pytraj.Trajectory¶

class pytraj.trajectory.trajectory.Trajectory(filename=None, top=None, xyz=None, velocity=None, force=None)¶

Bases: pytraj.trajectory.shared_trajectory.SharedTrajectory

Simple in-memory Trajectory. It has only information about 3D coordinates and unitcells (no time, no velocity, no force, ...)

Parameters:

Parameters:	filename: str, trajectory filename top : Topology xyz: 3D-array if filename is not given, pytraj will construct Trajectory from given Topology and given xyz array.

filename: str, trajectory filename

top : Topology

xyz: 3D-array

if filename is not given, pytraj will construct Trajectory from given Topology and given xyz array.

Examples

>>> import pytraj as pt
>>> from pytraj.testing import get_fn
>>> fn, tn = get_fn('ala3')

>>> # load from filename and topology name
>>> traj = pt.Trajectory(fn, tn)
>>> # load from a list of filenames
>>> traj = pt.Trajectory([fn, fn], tn)

>>> # load from 3D array-like
>>> xyz = traj.xyz
>>> traj_1 = pt.Trajectory(xyz=xyz, top=traj.top)

>>> # get new Trajectory with only CA atoms
>>> traj['@CA'].xyz[:, :, 0]
array([[  3.970048 ,   7.6400076,  10.1610562]])

>>> # iterate
>>> for frame in traj: pass

Attributes

`n_atoms`
`n_frames`
`shape`	(n_frames, n_atoms, 3)
`top`	Topology (having info about atom, residue, ...)
`topology`	Topology (having info about atom, residue, ...)
`unitcells`	return 2D ndarray, shape=(n_frames, 6)
`xyz`	Trajectory’s coordinates, shape=(n_frames, n_frames, 3), dtype=’f8’

Methods

`__call__`(\args, \\*kwd)	shortcut of `iterframe` method
`align_principal_axis`([command])	align principal axis
`append`(other)	other: xyz, Frame, Trajectory, ...
`append_xyz`(xyz)	append 3D numpy array
`autoimage`([command])	perform autoimage
`center`(\args, \\*kwargs)	do centering
`copy`()	return a deep copy of trajectory
`from_iterable`(iterables[, top])	create a new Trajectory from iterable (produce Frame)
`iterframe`([start, stop, step, mask, ...])	iterate trajectory with given frame_indices or given (start, stop, step)
`load`([filename])	load file or files. This is for internal use. User should always use
`rmsfit`(\args, \\*kwd)	do the fitting to reference Frame by rotation and translation
`rotate`([command])	do rotation
`save`([filename, overwrite])
`scale`([command])	do scaling
`strip`(mask)	strip atoms with given mask
`superpose`([mask, ref, ref_mask, ...])	do the fitting to reference Frame by rotation and translation
`transform`(commands[, frame_indices])	apply a series of cpptraj commands to trajectory
`translate`([command])	do translation
`view`(\args, \\*kwargs)
`visualize`(\args, \\*kwargs)	require NGLView

align_principal_axis(command='')¶

align principal axis

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('ala3')[:]
>>> traj = traj.align_principal_axis()

append(other)¶

other: xyz, Frame, Trajectory, ...

Notes

Can not append TrajectoryIterator object since we use Trajectory in TrajectoryIterator class
This method is not well optimized for speed.

Examples

>>> import pytraj as pt
>>> import numpy as np
>>> traj = pt.load_sample_data('tz2')[:]
>>> t0 = pt.Trajectory(top=traj.top)
>>> t0.n_frames
0
>>> f0 = traj[0]
>>> t0.append(f0)
>>> t0.n_frames
1
>>> t0.append(np.array([traj[3].xyz,]))
>>> t0.n_frames
2
>>> t0.append(traj)
>>> t0.n_frames
12
>>> t0.append(traj())
>>> t0.n_frames
22

>>> t1 = pt.Trajectory(top=traj.top)
>>> t1.append(traj)

>>> t2 = pt.Trajectory(top=traj.top)
>>> t2.append(traj.xyz)

append_xyz(xyz)¶

append 3D numpy array

Notes

This method is not well optimized for speed.

