JDBetteridge/merge pyop2 tsfc #6393
JDBetteridgezenodo-canary.yml
on: pull_request
Run zenodo canary
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Annotations
40 errors and 1 warning
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TestMixedIndirectLoop.test_mixed_non_mixed_dat_itspace[iterset0]:
TestMixedIndirectLoop#L1
AssertionError: assert (False)
+ where False = all(array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) == 1.0)
+ where array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) = Dat(DataSet(Set((4096, 4096, 4096), 'indset'), (1,), 'dset_#x7f5a808bf110'), None, dtype('complex128'), 'dat_#x7f5a808bf740').data
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TestMixedIndirectLoop.test_mixed_non_mixed_dat_itspace[iterset1]:
TestMixedIndirectLoop#L1
AssertionError: assert (False)
+ where False = all(array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) == 1.0)
+ where array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) = Dat(DataSet(Set((4096, 4096, 4096), 'indset'), (1,), 'dset_#x7f5a7bcafcb0'), None, dtype('complex128'), 'dat_#x7f5a7bcafbf0').data
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TestMixedIndirectLoop.test_mixed_non_mixed_dat_itspace[iterset2]:
TestMixedIndirectLoop#L1
AssertionError: assert (False)
+ where False = all(array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) == 1.0)
+ where array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) = Dat(DataSet(Set((4096, 4096, 4096), 'indset'), (1,), 'dset_#x7f5a7ba709e0'), None, dtype('complex128'), 'dat_#x7f5a7ba70080').data
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TestMatrices.test_minimal_zero_mat:
TestMatrices#L1
RuntimeError: Can only create a matrix of type <class 'numpy.complex128'>, float64 is not supported
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TestMatrices.test_assemble_mat:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-05, atol=0
Mismatched elements: 14 / 16 (87.5%)
Max absolute difference among violations: 0.291667
Max relative difference among violations: 1.
ACTUAL: array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])
DESIRED: array([[0.25 +0.j, 0.125 +0.j, 0. +0.j, 0.125 +0.j],
[0.125 +0.j, 0.291667+0.j, 0.020833+0.j, 0.145833+0.j],
[0. +0.j, 0.020833+0.j, 0.041667+0.j, 0.020833+0.j],
[0.125 +0.j, 0.145833+0.j, 0.020833+0.j, 0.291667+0.j]])
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TestMatrices.test_assemble_rhs:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-12, atol=0
Mismatched elements: 4 / 4 (100%)
Max absolute difference among violations: 1.64583326
Max relative difference among violations: 1.
ACTUAL: array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j])
DESIRED: array([1. +0.j, 1.354167+0.j, 0.25 +0.j, 1.645833+0.j])
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TestMatrices.test_solve:
TestMatrices#L1
numpy.linalg.LinAlgError: Singular matrix
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TestMatrices.test_set_matrix:
TestMatrices#L1
AssertionError: assert np.complex128(10+8j) == ((3 * 3) * 2)
+ where np.complex128(10+8j) = <built-in method sum of numpy.ndarray object at 0x7f5a7a149dd0>()
+ where <built-in method sum of numpy.ndarray object at 0x7f5a7a149dd0> = array([[1.+1.j, 1.+1.j, 0.+0.j, 1.+1.j],\n [1.+1.j, 1.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 1.+1.j, 1.+1.j, 1.+1.j],\n [0.+0.j, 0.+0.j, 1.+1.j, 1.+0.j]]).sum
+ where array([[1.+1.j, 1.+1.j, 0.+0.j, 1.+1.j],\n [1.+1.j, 1.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 1.+1.j, 1.+1.j, 1.+1.j],\n [0.+0.j, 0.+0.j, 1.+1.j, 1.+0.j]]) = Mat(Sparsity((DataSet(Set((4, 4, 4), 'nodes'), (1,), 'dnodes'), DataSet(Set((4, 4, 4), 'nodes'), (1,), 'dnodes')), {(0, 0): frozenset({(Map(Set((2, 2, 2), 'elements'), Set((4, 4, 4), 'nodes'), 3, None, 'elem_node', None, None), Map(Set((2, 2, 2), 'elements'), Set((4, 4, 4), 'nodes'), 3, None, 'elem_node', None, None), (<IterationRegion.ALL: 4>,))})}, name='sparsity', nested=False, block_sparse=True, diagonal_block=True), dtype('complex128'), 'mat').values
+ and 2 = Set((2, 2, 2), 'elements').size
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TestMatrices.test_assemble_ffc:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-05, atol=0
Mismatched elements: 14 / 16 (87.5%)
Max absolute difference among violations: 0.291667
Max relative difference among violations: 1.
