Probabilistic state annotation - vanTeeffelenLab/ExTrack GitHub Wiki
The following function allows to compute state probabilities for each track at every time points given the parameters of the model.
extrack.tracking.predict_Bs
Function pred_Bs = extrack.tracking.predict_Bs(all_tracks,
dt,
params,
cell_dims=[1],
nb_states=2,
frame_len=8,
workers = 1,
input_LocErr = None)
Arguments:
all_tracks
: dictionary describing the tracks with track length as keys (number of time positions, e.g. '23') of 3D arrays: dim 0 = track, dim 1 = time position, dim 2 = x, y position. This means 15 tracks of 7 time points in 2D will correspond to an array of shape [15,7,2].params
: lmfit parameters used for the model.dt
: time in between frames.cell_dims
: dimension limits (um). estimated_vals, min_values, max_values should be changed accordingly to describe all states and transitions.nb_states
: number of states. estimated_vals, min_values, max_values should be changed accordingly to describe all states and transitions.frame_len
: number of frames for which the probability is perfectly computed. See method of the paper for more details.
Outputs:
pred_Bs
: dictionary describing the state probability of each track for each time position with track length as keys (number of time positions, e.g. '23') of 3D arrays: dim 0 = track, dim 1 = time position, dim 2 = state.