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| // _ _ | |
| // __ _____ __ ___ ___ __ _| |_ ___ | |
| // \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \ | |
| // \ V V / __/ (_| |\ V /| | (_| | || __/ | |
| // \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___| | |
| // | |
| // Copyright © 2016 - 2024 Weaviate B.V. All rights reserved. | |
| // | |
| // CONTACT: [email protected] | |
| // | |
| package classification | |
| import ( | |
| "testing" | |
| "github.com/stretchr/testify/assert" | |
| "github.com/weaviate/weaviate/entities/models" | |
| ) | |
| func Test_RefMeta(t *testing.T) { | |
| t.Run("without a losing group", func(t *testing.T) { | |
| source := NeighborRef{ | |
| WinningCount: 3, | |
| OverallCount: 3, | |
| LosingCount: 0, | |
| Distances: NeighborRefDistances{ | |
| ClosestWinningDistance: 0.1, | |
| ClosestOverallDistance: 0.1, | |
| MeanWinningDistance: 0.2, | |
| }, | |
| } | |
| expected := &models.ReferenceMetaClassification{ | |
| ClosestWinningDistance: 0.1, | |
| ClosestOverallDistance: 0.1, | |
| MeanWinningDistance: 0.2, | |
| WinningDistance: 0.2, // deprecated, must be removed in 0.23.0 | |
| OverallCount: 3, | |
| WinningCount: 3, | |
| LosingCount: 0, | |
| } | |
| actual := source.Meta() | |
| assert.InDelta(t, expected.ClosestWinningDistance, actual.ClosestWinningDistance, 0.001) | |
| assert.InDelta(t, expected.ClosestOverallDistance, actual.ClosestOverallDistance, 0.001) | |
| assert.InDelta(t, expected.MeanWinningDistance, actual.MeanWinningDistance, 0.001) | |
| assert.InDelta(t, expected.WinningDistance, actual.WinningDistance, 0.001) | |
| assert.Equal(t, expected.OverallCount, actual.OverallCount) | |
| assert.Equal(t, expected.WinningCount, actual.WinningCount) | |
| assert.Equal(t, expected.LosingCount, actual.LosingCount) | |
| }) | |
| t.Run("with a losing group", func(t *testing.T) { | |
| source := NeighborRef{ | |
| WinningCount: 3, | |
| OverallCount: 5, | |
| LosingCount: 2, | |
| Distances: NeighborRefDistances{ | |
| ClosestWinningDistance: 0.1, | |
| ClosestOverallDistance: 0.1, | |
| MeanWinningDistance: 0.2, | |
| ClosestLosingDistance: ptFloat32(0.15), | |
| MeanLosingDistance: ptFloat32(0.25), | |
| }, | |
| } | |
| expected := &models.ReferenceMetaClassification{ | |
| ClosestOverallDistance: 0.1, | |
| ClosestWinningDistance: 0.1, | |
| MeanWinningDistance: 0.2, | |
| WinningDistance: 0.2, // deprecated, must be removed in 0.23.0 | |
| ClosestLosingDistance: ptFloat64(0.15), | |
| MeanLosingDistance: ptFloat64(0.25), | |
| LosingDistance: ptFloat64(0.25), // deprecated, must be removed in 0.23.0 | |
| OverallCount: 5, | |
| WinningCount: 3, | |
| LosingCount: 2, | |
| } | |
| actual := source.Meta() | |
| assert.InDelta(t, expected.ClosestOverallDistance, actual.ClosestOverallDistance, 0.001) | |
| assert.InDelta(t, expected.ClosestWinningDistance, actual.ClosestWinningDistance, 0.001) | |
| assert.InDelta(t, expected.MeanWinningDistance, actual.MeanWinningDistance, 0.001) | |
| assert.InDelta(t, expected.WinningDistance, actual.WinningDistance, 0.001) | |
| assert.InDelta(t, *expected.ClosestLosingDistance, *actual.ClosestLosingDistance, 0.001) | |
| assert.InDelta(t, *expected.MeanLosingDistance, *actual.MeanLosingDistance, 0.001) | |
| assert.InDelta(t, *expected.LosingDistance, *actual.LosingDistance, 0.001) | |
| assert.Equal(t, expected.OverallCount, actual.OverallCount) | |
| assert.Equal(t, expected.OverallCount, actual.OverallCount) | |
| assert.Equal(t, expected.WinningCount, actual.WinningCount) | |
| assert.Equal(t, expected.LosingCount, actual.LosingCount) | |
| }) | |
| } | |
| func ptFloat32(in float32) *float32 { | |
| return &in | |
| } | |