ACTUAL: array([[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])
DESIRED: array([[0.25 +0.j, 0.125 +0.j, 0. +0.j, 0.125 +0.j],
[0.125 +0.j, 0.291667+0.j, 0.020833+0.j, 0.145833+0.j],
[0. +0.j, 0.020833+0.j, 0.041667+0.j, 0.020833+0.j],
[0.125 +0.j, 0.145833+0.j, 0.020833+0.j, 0.291667+0.j]])
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TestMatrices.test_rhs_ffc:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-06, atol=0
Mismatched elements: 4 / 4 (100%)
Max absolute difference among violations: 1.64583326
Max relative difference among violations: 1.
ACTUAL: array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j])
DESIRED: array([1. +0.j, 1.354167+0.j, 0.25 +0.j, 1.645833+0.j])
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TestMatrices.test_rhs_ffc_itspace:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-06, atol=0
Mismatched elements: 4 / 4 (100%)
Max absolute difference among violations: 1.64583326
Max relative difference among violations: 1.
ACTUAL: array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j])
DESIRED: array([1. +0.j, 1.354167+0.j, 0.25 +0.j, 1.645833+0.j])
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TestMatrices.test_zero_rows:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-05, atol=0
Mismatched elements: 11 / 16 (68.8%)
Max absolute difference among violations: 0.291667
Max relative difference among violations: 1.
ACTUAL: array([[12.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])
DESIRED: array([[12. +0.j, 0. +0.j, 0. +0.j, 0. +0.j],
[ 0.125 +0.j, 0.291667+0.j, 0.020833+0.j, 0.145833+0.j],
[ 0. +0.j, 0.020833+0.j, 0.041667+0.j, 0.020833+0.j],
[ 0.125 +0.j, 0.145833+0.j, 0.020833+0.j, 0.291667+0.j]])
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TestMatrices.test_zero_rows_subset:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-05, atol=0
Mismatched elements: 11 / 16 (68.8%)
Max absolute difference among violations: 0.291667
Max relative difference among violations: 1.
ACTUAL: array([[12.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]])
DESIRED: array([[12. +0.j, 0. +0.j, 0. +0.j, 0. +0.j],
[ 0.125 +0.j, 0.291667+0.j, 0.020833+0.j, 0.145833+0.j],
[ 0. +0.j, 0.020833+0.j, 0.041667+0.j, 0.020833+0.j],
[ 0.125 +0.j, 0.145833+0.j, 0.020833+0.j, 0.291667+0.j]])
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TestMatrices.test_zero_last_row:
TestMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-05, atol=0
Mismatched elements: 7 / 16 (43.8%)
Max absolute difference among violations: 0.291667
Max relative difference among violations: 1.
ACTUAL: array([[12.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, 4.+0.j]])
DESIRED: array([[12. +0.j, 0. +0.j, 0. +0.j, 0. +0.j],
[ 0.125 +0.j, 0.291667+0.j, 0.020833+0.j, 0.145833+0.j],
[ 0. +0.j, 0.020833+0.j, 0.041667+0.j, 0.020833+0.j],
[ 0. +0.j, 0. +0.j, 0. +0.j, 4. +0.j]])
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TestMatrices.test_mat_nbytes:
TestMatrices#L1
AssertionError: assert np.int64(224) == (14 * 8)
+ where np.int64(224) = Mat(Sparsity((DataSet(Set((4, 4, 4), 'nodes'), (1,), 'dnodes'), DataSet(Set((4, 4, 4), 'nodes'), (1,), 'dnodes')), {(0, 0): frozenset({(Map(Set((2, 2, 2), 'elements'), Set((4, 4, 4), 'nodes'), 3, None, 'elem_node', None, None), Map(Set((2, 2, 2), 'elements'), Set((4, 4, 4), 'nodes'), 3, None, 'elem_node', None, None), (<IterationRegion.ALL: 4>,))})}, name='sparsity', nested=False, block_sparse=True, diagonal_block=True), dtype('complex128'), 'mat').nbytes
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TestMixedMatrices.test_assemble_mixed_mat:
TestMixedMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-12, atol=0
Mismatched elements: 3 / 9 (33.3%)
Max absolute difference among violations: 9.
Max relative difference among violations: 1.
ACTUAL: array([[1.+1.j, 0.+0.j, 0.+0.j],
[0.+0.j, 4.+4.j, 0.+0.j],
[0.+0.j, 0.+0.j, 9.+9.j]])
DESIRED: array([[1., 0., 0.],
[0., 4., 0.],
[0., 0., 9.]])
