Austin Godber
a1f533c6a8
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91 lines
2.8 KiB
Python
91 lines
2.8 KiB
Python
import pytest
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import numpy as np
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from src.embeddingbuddy.models.reducers import (
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ReducerFactory,
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PCAReducer,
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TSNEReducer,
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UMAPReducer,
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)
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class TestReducerFactory:
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def test_create_pca_reducer(self):
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reducer = ReducerFactory.create_reducer("pca", n_components=2)
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assert isinstance(reducer, PCAReducer)
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assert reducer.n_components == 2
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def test_create_tsne_reducer(self):
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reducer = ReducerFactory.create_reducer("tsne", n_components=3)
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assert isinstance(reducer, TSNEReducer)
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assert reducer.n_components == 3
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def test_create_umap_reducer(self):
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reducer = ReducerFactory.create_reducer("umap", n_components=2)
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assert isinstance(reducer, UMAPReducer)
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assert reducer.n_components == 2
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def test_invalid_method(self):
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with pytest.raises(ValueError, match="Unknown reduction method"):
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ReducerFactory.create_reducer("invalid_method")
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def test_available_methods(self):
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methods = ReducerFactory.get_available_methods()
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assert "pca" in methods
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assert "tsne" in methods
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assert "umap" in methods
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class TestPCAReducer:
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def test_fit_transform(self):
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embeddings = np.random.rand(100, 512)
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reducer = PCAReducer(n_components=2)
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result = reducer.fit_transform(embeddings)
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assert result.reduced_embeddings.shape == (100, 2)
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assert result.variance_explained is not None
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assert result.method == "PCA"
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assert result.n_components == 2
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def test_method_name(self):
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reducer = PCAReducer()
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assert reducer.get_method_name() == "PCA"
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class TestTSNEReducer:
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def test_fit_transform_small_dataset(self):
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embeddings = np.random.rand(30, 10) # Small dataset for faster testing
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reducer = TSNEReducer(n_components=2)
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result = reducer.fit_transform(embeddings)
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assert result.reduced_embeddings.shape == (30, 2)
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assert result.variance_explained is None # t-SNE doesn't provide this
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assert result.method == "t-SNE"
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assert result.n_components == 2
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def test_method_name(self):
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reducer = TSNEReducer()
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assert reducer.get_method_name() == "t-SNE"
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class TestUMAPReducer:
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def test_fit_transform(self):
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embeddings = np.random.rand(50, 10)
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reducer = UMAPReducer(n_components=2)
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result = reducer.fit_transform(embeddings)
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assert result.reduced_embeddings.shape == (50, 2)
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assert result.variance_explained is None # UMAP doesn't provide this
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assert result.method == "UMAP"
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assert result.n_components == 2
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def test_method_name(self):
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reducer = UMAPReducer()
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assert reducer.get_method_name() == "UMAP"
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if __name__ == "__main__":
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pytest.main([__file__])
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