6.18. AMBER trajectories — `MDAnalysis.coordinates.TRJ`

AMBER can write ASCII trajectories (“traj”) and binary trajectories (“netcdf”). MDAnalysis supports reading of both formats and writing for the binary trajectories.

Note

Support for AMBER is still somewhat experimental and feedback and contributions are highly appreciated. Use the Issue Tracker or get in touch on the MDAnalysis mailinglist.

Units

AMBER trajectories are assumed to be in the following units:

lengths in Angstrom (Å)
time in ps (but see below)

6.18.1. Binary NetCDF trajectories

The AMBER netcdf format make use of NetCDF (Network Common Data Form) format. Such binary trajectories are recognized in MDAnalysis by the ‘.ncdf’ suffix and read by the NCDFReader.

Binary trajectories can also contain velocities and forces, and can record the exact time step. In principle, the trajectories can be in different units than the AMBER defaults of ångström and picoseconds but at the moment MDAnalysis only supports those and will raise a NotImplementedError if anything else is detected.

class MDAnalysis.coordinates.TRJ.NCDFReader(filename, n_atoms=None, mmap=None, **kwargs)[source]

Reader for AMBER NETCDF format (version 1.0).

AMBER binary trajectories are automatically recognised by the file extension “.ncdf”.

The number of atoms (n_atoms) does not have to be provided as it can be read from the trajectory. The trajectory reader can randomly access frames and therefore supports direct indexing (with 0-based frame indices) and full-feature trajectory iteration, including slicing.

Velocities are autodetected and read into the Timestep._velocities attribute.

Forces are autodetected and read into the Timestep._forces attribute.

Periodic unit cell information is detected and used to populate the Timestep.dimensions attribute. (If no unit cell is available in the trajectory, then Timestep.dimensions will return [0,0,0,0,0,0]).

Current limitations:

only trajectories with time in ps and lengths in Angstroem are processed

The NCDF reader uses scipy.io.netcdf and therefore scipy must be installed. It supports the mmap keyword argument (when reading): mmap=True is memory efficient and directly maps the trajectory on disk to memory (using the mmap); mmap=False may consume large amounts of memory because it loads the whole trajectory into memory but it might be faster. The default is mmap=None and then default behavior of scipy.io.netcdf_file prevails, i.e. True when filename is a file name, False when filename is a file-like object.

See also

NCDFWriter

Changed in version 0.10.0: Added ability to read Forces

Changed in version 0.11.0: Frame labels now 0-based instead of 1-based. kwarg delta renamed to dt, for uniformity with other Readers.

Changed in version 0.17.0: Uses scipy.io.netcdf and supports the mmap kwarg.

Changed in version 0.20.0: Now reads scale_factors for all expected AMBER convention variables. Timestep variables now adhere standard MDAnalysis units, with lengths of angstrom, time of ps, velocity of angstrom/ps and force of kJ/(mol*Angstrom). It is noted that with 0.19.2 and earlier versions, velocities would have often been reported in values of angstrom/AKMA time units instead (Issue #2323).

Changed in version 1.0.0: Support for reading degrees units for cell_angles has now been removed (Issue #2327)

Changed in version 2.0.0: Now use a picklable scipy.io.netcdf_file– NCDFPicklable. Reading of dt now defaults to 1.0 ps if dt cannot be extracted from the first two frames of the trajectory. Writer() now also sets convert_units, velocities, forces and scale_factor information for the NCDFWriter.

Writer(filename, **kwargs)[source]

Returns a NCDFWriter for filename with the same parameters as this NCDF.

All values can be changed through keyword arguments.

Parameters

filename (str) – filename of the output NCDF trajectory
n_atoms (int (optional)) – number of atoms
remarks (str (optional)) – string that is stored in the title field
convert_units (bool (optional)) – True: units are converted to the AMBER base format
velocities (bool (optional)) – Write velocities into the trajectory
forces (bool (optional)) – Write forces into the trajectory
scale_time (float (optional)) – Scale factor for time units
scale_cell_lengths (float (optional)) – Scale factor for cell lengths
scale_cell_angles (float (optional)) – Scale factor for cell angles
scale_coordinates (float (optional)) – Scale factor for coordinates
scale_velocities (float (optional)) – Scale factor for velocities
scale_forces (float (optional)) – Scale factor for forces

Return type

NCDFWriter

close()[source]: Close trajectory; any further access will raise an IOError.

Note

The underlying scipy.io.netcdf module may open netcdf files with mmap if mmap=True was set. Hence any reference to an array must be removed before the file can be closed.

static parse_n_atoms(filename, **kwargs)[source]

Read the coordinate file and deduce the number of atoms

Returns: n_atoms – the number of atoms in the coordinate file
Return type: int
Raises: NotImplementedError – when the number of atoms can’t be deduced

units = {'force': 'kcal/(mol*Angstrom)', 'length': 'Angstrom', 'time': 'ps', 'velocity': 'Angstrom/ps'}: dict with units of of time and length (and velocity, force, … for formats that support it)

class MDAnalysis.coordinates.TRJ.NCDFWriter(filename, n_atoms, remarks=None, convert_units=True, velocities=False, forces=False, scale_time=None, scale_cell_lengths=None, scale_cell_angles=None, scale_coordinates=None, scale_velocities=None, scale_forces=None, **kwargs)[source]

Writer for AMBER NETCDF format (version 1.0).

AMBER binary trajectories are automatically recognised by the file extension “.ncdf” or “.nc”.

Velocities are written out if they are detected in the input Timestep. The trajectories are always written with ångström for the lengths and picoseconds for the time (and hence Å/ps for velocities and kilocalorie/mole/Å for forces).

