route/vendor/github.com/aclements/go-moremath/stats/udist_test.go

325 lines
8.9 KiB
Go

// Copyright 2015 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 stats
import (
"fmt"
"math"
"testing"
"github.com/aclements/go-moremath/mathx"
)
func aeqTable(a, b [][]float64) bool {
if len(a) != len(b) {
return false
}
for i := range a {
if len(a[i]) != len(b[i]) {
return false
}
for j := range a[i] {
// "%f" precision
if math.Abs(a[i][j]-b[i][j]) >= 0.000001 {
return false
}
}
}
return true
}
// U distribution for N=3 up to U=5.
var udist3 = [][]float64{
// m=1 2 3
{0.250000, 0.100000, 0.050000}, // U=0
{0.500000, 0.200000, 0.100000}, // U=1
{0.750000, 0.400000, 0.200000}, // U=2
{1.000000, 0.600000, 0.350000}, // U=3
{1.000000, 0.800000, 0.500000}, // U=4
{1.000000, 0.900000, 0.650000}, // U=5
}
// U distribution for N=5 up to U=5.
var udist5 = [][]float64{
// m=1 2 3 4 5
{0.166667, 0.047619, 0.017857, 0.007937, 0.003968}, // U=0
{0.333333, 0.095238, 0.035714, 0.015873, 0.007937}, // U=1
{0.500000, 0.190476, 0.071429, 0.031746, 0.015873}, // U=2
{0.666667, 0.285714, 0.125000, 0.055556, 0.027778}, // U=3
{0.833333, 0.428571, 0.196429, 0.095238, 0.047619}, // U=4
{1.000000, 0.571429, 0.285714, 0.142857, 0.075397}, // U=5
}
func TestUDist(t *testing.T) {
makeTable := func(n int) [][]float64 {
out := make([][]float64, 6)
for U := 0; U < 6; U++ {
out[U] = make([]float64, n)
for m := 1; m <= n; m++ {
out[U][m-1] = UDist{N1: m, N2: n}.CDF(float64(U))
}
}
return out
}
fmtTable := func(a [][]float64) string {
out := fmt.Sprintf("%8s", "m=")
for m := 1; m <= len(a[0]); m++ {
out += fmt.Sprintf("%9d", m)
}
out += "\n"
for U, row := range a {
out += fmt.Sprintf("U=%-6d", U)
for m := 1; m <= len(a[0]); m++ {
out += fmt.Sprintf(" %f", row[m-1])
}
out += "\n"
}
return out
}
// Compare against tables given in Mann, Whitney (1947).
got3 := makeTable(3)
if !aeqTable(got3, udist3) {
t.Errorf("For n=3, want:\n%sgot:\n%s", fmtTable(udist3), fmtTable(got3))
}
got5 := makeTable(5)
if !aeqTable(got5, udist5) {
t.Errorf("For n=5, want:\n%sgot:\n%s", fmtTable(udist5), fmtTable(got5))
}
}
func BenchmarkUDist(b *testing.B) {
for i := 0; i < b.N; i++ {
// R uses the exact distribution up to N=50.
// N*M/2=1250 is the hardest point to get the CDF for.
UDist{N1: 50, N2: 50}.CDF(1250)
}
}
func TestUDistTies(t *testing.T) {
makeTable := func(m, N int, t []int, minx, maxx float64) [][]float64 {
out := [][]float64{}
dist := UDist{N1: m, N2: N - m, T: t}
for x := minx; x <= maxx; x += 0.5 {
// Convert x from uQt' to uQv'.
