Slicing trajectories

MDAnalysis trajectories can be indexed to return a Timestep, or sliced to give a FrameIterator.

In [1]: import MDAnalysis as mda

In [2]: from MDAnalysis.tests.datafiles import PSF, DCD

In [3]: u = mda.Universe(PSF, DCD)

In [4]: u.trajectory[4]
Out[4]: < Timestep 4 with unit cell dimensions [ 0.  0.  0. 90. 90. 90.] >

Indexing a trajectory shifts the Universe to point towards that particular frame, updating dynamic data such as Universe.atoms.positions.

Note

The trajectory frame is not read from the MD data. It is the internal index assigned by MDAnalysis.

In [5]: u.trajectory.frame
Out[5]: 4

Creating a FrameIterator by slicing a trajectory does not shift the Universe to a new frame, but iterating over the sliced trajectory will rewind the trajectory back to the first frame.

In [6]: fiter = u.trajectory[10::10]

In [7]: frames = [ts.frame for ts in fiter]

In [8]: print(frames, u.trajectory.frame)
[10, 20, 30, 40, 50, 60, 70, 80, 90] 0

You can also create a sliced trajectory with boolean indexing and fancy indexing. Boolean indexing allows you to select only frames that meet a certain condition, by passing a ndarray with the same length as the original trajectory. Only frames that have a boolean value of True will be in the resulting FrameIterator. For example, to select only the frames of the trajectory with an RMSD under 2 angstrom:

In [9]: from MDAnalysis.analysis import rms

In [10]: protein = u.select_atoms('protein')

In [11]: rmsd = rms.RMSD(protein, protein).run()

In [12]: bools = rmsd.rmsd.T[-1] < 2

In [13]: print(bools)
[ True  True  True  True  True  True  True  True  True  True  True  True
  True  True False False False False False False False False False False
 False False False False False False False False False False False False
 False False False False False False False False False False False False
 False False False False False False False False False False False False
 False False False False False False False False False False False False
 False False False False False False False False False False False False
 False False False False False False False False False False False False
 False False]

In [14]: fiter = u.trajectory[bools]

In [15]: print([ts.frame for ts in fiter])
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]

You can also use fancy indexing to control the order of specific frames.

In [16]: indices = [10, 2, 3, 9, 4, 55, 2]

In [17]: print([ts.frame for ts in u.trajectory[indices]])
[10, 2, 3, 9, 4, 55, 2]

You can even slice a FrameIterator to create a new FrameIterator.

In [18]: print([ts.frame for ts in fiter[::3]])
[0, 3, 6, 9, 12]