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embedding-buddy/tests/test_reducers.py
Austin Godber 1ec7e2c38c
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91 lines
2.8 KiB
Python

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