275 lines
8.3 KiB
Python
275 lines
8.3 KiB
Python
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import numpy as np
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import pytest
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from scipy.sparse import coo_array
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def test_shape_constructor():
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empty1d = coo_array((3,))
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assert empty1d.shape == (3,)
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assert np.array_equal(empty1d.toarray(), np.zeros((3,)))
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empty2d = coo_array((3, 2))
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assert empty2d.shape == (3, 2)
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assert np.array_equal(empty2d.toarray(), np.zeros((3, 2)))
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with pytest.raises(TypeError, match='invalid input format'):
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coo_array((3, 2, 2))
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def test_dense_constructor():
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res1d = coo_array([1, 2, 3])
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assert res1d.shape == (3,)
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assert np.array_equal(res1d.toarray(), np.array([1, 2, 3]))
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res2d = coo_array([[1, 2, 3], [4, 5, 6]])
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assert res2d.shape == (2, 3)
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assert np.array_equal(res2d.toarray(), np.array([[1, 2, 3], [4, 5, 6]]))
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with pytest.raises(ValueError, match='shape must be a 1- or 2-tuple'):
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coo_array([[[3]], [[4]]])
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def test_dense_constructor_with_shape():
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res1d = coo_array([1, 2, 3], shape=(3,))
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assert res1d.shape == (3,)
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assert np.array_equal(res1d.toarray(), np.array([1, 2, 3]))
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res2d = coo_array([[1, 2, 3], [4, 5, 6]], shape=(2, 3))
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assert res2d.shape == (2, 3)
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assert np.array_equal(res2d.toarray(), np.array([[1, 2, 3], [4, 5, 6]]))
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with pytest.raises(ValueError, match='shape must be a 1- or 2-tuple'):
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coo_array([[[3]], [[4]]], shape=(2, 1, 1))
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def test_dense_constructor_with_inconsistent_shape():
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with pytest.raises(ValueError, match='inconsistent shapes'):
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coo_array([1, 2, 3], shape=(4,))
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with pytest.raises(ValueError, match='inconsistent shapes'):
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coo_array([1, 2, 3], shape=(3, 1))
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with pytest.raises(ValueError, match='inconsistent shapes'):
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coo_array([[1, 2, 3]], shape=(3,))
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with pytest.raises(ValueError,
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match='axis 0 index 2 exceeds matrix dimension 2'):
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coo_array(([1], ([2],)), shape=(2,))
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with pytest.raises(ValueError, match='negative axis 0 index: -1'):
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coo_array(([1], ([-1],)))
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def test_1d_sparse_constructor():
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empty1d = coo_array((3,))
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res = coo_array(empty1d)
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assert res.shape == (3,)
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assert np.array_equal(res.toarray(), np.zeros((3,)))
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def test_1d_tuple_constructor():
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res = coo_array(([9,8], ([1,2],)))
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assert res.shape == (3,)
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assert np.array_equal(res.toarray(), np.array([0, 9, 8]))
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def test_1d_tuple_constructor_with_shape():
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res = coo_array(([9,8], ([1,2],)), shape=(4,))
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assert res.shape == (4,)
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assert np.array_equal(res.toarray(), np.array([0, 9, 8, 0]))
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def test_non_subscriptability():
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coo_2d = coo_array((2, 2))
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with pytest.raises(TypeError,
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match="'coo_array' object does not support item assignment"):
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coo_2d[0, 0] = 1
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with pytest.raises(TypeError,
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match="'coo_array' object is not subscriptable"):
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coo_2d[0, :]
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def test_reshape():
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arr1d = coo_array([1, 0, 3])
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assert arr1d.shape == (3,)
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col_vec = arr1d.reshape((3, 1))
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assert col_vec.shape == (3, 1)
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assert np.array_equal(col_vec.toarray(), np.array([[1], [0], [3]]))
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row_vec = arr1d.reshape((1, 3))
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assert row_vec.shape == (1, 3)
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assert np.array_equal(row_vec.toarray(), np.array([[1, 0, 3]]))
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arr2d = coo_array([[1, 2, 0], [0, 0, 3]])
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assert arr2d.shape == (2, 3)
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flat = arr2d.reshape((6,))
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assert flat.shape == (6,)
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assert np.array_equal(flat.toarray(), np.array([1, 2, 0, 0, 0, 3]))
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def test_nnz():
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arr1d = coo_array([1, 0, 3])
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assert arr1d.shape == (3,)
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assert arr1d.nnz == 2
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arr2d = coo_array([[1, 2, 0], [0, 0, 3]])
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assert arr2d.shape == (2, 3)
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assert arr2d.nnz == 3
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def test_transpose():
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arr1d = coo_array([1, 0, 3]).T
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assert arr1d.shape == (3,)
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assert np.array_equal(arr1d.toarray(), np.array([1, 0, 3]))
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arr2d = coo_array([[1, 2, 0], [0, 0, 3]]).T
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assert arr2d.shape == (3, 2)
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assert np.array_equal(arr2d.toarray(), np.array([[1, 0], [2, 0], [0, 3]]))
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def test_transpose_with_axis():
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arr1d = coo_array([1, 0, 3]).transpose(axes=(0,))
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assert arr1d.shape == (3,)
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assert np.array_equal(arr1d.toarray(), np.array([1, 0, 3]))
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arr2d = coo_array([[1, 2, 0], [0, 0, 3]]).transpose(axes=(0, 1))
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assert arr2d.shape == (2, 3)
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assert np.array_equal(arr2d.toarray(), np.array([[1, 2, 0], [0, 0, 3]]))
