Module: landmarks
| Description | Usage |
|---|---|
| various tools for selecting a subset of points from an input vector/matrix | |
| Authors: Gareth Tribello |   |
Details
The tools in this module take a vector or matrix as input and return a vector or matrix that contains a subset of the points in the input vector/matrix that have been chosen in some systematic way. These tools were developed to be used in conjuction with the tools in the dimred module. However, the landmark selection algorithms in this module may also find an application in some other context.
Actions
The following actions are part of this module
| Name | Description | Tags |
|---|---|---|
| COLLECT_FRAMES | Collect atomic positions or argument values from the trajectory for later analysis | ANALYSIS |
| FARTHEST_POINT_SAMPLING | Select a set of landmarks using farthest point sampling. | LANDMARKS |
| LANDMARK_SELECT_FPS | Select a of landmarks from a large set of configurations using farthest point sampling. | LANDMARKS |
| LANDMARK_SELECT_RANDOM | Select a random set of landmarks from a large set of configurations. | LANDMARKS |
| LANDMARK_SELECT_STRIDE | Select every ith frame from the stored set of configurations | LANDMARKS |
| LOGSUMEXP | This action takes the exponential of a vector of logarithms and divides each element of the vector by the sum of the exponentials. | ANALYSIS |
References
More information about this module is available in the following articles:
- G. A. Tribello, P. Gasparotto, "Using Data-Reduction Techniques to Analyze Biomolecular Trajectories" in Biomolecular Simulations (Springer New York, 2019; http://dx.doi.org/10.1007/978-1-4939-9608-7_19), pp. 453–502
- G. A. Tribello, P. Gasparotto, Using Dimensionality Reduction to Analyze Protein Trajectories. Frontiers in Molecular Biosciences. 6 (2019)