mst_from_trj: Create the minimum spanning tree from time series
In CampaR1: Trajectory Analysis

Description Usage Arguments Details Value See Also Examples

View source: R/loader.R

mst_from_trj creates a minimum spanning tree from a time series (e.g. a trajectory in molecular dynamics) using different distance metrics between pairwise snapshots.

mst_from_trj(trj, distance_method = 5, distance_weights = NULL,
  clu_radius = NULL, clu_hardcut = NULL, normalize_d = TRUE,
  birch_clu = FALSE, min_span_tree = TRUE, mode = "fortran",
  rootmax_rad = NULL, tree_height = NULL, n_search_attempts = NULL,
  cores = NULL, logging = FALSE)

`trj`	Input trajectory (variables on the columns and equal-time spaced snpashots on the row). It must be a `matrix` or a `data.frame` of numeric.
`distance_method`	Distance metric between snapshots. This value can be set 1 (dihedral angles) or 5 (root mean square deviation).
`distance_weights`	Vector of weights to be applied in order to compute averaged weighted distance using multiple `distance_method`. Each value must be between 0 and 1. This option works only if `birch_clu=F`.
`clu_radius`	This numeric argument is used in the clustering step in order to make clusters of the same radius at the base level.
`clu_hardcut`	This option is used only with `birch_clu=F` and defines the inter-clusters distance threshold.
`normalize_d`	A logical that indicates whether the distances must be normalized or not. Usually used with averaging.
`birch_clu`	A logical that indicates whether the algorithm will use a birch-tree like clustering step (short spanning tree - fast) or it will be generated using a simple leader clustering algorithm (minimum spanning tree).
`min_span_tree`	This option is used only with `birch_clu=F` and defines if the returning adjacency list must be a minimum spanning tree.
`mode`	It takes a string in input and can be either "fortran" (highly advised and default) or "R".
`rootmax_rad`	If `birch_clu=T` this option defines the maximum radius at the root level of the tree in the advanced clustering algorithm.
`tree_height`	If `birch_clu=T` this option defines the height of the tree in the advanced clustering algorithm.
`n_search_attempts`	If `birch_clu=T` a number of search attempts must be provided for the minimum spanning tree search.
`cores`	If `mode="R"` a complete adjacency matrix can be created in parallel using multiple cores (anyhow slower than "fortran" mode).
`logging`	If `logging=T` the function will print to file the fortran messages ("campari.log").

For details, please refer to the main documentation of the original campari software http://campari.sourceforge.net/documentation.html.

If no netcdf support is available the function will return a list with 3 arguments: node degrees, adjacency list and associated distances. If netcdf support is activated the function will dump the mst in the file "DUMPLING.nc".

adjl_from_progindex, gen_progindex, gen_annotation.

adjl <- mst_from_trj(trj = matrix(rnorm(1000), nrow = 100, ncol = 10))

## Not run: 
adjl <- mst_from_trj(trj = matrix(rnorm(1000),ncol=10,nrow=100),
distance_method = 5, clu_radius = 100, clu_hardcut = 100,
birch_clu = FALSE, mode = "fortran", logging = FALSE)

adjl <- adjl_from_trj(trj = matrix(rnorm(1000),ncol=10,nrow=100),
distance_method = 5, clu_radius = 0.1,
birch_clu = TRUE, mode = "fortran", rootmax_rad = 1.3, logging = FALSE,
tree_height = 5, n_search_attempts = 50)

## End(Not run)