mirror of
https://github.com/gonum/gonum.git
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d0fc09f7d6
Removed duplicated interface Improve MH comment Made MH examples Documentation fixes Fix documentation and permute LHC
99 lines
2.4 KiB
Go
99 lines
2.4 KiB
Go
// Copyright ©2015 The gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package sample
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import (
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"math"
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"sort"
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"testing"
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"github.com/gonum/stat"
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"github.com/gonum/stat/dist"
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)
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type lhDist interface {
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Quantile(float64) float64
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CDF(float64) float64
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}
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func TestLatinHypercube(t *testing.T) {
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for _, nSamples := range []int{1, 2, 5, 10, 20} {
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samples := make([]float64, nSamples)
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for _, dist := range []lhDist{
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dist.Uniform{Min: 0, Max: 1},
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dist.Uniform{Min: 0, Max: 10},
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dist.Normal{Mu: 5, Sigma: 3},
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} {
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LatinHypercube(samples, dist, nil)
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sort.Float64s(samples)
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for i, v := range samples {
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p := dist.CDF(v)
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if p < float64(i)/float64(nSamples) || p > float64(i+1)/float64(nSamples) {
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t.Errorf("probability out of bounds")
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}
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}
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}
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}
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}
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func TestImportance(t *testing.T) {
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// Test by finding the expected value of a Normal
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trueMean := 3.0
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target := dist.Normal{Mu: trueMean, Sigma: 2}
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proposal := dist.Normal{Mu: 0, Sigma: 5}
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nSamples := 100000
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x := make([]float64, nSamples)
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weights := make([]float64, nSamples)
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Importance(x, weights, target, proposal)
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ev := stat.Mean(x, weights)
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if math.Abs(ev-trueMean) > 1e-2 {
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t.Errorf("Mean mismatch: Want %v, got %v", trueMean, ev)
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}
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}
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func TestRejection(t *testing.T) {
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// Test by finding the expected value of a Normal
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trueMean := 3.0
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target := dist.Normal{Mu: trueMean, Sigma: 2}
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proposal := dist.Normal{Mu: 0, Sigma: 5}
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nSamples := 100000
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x := make([]float64, nSamples)
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Rejection(x, target, proposal, 100, nil)
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ev := stat.Mean(x, nil)
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if math.Abs(ev-trueMean) > 1e-2 {
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t.Errorf("Mean mismatch: Want %v, got %v", trueMean, ev)
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}
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}
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type condNorm struct {
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Sigma float64
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}
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func (c condNorm) ConditionalRand(y float64) float64 {
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return dist.Normal{Mu: y, Sigma: c.Sigma}.Rand()
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}
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func (c condNorm) ConditionalLogProb(x, y float64) float64 {
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return dist.Normal{Mu: y, Sigma: c.Sigma}.LogProb(x)
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}
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func TestMetropolisHastings(t *testing.T) {
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// Test by finding the expected value of a Normal
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trueMean := 3.0
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target := dist.Normal{Mu: trueMean, Sigma: 2}
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proposal := condNorm{Sigma: 5}
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burnin := 500
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nSamples := 100000 + burnin
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x := make([]float64, nSamples)
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MetropolisHastings(x, 100, target, proposal, nil)
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// Remove burnin
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x = x[burnin:]
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ev := stat.Mean(x, nil)
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if math.Abs(ev-trueMean) > 1e-2 {
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t.Errorf("Mean mismatch: Want %v, got %v", trueMean, ev)
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}
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}
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