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> t0 = pt.Trajectory(top=traj.top)
>>> t0.append_xyz(traj.xyz)
>>> t0.n_frames
10
>>> t0.append_xyz(traj.xyz)
>>> t0.n_frames
20

autoimage(command='')¶

perform autoimage

Returns:	self

Examples

>>> import pytraj as pt; from pytraj.testing import get_fn
>>> t0 = pt.load(*get_fn('tz2'))
>>> t0.top.has_box()
True
>>> t0 = t0.autoimage()

center(*args, **kwargs)¶

do centering

Returns:	self

See also

pytraj.all_actions.center

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('ala3')[:]
>>> traj = traj.center('@CA origin')

copy()¶

return a deep copy of trajectory

Examples

>>> import pytraj as pt
>>> t0 = pt.datafiles.load_rna()[:]
>>> isinstance(t0.copy(), pt.Trajectory)
True

classmethod from_iterable(iterables, top=None)¶

create a new Trajectory from iterable (produce Frame)

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> t0 = pt.Trajectory.from_iterable(traj(3, 8, 2))
>>> from pytraj import pipe
>>> fi = pipe(traj, ['autoimage', 'rms'])
>>> t0 = pt.Trajectory.from_iterable(fi, top=traj.top)
>>> t0.n_frames
10
>>> pt.radgyr(t0)
array([ 18.90953437,  18.93564662,  18.85415458,  18.90994856,
        18.85884218,  18.88551081,  18.9364612 ,  18.89353463,
        18.91772124,  18.87070283])

iterframe(start=0, stop=None, step=1, mask=None, autoimage=False, frame_indices=None, rmsfit=None)¶

iterate trajectory with given frame_indices or given (start, stop, step)

Parameters:

Parameters:	start : int, default 0 stop : {None, int}, default None if None, iterate to final frame step : int, default 1 mask : {None, str}, default None if None, use all atoms. If not None, use given mask autoimage : bool, default False if True, perform autoimage for each frame rmsfit : {None, int, tuple}, default None if not None, perform superpose each Frame to to reference. frame_indices : {None, array-like} if not None, iterate trajectory for given indices. If frame_indices is given, (start, stop, step) will be ignored.

start : int, default 0

stop : {None, int}, default None

if None, iterate to final frame

step : int, default 1

mask : {None, str}, default None

if None, use all atoms. If not None, use given mask

autoimage : bool, default False

if True, perform autoimage for each frame

rmsfit : {None, int, tuple}, default None

if not None, perform superpose each Frame to to reference.

frame_indices : {None, array-like}

if not None, iterate trajectory for given indices. If frame_indices is given, (start, stop, step) will be ignored.

Examples

>>> import pytraj as pt
>>> from pytraj.testing import get_fn
>>> traj = pt.load(*get_fn('tz2'))
>>> for frame in traj.iterframe(0, 8, 2): pass
>>> for frame in traj.iterframe(0, 8, 2, autoimage=True): pass
>>> # use negative index
>>> traj.n_frames
10
>>> fi = traj.iterframe(0, -1, 2, autoimage=True)
>>> fi.n_frames
5
>>> # mask is atom indices
>>> fi = traj.iterframe(0, -1, 2, mask=range(100), autoimage=True)
>>> fi.n_atoms
100

load(filename='')¶

load file or files. This is for internal use. User should always use pytraj.load (or iterload) method

Notes

It’s better to use pytraj.load method

>>> traj = pt.load(fname, tname)
>>> traj.n_atoms
5293

Examples

>>> import pytraj as pt
>>> from pytraj.testing import get_fn
>>> fname, tname = get_fn('tz2')
>>> traj = pt.Trajectory()
>>> traj.top = pt.load_topology(tname)
>>> traj.load(fname)
>>> traj.n_atoms
5293

>>> # from list/tuple
>>> traj.load([fname, fname])
>>> traj.load((fname, fname))

n_atoms¶

n_frames¶

rmsfit(*args, **kwd)¶

do the fitting to reference Frame by rotation and translation

Parameters:

Parameters:	ref : {Frame, int}, default=None (first Frame) Reference mask : str or AtomMask object, default=’*’ (fit all atoms)
Returns:	self

ref : {Frame, int}, default=None (first Frame)

Reference

mask : str or AtomMask object, default=’*’ (fit all atoms)

