MGC: Moving Generator Cluster

In stream: Infrastructure for Data Stream Mining

Moving Generator Cluster

Description

Creates an evolving cluster for use as a component of a DSD_MG data stream.

Usage

MGC(...)

MGC_Function(density, center, parameter, shape = Shape_Gaussian)

MGC_Linear(dimension = 2, keyframelist = NULL, shape = Shape_Gaussian)

keyframe(time, density, center, parameter, reset = FALSE)

add_keyframe(x, time, density, center, parameter, reset = FALSE)

get_keyframes(x)

remove_keyframe(x, time)

MGC_Noise(density, range)

MGC_Random(density, center, parameter, randomness = 1, shape = Shape_Gaussian)

Shape_Gaussian(center, parameter)

Shape_Block(center, parameter)

MGC_Static(density = 1, center, parameter, shape = Shape_Gaussian)

Arguments

...	Further arguments.
density	The density of the cluster. For 'MGC_Function, this attribute is a function and defines the density of a cluster (i.e., how many points it creates) at each given timestamp.
center	A list that defines the center of the cluster. The list should have a length equal to the dimensionality. For MGC_Function, this list consists of functions that define the movement of the cluster. For MGC_Random, this attribute defines the beginning location for the MGC before it begins moving.
parameter	Parameters for the shape. For the default shape Shape_Gaussian the parameter is the standard deviation, one per dimension. If a single value is specified then it is recycled for all dimensions.
shape	A function creating the shape of the cluster. It gets passed on the parameters argument from above. Available functions are Shape_Gaussian (the parameters are a vector containing standard deviations) and Shape_Block (parameters are the dimensions of the uniform block).
dimension	Dimensionality of the data stream.
keyframelist	a list of keyframes to initialize the MGC_Linear object with.
time	The time stamp the keyframe should be located or which keyframe should be removed.
reset	Should the cluster reset to the first keyframe (time 0) after this keyframe is finished?
x	An object of class MGC_Linear.
range	The area in which the noise should appear.
randomness	The maximum amount the cluster will move during one time step.

Details

An MGC describes a single cluster for use as a component in a DSD_MG. Different MGCs allow the user to express different cluster behaviors within a single data stream. Static, (i.e., not moving) clusters are defined as:

• MGC_Static cluster positions are fixed

• MGC_Noise allows to add random noise.

Moving (evolving) clusters are defined as:

• MGC_Linear creates an evolving cluster for a who's behavior is determined by keyframes. Several keyframe functions are provided to create, add and remove keyframes. See Examples section for details.

• MGC_Function allows to specify density, center, and parameter as a function of time.

• MGC_Random allows for a creation of a cluster that follows a random walk.

Cluster shapes can be specified using the functions:

• Shape_Gaussian

• Shape_Block

New shapes can be defined as a function with parameters center and parameter that return a single new point. Here is an example:

Shape_Gaussian <- function(center, parameter)
   rnorm(length(center), mean = center, sd = parameter)

Author(s)

Matthew Bolanos

See Also

DSD_MG for details on how to use an MGC within a DSD.

Examples

MGC()

### Two static clusters (Gaussian with sd of .1 and a Block with width .4)
###   with added noise
stream <- DSD_MG(dim = 2,
  MGC_Static(den = .45, center = c(1, 0), par = .1, shape = Shape_Gaussian),
  MGC_Static(den = .45, center = c(2, 0), par = .4, shape = Shape_Block),
  MGC_Noise( den = .1, range = rbind(c(0, 3), c(-1,1)))
)
stream

plot(stream)

### Example of several MGC_Randoms which define clusters that randomly move.
stream <- DSD_MG(dim = 2,
  MGC_Random(den = 100, center=c(1, 0), par = .1, rand = .2),
  MGC_Random(den = 100, center=c(2, 0), par = .4, shape = Shape_Block, rand = .2)
)

## Not run: 
  animate_data(stream, 2500, xlim = c(0,3), ylim = c(-1,1), horizon = 100)

## End(Not run)


### Example of several MGC_Functions

### a block-shaped cluster moving from bottom-left to top-right increasing size
c1 <- MGC_Function(
  density = function(t){ 100 },
  parameter = function(t){ 1 * t },
  center = function(t) c(t, t),
  shape = Shape_Block
  )

### a cluster moving in a circle (default shape is Gaussian)
c2 <- MGC_Function(
  density = function(t){ 25 },
  parameter = function(t){ 5 },
  center= function(t) c(sin(t / 10) * 50 + 50, cos(t / 10) * 50 + 50)
)

stream <- DSD_MG(dim = 2, c1, c2)

## adding noise after the stream was created
add_cluster(stream, MGC_Noise(den = 10, range = rbind(c(-20, 120), c(-20, 120))))

stream

## Not run: 
animate_data(stream, 10000, xlim = c(-20, 120), ylim = c(-20, 120), horizon = 100)

## End(Not run)

### Example of several MGC_Linear: A single cluster splits at time 50 into two.
### Note that c2 starts at time = 50!
stream <- DSD_MG(dim = 2)
c1 <- MGC_Linear(dim = 2)
add_keyframe(c1, time = 1,  dens = 50, par = 5, center = c(0, 0))
add_keyframe(c1, time = 50, dens = 50, par = 5, center = c(50, 50))
add_keyframe(c1, time = 100,dens = 50, par = 5, center = c(50, 100))
add_cluster(stream, c1)

c2 <- MGC_Linear(dim = 2, shape = Shape_Block)
add_keyframe(c2, time = 50, dens = 25, par = c(10, 10), center = c(50, 50))
add_keyframe(c2, time = 100,dens = 25, par = c(30, 30), center = c(100, 50))
add_cluster(stream, c2)

## Not run: 
animate_data(stream, 5000, xlim = c(0, 100), ylim = c(0, 100), horiz = 100)

## End(Not run)

### two fixed and a moving cluster
stream <- DSD_MG(dim = 2,
  MGC_Static(dens = 1, par = .1, center = c(0, 0)),
  MGC_Static(dens = 1, par = .1, center = c(1, 1)),
  MGC_Linear(dim = 2, list(
    keyframe(time = 0,    dens = 1, par = .1, center = c(0, 0)),
    keyframe(time = 1000, dens = 1, par = .1, center = c(1, 1)),
    keyframe(time = 2000, dens = 1, par = .1, center = c(0, 0), reset = TRUE)
  )))

noise <- MGC_Noise(dens = .1, range = rbind(c(-.2, 1.2), c(-.2, 1.2)))
add_cluster(stream, noise)

## Not run: 
animate_data(stream, n = 2000 * 3.1, xlim = c(-.2, 1.2), ylim = c(-.2, 1.2), horiz = 200)

## End(Not run)

stream documentation built on May 29, 2024, 9:43 a.m.