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with pytest.raises(ValueError, match="axes don't match matrix dimensions"):
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coo_array([1, 0, 3]).transpose(axes=(0, 1))
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with pytest.raises(ValueError, match="repeated axis in transpose"):
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coo_array([[1, 2, 0], [0, 0, 3]]).transpose(axes=(1, 1))
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def test_1d_row_and_col():
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res = coo_array([1, -2, -3])
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assert np.array_equal(res.col, np.array([0, 1, 2]))
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assert np.array_equal(res.row, np.zeros_like(res.col))
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assert res.row.dtype == res.col.dtype
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assert res.row.flags.writeable is False
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res.col = [1, 2, 3]
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assert len(res.coords) == 1
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assert np.array_equal(res.col, np.array([1, 2, 3]))
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assert res.row.dtype == res.col.dtype
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with pytest.raises(ValueError, match="cannot set row attribute"):
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res.row = [1, 2, 3]
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def test_1d_toformats():
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res = coo_array([1, -2, -3])
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for f in [res.tocsc, res.tocsr, res.todia, res.tolil, res.tobsr]:
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with pytest.raises(ValueError, match='Cannot convert'):
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f()
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for f in [res.tocoo, res.todok]:
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assert np.array_equal(f().toarray(), res.toarray())
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@pytest.mark.parametrize('arg', [1, 2, 4, 5, 8])
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def test_1d_resize(arg: int):
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den = np.array([1, -2, -3])
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res = coo_array(den)
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den.resize(arg, refcheck=False)
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res.resize(arg)
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assert res.shape == den.shape
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assert np.array_equal(res.toarray(), den)
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@pytest.mark.parametrize('arg', zip([1, 2, 3, 4], [1, 2, 3, 4]))
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def test_1d_to_2d_resize(arg: tuple[int, int]):
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den = np.array([1, 0, 3])
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res = coo_array(den)
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den.resize(arg, refcheck=False)
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res.resize(arg)
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assert res.shape == den.shape
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assert np.array_equal(res.toarray(), den)
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@pytest.mark.parametrize('arg', [1, 4, 6, 8])
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def test_2d_to_1d_resize(arg: int):
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den = np.array([[1, 0, 3], [4, 0, 0]])
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res = coo_array(den)
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den.resize(arg, refcheck=False)
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res.resize(arg)
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assert res.shape == den.shape
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assert np.array_equal(res.toarray(), den)
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def test_sum_duplicates():
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arr1d = coo_array(([2, 2, 2], ([1, 0, 1],)))
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assert arr1d.nnz == 3
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assert np.array_equal(arr1d.toarray(), np.array([2, 4]))
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arr1d.sum_duplicates()
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assert arr1d.nnz == 2
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assert np.array_equal(arr1d.toarray(), np.array([2, 4]))
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def test_eliminate_zeros():
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arr1d = coo_array(([0, 0, 1], ([1, 0, 1],)))
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assert arr1d.nnz == 3
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assert arr1d.count_nonzero() == 1
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assert np.array_equal(arr1d.toarray(), np.array([0, 1]))
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arr1d.eliminate_zeros()
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assert arr1d.nnz == 1
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assert arr1d.count_nonzero() == 1
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assert np.array_equal(arr1d.toarray(), np.array([0, 1]))
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assert np.array_equal(arr1d.col, np.array([1]))
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assert np.array_equal(arr1d.row, np.array([0]))
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def test_1d_add_dense():
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den_a = np.array([0, -2, -3, 0])
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den_b = np.array([0, 1, 2, 3])
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exp = den_a + den_b
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res = coo_array(den_a) + den_b
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assert type(res) == type(exp)
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assert np.array_equal(res, exp)
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def test_1d_add_sparse():
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den_a = np.array([0, -2, -3, 0])
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den_b = np.array([0, 1, 2, 3])
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# Currently this routes through CSR format, so 1d sparse addition
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# isn't supported.
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with pytest.raises(ValueError,
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match='Cannot convert a 1d sparse array'):
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coo_array(den_a) + coo_array(den_b)
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def test_1d_matmul_vector():
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den_a = np.array([0, -2, -3, 0])
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den_b = np.array([0, 1, 2, 3])
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exp = den_a @ den_b
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res = coo_array(den_a) @ den_b
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assert np.ndim(res) == 0
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assert np.array_equal(res, exp)
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def test_1d_matmul_multivector():
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den = np.array([0, -2, -3, 0])
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other = np.array([[0, 1, 2, 3], [3, 2, 1, 0]]).T
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exp = den @ other
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res = coo_array(den) @ other
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assert type(res) == type(exp)
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assert np.array_equal(res, exp)
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def test_2d_matmul_multivector():
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den = np.array([[0, 1, 2, 3], [3, 2, 1, 0]])
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arr2d = coo_array(den)
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exp = den @ den.T
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res = arr2d @ arr2d.T
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assert np.array_equal(res.toarray(), exp)
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def test_1d_diagonal():
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den = np.array([0, -2, -3, 0])
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with pytest.raises(ValueError, match='diagonal requires two dimensions'):
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coo_array(den).diagonal()
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