U := x - float64(m*m)/2
P := dist.CDF(U)
if len(out) == 0 || !aeq(out[len(out)-1][1], P) {
out = append(out, []float64{x, P})
}
}
return out
}
fmtTable := func(table [][]float64) string {
out := ""
for _, row := range table {
out += fmt.Sprintf("%5.1f %f\n", row[0], row[1])
}
return out
}
// Compare against Table 1 from Klotz (1966).
got := makeTable(5, 10, []int{1, 1, 2, 1, 1, 2, 1, 1}, 12.5, 19.5)
want := [][]float64{
{12.5, 0.003968}, {13.5, 0.007937},
{15.0, 0.023810}, {16.5, 0.047619},
{17.5, 0.071429}, {18.0, 0.087302},
{19.0, 0.134921}, {19.5, 0.138889},
}
if !aeqTable(got, want) {
t.Errorf("Want:\n%sgot:\n%s", fmtTable(want), fmtTable(got))
}
got = makeTable(10, 21, []int{6, 5, 4, 3, 2, 1}, 52, 87)
want = [][]float64{
{52.0, 0.000014}, {56.5, 0.000128},
{57.5, 0.000145}, {60.0, 0.000230},
{61.0, 0.000400}, {62.0, 0.000740},
{62.5, 0.000797}, {64.0, 0.000825},
{64.5, 0.001165}, {65.5, 0.001477},
{66.5, 0.002498}, {67.0, 0.002725},
{67.5, 0.002895}, {68.0, 0.003150},
{68.5, 0.003263}, {69.0, 0.003518},
{69.5, 0.003603}, {70.0, 0.005648},
{70.5, 0.005818}, {71.0, 0.006626},
{71.5, 0.006796}, {72.0, 0.008157},
{72.5, 0.009688}, {73.0, 0.009801},
{73.5, 0.010430}, {74.0, 0.011111},
{74.5, 0.014230}, {75.0, 0.014612},
{75.5, 0.017249}, {76.0, 0.018307},
{76.5, 0.020178}, {77.0, 0.022270},
{77.5, 0.023189}, {78.0, 0.026931},
{78.5, 0.028207}, {79.0, 0.029979},
{79.5, 0.030931}, {80.0, 0.038969},
{80.5, 0.043063}, {81.0, 0.044262},
{81.5, 0.046389}, {82.0, 0.049581},
{82.5, 0.056300}, {83.0, 0.058027},
{83.5, 0.063669}, {84.0, 0.067454},
{84.5, 0.074122}, {85.0, 0.077425},
{85.5, 0.083498}, {86.0, 0.094079},
{86.5, 0.096693}, {87.0, 0.101132},
}
if !aeqTable(got, want) {
t.Errorf("Want:\n%sgot:\n%s", fmtTable(want), fmtTable(got))
}
got = makeTable(8, 16, []int{2, 2, 2, 2, 2, 2, 2, 2}, 32, 54)
want = [][]float64{
{32.0, 0.000078}, {34.0, 0.000389},
{36.0, 0.001088}, {38.0, 0.002642},
{40.0, 0.005905}, {42.0, 0.011500},
{44.0, 0.021057}, {46.0, 0.035664},
{48.0, 0.057187}, {50.0, 0.086713},
{52.0, 0.126263}, {54.0, 0.175369},
}
if !aeqTable(got, want) {
t.Errorf("Want:\n%sgot:\n%s", fmtTable(want), fmtTable(got))
}
// Check remaining tables from Klotz against the reference
// implementation.
checkRef := func(n1 int, tie []int) {
wantPMF1, wantCDF1 := udistRef(n1, tie)
dist := UDist{N1: n1, N2: sumint(tie) - n1, T: tie}
gotPMF, wantPMF := [][]float64{}, [][]float64{}
gotCDF, wantCDF := [][]float64{}, [][]float64{}
N := sumint(tie)
for U := 0.0; U <= float64(n1*(N-n1)); U += 0.5 {
gotPMF = append(gotPMF, []float64{U, dist.PMF(U)})
gotCDF = append(gotCDF, []float64{U, dist.CDF(U)})
wantPMF = append(wantPMF, []float64{U, wantPMF1[int(U*2)]})
wantCDF = append(wantCDF, []float64{U, wantCDF1[int(U*2)]})
}
if !aeqTable(wantPMF, gotPMF) {
t.Errorf("For PMF of n1=%v, t=%v, want:\n%sgot:\n%s", n1, tie, fmtTable(wantPMF), fmtTable(gotPMF))
}
if !aeqTable(wantCDF, gotCDF) {
t.Errorf("For CDF of n1=%v, t=%v, want:\n%sgot:\n%s", n1, tie, fmtTable(wantCDF), fmtTable(gotCDF))
}
}
checkRef(5, []int{1, 1, 2, 1, 1, 2, 1, 1})
checkRef(5, []int{1, 1, 2, 1, 1, 1, 2, 1})
checkRef(5, []int{1, 3, 1, 2, 1, 1, 1})
checkRef(8, []int{1, 2, 1, 1, 1, 1, 2, 2, 1, 2})
checkRef(12, []int{3, 3, 4, 3, 4, 5})
checkRef(10, []int{1, 2, 3, 4, 5, 6})
}
func BenchmarkUDistTies(b *testing.B) {
// Worst case: just one tie.
