blob: 73b8a60b57fab842216027be4350e9deb229e28b [file] [log] [blame]
// Copyright 2016 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package ggstat
import (
// TODO: Default to first (and second) column for X (and Y)?
// Density constructs a probability density estimate from a set of
// samples using kernel density estimation.
// X is the only required field. All other fields have reasonable
// default zero values.
// The result of Density has three columns in addition to constant
// columns from the input:
// - Column X is the points at which the density estimate is sampled.
// - Column "probability density" is the density estimate.
// - Column "cumulative density" is the cumulative density estimate.
type Density struct {
// X is the name of the column to use for samples.
X string
// W is the optional name of the column to use for sample
// weights. It may be "" to uniformly weight samples.
W string
// N is the number of points to sample the KDE at. If N is 0,
// a reasonable default is used.
// TODO: This is particularly sensitive to the scale
// transform.
// TODO: Base the default on the bandwidth. If the bandwidth
// is really narrow, we may need a lot of samples to exceed
// the Nyquist rate.
N int
// Domain specifies the domain at which to sample this function.
// If Domain is nil, it defaults to DomainData{}.
Domain FunctionDomainer
// Kernel is the kernel to use for the KDE.
Kernel stats.KDEKernel
// Bandwidth is the bandwidth to use for the KDE.
// If this is zero, the bandwidth is computed from the data
// using a default bandwidth estimator (currently
// stats.BandwidthScott).
Bandwidth float64
// BoundaryMethod is the boundary correction method to use for
// the KDE. The default value is BoundaryReflect; however, the
// default bounds are effectively +/-inf, which is equivalent
// to performing no boundary correction.
BoundaryMethod stats.KDEBoundaryMethod
// [BoundaryMin, BoundaryMax) specify a bounded support for
// the KDE. If both are 0 (their default values), they are
// treated as +/-inf.
// To specify a half-bounded support, set Min to math.Inf(-1)
// or Max to math.Inf(1).
BoundaryMin float64
BoundaryMax float64
func (d Density) F(g table.Grouping) table.Grouping {
kde := stats.KDE{
Kernel: d.Kernel,
Bandwidth: d.Bandwidth,
BoundaryMethod: d.BoundaryMethod,
BoundaryMin: d.BoundaryMin,
BoundaryMax: d.BoundaryMax,
dname, cname := "probability density", "cumulative density"
addEmpty := func(out *table.Builder) {
out.Add(dname, []float64{})
out.Add(cname, []float64{})
return Function{
X: d.X, N: d.N, Domain: d.Domain,
Fn: func(gid table.GroupID, in *table.Table, sampleAt []float64, out *table.Builder) {
if len(sampleAt) == 0 {
// Get input sample.
var sample stats.Sample
slice.Convert(&sample.Xs, in.MustColumn(d.X))
if d.W != "" {
slice.Convert(&sample.Weights, in.MustColumn(d.W))
if sample.Weight() == 0 {
// Compute KDE.
kde.Sample = sample
if d.Bandwidth == 0 {
kde.Bandwidth = stats.BandwidthScott(sample)
out.Add(dname, vec.Map(kde.PDF, sampleAt))
out.Add(cname, vec.Map(kde.CDF, sampleAt))