Python package for the study of particle dynamics from 2D tracks
Project description
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.
Project details
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Source Distribution
dyntrack-1.1.2.tar.gz
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