def test_center(self):
traj = pt.iterload(fn('tz2.ortho.nc'), fn('tz2.ortho.parm7'))
pt.load(fn("tz2.center_mass.nc"), traj.top)
fa = traj[:]
fa2 = traj[:].copy()
pt.center(fa, mask=':1', mass=True)
aa_eq(fa.xyz, fa.xyz, decimal=5)
# raise if center not in 'origin', 'box'
with pytest.raises(ValueError):
pt.center(fa, center='oh')
# center to point
pt.center(fa, ':1', center=[0, 1, 2], mass=True)
aa_eq(pt.center_of_mass(fa, ':1')[0], [0, 1, 2])
pt.center(fa, ':1', center=[0, 1, 2], mass=False)
aa_eq(pt.center_of_geometry(fa, ':1')[0], [0, 1, 2])
fa2.center(':1', center=[0, 1, 2], mass=False)
aa_eq(pt.center_of_geometry(fa2, ':1')[0], [0, 1, 2])
# on_disk
traj_on_disk = pt.iterload(fn('tz2.ortho.nc'), fn('tz2.ortho.parm7'))
pt.center(traj_on_disk, ':1', center=[0, 1, 2], mass=True)
aa_eq(pt.center_of_mass(traj_on_disk, ':1')[0], [0, 1, 2])
def prepare(self):
'''Load trajectory, print information and
perform initial alignment and fit.'''
self.load_traj()
self.atoms = self.traj.n_atoms
self.frames = self.traj.n_frames
print('\nPROTEIN INFORMATION')
print('PDB code: {}'.format(self.PDB))
print('residues: {}'.format(self.atoms))
print('frames: {}'.format(self.frames))
print('temperature: {}'.format(self.temperature))
# Align molecule to principal axes
pt.principal_axes(self.traj, dorotation=True)
# Center molecule at the origin
pt.center(self.traj, center='origin')
# First rmsd fit
pt.rmsd(self.traj)
# Calculate average structure
self.avg = pt.mean_structure(self.traj)
# Perform rms fit to average structure
pt.rmsd(self.traj, ref=self.avg)
# Initialize arrays
self.initialize_arrays()
def test_density(self):
rst7 = fn('DOPC.rst7')
tn = fn('DOPC.parm7')
traj = pt.load(fn('DOPC.rst7'), fn('DOPC.parm7'))
delta = '0.25'
masks = [":PC@P31", ":PC@N31", ":PC@C2", ":PC | :OL | :OL2"]
keys_no_space = [''.join(m.split()) for m in masks]
mask_str = ' '.join(['"' + m + '"' for m in masks])
density_types = ['number', 'mass', 'charge', 'electron']
state_data_dict = dict()
for density_type in density_types:
command = """
parm {parm}
trajin {trajin}
center ":PC | :OL | :OL2" origin
density {density_type} delta {delta} {mask}
""".format(
parm=tn,
trajin=rst7,
delta=delta,
mask=mask_str,
density_type=density_type)
state = pt.load_cpptraj_state(command)
state.run()
state_data_dict[density_type] = state.data[1:].to_dict()
pt.center(traj, '":PC | :OL | :OL2" origin')
density_dict = {}
for density_type in density_types:
density_data = pt.density(
traj, mask=masks, delta=delta, density_type=density_type)
density_dict[density_type] = density_data
# compate to cpptraj
for density_type in density_types:
for key in keys_no_space:
aa_eq(state_data_dict[density_type][key],
density_dict[density_type][key])
# assert raise: wrong density_type
def func():
pt.density(traj, mask=':WAT', density_type='hello')
with pytest.raises(AssertionError):
func()
# test 'z' value
saved_z_values = np.linspace(-24.1250, 23.8750, 193)
aa_eq(density_data['z'], saved_z_values)
def test_center_autoimagesuperpose(self):
traj = pt.iterload(fn('tz2.ortho.nc'), fn('tz2.ortho.parm7'))
t0 = traj[:]
t1 = traj[:]
pt.center(t0)
pt.autoimage(t0)
pt.superpose(t0)
aa_eq(pt.center(t1).autoimage().superpose().xyz, t0.xyz)
