Package smile.plot.vega

Class DensityTransform

java.lang.Object

smile.plot.vega.DensityTransform

public class DensityTransform
extends Object

The density transform performs one-dimensional kernel density estimation over an input data stream and generates a new data stream of samples of the estimated densities.

Method Summary

Modifier and Type	Method	Description
DensityTransform	as(String... fields)	Sets the output fields for the sample value and corresponding density estimate.
DensityTransform	bandwidth(double width)	Sets the bandwidth (standard deviation) of the Gaussian kernel.
DensityTransform	counts(boolean flag)	Produces probability estimates or smoothed counts.
DensityTransform	cumulative(boolean flag)	Produces density estimates or cumulative density estimates.
DensityTransform	extent(double min, double max)	Sets a [min, max] domain from which to sample the distribution.
DensityTransform	maxSteps(int steps)	Sets the maximum number of samples to take along the extent domain for plotting the density.
DensityTransform	minSteps(int steps)	Sets the minimum number of samples to take along the extent domain for plotting the density.
DensityTransform	steps(int steps)	Sets the exact number of samples to take along the extent domain for plotting the density.
String	toPrettyString()	Returns the specification in pretty print.
String	toString()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Method Details

toString

public String toString()

Overrides:

toString in class Object

toPrettyString

public String toPrettyString()

Returns the specification in pretty print.

Returns:

the specification in pretty print.

cumulative

public DensityTransform cumulative(boolean flag)

Produces density estimates or cumulative density estimates.

Parameters:

flag - If true, produce cumulative density estimates. Otherwise, density estimates.

Returns:

this object.

counts

public DensityTransform counts(boolean flag)

Produces probability estimates or smoothed counts.

Parameters:

flag - If true, produce smoothed counts. Otherwise, probability estimates.

Returns:

this object.

bandwidth

public DensityTransform bandwidth(double width)

Sets the bandwidth (standard deviation) of the Gaussian kernel. If unspecified or set to zero, the bandwidth value is automatically estimated from the input data using Scott's rule.

Parameters:

width - the bandwidth (standard deviation) of the Gaussian kernel.

Returns:

this object.

extent

public DensityTransform extent(double min,
 double max)

Sets a [min, max] domain from which to sample the distribution. If unspecified, the extent will be determined by the observed minimum and maximum values of the density value field.

Parameters:

min - the minimum value of the density value field.

max - the maximum value of the density value field.

Returns:

this object.

minSteps

public DensityTransform minSteps(int steps)

Sets the minimum number of samples to take along the extent domain for plotting the density.

Parameters:

steps - the minimum number of samples to take.

Returns:

this object.

maxSteps

public DensityTransform maxSteps(int steps)

Sets the maximum number of samples to take along the extent domain for plotting the density.

Parameters:

steps - the maximum number of samples to take.

Returns:

this object.

steps

public DensityTransform steps(int steps)

Sets the exact number of samples to take along the extent domain for plotting the density. If specified, overrides both minsteps and maxsteps to set an exact number of uniform samples. Potentially useful in conjunction with a fixed extent to ensure consistent sample points for stacked densities.

Parameters:

steps - the exact number of samples to take.

Returns:

this object.

as

public DensityTransform as(String... fields)

Sets the output fields for the sample value and corresponding density estimate.

Parameters:

fields - the output fields.

Returns:

this object.