DynTrack

Python package for the study of particle dynamics from 2D tracks

Installation

pip install -U dyntrack

Usage

import dyntrack as dt

DT = dt.ut.load_data("tracks.csv","Position X","Position Y","Parent","Time","background.tiff")

dt.tl.vector_field(DT)
dt.pl.vector_field(DT)

dt.tl.FTLE(DT, 20000,5)
dt.pl.FTLE(DT)

dt.tl.fit_ppt(DT,seed=1)
dt.pl.fit_ppt(DT)

Workflow

Source build and run issues with windows

If missing DLL errors occurs while running, or gcc is not available while building from source please install MinGW-w64:

choco install mingw

Citations and used works

Vector field building

The function dyntrack.tl.vector_field uses vfkm to generate vector fields (see license), please cite the related study if you use it:

Ferreira, N., Klosowski, J. T., Scheidegger, C. & Silva, C.
Vector Field k-Means: Clustering Trajectories by Fitting Multiple Vector Fields.
Comput. Graph. Forum 32, 201–210 (2012).

FTLE scalar field generation

Code from dyntrack.tl.FTLE have been adapted and optimized from Richard Galvez's notebook.

Principal tree fitting with SimplePPT

Code from dyntrack.tl.fit_ppt uses SimplePPT algorithm to fit principal trees on each frames. SimplePPT has been described in the following paper:

Mao et al. (2015), SimplePPT: A simple principal tree algorithm
SIAM International Conference on Data Mining.