def test_coordinates_meta():
from mdtraj.testing import get_fn
fn, tn = [get_fn('frame0.pdb'),] * 2
trajs = [pt.load(fn, tn), md.load(fn, top=tn), pmd.load_file(tn, fn)]
N_FRAMES = trajs[0].n_frames
from MDAnalysis import Universe
u = Universe(tn, fn)
trajs.append(Universe(tn, fn))
views = [nv.show_pytraj(trajs[0]), nv.show_mdtraj(trajs[1]), nv.show_parmed(trajs[2])]
views.append(nv.show_mdanalysis(trajs[3]))
for index, (view, traj) in enumerate(zip(views, trajs)):
view.frame = 3
nt.assert_equal(view.trajlist[0].n_frames, N_FRAMES)
nt.assert_equal(len(view.trajlist[0].get_coordinates_dict().keys()), N_FRAMES)
if index in [0, 1]:
# pytraj, mdtraj
if index == 0:
aa_eq(view.coordinates[0], traj.xyz[3], decimal=4)
else:
aa_eq(view.coordinates[0],10*traj.xyz[3], decimal=4)
view.coordinates = traj.xyz[2]
def view_nucl(*args,gui=False):
nuclMD=mda.Universe(*args)
#prot = nuclMD.select_atoms("protein")
show=nv.show_mdanalysis(nuclMD,gui=gui)
show.representations = [
{"type": "cartoon", "params": {
"sele": ":A :E", "color": 0x020AED,"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":B :F", "color": "green","aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":C :G", "color": 0xE0F705,"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":D :H", "color": 0xCE0000,"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": "nucleic", "color": "grey","aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "base", "params": {
"sele": "nucleic", "color": "grey",
}},
]
show.camera = 'orthographic'
return show
def affinity_propagation(self, preference=-6.0):
'''Performing Affinity Propagation clustering of AMOEBA-run Trp-Cage folding trajectory:-
Default parameter values from MDAnalysis - damping=0.9, max_iter=500, convergence_iter=50
Preference reduced to -10 from -1 to reflect local homogenity within the trajectory'''
print("Performing Affinity Propagation with input preference = %f" %
preference)
clust = encore.cluster(self.univ_cut,
method=encore.AffinityPropagation(
preference=preference, verbose=True))
centroids = [cluster.centroid * self.ncut for cluster in clust]
ids = [cluster.id for cluster in clust]
print(
"Clustering complete! - %d clusters formed with average size = %d frames"
% (len(ids), np.average([cluster.size for cluster in clust])))
coords_centroids = np.zeros((len(centroids), 304, 3), dtype=np.float64)
coords_centroids[:, :, :] = [
self.coords_protein[centroids[i], :, :]
for i in np.arange(0, len(centroids))
]
protein = self.univ2.select_atoms("protein")
univ_centroids = mda.Merge(protein)
univ_centroids.load_new(coords_centroids, format=MemoryReader)
ref = mda.Universe("folded.pdb")
nframes = len(univ_centroids.trajectory)
alignment = align.AlignTraj(univ_centroids,
ref,
select='protein and name CA',
in_memory=True,
verbose=True)
alignment.run()
idvscenter = {
'Cluster ID': [ids[i] for i in range(0, len(ids))],
'Centroid Time (ps)':
[centroids[i] * 10 for i in range(0, len(centroids))],
'Cluster Size': [cluster.size for cluster in clust]
}
idtable = pd.DataFrame(data=idvscenter)
#Visualisation representation set for Trp-Cage - will expand to general proteins later
view = nglview.show_mdanalysis(univ_centroids)
view.add_cartoon(selection="protein")
view.add_licorice('TRP')
view.add_licorice('PRO')
view.center(selection='protein', duration=nframes)
view.player.parameters = dict(frame=True)
return view, idtable, univ_centroids
def view_nucl(*args,gui=False,chconv={},selection='all',color=False):
ch_conv={'A':'A','B':'B','C':'C','D':'D','E':'E','F':'F','G':'G','H':'H','I':'I','J':'J'}
ch_conv.update(chconv)
if(isinstance(args[0],mda.Universe)):
nuclMD=args[0]
else:
nuclMD=mda.Universe(*args)
#prot = nuclMD.select_atoms("protein")
sel=nuclMD.select_atoms(selection)
show=nv.show_mdanalysis(sel,gui=gui)
if(color==False):
color={'A':0x020AED,'B':"green",'C':0xE0F705,'D':0xCE0000,'DNA':"grey"}
show.representations = [
{"type": "cartoon", "params": {
"sele": ":%s"%(ch_conv['A']), "color": color['A'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s"%(ch_conv['B']), "color": color['B'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s"%(ch_conv['C']), "color": color['C'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s"%(ch_conv['D']), "color": color['D'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s"%(ch_conv['E']), "color": color['A'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s "%(ch_conv['F']), "color": color['B'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s"%(ch_conv['G']), "color": color['C'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": ":%s "%(ch_conv['H']), "color": color['D'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "cartoon", "params": {
"sele": "nucleic", "color": color['DNA'],"aspectRatio":2, "radius":1.5,"radiusSegments":1,"capped":1
}},
{"type": "base", "params": {
"sele": "nucleic", "color": color['DNA'],
}},
]
show.camera = 'orthographic'
return show
def test_coordinates_meta():
from mdtraj.testing import get_fn
fn, tn = [get_fn('frame0.pdb'),] * 2
trajs = [pt.load(fn, tn), md.load(fn, top=tn), pmd.load_file(tn, fn)]
N_FRAMES = trajs[0].n_frames
from MDAnalysis import Universe
u = Universe(tn, fn)
trajs.append(Universe(tn, fn))
views = [nv.show_pytraj(trajs[0]), nv.show_mdtraj(trajs[1]), nv.show_parmed(trajs[2])]
views.append(nv.show_mdanalysis(trajs[3]))
for index, (view, traj) in enumerate(zip(views, trajs)):
view.frame = 3
nt.assert_equal(view._trajlist[0].n_frames, N_FRAMES)
def _show_trajectory(pdb_path, dcd_path):
"""
Show the MD trajectory that is the bases for the dynophore.
