/
weighted_test.go
233 lines (206 loc) · 6.37 KB
/
weighted_test.go
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// Copyright ©2012 Dan Kortschak <dan.kortschak@adelaide.edu.au>
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
package graph
import (
check "launchpad.net/gocheck"
"math/rand"
"time"
)
// Tests
var (
exp = []float64{1 << 0, 1 << 1, 1 << 2, 1 << 3, 1 << 4, 1 << 5, 1 << 6, 1 << 7, 1 << 8, 1 << 9}
sigChi2 = 16.92 // p = 0.05 df = 9
sel = Selector{
{Index: 1, Weight: exp[0]},
{Index: 2, Weight: exp[1]},
{Index: 3, Weight: exp[2]},
{Index: 4, Weight: exp[3]},
{Index: 5, Weight: exp[4]},
{Index: 6, Weight: exp[5]},
{Index: 7, Weight: exp[6]},
{Index: 8, Weight: exp[7]},
{Index: 9, Weight: exp[8]},
{Index: 10, Weight: exp[9]},
}
tot = Selector{
{Index: 1, Weight: exp[0], total: exp[0] + exp[1] + exp[3] + exp[4] + exp[7] + exp[8] + exp[9] + exp[2] + exp[5] + exp[6]},
{Index: 2, Weight: exp[1], total: exp[1] + exp[3] + exp[4] + exp[7] + exp[8] + exp[9]},
{Index: 3, Weight: exp[2], total: exp[2] + exp[5] + exp[6]},
{Index: 4, Weight: exp[3], total: exp[3] + exp[7] + exp[8]},
{Index: 5, Weight: exp[4], total: exp[4] + exp[9]},
{Index: 6, Weight: exp[5], total: exp[5]},
{Index: 7, Weight: exp[6], total: exp[6]},
{Index: 8, Weight: exp[7], total: exp[7]},
{Index: 9, Weight: exp[8], total: exp[8]},
{Index: 10, Weight: exp[9], total: exp[9]},
}
dnw = Selector{
{Index: 1, Weight: exp[0], total: exp[0] + exp[1] + exp[3] + exp[4] + exp[7] + exp[8] + exp[9] + exp[2] + exp[5]},
{Index: 2, Weight: exp[1], total: exp[1] + exp[3] + exp[4] + exp[7] + exp[8] + exp[9]},
{Index: 3, Weight: exp[2], total: exp[2] + exp[5]},
{Index: 4, Weight: exp[3], total: exp[3] + exp[7] + exp[8]},
{Index: 5, Weight: exp[4], total: exp[4] + exp[9]},
{Index: 6, Weight: exp[5], total: exp[5]},
{Index: 7, Weight: 0, total: 0},
{Index: 8, Weight: exp[7], total: exp[7]},
{Index: 9, Weight: exp[8], total: exp[8]},
{Index: 10, Weight: exp[9], total: exp[9]},
}
upw = Selector{
{Index: 1, Weight: exp[0], total: exp[0] + exp[1] + exp[3] + exp[4] + exp[7] + exp[8] + exp[9] + exp[2] + exp[5] + exp[9]*2},
{Index: 2, Weight: exp[1], total: exp[1] + exp[3] + exp[4] + exp[7] + exp[8] + exp[9]},
{Index: 3, Weight: exp[2], total: exp[2] + exp[5] + exp[9]*2},
{Index: 4, Weight: exp[3], total: exp[3] + exp[7] + exp[8]},
{Index: 5, Weight: exp[4], total: exp[4] + exp[9]},
{Index: 6, Weight: exp[5], total: exp[5]},
{Index: 7, Weight: exp[9] * 2, total: exp[9] * 2},
{Index: 8, Weight: exp[7], total: exp[7]},
{Index: 9, Weight: exp[8], total: exp[8]},
{Index: 10, Weight: exp[9], total: exp[9]},
}
obt = []float64{973, 1937, 3898, 7897, 15769, 31284, 62176, 125408, 250295, 500363}
)
func (s *S) TestWeightedUnseeded(c *check.C) {
rand.Seed(0)
f := make([]float64, len(sel))
ts := make(Selector, len(sel))
copy(ts, sel)
ts.Init()
c.Check(ts, check.DeepEquals, tot)
for i := 0; i < 1e6; i++ {
copy(ts, sel)
ts.Init()
item, err := ts.Select()
if err != nil {
c.Fatal(err)
}
f[item-1]++
}
fsum, exsum := 0., 0.
