Dataset generated by TrajPy for training a trajectory classifier. For more details: https://trajpy.readthedocs.io Classes: normal diffusion, direct motion, anomalous diffusion and confined. Columns: alpha: anomalous exponent ratio: mean squared displacement ratio df: fractal dimension anisotropy: radius of gyration anisotropy kurtosis: radius of gyration kurtosis straightness: similarity to a straight trajectory gaussianity: similarity to a Gaussian distribution trappedness: probability of being trapped diffusivity: short-time diffusion coefficient efficiency: movement efficienc
Datasets used as examples in "Learning Anisotropic Interaction Rules from Individual Trajectories in...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Teetool is a Python package which models and visualises motion patterns found in two- and three-dime...
The anomalous diffusion classification classifiers used in: J. Janczura, P. Kowalek, H. Loch-Olszews...
This DOI contains an example of the implementation of a Random Forest algorithm for the characterisa...
Single-particle tracking is a powerful approach to study the motion of individual molecules and part...
An updated, stable and maintained version of this code can be found in https://github.com/AnDiChall...
[EN] In order to study transport in complex environments, it is extremely important to determine the...
Due to the advent of new mobile devices and tracking sensors in recent years, huge amounts of data a...
We introduce a representation learning framework for spatial trajectories. We represent partial obse...
Kurtosis now is computed as a function of the projection of the trajectory along the principal axis....
Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport d...
Rizk et al. Trajectory data analysis in support of understanding movement pattern
Teetool is a Python package which models and visualises motion patterns found in two- and three-dime...
We propose a segmentation and feature extraction method for trajectories of moving objects. The meth...
Datasets used as examples in "Learning Anisotropic Interaction Rules from Individual Trajectories in...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Teetool is a Python package which models and visualises motion patterns found in two- and three-dime...
The anomalous diffusion classification classifiers used in: J. Janczura, P. Kowalek, H. Loch-Olszews...
This DOI contains an example of the implementation of a Random Forest algorithm for the characterisa...
Single-particle tracking is a powerful approach to study the motion of individual molecules and part...
An updated, stable and maintained version of this code can be found in https://github.com/AnDiChall...
[EN] In order to study transport in complex environments, it is extremely important to determine the...
Due to the advent of new mobile devices and tracking sensors in recent years, huge amounts of data a...
We introduce a representation learning framework for spatial trajectories. We represent partial obse...
Kurtosis now is computed as a function of the projection of the trajectory along the principal axis....
Deviations from Brownian motion leading to anomalous diffusion are ubiquitously found in transport d...
Rizk et al. Trajectory data analysis in support of understanding movement pattern
Teetool is a Python package which models and visualises motion patterns found in two- and three-dime...
We propose a segmentation and feature extraction method for trajectories of moving objects. The meth...
Datasets used as examples in "Learning Anisotropic Interaction Rules from Individual Trajectories in...
Dynamic Movement Primitives (DMP) are nowadays widely used as movement parametrization for learning ...
Teetool is a Python package which models and visualises motion patterns found in two- and three-dime...