Misc¶

try pytraj online:

seperate module, only use stdlib If want to use external package, import it inside the function

This module stores all useful functions that does not fit to anywhere else.

pytraj.tools.as_2darray(traj_or_xyz)¶

reshape traj.xyz to 2d array, shape=(n_frames, n_atoms * 3)

Notes

if traj is mutable, this method return a view of its coordinates.

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> traj.xyz.shape
(10, 5293, 3)
>>> as_2darray(traj).shape
(10, 15879)
>>> as_2darray(traj.xyz).shape
(10, 15879)

pytraj.tools.as_3darray(xyz)¶

reshape xyz to 3d array, shape=(n_frames, n_atoms, 3)

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> traj.xyz.shape
(10, 5293, 3)
>>> xyz_2d = as_2darray(traj)
>>> xyz_2d.shape
(10, 15879)
>>> as_3darray(xyz_2d).shape
(10, 5293, 3)
>>> as_3darray(traj.xyz)
Traceback (most recent call last):
    ...
ValueError: ndim must be 2

pytraj.tools.block_average(self, n_chunk)¶

average by chunk

Examples

>>> block_average(range(30), 3)
array([  4.5,  14.5,  24.5])

pytraj.tools.compose(*funcs)¶

Notes: copied from pandas (added pytraj’s example) see license in pytraj/license/

Compose 2 or more callables

Examples

>>> import pytraj as pt
>>> from pytraj.testing import get_fn
>>> func = compose(pt.calc_radgyr, pt.iterload)
>>> fname, tname = get_fn('tz2')
>>> func(fname, tname)
array([ 18.91114428,  18.93654996,  18.84969884,  18.90449256,
        18.8568644 ,  18.88917208,  18.9430491 ,  18.88878079,
        18.91669565,  18.87069722])

pytraj.tools.concat_dict(iterables)¶

concat dict

Examples

>>> dict_0 = {'x' : [1, 2, 3,]}
>>> dict_1 = {'x' : [4, 5]}
>>> concat_dict((dict_0, dict_1))
OrderedDict([('x', array([1, 2, 3, 4, 5]))])

pytraj.tools.dict_to_ndarray(dict_of_array)¶

convert OrderedDict to numpy array

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> dslist = pt.multidihedral(traj, dhtypes='phi psi', resrange='2', dtype='dict')
>>> list(dslist.keys())
['phi:2', 'psi:2']
>>> dict_to_ndarray(dslist)
array([[-128.72617304, -109.44321317, -130.93278259, ..., -146.70146067,
        -121.58263643, -112.74485175],
       [ 150.11249102,  142.52303293,  131.11609265, ...,  123.44883266,
         141.18992429,  120.03168126]])

pytraj.tools.dir_(obj)¶

return a list of obj’s attributes with no private method

pytraj.tools.estimate_size(n_frames, n_atoms, dtype='f8')¶

return MB

>>> import pytraj as pt
>>> traj = pt.datafiles.load_tz2_ortho()
>>> estimate_size(traj.n_frames, traj.n_atoms, 'f8')
1.2114715576171875
>>> estimate_size(traj.n_frames, traj.n_atoms, 'f4')
0.6057357788085938

pytraj.tools.find_lib(libname)¶

return a list of all library files

pytraj.tools.flatten(x)¶

Returns a single, flat list which contains all elements retrieved from the sequence and all recursively contained sub-sequences (iterables).

Notes

from: http://kogs-www.informatik.uni-hamburg.de/~meine/python_tricks

Examples

>>> [1, 2, [3,4], (5,6)]
[1, 2, [3, 4], (5, 6)]
>>> flatten([[[1,2,3], (42,None)], [4,5], [6], 7, (8,9,10)])
[1, 2, 3, 42, None, 4, 5, 6, 7, 8, 9, 10]

pytraj.tools.grep_key(self, key)¶

grep key

Examples

>>> import pytraj as pt
>>> traj  = pt.load_sample_data('tz2')
>>> dslist = pt.calc_multidihedral(traj, dtype='dataset')
>>> pt.tools.grep_key(dslist, 'psi').values[0]
array([ 176.6155643 ,  166.82129574,  168.79510009,  167.42561927,
        151.18334989,  134.17610997,  160.99207908,  165.1126967 ,
        147.94332109,  145.42901383])

pytraj.tools.groupby(key, seq)¶

Examples

>>> names = ['Alice', 'Bob', 'Charlie', 'Dan', 'Edith', 'Frank']
>>> groupby(len, names)
{3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']}

pytraj.tools.iteritems(d, **kw)¶

Return an iterator over the (key, value) pairs of a dictionary.

Examples

>>> for k, v in iteritems({'x': 3, 'y': 4}): print(k, v) : 
x 3
y 4

pytraj.tools.make_fake_topology(n_atoms)¶

make fake Topology, just for writing xyz array to supported formats (netcdf, dcd, trr, ...)

