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def test_complex_system():
sys = pc.System()
sys.read_inputfile('examples/cluster.dump')
sys.find_neighbors(method='cutoff', cutoff=3.63)
assert 176 == sys.find_solids(bonds=6, threshold=0.5, avgthreshold=0.6, cluster=True)
def test_neighbors_system():
#create some atoms
atoms, boxdims = pcs.make_crystal('bcc', repetitions = [6, 6, 6])
sys = pc.System()
sys.atoms = atoms
sys.box = boxdims
#test that atoms are set properly
assert len(sys.atoms) == 432
#then lets find neighbors
#cutoff method - first shell only
sys.find_neighbors(method = 'cutoff', cutoff=0.867)
#any atom should have 8 neighbors
atoms = sys.atoms
assert atoms[0].coordination == 8
sys.reset_neighbors()
#cutoff method - second shell
def test_pickle_system():
atoms, boxdims = pcs.make_crystal('bcc', repetitions = [1, 1, 1])
sys = pc.System()
sys.atoms = atoms
sys.box = boxdims
sys.find_neighbors(method = 'voronoi')
#test write and read system
sys.to_pickle('tests/sy.npy')
#now read the pickled system
psys = pc.System()
psys.from_pickle('tests/sy.npy')
#now get atoms and a random number of atom
satoms = sys.atoms
patoms = psys.atoms
rn = np.random.randint(0, len(satoms)-1)
def test_q_10():
atoms, boxdims = pcs.make_crystal('bcc', repetitions = [4, 4, 4])
sys = pc.System()
sys.atoms = atoms
sys.box = boxdims
sys.find_neighbors(method = 'voronoi')
sys.calculate_q(10, averaged=True)
q = sys.get_qvals(10, averaged=True)
assert np.round(np.mean(np.array(q)), decimals=2) == 0.41
def test_q_8():
atoms, boxdims = pcs.make_crystal('bcc', repetitions = [4, 4, 4])
sys = pc.System()
sys.atoms = atoms
sys.box = boxdims
sys.find_neighbors(method = 'voronoi')
sys.calculate_q(8, averaged=True)
q = sys.get_qvals(8, averaged=True)
assert np.round(np.mean(np.array(q)), decimals=2) == 0.33
def test_voro_props():
atoms, boxdims = pcs.make_crystal('bcc', repetitions = [2, 2, 2])
sys = pc.System()
sys.atoms = atoms
sys.box = boxdims
sys.find_neighbors(method = 'voronoi')
sys.calculate_vorovector()
atoms = sys.atoms
atom = atoms[0]
v = atom.vorovector
assert v == [0,6,0,8]
def _get_steinhardt_parameter(cell, positions, cutoff=3.50, n_clusters=2, q=[4, 6]):
sys = pc.System()
prism = UnfoldingPrism(cell, digits=15)
xhi, yhi, zhi, xy, xz, yz = prism.get_lammps_prism_str()
coords = [prism.pos_to_lammps(position) for position in positions]
sys.box = [[0.0, float(xhi)], [0.0, float(yhi)], [0.0, float(zhi)]]
sys.atoms = [pc.Atom(pos=p, id=i) for i, p in enumerate(coords)]
sys.find_neighbors(method='cutoff', cutoff=cutoff)
sys.calculate_q(q, averaged=True)
sysq = sys.get_qvals(q, averaged=True)
cl = cluster.KMeans(n_clusters=n_clusters)
ind = cl.fit(list(zip(*sysq))).labels_ == 0
return sysq, ind