Inferring a trajectory inference using ElPiGraph

Will generate a trajectory using ElPiGraph.

This method was wrapped inside a container. The original code of this method is available here.

ti_elpigraph(topology = "tree", NumNodes = 50L, NumEdges = 100000L,
  InitNodes = 2L, Mu = 0.1, Lambda = 0.01,
  MaxNumberOfIterations = 10L, eps = 0.01, CenterData = FALSE,
  run_environment = NULL)

Arguments

topology	discrete; The kind of topology to detect (default: "tree"; values: "cycle", "tree", "linear")
NumNodes	integer; The number of nodes of the principal graph (default: 50L; range: from 2L to 1000L)
NumEdges	integer; The maximum number of edges (default: 100000L; range: from 2L to 100000L)
InitNodes	integer; Number of points to include in the initial graph (default: 2L; range: from 2L to 1000L)
Mu	numeric; Controls the elastic energy (default: 0.1; range: from 0.001 to 1L)
Lambda	numeric; Controls the elastic energy (default: 0.01; range: from 0.001 to 1L)
MaxNumberOfIterations	integer; Maximum number of steps to embed the nodes (default: 10L; range: from 1L to 1000L)
eps	numeric; Minimal relative change in the position of the nodes to stop embedment (default: 0.01; range: from 0.001 to 1L)
CenterData	logical; Should data and initial node positions be centered?
run_environment	In which environment to run the method, can be "docker" or "singularity".

Value

A TI method wrapper to be used together with infer_trajectory