fastclime.plot: Graph visualization

In fastclime: A Fast Solver for Parameterized LP Problems, Constrained L1 Minimization Approach to Sparse Precision Matrix Estimation and Dantzig Selector

Description

Implements the graph visualization using adjacency matrix. It can automatic organize 2D embedding layout.

Usage

fastclime.plot(G, epsflag = FALSE, graph.name = "default", cur.num = 1, 
location)

Arguments

G	The adjaceny matrix corresponding to the graph.
epsflag	If epsflag = TRUE, save the plot as an eps file in the target directory. The default value is FALSE.
graph.name	The name of the output eps files. The default value is "default".
cur.num	The number of plots saved as eps files. Only applicale when epsflag = TRUE. The default value is 1.
location	Target directory. The default value is the current working directory.

Details

The user can change cur.num to plot several figures and select the best one. The implementation is based on the popular package "igraph".

Author(s)

Haotian Pang, Han Liu and Robert Vanderbei
Maintainer: Haotan Pang<[e-mail]>

See Also

fastclime and fastclime-package

Examples

## visualize the hub graph
L = fastclime.generator(graph = "hub")
fastclime.plot(L$theta)

## visualize the band graph
L = fastclime.generator(graph = "band",g=5)
fastclime.plot(L$theta)

## visualize the cluster graph
L = fastclime.generator(graph = "cluster")
fastclime.plot(L$theta)

#show working directory
getwd()
#plot 5 graphs and save the plots as eps files in the working directory  
fastclime.plot(L$theta, epsflag = TRUE, cur.num = 5)

fastclime documentation built on May 2, 2019, 1:06 p.m.