def _run_multiple(trj, mol):
D_pop = list()
for start_frame in np.linspace(0, 4999, num=200, dtype=np.int):
end_frame = start_frame + 400
if end_frame < 5000:
chunk = trj[start_frame:end_frame]
print('\t\t\t...frame {} to {}'.format(start_frame, end_frame))
try:
D_pop.append(calc_msd(chunk)[0])
except TypeError:
import pdb
pdb.set_trace()
else:
continue
D_bar = np.mean(D_pop)
D_std = np.std(D_pop)
return D_bar, D_std
def _run_multiple(trj, dims):
D_pop = list()
msd_pop = list()
for start_frame in np.linspace(0, trj.n_frames, num=200, dtype=np.int):
end_frame = start_frame + 1000
if end_frame < trj.n_frames:
chunk = trj[start_frame:end_frame]
print('\t\t\t...frame {} to {}'.format(start_frame, end_frame))
try:
D, msd, x_fit, y_fit = calc_msd(chunk, dims=dims)
D_pop.append(D)
msd_pop.append(msd)
except TypeError:
import pdb
pdb.set_trace()
else:
continue
D_bar = np.mean(D_pop)
D_std = np.std(D_pop)
msd_bar = np.mean(msd_pop, axis=0)
return D_bar, D_std, msd_bar
def _run_overall(trj, mol):
D, MSD, x_fit, y_fit = calc_msd(trj)
return D, MSD