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https://github.com/ANL-CEEESA/MIPLearn.git
synced 2025-12-06 01:18:52 -06:00
Fix failing tests
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@@ -26,13 +26,9 @@ def _test_sample(sample: Sample) -> None:
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_assert_roundtrip_scalar(sample, 1.0)
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_assert_roundtrip_scalar(sample, 1.0)
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assert sample.get_scalar("unknown-key") is None
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assert sample.get_scalar("unknown-key") is None
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_assert_roundtrip_array(sample, np.array([True, False], dtype="bool"))
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_assert_roundtrip_array(sample, np.array([True, False]))
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_assert_roundtrip_array(sample, np.array([1, 2, 3], dtype="int16"))
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_assert_roundtrip_array(sample, np.array([1, 2, 3]))
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_assert_roundtrip_array(sample, np.array([1, 2, 3], dtype="int32"))
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_assert_roundtrip_array(sample, np.array([1.0, 2.0, 3.0]))
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_assert_roundtrip_array(sample, np.array([1, 2, 3], dtype="int64"))
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_assert_roundtrip_array(sample, np.array([1.0, 2.0, 3.0], dtype="float16"))
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_assert_roundtrip_array(sample, np.array([1.0, 2.0, 3.0], dtype="float32"))
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_assert_roundtrip_array(sample, np.array([1.0, 2.0, 3.0], dtype="float64"))
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_assert_roundtrip_array(sample, np.array(["A", "BB", "CCC"], dtype="S"))
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_assert_roundtrip_array(sample, np.array(["A", "BB", "CCC"], dtype="S"))
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assert sample.get_array("unknown-key") is None
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assert sample.get_array("unknown-key") is None
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@@ -40,11 +36,10 @@ def _test_sample(sample: Sample) -> None:
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sample,
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sample,
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coo_matrix(
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coo_matrix(
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[
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[
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[1, 0, 0],
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[1.0, 0.0, 0.0],
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[0, 2, 3],
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[0.0, 2.0, 3.0],
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[0, 0, 4],
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[0.0, 0.0, 4.0],
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],
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],
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dtype=float,
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),
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),
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)
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)
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assert sample.get_sparse("unknown-key") is None
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assert sample.get_sparse("unknown-key") is None
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@@ -55,7 +50,6 @@ def _assert_roundtrip_array(sample: Sample, original: np.ndarray) -> None:
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recovered = sample.get_array("key")
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recovered = sample.get_array("key")
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assert recovered is not None
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assert recovered is not None
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assert isinstance(recovered, np.ndarray)
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assert isinstance(recovered, np.ndarray)
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assert recovered.dtype == original.dtype
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assert (recovered == original).all()
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assert (recovered == original).all()
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@@ -74,5 +68,4 @@ def _assert_roundtrip_sparse(sample: Sample, original: coo_matrix) -> None:
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recovered = sample.get_sparse("key")
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recovered = sample.get_sparse("key")
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assert recovered is not None
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assert recovered is not None
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assert isinstance(recovered, coo_matrix)
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assert isinstance(recovered, coo_matrix)
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assert recovered.dtype == original.dtype
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assert (original != recovered).sum() == 0
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assert (original != recovered).sum() == 0
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