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TestMixedMatrices.test_assemble_mixed_rhs:
TestMixedMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-12, atol=0
Mismatched elements: 3 / 3 (100%)
Max absolute difference among violations: 3.
Max relative difference among violations: 1.
ACTUAL: array([1.+1.j, 2.+2.j, 3.+3.j])
DESIRED: array([1., 2., 3.])
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TestMixedMatrices.test_assemble_mixed_rhs_vector:
TestMixedMatrices#L1
AssertionError:
Not equal to tolerance rtol=1e-12, atol=0
Mismatched elements: 6 / 6 (100%)
Max absolute difference among violations: 3.
Max relative difference among violations: 1.
ACTUAL: array([[1.+1.j, 1.+1.j],
[2.+2.j, 2.+2.j],
[3.+3.j, 3.+3.j]])
DESIRED: array([[1., 1.],
[2., 2.],
[3., 3.]])
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TestSubSet.test_matrix:
TestSubSet#L1
RuntimeError: Can only create a matrix of type <class 'numpy.complex128'>, float64 is not supported
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TestDatAPI.test_dat_initialise_data[1]:
TestDatAPI#L1
AssertionError: assert (5 == (5 * 1) and dtype('complex128') == <class 'numpy.float64'>)
+ where 5 = array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]).size
+ where array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]) = Dat(DataSet(Set((5, 5, 5), 'foo'), (1,), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44ebdf08f0').data
+ and 5 = DataSet(Set((5, 5, 5), 'foo'), (1,), 'dfoo').size
+ and 1 = DataSet(Set((5, 5, 5), 'foo'), (1,), 'dfoo').cdim
+ and dtype('complex128') = array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]).dtype
+ where array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j]) = Dat(DataSet(Set((5, 5, 5), 'foo'), (1,), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44ebdf08f0').data
+ and <class 'numpy.float64'> = np.float64
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TestDatAPI.test_dat_initialise_data[2]:
TestDatAPI#L1
AssertionError: assert (10 == (5 * 2) and dtype('complex128') == <class 'numpy.float64'>)
+ where 10 = array([[0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j]]).size
+ where array([[0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j]]) = Dat(DataSet(Set((5, 5, 5), 'foo'), (2,), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44ebdf1d00').data
+ and 5 = DataSet(Set((5, 5, 5), 'foo'), (2,), 'dfoo').size
+ and 2 = DataSet(Set((5, 5, 5), 'foo'), (2,), 'dfoo').cdim
+ and dtype('complex128') = array([[0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j]]).dtype
+ where array([[0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j]]) = Dat(DataSet(Set((5, 5, 5), 'foo'), (2,), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44ebdf1d00').data
+ and <class 'numpy.float64'> = np.float64
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TestDatAPI.test_dat_initialise_data[dset2]:
TestDatAPI#L1
AssertionError: assert (30 == (5 * 6) and dtype('complex128') == <class 'numpy.float64'>)
+ where 30 = array([[[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]]]).size
+ where array([[[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]]]) = Dat(DataSet(Set((5, 5, 5), 'foo'), (2, 3), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44ebdf1670').data
+ and 5 = DataSet(Set((5, 5, 5), 'foo'), (2, 3), 'dfoo').size
+ and 6 = DataSet(Set((5, 5, 5), 'foo'), (2, 3), 'dfoo').cdim
+ and dtype('complex128') = array([[[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]]]).dtype
+ where array([[[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]],\n\n [[0.+0.j, 0.+0.j, 0.+0.j],\n [0.+0.j, 0.+0.j, 0.+0.j]]]) = Dat(DataSet(Set((5, 5, 5), 'foo'), (2, 3), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44ebdf1670').data
+ and <class 'numpy.float64'> = np.float64
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TestDatAPI.test_dat_dtype[1]:
TestDatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Dat(DataSet(Set((5, 5, 5), 'foo'), (1,), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44eb4f04d0').dtype
+ and <class 'numpy.float64'> = np.double
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TestDatAPI.test_dat_dtype[2]:
TestDatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Dat(DataSet(Set((5, 5, 5), 'foo'), (2,), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44eb4f1a00').dtype
