64 lines
2.0 KiB
Python
64 lines
2.0 KiB
Python
import numpy as np
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import pytest
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from sklearn.cluster._hdbscan._reachability import mutual_reachability_graph
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from sklearn.utils._testing import (
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_convert_container,
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assert_allclose,
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)
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def test_mutual_reachability_graph_error_sparse_format():
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"""Check that we raise an error if the sparse format is not CSR."""
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rng = np.random.RandomState(0)
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X = rng.randn(10, 10)
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X = X.T @ X
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np.fill_diagonal(X, 0.0)
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X = _convert_container(X, "sparse_csc")
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err_msg = "Only sparse CSR matrices are supported"
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with pytest.raises(ValueError, match=err_msg):
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mutual_reachability_graph(X)
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@pytest.mark.parametrize("array_type", ["array", "sparse_csr"])
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def test_mutual_reachability_graph_inplace(array_type):
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"""Check that the operation is happening inplace."""
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rng = np.random.RandomState(0)
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X = rng.randn(10, 10)
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X = X.T @ X
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np.fill_diagonal(X, 0.0)
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X = _convert_container(X, array_type)
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mr_graph = mutual_reachability_graph(X)
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assert id(mr_graph) == id(X)
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def test_mutual_reachability_graph_equivalence_dense_sparse():
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"""Check that we get the same results for dense and sparse implementation."""
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rng = np.random.RandomState(0)
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X = rng.randn(5, 5)
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X_dense = X.T @ X
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X_sparse = _convert_container(X_dense, "sparse_csr")
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mr_graph_dense = mutual_reachability_graph(X_dense, min_samples=3)
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mr_graph_sparse = mutual_reachability_graph(X_sparse, min_samples=3)
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assert_allclose(mr_graph_dense, mr_graph_sparse.toarray())
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@pytest.mark.parametrize("array_type", ["array", "sparse_csr"])
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@pytest.mark.parametrize("dtype", [np.float32, np.float64])
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def test_mutual_reachability_graph_preserve_dtype(array_type, dtype):
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"""Check that the computation preserve dtype thanks to fused types."""
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rng = np.random.RandomState(0)
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X = rng.randn(10, 10)
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X = (X.T @ X).astype(dtype)
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np.fill_diagonal(X, 0.0)
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X = _convert_container(X, array_type)
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assert X.dtype == dtype
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mr_graph = mutual_reachability_graph(X)
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assert mr_graph.dtype == dtype
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