def test_center(self):
traj = pt.iterload("./data/tz2.ortho.nc", "./data/tz2.ortho.parm7")
saved_traj = pt.load("./data/tz2.center_mass.nc", traj.top)
fa = traj[:]
pt.center(fa, mask=':1', mass=True)
aa_eq(fa.xyz, fa.xyz, decimal=5)
# raise if center not in 'origin', 'box'
self.assertRaises(ValueError, lambda: pt.center(fa, center='oh'))
def test_center_autoimagesuperpose(self):
traj = pt.iterload("./data/tz2.ortho.nc", "./data/tz2.ortho.parm7")
t0 = traj[:]
t1 = traj[:]
pt.center(t0)
pt.autoimage(t0)
pt.superpose(t0)
aa_eq(pt.center(t1).autoimage().superpose().xyz, t0.xyz)
def test_center_autoimagesuperpose(self):
traj = pt.iterload("./data/tz2.ortho.nc", "./data/tz2.ortho.parm7")
t0 = traj[:]
t1 = traj[:]
pt.center(t0)
pt.autoimage(t0)
pt.superpose(t0)
aa_eq(pt.center(t1).autoimage().superpose().xyz, t0.xyz)
def test_center(self):
traj = pt.iterload("./data/tz2.ortho.nc", "./data/tz2.ortho.parm7")
saved_traj = pt.load("./data/tz2.center_mass.nc", traj.top)
fa = traj[:]
pt.center(fa, mask=':1', mass=True)
aa_eq(fa.xyz, fa.xyz, decimal=5)
# raise if center not in 'origin', 'box'
self.assertRaises(ValueError, lambda: pt.center(fa, center='oh'))
def clean_traj(self):
# Align molecule to principal axes
pt.principal_axes(self.traj, dorotation=True)
# Center molecule at the origin
pt.center(self.traj, center='origin')
# First rmsd fit
pt.rmsd(self.traj)
# Calculate average structure
self.avg = pt.mean_structure(self.traj)
# Perform rms fit to average structure
pt.rmsd(self.traj, ref=self.avg)
def test_mpi_cpptraj_style():
comm = MPI.COMM_WORLD
# end. you are free to update anything below here
# split remd.x.000 to N cores and do calc_surf in parallel
root_dir = "data/"
traj_name = root_dir + "tz2.ortho.nc"
parm_name = root_dir + "tz2.ortho.parm7"
# load to TrajectoryIterator
traj = pt.iterload(traj_name, parm_name)
# save `total_arr` to rank=0
# others: total_arr = None
total_arr = pt.pmap_mpi(
['autoimage', 'center :2', 'distance :3 :7', 'angle :3 :7 :8'], traj)
if comm.rank != 0:
assert total_arr is None
if comm.rank == 0:
# assert to serial
from pytraj.utils.tools import dict_to_ndarray
arr = dict_to_ndarray(total_arr)
t0 = pt.center(traj[:].autoimage(), ':2')
aa_eq(pt.distance(t0, ':3 :7'), arr[0])
aa_eq(pt.angle(t0, ':3 :7 :8'), arr[1])
def test_center():
# OK
for f in traj:
pt.center(f, top=traj.top)
def test_center():
# OK
for f in traj:
pt.center(f, top=traj.top)
import pytraj as pt
from pytraj.testing import aa_eq
comm = MPI.COMM_WORLD
# end. you are free to update anything below here
# split remd.x.000 to N cores and do calc_surf in parallel
root_dir = "data/"
traj_name = root_dir + "tz2.ortho.nc"
parm_name = root_dir + "tz2.ortho.parm7"
# load to TrajectoryIterator
traj = pt.iterload(traj_name, parm_name)
# save `total_arr` to rank=0
# others: total_arr = None
total_arr = pt.pmap_mpi(
['autoimage', 'center :2', 'distance :3 :7', 'angle :3 :7 :8'], traj)
if comm.rank != 0:
assert total_arr is None
if comm.rank == 0:
# assert to serial
from pytraj.tools import dict_to_ndarray
arr = dict_to_ndarray(total_arr)
t0 = pt.center(traj[:].autoimage(), ':2')
aa_eq(pt.distance(t0, ':3 :7'), arr[0])
aa_eq(pt.angle(t0, ':3 :7 :8'), arr[1])