>>> import pytraj as pt
>>> top = pt.tools.make_fake_topology(100)
>>> top.n_atoms
100
>>> isinstance(top, pt.Topology)
True
>>> import numpy as np
>>> xyz = np.random.rand(10*100*3).reshape(10, 100, 3)
>>> traj0 = pt.Trajectory(xyz=xyz, top=top)
>>> pt.write_traj('output/test.nc', traj0, overwrite=True)
>>> traj = pt.iterload('output/test.nc', top=top)
>>> traj.n_atoms
100

pytraj.tools.mean_and_error(a1, a2)¶

calculate mean and error from two 1D array-like

Examples

>>> import pytraj as pt
>>> a0 = [2, 4, 6]
>>> a1 = [3, 5, 7]
>>> mean_and_error(a0, a1)
(4.5, 0.5)

pytraj.tools.merge_coordinates(iterables)¶

merge_coordinates from frames

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> merge_coordinates(traj(0, 3)) 
array([[ 15.55458927,  28.54844856,  17.18908691],
       [ 16.20579147,  29.07935524,  17.74959946],
       [ 14.95065975,  29.27651787,  16.83513069],
       ...,
       [ 34.09399796,   7.88915873,  15.6500845 ],
       [ 34.4160347 ,   8.53098011,  15.01716137],
       [ 34.29132462,   8.27471733,  16.50368881]])

pytraj.tools.merge_frame_from_trajs(trajlist)¶

Examples

>>> import numpy as np
>>> import pytraj as pt
>>> traj0 = pt.load_sample_data('tz2')[:3]
>>> traj1 = pt.load_sample_data('tz2')[3:6]
>>> traj2 = pt.load_sample_data('tz2')[6:9]
>>> print(traj0.n_atoms, traj1.n_atoms, traj2.n_atoms)
5293 5293 5293
>>> for frame in pt.tools.merge_frame_from_trajs((traj0, traj1, traj2)): print(frame)
<Frame with 15879 atoms>
<Frame with 15879 atoms>
<Frame with 15879 atoms>

pytraj.tools.merge_frames(iterables)¶

merge from frames to a single Frame. Order matters. Examples ——– >>> import pytraj as pt >>> traj = pt.load_sample_data(‘tz2’) >>> traj[0] <Frame with 5293 atoms> >>> merge_frames(traj(0, 3)) <Frame with 15879 atoms>

pytraj.tools.merge_trajs(traj1, traj2, start_new_mol=True, n_frames=None)¶

Notes

Code might be changed

Examples

>>> import pytraj as pt
>>> import numpy as np
>>> traj1 = pt.load_sample_data('ala3')[:1]
>>> traj2 = pt.load_sample_data('tz2')[:1]
>>> traj3 = merge_trajs(traj1, traj2)
>>> # from frame_iter for saving memory
>>> traj3 = merge_trajs((traj1(0, 10, 2), traj1.top), (traj2(100, 110, 2), traj2.top), n_frames=6)

>>> # raise error if not having the same n_frames
>>> traj4 = pt.load_sample_data('tz2')[:]
>>> traj4.n_frames
10
>>> traj1.n_frames
1
>>> merge_trajs(traj1, traj4)
Traceback (most recent call last):
    ...
ValueError: must have the same n_frames

pytraj.tools.moving_average(data, n)¶

moving average

Notes

from stackoverflow

Examples

>>> moving_average([1, 2, 3, 4, 6], 2)
array([ 0.5,  1.5,  2.5,  3.5,  5. ])

pytraj.tools.n_grams(a, n)¶

Parameters:	a : sequence n : number of elements asarray : bool, default False if False: return an iterator if True: return a numpy array

Notes

adapted from: http://sahandsaba.com/thirty-python-language-features-and-tricks-you-may-not-know.html

Examples

>>> list(n_grams([2, 3, 4 ,5], 2))
[(2, 3), (3, 4), (4, 5)]

pytraj.tools.read_gaussian_output(filename=None, top=None)¶

return a pytraj.trajectory.Trajectory object

Parameters:	fname : str, filename top : {str, Topology}, optional, default None pytraj.Topology or a filename or None if None, use antechamber to generate mol2 file, need set $AMBERHOME env

pytraj.tools.read_to_array(fname)¶

read text from file to numpy array

pytraj.tools.rmsd(a1, a2, flatten=True)¶

rmsd for two array with the same shape

Parameters:	a1, a2: np.ndarray flatten : bool, default True if True: always flatten two input arrays

Notes

This method is different from pytraj.rmsd

Examples

>>> import pytraj as pt
>>> t0 = pt.load_sample_data('ala3')
>>> t1 = t0[:]
>>> t1.xyz += 1.
>>> rmsd(t0.xyz, t1.xyz)
1.0

pytraj.tools.rmsd_1darray(a1, a2)¶

rmsd of a1 and a2

Examples

>>> a0 = [1, 3, 4]
>>> a1 = [1.4, 3.5, 4.2]
>>> rmsd_1darray(a0, a1)
0.3872983346207417

>>> rmsd_1darray(a0, [3, 4, 5, 7, 8])
Traceback (most recent call last):
    ...
ValueError: must have the same shape

pytraj.tools.split(data, n_chunks)¶

split self.data to n_chunks

Notes

same as numpy.array_split

Examples

>>> for data in split(range(30), 3): print(data)
[0 1 2 3 4 5 6 7 8 9]
[10 11 12 13 14 15 16 17 18 19]
[20 21 22 23 24 25 26 27 28 29]

pytraj.tools.split_and_write_traj(self, n_chunks=None, root_name='trajx', ext='nc', *args, **kwd)¶

Examples

>>> import pytraj as pt
>>> traj = pt.load_sample_data('tz2')
>>> split_and_write_traj(traj, n_chunks=3, root_name='output/trajx', overwrite=True)

pytraj.tools.split_traj_by_residues(traj, start=0, stop=-1, step=1)¶

return a generator

Examples

>>> import pytraj as pt
>>> traj = pt.datafiles.load_rna()
>>> g = pt.tools.split_traj_by_residues(traj)
>>> t0 = next(g)
>>> print(t0.top.n_residues)
1