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scale function(_get_mean_var) updated for dense array, speedup upto ~4.65x #3099

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Merge pull request #2 from scverse/scale-mean-variance

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scale function(_get_mean_var) updated for dense array, speedup upto ~4.65x #3099

Merge pull request #2 from scverse/scale-mean-variance
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Azure Pipelines / scverse.scanpy failed Jun 26, 2024 in 23m 54s

Build #20240626.3 had test failures

5 errors / 1 warnings

Details

Tests

  • Failed: 18 (0.25%)
  • Passed: 6,518 (91.65%)
  • Other: 576 (8.10%)
  • Total: 7,112
Code coverage

  • 9556 of 12552 line covered (76.13%)

Annotations

Check failure on line 2042 in Build log

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@azure-pipelines azure-pipelines / scverse.scanpy

Build log #L2042 

Bash exited with code '1'.

Check failure on line 2176 in Build log

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@azure-pipelines azure-pipelines / scverse.scanpy

Build log #L2176 

Bash exited with code '1'.

Check failure on line 2504 in Build log

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@azure-pipelines azure-pipelines / scverse.scanpy

Build log #L2504 

Bash exited with code '1'.

Check failure on line 1849 in Build log

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@azure-pipelines azure-pipelines / scverse.scanpy

Build log #L1849 

Bash exited with code '132'.

Check failure on line 1 in tests/test_score_genes.py::test_score_with_reference

See this annotation in the file changed.

@azure-pipelines azure-pipelines / scverse.scanpy

tests/test_score_genes.py::test_score_with_reference 

def test_score_with_reference():
        """
        Checks if score_genes output agrees with pre-computed reference values.
        The reference values had been generated using the same code
        and stored as a pickle object in ./data
        """
    
        adata = paul15()
        sc.pp.normalize_per_cell(adata, counts_per_cell_after=10000)
        sc.pp.scale(adata)
    
        sc.tl.score_genes(adata, gene_list=adata.var_names[:100], score_name="Test")
        with (HERE / "score_genes_reference_paul2015.pkl").open("rb") as file:
            reference = pickle.load(file)
        # np.testing.assert_allclose(reference, adata.obs["Test"].to_numpy())
>       np.testing.assert_array_equal(reference, adata.obs["Test"].to_numpy())

tests/test_score_genes.py:77: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

args = (<built-in function eq>, array([-0.2027711941, -0.0095327853, -0.0092715188, ...,  0.2243069104,
       -0.0767864967,...61957]), array([-0.2327050515,  0.0162357776, -0.0057529853, ...,  0.1831248169,
       -0.0875716893, -0.0273508919]))
kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True}

    @wraps(func)
    def inner(*args, **kwds):
        with self._recreate_cm():
>           return func(*args, **kwds)
E           AssertionError: 
E           Arrays are not equal
E           
E           Mismatched elements: 2730 / 2730 (100%)
E           Max absolute difference: 0.1607912583
E           Max relative difference: 1538.698935321
E            x: array([-0.202771, -0.009533, -0.009272, ...,  0.224307, -0.076786,
E                  -0.012066])
E            y: array([-0.232705,  0.016236, -0.005753, ...,  0.183125, -0.087572,
E                  -0.027351])

/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/contextlib.py:81: AssertionError
Raw output 
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/contextlib.py:81: AssertionError:

Check failure on line 1 in tests/test_score_genes.py::test_score_with_reference

See this annotation in the file changed.

@azure-pipelines azure-pipelines / scverse.scanpy

tests/test_score_genes.py::test_score_with_reference 

def test_score_with_reference():
        """
        Checks if score_genes output agrees with pre-computed reference values.
        The reference values had been generated using the same code
        and stored as a pickle object in ./data
        """
    
        adata = paul15()
        sc.pp.normalize_per_cell(adata, counts_per_cell_after=10000)
        sc.pp.scale(adata)
    
        sc.tl.score_genes(adata, gene_list=adata.var_names[:100], score_name="Test")
        with (HERE / "score_genes_reference_paul2015.pkl").open("rb") as file:
            reference = pickle.load(file)
        # np.testing.assert_allclose(reference, adata.obs["Test"].to_numpy())
>       np.testing.assert_array_equal(reference, adata.obs["Test"].to_numpy())

tests/test_score_genes.py:77: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

args = (<built-in function eq>, array([-0.2027711941, -0.0095327853, -0.0092715188, ...,  0.2243069104,
       -0.0767864967,...61957]), array([-0.2327050515,  0.0162357776, -0.0057529853, ...,  0.1831248169,
       -0.0875716893, -0.0273508919]))
kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True}

    @wraps(func)
    def inner(*args, **kwds):
        with self._recreate_cm():
>           return func(*args, **kwds)
E           AssertionError: 
E           Arrays are not equal
E           
E           Mismatched elements: 2730 / 2730 (100%)
E           Max absolute difference: 0.1607912583
E           Max relative difference: 1538.698935321
E            x: array([-0.202771, -0.009533, -0.009272, ...,  0.224307, -0.076786,
E                  -0.012066])
E            y: array([-0.232705,  0.016236, -0.005753, ...,  0.183125, -0.087572,
E                  -0.027351])

/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/contextlib.py:81: AssertionError
Raw output 
/opt/hostedtoolcache/Python/3.12.4/x64/lib/python3.12/contextlib.py:81: AssertionError:

Check failure on line 1 in tests/test_score_genes.py::test_score_with_reference

See this annotation in the file changed.

@azure-pipelines azure-pipelines / scverse.scanpy

tests/test_score_genes.py::test_score_with_reference 

def test_score_with_reference():
        """
        Checks if score_genes output agrees with pre-computed reference values.
        The reference values had been generated using the same code
        and stored as a pickle object in ./data
        """
    
        adata = paul15()
        sc.pp.normalize_per_cell(adata, counts_per_cell_after=10000)
        sc.pp.scale(adata)
    
        sc.tl.score_genes(adata, gene_list=adata.var_names[:100], score_name="Test")
        with (HERE / "score_genes_reference_paul2015.pkl").open("rb") as file:
            reference = pickle.load(file)
        # np.testing.assert_allclose(reference, adata.obs["Test"].to_numpy())
>       np.testing.assert_array_equal(reference, adata.obs["Test"].to_numpy())
E       AssertionError: 
E       Arrays are not equal
E       
E       Mismatched elements: 2730 / 2730 (100%)
E       Max absolute difference: 0.1607912583
E       Max relative difference: 1538.698935321
E        x: array([-0.202771, -0.009533, -0.009272, ...,  0.224307, -0.076786,
E              -0.012066])
E        y: array([-0.232705,  0.016236, -0.005753, ...,  0.183125, -0.087572,
E              -0.027351])

tests/test_score_genes.py:77: AssertionError
Raw output 
/home/vsts/work/1/s/tests/test_score_genes.py:77: AssertionError:

Check failure on line 1 in tests/test_backed.py::test_backed_error[sparse-pca]

See this annotation in the file changed.

@azure-pipelines azure-pipelines / scverse.scanpy

tests/test_backed.py::test_backed_error[sparse-pca] 

Test failed
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