73 lines
1.3 KiB
Go
73 lines
1.3 KiB
Go
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package clusters
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import (
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"reflect"
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"testing"
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)
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func TestDBSCANCluster(t *testing.T) {
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tests := []struct {
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MinPts int
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Eps float64
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Points [][]float64
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Expected []int
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}{
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{
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MinPts: 1,
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Eps: 1,
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Points: [][]float64{{1}},
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Expected: []int{1},
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},
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{
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MinPts: 1,
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Eps: 1,
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Points: [][]float64{{1}, {1.5}},
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Expected: []int{1, 1},
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},
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{
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MinPts: 1,
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Eps: 1,
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Points: [][]float64{{1}, {1}},
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Expected: []int{1, 1},
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},
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{
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MinPts: 1,
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Eps: 1,
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Points: [][]float64{{1}, {1}, {1}},
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Expected: []int{1, 1, 1},
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},
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{
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MinPts: 1,
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Eps: 1,
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Points: [][]float64{{1}, {1.5}, {2}},
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Expected: []int{1, 1, 1},
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},
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{
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MinPts: 1,
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Eps: 1,
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Points: [][]float64{{1}, {1.5}, {3}},
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Expected: []int{1, 1, 2},
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},
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{
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MinPts: 2,
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Eps: 1,
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Points: [][]float64{{1}, {3}},
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Expected: []int{-1, -1},
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},
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}
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for _, test := range tests {
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c, e := DBSCAN(test.MinPts, test.Eps, 0, EuclideanDistance)
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if e != nil {
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t.Errorf("Error initializing kmeans clusterer: %s\n", e.Error())
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}
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if e = c.Learn(test.Points); e != nil {
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t.Errorf("Error learning data: %s\n", e.Error())
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}
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if !reflect.DeepEqual(c.Guesses(), test.Expected) {
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t.Errorf("guesses does not match: %d vs %d\n", c.Guesses(), test.Expected)
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}
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}
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}
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