Frequently Asked Questions ¶

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Frequently Asked Questions

Why do most of examples use `pytraj.iterload` instead of `pytraj.load`¶

Because we encourage user to use out-of-core calculation for memory saving. Most of the time we don’t need change trajecotry’s coordinate, so it’s OK to just use immutable trajectory.

So does not `pytraj` support much for in-memory calculation?¶

Yes, pytraj does support in-memory calculation very well. Just consider pytraj.Trajectory as a mutable Python’s list and pytraj.TrajectoryIterator as immutable Python’s tuple.

The difference between `traj[1:11:2]` and `traj(1, 11, 2)`?¶

traj[1:11:2] returns a new pytraj.Trajectory while traj(1, 11, 2) returns a FrameIterator for lazy loading. You can use both for analysis.

In [1]: import pytraj as pt

In [2]: traj = pt.iterload('tz2.nc', 'tz2.parm7')

In [3]: traj[1:11:2]
Out[3]: 
pytraj.Trajectory, 5 frames: 
Size: 0.000025 (GB)
<Topology: 223 atoms, 13 residues, 1 mols, non-PBC>
           

In [4]: pt.radgyr(traj[1:11:2])
Out[4]: array([ 9.5746,  9.9404,  8.9159,  8.0262,  8.6852])

In [5]: traj(1, 11, 2)
Out[5]: 
<FrameIterator with start=1, stop=11, step=2, n_frames=5, 
frame_indices=None, 
mask=None, autoimage=False, rmsfit=None, copy=False> 

In [6]: pt.radgyr(traj(1, 11, 2))
Out[6]: array([ 9.5746,  9.9404,  8.9159,  8.0262,  8.6852])

It’s too slow to convert Frame.xyz to numpy array, about 3 us for only 10 atom-Frame ¶

It’s constant time to cast to numpy array. It takes similar time to cast from 1 million-atom Frame too. This is not problem since you only need cast once without making extra data copying.

What’s the idiom to load data to memory for specific atoms?¶

In [7]: import pytraj as pt

In [8]: traj = pt.iterload('tz2.nc', 'tz2.parm7')

In [9]: traj
Out[9]: 
pytraj.TrajectoryIterator, 101 frames: 
Size: 0.000503 (GB)
<Topology: 223 atoms, 13 residues, 1 mols, non-PBC>
           

In [10]: traj[:8, '@CA']
Out[10]: 
pytraj.Trajectory, 8 frames: 
Size: 0.000002 (GB)
<Topology: 12 atoms, 12 residues, 12 mols, non-PBC>

List comprehensions give identical frames when iterating trajecotry ¶

This is our intention for memory saving. Use copy method. (But what do you need list comprehensions for in this case?)

# same frames
[frame for frame in traj]

# different frames
[frame.copy() for frame in traj]

Get undefined symbol error when import `pytraj`¶

Probably you use old libcpptraj. You can export LD_LIBRARY_PATH

# supposed you have libcpptraj in /home/lib/cpptraj/, do
$ export LD_LIBRARY_PATH=/home/lib/cpptraj/:$LD_LIBRARY_PATH

ImportError ... undefined symbol

Solution:

since pytraj requires cpptraj at both compiling and running time, if you update libcpptraj.so, you need to rebbuild pytraj from fresh.

# supposed you are in pytraj home folder (having README.md, tests, ...)
rm -rf build
python setup.py install

ValueError: Buffer not C contiguous ¶

Symtoms:

File "pytraj/cyutils.pyx", line 76, in _fast_iterptr (pytraj/cyutils.cpp:5078)...
ValueError: Buffer not C contiguous.