Returns:

self

Notes

this is alias of superpose

Examples

>>> traj.rmsfit(0) # fit to 1st frame 
>>> traj.rmsfit(-1, '@CA') # fit to last frame using @CA atoms 

rotate(command='')¶

do rotation

Returns:	self

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('ala3')[:]
>>> traj = traj.rotate('@CA x 20')

save(filename='', overwrite=False, **kwd)¶

scale(command='')¶

do scaling

Returns:	self

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('ala3')[:]
>>> traj = traj.scale('@CA x 1.2')

shape¶: (n_frames, n_atoms, 3)

strip(mask)¶

strip atoms with given mask

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data()[:]
>>> traj.n_atoms
34
>>> t0 = traj.strip('!@CA') # keep only CA atoms
>>> isinstance(t0, pt.Trajectory)
True
>>> t0.n_atoms
3

superpose(mask='*', ref=None, ref_mask='', frame_indices=None, mass=False)¶

do the fitting to reference Frame by rotation and translation

Parameters:

Parameters:	mask : str or AtomMask object, default=’’ (fit all atoms) ref* : {Frame object, int, str}, default=None Reference ref_mask : str, default ‘’ if not given, use mask if given, use it mass : bool, default False if True, use mass-weighted frame_indices : array-like, default None, optional if not None, only do fitting for specific frames
Returns:	self

mask : str or AtomMask object, default=’*’ (fit all atoms)

ref : {Frame object, int, str}, default=None

Reference

ref_mask : str, default ‘’

if not given, use mask if given, use it

mass : bool, default False

if True, use mass-weighted

frame_indices : array-like, default None, optional

if not None, only do fitting for specific frames

Returns:

self

Examples

>>> import pytraj as pt
>>> from pytraj.testing import get_fn
>>> traj = pt.load(*get_fn('tz2'))
>>> traj = traj.superpose() # fit to 1st frame
>>> traj = traj.superpose(ref=0) # fit to 1st frame, explitly specify
>>> traj = traj.superpose(ref=-1, mask='@CA') # fit to last frame using @CA atoms

top¶: Topology (having info about atom, residue, ...)

See also

pytraj.Trajectory.topology

topology¶: Topology (having info about atom, residue, ...)

See also

pytraj.Trajectory.topology

transform(commands, frame_indices=None)¶

apply a series of cpptraj commands to trajectory

Returns:	self

Examples

>>> import pytraj as pt
>>> traj = pt.datafiles.load_tz2_ortho()[:]
>>> traj.xyz[0, 0]
array([ 15.55458927,  28.54844856,  17.18908691])
>>> traj = traj.transform(['autoimage', 'center @CA origin', 'translate x 1.2'])
>>> traj.xyz[0, 0]
array([-1.19438073,  8.75046229, -1.82742397])

>>> # which is similiar to below:
>>> traj2 = pt.datafiles.load_tz2_ortho()[:]
>>> traj2.xyz[0, 0] # before transforming
array([ 15.55458927,  28.54844856,  17.18908691])
>>> traj = traj2.autoimage().center('@CA origin').translate('x 1.2')

>>> traj2.xyz[0, 0] # after transforming
array([-1.19438073,  8.75046229, -1.82742397])

translate(command='')¶

do translation

Returns:	self

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('ala3')[:]
>>> traj = traj.translate('@CA x 1.2')

unitcells¶

return 2D ndarray, shape=(n_frames, 6)

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')[:]
>>> traj.unitcells[0]
array([ 35.26277966,  41.84554768,  36.16862953,  90.        ,
        90.        ,  90.        ])

view(*args, **kwargs)¶

visualize(*args, **kwargs)¶

require NGLView

Parameters:	args and kwargs : NGLView’s arguments

xyz¶

Trajectory’s coordinates, shape=(n_frames, n_frames, 3), dtype=’f8’

Examples

>>> import pytraj as pt
>>> traj0 = pt.datafiles.load_ala3()
>>> traj1 = pt.Trajectory(xyz=np.empty((traj0.n_frames, traj0.n_atoms, 3), dtype='f8'), top=traj0.top)
>>> traj1.xyz = traj0.xyz.copy()
>>> # autoconvert from fortran order to c order
>>> xyz = np.asfortranarray(traj0.xyz)
>>> traj1.xyz = xyz