def get_vecs(mol,
frame_funs=None,
frame_index=None,
mode='full',
n=100,
nr=10,
dt=None):
"Get the set of frame functions"
if frame_funs is None:
if mol._vf is not None:
frame_funs = mol._vf
if frame_index is None:
frame_index = mol._frame_info['frame_index']
else:
print('No frame functions provided')
return
traj = mol.mda_object.trajectory
index = trunc_t_axis(traj.n_frames, n, nr)
if dt is None: dt = traj.dt / 1e3
vec0 = ini_vec_load(traj, frame_funs, frame_index, index, dt)
if mode.lower() == 'both':
vecs, avgs, tensors = applyFrame(vec0, mode='full')
vecs_z, _, _ = applyFrame(vec0, mode='z')
return vecs, vecs_z, avgs, tensors
else:
vecs, avgs, tensors = applyFrame(vec0)
return vecs, avgs, tensors
def frames2Ct(mol, mode='separate', n=10, nr=10, dt=None):
"""
Sets up calculation of a correlation function from a molecule object. In
'full' mode or 'P2' mode, this will simply return the correlation functions
otherwise found in a data object (use frames2data). However, if the separated
correlation functions are desired, then one must use this function for setup
since the array dimensionality is incompatible with the 'data' object.
ct,avgs,tensors = frames2Ct(mol,mode='separate',n=10,nr=10,dt=None)
or for just the correlation functions (no frame index will be applied)
ct=frames2Ct(frame_funs,mode='separate',n=10,nr=10,dt=None)
"""
if dt is None: dt = mol.mda_object.trajectory.dt / 1e3
index = trunc_t_axis(mol.mda_object.trajectory.n_frames, n, nr)
vecs,avgs,tensors=get_vecs(mol=mol,frame_funs=mol._vf,frame_index=mol._frame_info['frame_index'],\
mode=mode,n=n,nr=nr,dt=dt)
ct = list()
for v in vecs:
if 'vX' in v.keys():
ct.append(
Ct(vZ=v['vZ'],
vX=v['vX'],
vY=v['vY'],
mode='separate',
index=index,
avgs=None,
dt=dt))
else:
ct.append(Ct(vZ=v['vZ'], index=index, dt=dt))
return ct, avgs, tensors
def get_vecs(mol,frame_funs=None,frame_index=None,ffavg='direction',n=100,nr=10,**kwargs):
"Get the set of frame functions"
if frame_funs is None:
if mol._vf is not None:
frame_funs=mol._vf
if frame_index is None:
frame_index=mol._frame_info['frame_index']
else:
print('No frame functions provided')
return
traj=mol.mda_object.trajectory
index=trunc_t_axis(traj.n_frames,n,nr)
dt=[kwargs['dt'] if 'dt' in kwargs else traj.dt/1e3]
vec0=ini_vec_load(traj,frame_funs,frame_index,index,dt)
if ffavg=='eta':
vecs,avgs,tensors=applyFrame2(vec0,return_avgs=True,tensor_avgs=True)
else:
vecs,avgs,tensors=applyFrame(vec0,ffavg,return_avgs=True,tensor_avgs=True)
return vecs,avgs,tensors