flacco (version 1.2)

plotCellMapping: Plot Cell Mapping

Description

Visualizes the transitions among the cells in the General Cell Mapping approach.

Usage

plotCellMapping(feat.object, control)

Arguments

feat.object

[FeatureObject] A feature object as created by createFeatureObject.

control

[list] A list, which stores additional control arguments. For further information, see details.

Value

• [plot].

item

• Plot Control
• gcm.color_attractor
• gcm.color_uncertain
• gcm.color_basin
• gcm.plot_arrows
• gcm.arrow.length_{x, y}
• gcm.arrowhead.{length, width}
• gcm.arrowhead.type
• gcm.color_grid
• gcm.label.{x, y}_coord
• gcm.label.{x, y}_id
• gcm.plot_{coord, id}_labels

itemize

• gcm.margin

code

TRUE

Details

Possible control arguments are:

• Computation of GCM Features

:

• gcm.approach

: Which approach should be used when computing the representatives of a cell. The default is "min", i.e. the observation with the best (minimum) value within per cell. gcm.cf_power: Theoretically, we need to compute the canonical form to the power of infinity. However, we use this value as approximation of infinity. The default is 256.

References

• Kerschke, P., Preuss, M., Hernandez, C., Schuetze, O., Sun, J.-Q., Grimme, C., Rudolph, G., Bischl, B., and Trautmann, H. (2014)

: Cell Mapping Techniques for Exploratory Landscape Analysis, in: EVOLVE -- A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V, pp. 115-131 (http://dx.doi.org/10.1007/978-3-319-07494-8_9).

Examples

# (1) Define a function:
library(smoof)
f = makeHosakiFunction()

# (2) Create a feature object:
X = cbind(
  x1 = runif(n = 100, min = -32, max = 32),
  x2 = runif(n = 100, min = 0, max = 10)
)
y = apply(X, 1, f)
feat.object = createFeatureObject(X = X, y = y, blocks = c(4, 6))

# (3) Plot the cell mapping:
plotCellMapping(feat.object)