for i := range f {
fsum += f[i]
exsum += exp[i]
}
fac := fsum / exsum
for i := range f {
exp[i] *= fac
}
// Check that we get exactly what we expect
c.Check(f, check.DeepEquals, obt)
// Check that this is within statistical expectations - we know this is true for this set.
X := chi2(f, exp)
c.Logf("H₀: d(Sample) = d(Expect), H₁: d(S) ≠ d(Expect). df = %d, p = 0.05, X² threshold = %.2f, X² = %f", len(f)-1, sigChi2, X)
c.Check(X < sigChi2, check.Equals, true)
}
func (s *S) TestWeightedTimeSeeded(c *check.C) {
c.Log("Note: This test is stochastic and is expected to fail with probability ≈ 0.05.")
rand.Seed(time.Now().Unix())
f := make([]float64, len(sel))
ts := make(Selector, len(sel))
for i := 0; i < 1e6; i++ {
copy(ts, sel)
ts.Init()
item, err := ts.Select()
if err != nil {
c.Fatal(err)
}
f[item-1]++
}
fsum, exsum := 0., 0.
for i := range f {
fsum += f[i]
exsum += exp[i]
}
fac := fsum / exsum
for i := range f {
exp[i] *= fac
}
// Check that our obtained values are within statistical expectations for p = 0.05.
// This will not be true approximately 1 in 20 tests.
X := chi2(f, exp)
c.Logf("H₀: d(Sample) = d(Expect), H₁: d(S) ≠ d(Expect). df = %d, p = 0.05, X² threshold = %.2f, X² = %f", len(f)-1, sigChi2, X)
c.Check(X < sigChi2, check.Equals, true)
}
func (s *S) TestWeightZero(c *check.C) {
rand.Seed(0)
f := make([]float64, len(sel))
ts := make(Selector, len(sel))
copy(ts, sel)
ts.Init()
ts.Weight(6, 0)
c.Check(ts, check.DeepEquals, dnw)
for i := 0; i < 1e6; i++ {
copy(ts, sel)
ts.Init()
ts.Weight(6, 0)
item, err := ts.Select()
if err != nil {
c.Fatal(err)
}
f[item-1]++
}
fsum, exsum := 0., 0.
for i := range f {
fsum += f[i]
exsum += exp[i]
}
fac := fsum / exsum
for i := range f {
exp[i] *= fac
}
// Check that we get exactly what we expect
c.Check(f[:6], check.Not(check.DeepEquals), obt[:6])
c.Check(f[7:], check.Not(check.DeepEquals), obt[7:])
c.Check(f[6], check.Equals, 0.)
}
func (s *S) TestWeightIncrease(c *check.C) {
rand.Seed(0)
f := make([]float64, len(sel))
ts := make(Selector, len(sel))
copy(ts, sel)
ts.Init()
ts.Weight(6, sel[len(sel)-1].Weight*2)
c.Check(ts, check.DeepEquals, upw)
for i := 0; i < 1e6; i++ {
copy(ts, sel)
ts.Init()
ts.Weight(6, sel[len(sel)-1].Weight*2)
item, err := ts.Select()
if err != nil {
c.Fatal(err)
}
f[item-1]++
}
fsum, exsum := 0., 0.
for i := range f {
fsum += f[i]
exsum += exp[i]
}
fac := fsum / exsum
for i := range f {
exp[i] *= fac
}
// Check that we get exactly what we expect
c.Check(f[:6], check.Not(check.DeepEquals), obt[:6])
c.Check(f[7:], check.Not(check.DeepEquals), obt[7:])
c.Check(f[6] > f[9], check.Equals, true)
}
func chi2(ob, ex []float64) (sum float64) {
for i := range ob {
x := ob[i] - ex[i]
sum += (x * x) / ex[i]
}
return
}