def test_order_from_traj():
"""Made a perfectly aligned monolayer, should have S2 = 1
"""
traj = md.load(get_fn('alkane-monolayer.pdb'))
indices = [list(range(1900+x, 1900+x+36)) for x in range(0, 64*36, 36)]
s2 = md.compute_nematic_order(traj, indices=indices)
assert_allclose(1.0, s2)
def test_order_from_traj():
"""Made a perfectly aligned monolayer, should have S2 = 1
"""
traj = md.load(get_fn('alkane-monolayer.pdb'))
indices = [
list(range(1900 + x, 1900 + x + 36)) for x in range(0, 64 * 36, 36)
]
s2 = md.compute_nematic_order(traj, indices=indices)
assert_allclose(1.0, s2)
def test_read_write_4():
traj = md.load(get_fn('frame0.nc'), top=get_fn('native.pdb'))
traj[0].save(temp2)
assert_true(os.path.exists(temp2))
rsttraj = md.load(temp2, top=get_fn('native.pdb'))
assert_allclose(rsttraj.xyz, traj[0].xyz)
os.unlink(temp2)
traj.save(temp2)
for i in range(traj.n_frames):
assert_true(os.path.exists('%s.%03d' % (temp2, i + 1)))
os.unlink('%s.%03d' % (temp2, i + 1))
def test_directors_angle_from_traj():
"""All chains in example system aligned along z axis
"""
traj = md.load(get_fn('alkane-monolayer.pdb'))
# only use the carbons for this calculation since they are excactly aligned
# with the z-axis, and the hydrogens can throw things off just a bit
indices = [list(range(1900+x, 1900+x+30, 3)) for x in range(0, 64*36, 36)]
directors = md.compute_directors(traj, indices=indices)
for axis, target_angle in zip(np.eye(3), [90.0, 90.0, 0.0]):
dotproducts = np.tensordot(directors, axis, axes=1)
angles = np.degrees(np.arccos(dotproducts))
angles = np.minimum(angles, 180-angles) # make vector point in positive z
assert_allclose(target_angle, angles)
def test_directors_angle_from_traj():
"""All chains in example system aligned along z axis
"""
traj = md.load(get_fn('alkane-monolayer.pdb'))
# only use the carbons for this calculation since they are excactly aligned
# with the z-axis, and the hydrogens can throw things off just a bit
indices = [
list(range(1900 + x, 1900 + x + 30, 3)) for x in range(0, 64 * 36, 36)
]
directors = md.compute_directors(traj, indices=indices)
for axis, target_angle in zip(np.eye(3), [90.0, 90.0, 0.0]):
dotproducts = np.tensordot(directors, axis, axes=1)
angles = np.degrees(np.arccos(dotproducts))
angles = np.minimum(angles,
180 - angles) # make vector point in positive z
assert_allclose(target_angle, angles)
def _run_amber_traj(traj, ext_ref):
# Test triclinic case where simple approach in Tuckerman text does not
# always work
distopt = md.compute_distances(traj, [[0, 9999]], opt=True)
distslw = md.compute_distances(traj, [[0, 9999]], opt=False)
dispopt = md.compute_displacements(traj, [[0, 9999]], opt=True)
dispslw = md.compute_displacements(traj, [[0, 9999]], opt=False)
eq(distopt, distslw, decimal=5)
eq(dispopt, dispslw, decimal=5)
assert_allclose(distopt.flatten(), ext_ref, atol=2e-5)
# Make sure distances from displacements are the same
eq(np.sqrt((dispopt.squeeze()**2).sum(axis=1)), distopt.squeeze())
eq(np.sqrt((dispslw.squeeze()**2).sum(axis=1)), distslw.squeeze())
eq(dispopt, dispslw, decimal=5)
def _run_amber_traj(trajname, ext_ref):
# Test triclinic case where simple approach in Tuckerman text does not
# always work
traj = md.load(get_fn(trajname), top=get_fn("test.parm7"))
distopt = md.compute_distances(traj, [[0, 9999]], opt=True)
distslw = md.compute_distances(traj, [[0, 9999]], opt=False)
dispopt = md.compute_displacements(traj, [[0, 9999]], opt=True)
dispslw = md.compute_displacements(traj, [[0, 9999]], opt=False)
eq(distopt, distslw, decimal=5)
eq(dispopt, dispslw, decimal=5)
assert_allclose(distopt.flatten(), ext_ref, atol=2e-5)
# Make sure distances from displacements are the same
eq(np.sqrt((dispopt.squeeze() ** 2).sum(axis=1)), distopt.squeeze())
eq(np.sqrt((dispslw.squeeze() ** 2).sum(axis=1)), distslw.squeeze())
eq(dispopt, dispslw, decimal=5)