Parameters
----------
dcd_path : None or str or pathlib.Path
Optionally: Path to DCD file (trajectory).
Returns
-------
nglview.widget.NGLWidget
Visualization with the NGL Viewer.
"""
md_universe = mda.Universe(str(pdb_path), str(dcd_path))
view = nv.show_mdanalysis(md_universe)
return view
def test_coordinates_meta():
from mdtraj.testing import get_fn
fn, tn = [get_fn('frame0.pdb'),] * 2
trajs = [pt.load(fn, tn), md.load(fn, top=tn), pmd.load_file(tn, fn)]
N_FRAMES = trajs[0].n_frames
from MDAnalysis import Universe
u = Universe(tn, fn)
trajs.append(Universe(tn, fn))
views = [nv.show_pytraj(trajs[0]), nv.show_mdtraj(trajs[1]), nv.show_parmed(trajs[2])]
views.append(nv.show_mdanalysis(trajs[3]))
for index, (view, traj) in enumerate(zip(views, trajs)):
view.frame = 3
nt.assert_equal(view._trajlist[0].n_frames, N_FRAMES)
def draw_fragments(*fragments):
"""Draw many fragments in a Jupyter notebook
Will make molecules whole and choose the image of each
which makes them as close as possible
Parameters
----------
fragments : list of AtomGroup
the thing to draw
"""
import nglview as nv
u, _ = _copy_universe(sum(fragments))
# gather network into same image
g = _gather_network(u.atoms.fragments)
v = nv.show_mdanalysis(sum(g.nodes()))
return v
def _show_trajectory(pdb_path, dcd_path):
"""
Show the MD trajectory that is the bases for the dynophore.
Parameters
----------
pdb_path : str or pathlib.Path
Path to PDB file (structure/topology)
dcd_path : None or str or pathlib.Path
Optionally: Path to DCD file (trajectory).
frame_range : list of in
Select frame range to display (list of two integers). If None (default), use all points.
Returns
-------
nglview.widget.NGLWidget
Visualization with the NGL Viewer.
"""
md_universe = mda.Universe(str(pdb_path), str(dcd_path))
view = nv.show_mdanalysis(md_universe)
return view
def to_nglview_NGLWidget(item,
atom_indices='all',
structure_indices='all',
check=True):
if check:
digest_item(item, 'mdanalysis.Universe')
atom_indices = digest_atom_indices(atom_indices)
structure_indices = digest_structure_indices(structure_indices)
from . import extract
from nglview import show_mdanalysis
tmp_item = extract(item,
atom_indices=atom_indices,
structure_indices=structure_indices,
copy_if_all=False,
check=False)
tmp_item = show_mdanalysis(tmp_item)
return tmp_item
def visualise_structures(self, traj, protein_ref):
'''Visualisation of a set of structures using NGLView:-
protein_ref - Reference structure used to align the input structures based
on rotational and translational matricies'''
ref = mda.Universe(protein_ref)
nframes = len(traj.trajectory)
alignment = align.AlignTraj(traj,
ref,
select='protein and name CA',
in_memory=True,
verbose=True)
alignment.run()
#Visualisation representation set for Trp-Cage - will expand to general proteins later
view = nglview.show_mdanalysis(traj)
view.add_cartoon(selection="protein")
view.add_licorice('TRP')
view.add_licorice('PRO')
view.center(selection='protein', duration=nframes)
view
def test_show_MDAnalysis():
from MDAnalysis import Universe
tn, fn = nv.datafiles.PDB, nv.datafiles.PDB
u = Universe(fn, tn)
view = nv.show_mdanalysis(u)
def test_show_MDAnalysis():
from MDAnalysis import Universe
tn, fn = nv.datafiles.PDB, nv.datafiles.PDB
u = Universe(fn, tn)
view = nv.show_mdanalysis(u)
# %%
import MDAnalysis as mda
import nglview as nv
from funcs import unwrap_traj, add_elements_to_universe
# %%
u = mda.Universe('pack.lmps', 'traj.dcd', topology_format='DATA')
add_elements_to_universe(u, 'pack.lmps')
unwrap_traj(u)
nv.show_mdanalysis(u)