Plot Data Stream Data

Method to plot data stream data. To plot DSC see plot.DSC().

Usage

# S3 method for class 'DSD'
plot(
  x,
  n = 500,
  col = NULL,
  pch = NULL,
  ...,
  method = c("pairs", "scatter", "pca", "ts"),
  dim = NULL,
  alpha = 0.6,
  transform = NULL
)

Arguments

x

the DSD object to be plotted.

n

number of plots taken from x to plot.

col

colors used for points.

pch

symbol type.

...

further arguments are passed on to graphics::plot.default() or graphics::pairs().

method

method used for plotting: "pairs" (pairs plot), "scatter" (scatter plot), "pca" (plot first 2 principal components), or "ts" (time series).

dim

an integer vector with the dimensions to plot. If NULL then for methods pairs and "pca" all dimensions are used and for "scatter" the first two dimensions are plotted.

alpha

alpha shading used to plot the points.

transform

a function that maps data stream points onto a 2-D plane for plotting.

See also

Other DSD: DSD(), DSD_BarsAndGaussians(), DSD_Benchmark(), DSD_Cubes(), DSD_Gaussians(), DSD_MG(), DSD_Memory(), DSD_Mixture(), DSD_NULL(), DSD_ReadDB(), DSD_ReadStream(), DSD_Target(), DSD_UniformNoise(), DSD_mlbenchData(), DSD_mlbenchGenerator(), DSF(), animate_data(), close_stream(), get_points(), reset_stream()

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

Author

Michael Hahsler

Examples

stream <- DSD_Gaussians(k=3, d=3)

## plot data
plot(stream, n = 500)

plot(stream, method = "pca", n = 500)

plot(stream, method = "scatter", dim = c(1, 3), n = 500)


## create and plot micro-clusters
dstream <- DSC_DStream(gridsize = 0.1)
update(dstream, stream, 500)
plot(dstream)


## plot with data, projected on the first two principal components
## and dimensions 2 and 3
plot(dstream, stream)

plot(dstream, stream, method = "pca")

plot(dstream, stream, dim = c(2, 3))


## plot micro and macro-clusters
plot(dstream, stream, type = "both")


## plot a time series using the AirPassenger data with the total monthly
## passengers from 1949 to 1960) a as a stream
AirPassengers
#>      Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
#> 1949 112 118 132 129 121 135 148 148 136 119 104 118
#> 1950 115 126 141 135 125 149 170 170 158 133 114 140
#> 1951 145 150 178 163 172 178 199 199 184 162 146 166
#> 1952 171 180 193 181 183 218 230 242 209 191 172 194
#> 1953 196 196 236 235 229 243 264 272 237 211 180 201
#> 1954 204 188 235 227 234 264 302 293 259 229 203 229
#> 1955 242 233 267 269 270 315 364 347 312 274 237 278
#> 1956 284 277 317 313 318 374 413 405 355 306 271 306
#> 1957 315 301 356 348 355 422 465 467 404 347 305 336
#> 1958 340 318 362 348 363 435 491 505 404 359 310 337
#> 1959 360 342 406 396 420 472 548 559 463 407 362 405
#> 1960 417 391 419 461 472 535 622 606 508 461 390 432
stream <- DSD_Memory(data.frame(
  .time = time(AirPassengers),
  passengers = AirPassengers))

get_points(stream, n = 10)
#>       .time passengers
#> 1  1949.000        112
#> 2  1949.083        118
#> 3  1949.167        132
#> 4  1949.250        129
#> 5  1949.333        121
#> 6  1949.417        135
#> 7  1949.500        148
#> 8  1949.583        148
#> 9  1949.667        136
#> 10 1949.750        119
plot(stream, n = 100, method = "ts")