animate_cluster: Animates Plots of the Clustering Process

In stream: Infrastructure for Data Stream Mining

Animates Plots of the Clustering Process

Description

Generates an animation of a data stream clustering process.

Usage

animate_cluster(
  dsc,
  dsd,
  measure = NULL,
  horizon = 100,
  n = 1000,
  type = c("auto", "micro", "macro"),
  assign = "micro",
  assignmentMethod = c("auto", "model", "nn"),
  excludeNoise = FALSE,
  wait = 0.1,
  plot.args = NULL,
  ...
)

Arguments

dsc	a DSC
dsd	a DSD
measure	the evaluation measure that should be graphed below the animation (see evaluate_stream().)
horizon	the number of points displayed at once/used for evaluation.
n	the number of points to be plotted
type, assign, assignmentMethod, excludeNoise	are passed on to evaluate_stream() to calculate the evaluation measure.
wait	the time interval between each frame
plot.args	a list with plotting parameters for the clusters.
...	extra arguments are added to plot.args.

Details

Animations are recorded using the library animation and can be replayed (which gives a smoother experience since the is no more computation done) and saved in various formats (see Examples section below).

Note: You need to install package animation and its system requirements.

Author(s)

Michael Hahsler

See Also

animation::ani.replay() for replaying and saving animations.

Other DSC: DSC_Macro(), DSC_Micro(), DSC_R(), DSC_SlidingWindow(), DSC_Static(), DSC_TwoStage(), DSC(), evaluate.DSC, get_assignment(), plot.DSC(), predict(), prune_clusters(), read_saveDSC, recluster()

Other plot: animate_data(), plot.DSC(), plot.DSD()

Other evaluation: evaluate.DSC, evaluate

Examples

if (interactive()) {
stream <- DSD_Benchmark(1)

### animate the clustering process with evaluation
### Note: we choose to exclude noise points from the evaluation
###       measure calculation, even if the algorithm would assign
###       them to a cluster.
dbstream <- DSC_DBSTREAM(r = .04, lambda = .1, gaptime = 100, Cm = 3,
  shared_density = TRUE, alpha = .2)

animate_cluster(dbstream, stream, horizon = 100, n = 5000,
  measure = "crand", type = "macro", assign = "micro",
  plot.args = list(xlim = c(0, 1), ylim = c(0, 1), shared = TRUE))
}

stream documentation built on March 7, 2023, 6:09 p.m.