Last data update: 2014.03.03

 R: Utilities for LSC class
LSC-utilsR Documentation

Utilities for LSC class

Description

The "LSC" class lies at the core of this package as it describes spatio-temporal patterns in the data. It is usually an array with the same spatio-temporal resolution as the original dataset.

plot.LSC plots LSC of (1+1)D and (2+1)D systems.

plot_LSC_1plus1D plots LSC for a (1+1)D field.

plot_LSC_2plus1D plots LSC for a (2+1)D field.

plot_LSC_0plus1D plots LSC for a (0+1)D field, i.e., a time series.

Usage

## S3 method for class 'LSC'
plot(x, ...)

plot_LSC_1plus1D(z, col = NULL, lsc.unit = "bits", heights = c(2, 5), widths = c(5, 
    2))

plot_LSC_2plus1D(z, type = "temporal", time.frames = NULL, zlim = NULL, heights = NULL, 
    lsc.unit = "bits", data = NULL, col = NULL)

plot_LSC_0plus1D(z, col = NULL, lsc.unit = "bits", ...)

Arguments

x

an object of class "LSC"

...

optional arguments passed to plot_LSC_2plus1D or plot_LSC_1plus1D.

widths

passed to layout for dividing the plotting region horizontally. A vector of length 2: image (left) & temporal average (right)

z

an object of class "LSC"

type

a "temporal" or a "spatial" summary plot of LSC

time.frames

a vector of length ≤q 6 to indicate what frames should be displayed (only for type = "temporal"). If NULL (default) then it chooses them automatically based on valleys and peaks in the spatial average LSC.

zlim

minimum and maximum z values for which colors should be plotted, defaulting to the range of the finite values of z.

lsc.unit

character string (default: "bits") to write next to the color legend

col

colors: either a string decribing a pallette from the RColorBrewer package (see also http://colorbrewer2.org/), or a list of colors (see image for suggestions).

data

(optional) original data to compare to LSC (relevant only for type = "spatial")

heights

passed to layout for dividing the plotting region vertically. If data = NULL a vector of length 2; otherwise a vector of length 3.

See Also

plot.mixed_LICORS, plot_LSC_2plus1D, plot_LSC_1plus1D

Examples

## Not run: 
data(contCA00)

temp_lsc <- states2LSC(states = contCA00$predictive_states - 
    min(contCA00$predictive_states) + 1)
class(temp_lsc) <- c("LSC", "LSC_1plus1D")
plot_LSC_1plus1D(temp_lsc)

## End(Not run)
## Not run: 
data(contCA00)

temp_lsc <- states2LSC(states = contCA00$predictive_states - 
    min(contCA00$predictive_states) + 1)
temp_lsc_3D <- array(temp_lsc, dim = c(25, 20, 40))
class(temp_lsc_3D) <- c("LSC", "LSC_2plus1D")
plot_LSC_2plus1D(temp_lsc_3D, type = "temporal")
plot_LSC_2plus1D(temp_lsc_3D, type = "spatial")

## End(Not run)
state.sim <- rpois(100, 1)

lsc.est <- states2LSC(states = state.sim)
class(lsc.est) <- c("LSC", "LSC_0plus1D")
plot_LSC_0plus1D(lsc.est)

weights.sim <- matrix(runif(1000, 0, 1), ncol = 10)
weights.sim <- normalize(weights.sim)
lsc.est <- states2LSC(weight.matrix = weights.sim)
plot_LSC_0plus1D(lsc.est)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(LSC)
Loading required package: LICORS
Loading required package: RColorBrewer
Loading required package: fields
Loading required package: spam
Loading required package: grid
Spam version 1.3-0 (2015-10-24) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: 'spam'

The following objects are masked from 'package:base':

    backsolve, forwardsolve

Loading required package: maps

 # maps v3.1: updated 'world': all lakes moved to separate new #
 # 'lakes' database. Type '?world' or 'news(package="maps")'.  #


Loading required package: gam
Loading required package: splines
Loading required package: foreach
Loaded gam 1.12

Loading required package: Matrix
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/LSC/LSC-utils.Rd_%03d_medium.png", width=480, height=480)
> ### Name: LSC-utils
> ### Title: Utilities for LSC class
> ### Aliases: LSC-utils plot.LSC plot_LSC_0plus1D plot_LSC_1plus1D
> ###   plot_LSC_2plus1D
> ### Keywords: hplot
> 
> ### ** Examples
> 
> ## Not run: 
> ##D data(contCA00)
> ##D 
> ##D temp_lsc <- states2LSC(states = contCA00$predictive_states - 
> ##D     min(contCA00$predictive_states) + 1)
> ##D class(temp_lsc) <- c("LSC", "LSC_1plus1D")
> ##D plot_LSC_1plus1D(temp_lsc)
> ## End(Not run)
> ## Not run: 
> ##D data(contCA00)
> ##D 
> ##D temp_lsc <- states2LSC(states = contCA00$predictive_states - 
> ##D     min(contCA00$predictive_states) + 1)
> ##D temp_lsc_3D <- array(temp_lsc, dim = c(25, 20, 40))
> ##D class(temp_lsc_3D) <- c("LSC", "LSC_2plus1D")
> ##D plot_LSC_2plus1D(temp_lsc_3D, type = "temporal")
> ##D plot_LSC_2plus1D(temp_lsc_3D, type = "spatial")
> ## End(Not run)
> state.sim <- rpois(100, 1)
> 
> lsc.est <- states2LSC(states = state.sim)
> class(lsc.est) <- c("LSC", "LSC_0plus1D")
> plot_LSC_0plus1D(lsc.est)
> 
> weights.sim <- matrix(runif(1000, 0, 1), ncol = 10)
> weights.sim <- normalize(weights.sim)
> lsc.est <- states2LSC(weight.matrix = weights.sim)
> plot_LSC_0plus1D(lsc.est)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and IMSBIO