Pcp-class {ClusterSignificance} | R Documentation |
Project points onto a principal curve.
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)
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 |
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().
The pcp function returns an object of class Pcp
Jesper R. Gadin and Jason T. Serviss
#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)