+ and <class 'numpy.float64'> = np.double
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TestDatAPI.test_dat_dtype[dset2]:
TestDatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Dat(DataSet(Set((5, 5, 5), 'foo'), (2, 3), 'dfoo'), None, dtype('complex128'), 'dat_#x7f44eb4f23f0').dtype
+ and <class 'numpy.float64'> = np.double
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TestMatAPI.test_mat_dtype:
TestMatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Mat(Sparsity((DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset'), DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset')), {(0, 0): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), (<IterationRegion.ALL: 4>,))})}, name='sparsity_#x7f44f1d8d670', nested=False, block_sparse=True, diagonal_block=True), dtype('complex128'), 'mat_#x7f44f1c665d0').dtype
+ and <class 'numpy.float64'> = np.double
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TestMatAPI.test_mat_properties:
TestMatAPI#L1
RuntimeError: Can only create a matrix of type <class 'numpy.complex128'>, float64 is not supported
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TestMatAPI.test_mat_mixed[ms0]:
TestMatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Mat(Sparsity((MixedDataSet((DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset'), DataSet(Set((5, 5, 5), 'foo'), (1,), 'dset_#x7f44f1bf6750'))), MixedDataSet((DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset'), DataSet(Set((5, 5, 5), 'foo'), (1,), 'dset_#x7f44f1bf6750')))), {(0, 0): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), (<IterationRegion.ALL: 4>,))}), (0, 1): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), Map(Set((2, 2, 2), 'iterset'), Set((5, 5, 5), 'foo'), 2, None, 'm_iterset_set', None, None), (<IterationRegion.ALL: 4>,))}), (1, 0): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((5, 5, 5), 'foo'), 2, None, 'm_iterset_set', None, None), Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), (<IterationRegion.ALL: 4>,))}), (1, 1): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((5, 5, 5), 'foo'), 2, None, 'm_iterset_set', None, None), Map(Set((2, 2, 2), 'iterset'), Set((5, 5, 5), 'foo'), 2, None, 'm_iterset_set', None, None), (<IterationRegion.ALL: 4>,))})}, name='sparsity_#x7f44f1bf63f0', nested=True, block_sparse=True, diagonal_block=True), dtype('complex128'), 'mat_#x7f44f14e1310').dtype
+ and <class 'numpy.float64'> = np.double
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TestMatAPI.test_mat_mixed[ms1]:
TestMatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Mat(Sparsity((MixedDataSet((DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset'), DataSet(Set((5, 5, 5), 'foo'), (1,), 'dset_#x7f44f1bcc620'))), DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset')), {(0, 0): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), (<IterationRegion.ALL: 4>,))}), (1, 0): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((5, 5, 5), 'foo'), 2, None, 'm_iterset_set', None, None), Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), (<IterationRegion.ALL: 4>,))})}, name='sparsity_#x7f44f1bcfe30', nested=True, block_sparse=True, diagonal_block=True), dtype('complex128'), 'mat_#x7f44f1d1f0b0').dtype
+ and <class 'numpy.float64'> = np.double
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TestMatAPI.test_mat_mixed[ms2]:
TestMatAPI#L1
AssertionError: assert dtype('complex128') == <class 'numpy.float64'>
+ where dtype('complex128') = Mat(Sparsity((DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset'), MixedDataSet((DataSet(Set((3, 3, 3), 'toset'), (1,), 'dtoset'), DataSet(Set((5, 5, 5), 'foo'), (1,), 'dset_#x7f44f1a1c3b0')))), {(0, 0): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), (<IterationRegion.ALL: 4>,))}), (0, 1): frozenset({(Map(Set((2, 2, 2), 'iterset'), Set((3, 3, 3), 'toset'), 2, None, 'm_iterset_toset', None, None), Map(Set((2, 2, 2), 'iterset'), Set((5, 5, 5), 'foo'), 2, None, 'm_iterset_set', None, None), (<IterationRegion.ALL: 4>,))})}, name='sparsity_#x7f44f1a1f710', nested=True, block_sparse=True, diagonal_block=True), dtype('complex128'), 'mat_#x7f44f1d1d1f0').dtype
+ and <class 'numpy.float64'> = np.double
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TestCallables.test_inverse_callable:
TestCallables#L1
AssertionError: assert False
