plotTensorBF {tensorBF}

Plot Tensor Components

Description

plotTensorBF shows the heatmap of components inferred by tensorBF.

Usage

plotTensorBF(res, Y = NULL, k = 1, modesOnAxis = c(1, 2, 3),
  nTopFeatures = c(5, 15, 3), margins = c(4, 4, 4, 12), cex.axis = 1,
  cols = colorRampPalette(c("blue", "white", "red"))(101), key = TRUE,
  plimit = NULL)

Arguments

res

The learned tensorBF model.

Y

The original input data to be plotted. If specified NULL, the function plots the data reconstruction using reconstructTensorBF (default: NULL).

k

the component number to visualize (default: 1).

modesOnAxis

which mode to plot on each axis c(Yaxis,Xaxis,lateral). Defaults to c(1,2,3).

nTopFeatures

The number of most relevant features to show for the data space visualizations in each of the modes. Defaults to c(5,15,3) for displaying top 10 features of 1^{st} mode, 20 of 2^{nd} mode and 5 of 3^{rd} mode.

margins

numeric vector of length 4 containing the margins (see par(mar= *))

cex.axis

positive numbers, used as cex.axis (default: 1)

cols

colors used for the image. Defaults to a blue-white-red color scale.

key

logical indicating whether a color-key should be drawn.

plimit

(optional) numerical number indicating the maximum absolute value to be plotted in the heatmap.

Examples

#Data generation
K <- 3
X <- matrix(rnorm(20*K),20,K)
W <- matrix(rnorm(30*K),30,K)
U <- matrix(rnorm(3*K),3,K)
Y = 0
for(k in 1:K) Y <- Y + outer(outer(X[,k],W[,k]),U[,k])
 Y <- Y + array(rnorm(20*30*3,0,0.25),dim=c(20,30,3))

#Run the method with default options
## Not run: res1 <- tensorBF(Y)
## Not run: plotTensorBF(res = res1,Y=Y,k=1)