Pcp-class {ClusterSignificance} | R Documentation

## Projection of points into one dimension.

### Description

Project points onto a principal curve.

### Usage

    getData(x, ...)

    ## S4 method for signature 'Pcp'
    getData(x, n = NULL)

    ## S4 method for signature 'Pcp'
    initialize(.Object, ..., classes, points.orig, line,
      points.onedim, index, class.color)

    ## S4 method for signature 'Pcp,missing'
    plot(x, y, steps = "all", class.color = NULL, ...)

    pcp(mat, ...)

    ## S4 method for signature 'matrix'
    pcp(mat, classes, df = NULL, warn = TRUE,
      class.color = NULL, ...)

    ## S4 method for signature 'Pcp'
    show(object)

### Arguments

`x` | matrix object for the function pcp otherwise it is a Pcp object
`...` | additional arguments to pass on
`n` | data to extract from Pcp (NULL gives all)
`.Object` | internal object
`classes` | vector in same order as rows in matrix
`points.orig` | multidimensional points describing the original data
`line` | multidimensional points describing a line
`points.onedim` | a vector of points
`index` | internal index from the projection
`class.color` | user assigned group coloring scheme
`y` | default plot param, which should be set to NULL
`steps` | 1,2,3,4,5,6 or "all"
`mat` | matrix with samples on rows, PCs in columns. Ordered PCs, with PC1 to the left.
`df` | degrees of freedom, passed to smooth.spline
`warn` | logical indicating if a change in the default df argument should generate a warning. mostly for internal use.
`object` | Pcp object

### Details

The resulting Pcp object containing results from a principal curve reduction to one dimension. The group and the one dimensional points will be the information needed to carry out a classification using the classify() function. As a help to illustrate the details of the dimension reduction, the information from some critical steps is stored in the object. To visually explore these there is a dedicated plot method for Pcp objects, use plot().

### Value

The pcp function returns an object of class Pcp

### Author(s)

Jesper R. Gadin and Jason T. Serviss

### Examples

    #use demo data
    data(pcpMatrix)
    classes <- rownames(pcpMatrix)

    #run function
    prj <- pcp(pcpMatrix, classes)

    #getData accessor
    getData(prj)

    #getData accessor specific
    getData(prj, "line")

    #plot the result (if dim >2, then plot in 3d)
    plot(prj)

    #plot the result (if dim=2, then plot in 2d)
    prj2 <- pcp(pcpMatrix[,1:2], classes)
    plot(prj2)

[Package ClusterSignificance version 1.20.0 Index]