+ where False = <function allclose at 0x7f4528f2a830>(array([[[-2. , 1. ],\n [ 1.5, -0.5]]]), array([[[ nan, -inf],\n [-inf, inf]]]))
+ where <function allclose at 0x7f4528f2a830> = np.allclose
+ and array([[[ nan, -inf],\n [-inf, inf]]]) = Dat(DataSet(Set((1, 1, 1), 'set_#x7f44ebfaf830'), (2, 2), 'dset_#x7f44ebfaeff0'), None, dtype('float64'), 'dat_#x7f44ebfaef30').data
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TestCallables.test_solve_callable:
TestCallables#L1
AssertionError: assert False
+ where False = <function allclose at 0x7f4528f2a830>(array([[[0.28571429],\n [0.42857143]]]), array([[[ 0.4],\n [-0.2]]]))
+ where <function allclose at 0x7f4528f2a830> = np.allclose
+ and array([[[ 0.4],\n [-0.2]]]) = Dat(DataSet(Set((1, 1, 1), 'set_#x7f44f1af6450'), (2, 1), 'dset_#x7f44f1af6ff0'), None, dtype('float64'), 'dat_#x7f44f1af4e90').data
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TestDat.test_dat_nbytes[1]:
TestDat#L1
AssertionError: assert 160 == ((10 * 8) * 1)
+ where 160 = Dat(DataSet(Set((10, 10, 10), 'set_#x7f44ebe16630'), (1,), 'dset_#x7f44ebe16120'), None, dtype('complex128'), 'dat_#x7f44ebe14200').nbytes
+ where Dat(DataSet(Set((10, 10, 10), 'set_#x7f44ebe16630'), (1,), 'dset_#x7f44ebe16120'), None, dtype('complex128'), 'dat_#x7f44ebe14200') = <class 'pyop2.types.dat.Dat'>((Set((10, 10, 10), 'set_#x7f44ebe16630') ** 1))
+ where <class 'pyop2.types.dat.Dat'> = op2.Dat
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TestDat.test_dat_nbytes[2]:
TestDat#L1
AssertionError: assert 320 == ((10 * 8) * 2)
+ where 320 = Dat(DataSet(Set((10, 10, 10), 'set_#x7f44ebe15970'), (2,), 'dset_#x7f44ebe15040'), None, dtype('complex128'), 'dat_#x7f44f1af4980').nbytes
+ where Dat(DataSet(Set((10, 10, 10), 'set_#x7f44ebe15970'), (2,), 'dset_#x7f44ebe15040'), None, dtype('complex128'), 'dat_#x7f44f1af4980') = <class 'pyop2.types.dat.Dat'>((Set((10, 10, 10), 'set_#x7f44ebe15970') ** 2))
+ where <class 'pyop2.types.dat.Dat'> = op2.Dat
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TestDat.test_dat_version:
TestDat#L1
AssertionError: Can't create Vec with type float64, must be <class 'numpy.complex128'>
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TestDat.test_mixed_dat_version:
TestDat#L1
pyop2.exceptions.DataValueError: MixedDat with different dtypes is not supported
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TestMixedIndirectLoop.test_mixed_non_mixed_dat[iterset0]:
TestMixedIndirectLoop#L1
AssertionError: assert (False)
+ where False = all(array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) == 1.0)
+ where array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) = Dat(DataSet(Set((4096, 4096, 4096), 'indset'), (1,), 'dset_#x7f44f0440aa0'), None, dtype('complex128'), 'dat_#x7f44f0442cf0').data
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TestMixedIndirectLoop.test_mixed_non_mixed_dat[iterset1]:
TestMixedIndirectLoop#L1
AssertionError: assert (False)
+ where False = all(array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) == 1.0)
+ where array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) = Dat(DataSet(Set((4096, 4096, 4096), 'indset'), (1,), 'dset_#x7f44f03033e0'), None, dtype('complex128'), 'dat_#x7f44f0319850').data
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TestMixedIndirectLoop.test_mixed_non_mixed_dat[iterset2]:
TestMixedIndirectLoop#L1
AssertionError: assert (False)
+ where False = all(array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) == 1.0)
+ where array([1.+1.j, 1.+1.j, 1.+1.j, ..., 1.+1.j, 1.+1.j, 1.+1.j]) = Dat(DataSet(Set((4096, 4096, 4096), 'indset'), (1,), 'dset_#x7f44f02061b0'), None, dtype('complex128'), 'dat_#x7f44f0378bf0').data
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test_scaled_mass.test_math_functions[tensor-Function-f=(1)-expr=(f + tanh(f))]:
tests/regression/test_scaled_mass.py#L1
failed on setup with "worker 'gw5' crashed while running 'tests/regression/test_scaled_mass.py::test_math_functions[tensor-Function-f=(1)-expr=(f + tanh(f))]'"
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Run zenodo canary
The following actions use a deprecated Node.js version and will be forced to run on node20: actions/setup-python@v4. For more info: https://github.blog/changelog/2024-03-07-github-actions-all-actions-will-run-on-node20-instead-of-node16-by-default/
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