n := 20
t := make([]int, 2*n-1)
for i := range t {
t[i] = 1
}
t[0] = 2
for i := 0; i < b.N; i++ {
UDist{N1: n, N2: n, T: t}.CDF(float64(n*n) / 2)
}
}
func XTestPrintUmemo(t *testing.T) {
// Reproduce table from Cheung, Klotz.
ties := []int{4, 5, 3, 4, 6}
printUmemo(makeUmemo(80, 10, ties), ties)
}
// udistRef computes the PMF and CDF of the U distribution for two
// samples of sizes n1 and sum(t)-n1 with tie vector t. The returned
// pmf and cdf are indexed by 2*U.
//
// This uses the "graphical method" of Klotz (1966). It is very slow
// (Θ(∏ (t[i]+1)) = Ω(2^|t|)), but very correct, and hence useful as a
// reference for testing faster implementations.
func udistRef(n1 int, t []int) (pmf, cdf []float64) {
// Enumerate all u vectors for which 0 <= u_i <= t_i. Count
// the number of permutations of two samples of sizes n1 and
// sum(t)-n1 with tie vector t and accumulate these counts by
// their U statistics in count[2*U].
counts := make([]int, 1+2*n1*(sumint(t)-n1))
u := make([]int, len(t))
u[0] = -1 // Get enumeration started.
enumu:
for {
// Compute the next u vector.
u[0]++
for i := 0; i < len(u) && u[i] > t[i]; i++ {
if i == len(u)-1 {
// All u vectors have been enumerated.
break enumu
}
// Carry.
u[i+1]++
u[i] = 0
}
// Is this a legal u vector?
if sumint(u) != n1 {
// Klotz (1966) has a method for directly
// enumerating legal u vectors, but the point
// of this is to be correct, not fast.
continue
}
// Compute 2*U statistic for this u vector.
twoU, vsum := 0, 0
for i, u_i := range u {
v_i := t[i] - u_i
// U = U + vsum*u_i + u_i*v_i/2
twoU += 2*vsum*u_i + u_i*v_i
vsum += v_i
}
// Compute Π choose(t_i, u_i). This is the number of
// ways of permuting the input sample under u.
prod := 1
for i, u_i := range u {
prod *= int(mathx.Choose(t[i], u_i) + 0.5)
}
// Accumulate the permutations on this u path.
counts[twoU] += prod
if false {
// Print a table in the form of Klotz's
// "direct enumeration" example.
//
// Convert 2U = 2UQV' to UQt' used in Klotz
// examples.
UQt := float64(twoU)/2 + float64(n1*n1)/2
fmt.Printf("%+v %f %-2d\n", u, UQt, prod)
}
}
// Convert counts into probabilities for PMF and CDF.
pmf = make([]float64, len(counts))
cdf = make([]float64, len(counts))
total := int(mathx.Choose(sumint(t), n1) + 0.5)
for i, count := range counts {
pmf[i] = float64(count) / float64(total)
if i > 0 {
cdf[i] = cdf[i-1]
}
cdf[i] += pmf[i]
}
return
}
// printUmemo prints the output of makeUmemo for debugging.
func printUmemo(A []map[ukey]float64, t []int) {
fmt.Printf("K\tn1\t2*U\tpr\n")
for K := len(A) - 1; K >= 0; K-- {
for i, pr := range A[K] {
_, ref := udistRef(i.n1, t[:K])
fmt.Printf("%v\t%v\t%v\t%v\t%v\n", K, i.n1, i.twoU, pr, ref[i.twoU])
}
}
}