Data format

tidynamics assumes that the data is provided as NumPy arrays where the first index indicates the timestep and the second index, if it exists, indicates in the spatial coordinates of the trajectory. Data is assumed to be sampled at equal time intervals.

For a 2D position dataset pos, \(x(t)\) is stored in pos[:,0] and \(y(t)\) is stored in pos[:,1], as we show in the example below:

Index i	pos[i,0]	pos[i,1]
0	x(0)	y(0)
1	x(1)	y(1)
2	x(2)	y(2)
…	…	…

By default, NumPy’s np.loadtxt routine returns this organization for columnar files. In the example code below, we load the example data file random_walk_sample_0.txt.gz in the variable pos and compute the corresponding mean-square displacement with tidynamics.

import numpy as np
import tidynamics
pos = np.loadtxt('random_walk_sample_0.txt.gz')
msd = tidynamics.msd(pos)