plotBarrierTree2D: Plot Barrier Tree in 2D

Description Usage Arguments Details Value Examples


Creates a 2D image containing the barrier tree of this cell mapping.


plotBarrierTree2D(feat.object, control)



A feature object as created by createFeatureObject.


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


Possible control arguments are:

  • Computation of Cell Mapping:

    • 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.

  • Plot Control:

    • bt.cm_surface: Should the underlying surface be based on a cell mapping plot (default is TRUE)? Alternatively, the cells would be coloured in shades of grey - according to their objective values.

    • bt.margin: Margins of the plot as used by par("mar"). The default is c(5, 5, 4, 4).

    • bt.color_surface: Color of the surface of the perspective plot. The default is "lightgrey".

    • bt.color_branches: Color used for the branches of the barrier tree. Per default there will be one color per level.

    • bt.pch_root: Symbol used for plotting the root. The default is 17 (filled triangle).

    • bt.pch_breakpoint: Symbol used for plotting a breakpoint. The default is 5 (non-filled diamond).

    • bt.pch_basin: Symbol used for plotting the leaf (i.e. a basin) of the barrier tree. The default is 19 (filled circle).

    • bt.col_root: Color of the root symbol. The default is "red".

    • bt.lwd: Width of the lines used for plotting the branches of a barrier tree. The default is 2.

    • bt.label.{x, y}_coord: Label of the x-/y-coordinate (below / left side of the plot).

    • bt.label.{x, y}_id: Label of the x-/y-cell ID (above / right side of the plot).


A 2D image, visualizing the barrier tree of this cell mapping.


# create a feature object
X = createInitialSample(n.obs = 900, dim = 2)
f = smoof::makeAckleyFunction(dimensions = 2)
y = apply(X, 1, f)
feat.object = createFeatureObject(X = X, y = y, fun = f, blocks = c(4, 6))

# plot the corresponing barrier tree

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