def test_run_4(self):
dslist = CpptrajDatasetList()
actlist = ActionList()
traj = pt.iterload(tc5b_trajin, tc5b_top)
mask_list = ['@CB @CA @N @H', '@CA @H @N @H=']
for mask in mask_list:
actlist.add(CA.Action_Dihedral(), mask, traj.top, dslist=dslist)
actlist.compute(traj)
dslist2 = pt.calc_dihedral(traj, mask_list)
dslist3_0 = pt.calc_dihedral(traj, mask_list[0])
dslist3_1 = pt.calc_dihedral(traj, mask_list[1])
aa_eq(dslist3_0, dslist2[0])
aa_eq(dslist3_1, dslist2[1])
aa_eq(dslist3_0, dslist[0].to_ndarray())
aa_eq(dslist3_1, dslist[1].to_ndarray())
def test_dihedral(self):
import numpy as np
traj = pt.iterload(fn('Tc5b.x'), fn('Tc5b.top'))
fa = traj[:]
mask = ':2@CA :14@CA :15@CA :16@CA'
txt = '''
parm {}
trajin {}
dihedral {}
'''.format(tc5b_top, tc5b_trajin, mask)
d0 = pt.dihedral(traj, mask, dtype='dataset').to_ndarray()
d1 = pt.dihedral(traj, mask)
d2 = pt.calc_dihedral(fa, mask)
state = pt.load_cpptraj_state(txt)
state.run()
dcpp = state.data[1:].values
aa_eq(d0, d1)
aa_eq(d0, d2)
aa_eq(d0, dcpp)
Nsize = 10
np.random.seed(1)
arr = np.random.randint(0, 300, size=Nsize * 4).reshape(Nsize, 4)
d3 = pt.calc_dihedral(fa, arr)
d4 = pt.dihedral(traj, arr)
d5 = pt.dihedral(traj, arr)
d6 = pt.dihedral(fa, arr)
d7 = pt.dihedral([fa, traj], arr, n_frames=2 * fa.n_frames)
aa_eq(d3, d4)
aa_eq(d3, d5)
aa_eq(d3, d6)
aa_eq(d3.T, d7.T[:fa.n_frames])
aa_eq(d3.T, d7.T[fa.n_frames:])
d8 = pt.dihedral(traj, mask, dtype='dataset')
d9 = pt.tools.dict_to_ndarray(pt.dihedral(traj, mask, dtype='dict'))
aa_eq(d0, d8.values)
aa_eq([d0], d9)
# raise
with pytest.raises(ValueError):
pt.dihedrals(traj, [[0, 3, 2]])
def test_dihedral(self):
import numpy as np
traj = mdio.iterload("./data/Tc5b.x", "./data/Tc5b.top")
fa = traj[:]
mask = ':2@CA :14@CA :15@CA :16@CA'
txt = '''
parm ./data/Tc5b.top
trajin ./data/Tc5b.x
dihedral %s
''' % mask
d0 = pt.dihedral(traj, mask, dtype='dataset').to_ndarray()
d1 = pt.dihedral(traj, mask)
d2 = pt.calc_dihedral(fa, mask)
state = pt.load_cpptraj_state(txt)
state.run()
dcpp = state.data[1:].values
aa_eq(d0, d1)
aa_eq(d0, d2)
aa_eq(d0, dcpp)
Nsize = 10
np.random.seed(1)
arr = np.random.randint(0, 300, size=Nsize * 4).reshape(Nsize, 4)
d3 = pt.calc_dihedral(fa, arr)
d4 = pt.dihedral(traj, arr)
d5 = pt.dihedral(traj, arr)
d6 = pt.dihedral(fa, arr)
d7 = pt.dihedral([fa, traj], arr, n_frames=2 * fa.n_frames)
aa_eq(d3, d4)
aa_eq(d3, d5)
aa_eq(d3, d6)
aa_eq(d3.T, d7.T[:fa.n_frames])
aa_eq(d3.T, d7.T[fa.n_frames:])
d8 = pt.dihedral(traj, mask, dtype='dataset')
d9 = pt.tools.dict_to_ndarray(pt.dihedral(traj, mask, dtype='dict'))
aa_eq(d0, d8.values)
aa_eq(d0, d9)
# raise
self.assertRaises(ValueError, lambda: pt.dihedrals(traj, [[0, 3, 2]]))
def test_run_4(self):
dslist = CpptrajDatasetList()
actlist = ActionList()
traj = pt.iterload("./data/Tc5b.x", "./data/Tc5b.top")
mask_list = ['@CB @CA @N @H', '@CA @H @N @H=']
for mask in mask_list:
actlist.add(CA.Action_Dihedral(),
mask,
traj.top,
dslist=dslist)
actlist.compute(traj)
dslist2 = pt.calc_dihedral(traj, mask_list)
dslist3_0 = pt.calc_dihedral(traj, mask_list[0])
dslist3_1 = pt.calc_dihedral(traj, mask_list[1])
aa_eq(dslist3_0, dslist2[0])
aa_eq(dslist3_1, dslist2[1])
aa_eq(dslist3_0, dslist[0].to_ndarray())
aa_eq(dslist3_1, dslist[1].to_ndarray())