHARMM CRD. 4.2.1. COORDINATE FITTING AND ALIGNMENT 4.2.1. Coordinate fitting and alignment — MDAnalysis.analysis.align . The module contains functions to fit a target structure to a reference structure. They use the fast QCP algorithm to calculate the root mean square distance (RMSD) between two coordinate sets and the rotation matrix R that minimizes the RMSD.
MOLECULAR VISUALIZATION IN THE JUPYTER NOTEBOOK WITH Molecular visualization in the Jupyter Notebook with nglview 14 Mar 2016. nglview is a Python package that makes it easy to visualize molecular systems, including trajectories, directly in the Jupyter Notebook.The recent 0.4.0 release of nglview brings a convenient interface for visualizing MDAnalysis Universe and AtomGroup objectsdirectly:
13.2.1. FAST DISTANCE ARRAY COMPUTATION 13.2.1.2. Functions¶ MDAnalysis.lib.distances.distance_array (reference, configuration, box=None, result=None, backend='serial') Calculate all possible distances between a reference set and another configuration. If there are n positions in reference and m positions in configuration, a distance array of shape (n, m) will be computed.. If the optional argument box is supplied, theTHE TOPOLOGY SYSTEM
The topology system ¶. The topology system. MDAnalysis groups static data about a Universe into its topology. This is typically loaded from a topology file. Topology information falls into 3 categories: Atom containers (Residues and Segments) Atom attributes (e.g. name, mass, bfactor) Topology objects: bonds, angles, dihedrals, impropers. 6.3. DCD TRAJECTORY I/O 6.3. DCD trajectory I/O — MDAnalysis.coordinates.DCD ¶. Classes to read and write DCD binary trajectories, the format used by CHARMM, NAMD, and also LAMMPS. Trajectories can be read regardless of system-endianness as this is auto-detected. Generally, DCD trajectories produced by any code can be read (with the DCDReader) although there can beMDANALYSIS
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It can write most of these formats, too, together with atom selections suitable for visualization or native analysis tools. MDAnalysis allows one to read particle-based trajectories (including individual coordinate frames such as biomolecules in the PDB format) and access the atomic coordinates through NumPy arrays. This provides a flexible and relatively fast framework for complex analysis tasks. In addition, powerful atom selection commands are implemented. Trajectories can also be manipulated (for instance, fit to a reference structure) and written out. The basic example demonstrates some of these features.Read more:
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