def load(self,
traj,
top=None,
skip_atoms=None,
skip_residues=None,
chunk_size=1000):
if self._method == 'ensemble':
print('Ensemble method not yet implemented.')
pass
#self._topfile = traj
#self._skip_atoms = skip_atoms
#self._skip_residues = skip_residues
#self._mdtraj = prepare.fetch(traj, skip_atoms, skip_residues)
#prepare.topology(self)
elif self._method == 'simulation':
#It isn't worth it right now to allow the trajectory conversion here. Probably better to give
#the user a .sh file to do the conversion themselves. The modularized Python yahoos can get over it.
self._trajfile = traj
self._topfile = top
self.protname = traj.split('.')[0]
N, NFRS, NATOMS = LE4PD.gen_protinfo(self.protname, self._trajfile,
self._topfile)
self.nres = N
self.nframes = NFRS
self.natoms = NATOMS
def hydrodynamics(self, path='./'):
self.Hmatrix, self.AIHI, self.QHA, self.QHAINV, self.lambda_eig = LE4PD.eigendecomp(
self.Cmatrix,
self.Rinv,
self.avfr,
self.fratio,
self.fric,
path=path)
def mode_mad(self, nmodes=10):
self.barriers, self.xi_traj, self.theta_phi_traj = LE4PD.mode_mad(
self.traj,
self.protname,
self.nres,
self.nframes,
self.Q, (self.Q).T,
self.temp,
nmodes=nmodes,
HA=False)
def mode_mad_HA(self, nmodes=10):
self.barriers_HA, self.xi_traj_HA, self.theta_phi_traj_HA = LE4PD.mode_mad(
self.traj,
self.protname,
self.nres,
self.nframes,
self.QHA,
self.QHAINV,
self.temp,
nmodes=nmodes,
HA=True)
def fric_calc(self,
intv=2.71828,
viscosity=1e-3,
fd20=0.0,
path_to_resarea='./'):
self.fratio, self.sigma, self.fric, self.avfr = LE4PD.fric_calc(
self._topfile,
self.protname,
self.nres,
self.nframes,
self.natoms,
self.mu_eig,
self.temp,
intv=intv,
viscosity=viscosity,
fd20=fd20,
path_to_resarea=path_to_resarea)
def Rij(self, path='./'):
self.Rinv = LE4PD.Rij(self.traj, path)
def calc_Cmatrix(self):
self.Cmatrix, self.Q, self.mu_eig = LE4PD.calc_Cmatrix(self.traj)
def prepare_traj(self):
self.unformatted_traj = LE4PD.convert_traj(self._trajfile)
self.traj = LE4PD.format_traj(self.unformatted_traj, self.nres,
self.nframes)
def LML_HA(self):
self.LML_HA = LE4PD.LML(self.QHA, self.mu_eig)
def LML(self):
self.LML = LE4PD.LML(self.Q, self.mu_eig)