Scale factor variables for time, velocities, cell lengths, cell angles, coordinates, velocities, or forces can be passed into the writer. If so, they will be written to the NetCDF file. In this case, the trajectory data will be written to the NetCDF file divided by the scale factor value. By default, scale factor variables are not written. The only exception is for velocities, where it is set to 20.455, replicating the default behaviour of AMBER.

Unit cell information is written if available.

Parameters

filename (str) – name of output file
n_atoms (int) – number of atoms in trajectory file
convert_units (bool (optional)) – True: units are converted to the AMBER base format; [True]
velocities (bool (optional)) – Write velocities into the trajectory [False]
forces (bool (optional)) – Write forces into the trajectory [False]
scale_time (float (optional)) – Scale factor for time units [None]
scale_cell_lengths (float (optional)) – Scale factor for cell lengths [None]
scale_cell_angles (float (optional)) – Scale factor for cell angles [None]
scale_coordinates (float (optional)) – Scale factor for coordinates [None]
scale_velocities (float (optional)) – Scale factor for velocities [20.455]
scale_forces (float (optional)) – Scale factor for forces [None]

Note

MDAnalysis uses scipy.io.netcdf to access AMBER files, which are in netcdf 3 format. Although scipy.io.netcdf is very fast at reading these files, it is very slow when writing, and it becomes slower the longer the files are. On the other hand, the netCDF4 package (which requires the compiled netcdf library to be installed) is fast at writing but slow at reading. Therefore, we try to use netCDF4 for writing if available but otherwise fall back to the slower scipy.io.netcdf.

AMBER users might have a hard time getting netCDF4 to work with a conda-based installation (as discussed in Issue #506) because of the way that AMBER itself handles netcdf: When the AMBER environment is loaded, the following can happen when trying to import netCDF4:

>>> import netCDF4
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/scratch2/miniconda/envs/py35/lib/python3.5/site-packages/netCDF4/__init__.py", line 3, in <module>
    from ._netCDF4 import *
ImportError: /scratch2/miniconda/envs/py35/lib/python3.5/site-packages/netCDF4/_netCDF4.cpython-35m-x86_64-linux-gnu.so: undefined symbol: nc_inq_var_fletcher32

The reason for this (figured out via ldd) is that AMBER builds its own NetCDF library that it now inserts into LD_LIBRARY_PATH without the NetCDF4 API and HDF5 bindings. Since the conda version of netCDF4 was built against the full NetCDF package, the one ld tries to link to at runtime (because AMBER requires LD_LIBRARY_PATH) is missing some symbols. Removing AMBER from the environment fixes the import but is not really a convenient solution for users of AMBER.

At the moment there is no obvious solution if one wants to use netCDF4 and AMBER in the same shell session. If you need the fast writing capabilities of netCDF4 then you need to unload your AMBER environment before importing MDAnalysis.

Raises: FutureWarning – When writing. The NCDFWriter currently does not write any scale_factor values for the data variables. Whilst not in breach of the AMBER NetCDF standard, this behaviour differs from that of most AMBER writers, especially for velocities which usually have a scale_factor of 20.455. In MDAnalysis 2.0, the NCDFWriter will enforce scale_factor writing to either match user inputs (either manually defined or via the NCDFReader) or those as written by AmberTools’s sander under default operation.

6.18.2. ASCII TRAJ trajectories

ASCII AMBER TRJ coordinate files (as defined in AMBER TRJ format) are handled by the TRJReader. It is also possible to directly read bzip2 or gzip compressed files.

AMBER ASCII trajectories are recognised by the suffix ‘.trj’, ‘.mdcrd’ or ‘.crdbox (possibly with an additional ‘.gz’ or ‘.bz2’).

Note

In the AMBER community, these trajectories are often saved with the suffix ‘.crd’ but this extension conflicts with the CHARMM CRD format and MDAnalysis will not correctly autodetect AMBER “.crd” trajectories. Instead, explicitly provide the format="TRJ" argument to Universe:

u = MDAnalysis.Universe("top.prmtop", "traj.crd", format="TRJ")

In this way, the AMBER TRJReader is used.

Limitations

Periodic boxes are only stored as box lengths A, B, C in an AMBER trajectory; the reader always assumes that these are orthorhombic boxes.
The trajectory does not contain time information so we simply set the time step to 1 ps (or the user could provide it as kwarg dt)
Trajectories with fewer than 4 atoms probably fail to be read (BUG).
If the trajectory contains exactly one atom then it is always assumed to be non-periodic (for technical reasons).
Velocities are currently not supported as ASCII trajectories.

class MDAnalysis.coordinates.TRJ.TRJReader(filename, n_atoms=None, **kwargs)[source]

AMBER trajectory reader.

Reads the ASCII formatted AMBER TRJ format. Periodic box information is auto-detected.

The number of atoms in a timestep must be provided in the n_atoms keyword because it is not stored in the trajectory header and cannot be reliably autodetected. The constructor raises a ValueError if n_atoms is left at its default value of None.

The length of a timestep is not stored in the trajectory itself but can be set by passing the dt keyword argument to the constructor; it is assumed to be in ps. The default value is 1 ps.

Changed in version 0.11.0: Frames now 0-based instead of 1-based. kwarg delta renamed to dt, for uniformity with other Readers

close()[source]: Close trj trajectory file if it was open.

property n_frames: Number of frames (obtained from reading the whole trajectory).

open_trajectory()[source]: Open the trajectory for reading and load first frame.

units = {'length': 'Angstrom', 'time': 'ps'}: dict with units of of time and length (and velocity, force, … for formats that support it)

6.18. AMBER trajectories — MDAnalysis.coordinates.TRJ

6.18.1. Binary NetCDF trajectories

6.18.2. ASCII TRAJ trajectories

6.18. AMBER trajectories — `MDAnalysis.coordinates.TRJ`