make[1]: Entering directory '/build/reproducible-path/python-numpy-groupies-0.10.2'20, 20, 20],\n dtype=int64).dtype
pytest-3 -rls
============================= test session starts ==============================
platform linux -- Python 3.13.2, pytest-8.3.5, pluggy-1.5.0
rootdir: /build/reproducible-path/python-numpy-groupies-0.10.2
configfile: pyproject.toml
plugins: typeguard-4.4.2
collected 1117 items / 260 deselected / 857 selected
numpy_groupies/tests/test_compare.py ..............s..s...........s..s.. [ 4%]
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numpy_groupies/tests/test_generic.py .......................sss......... [ 38%]
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numpy_groupies/tests/test_indices.py ss [ 99%]
numpy_groupies/tests/test_utils.py ... [100%]
=================================== FAILURES ===================================
__________________________ test_cmp[pandas/np-len-0] ___________________________
aggregate_cmp = {'request': <SubRequest 'aggregate_cmp' for <Function test_cmp[pandas/np-sum-0]>>, 'seed': 100, 'test_pair': 'pandas/n..., 'somea': array([ nan, 0. , 0.51545692, ..., 1.51932228, 0. ,
0.87432034], shape=(20000,))}
func = 'len', fill_value = 0, decimal = 10
@pytest.mark.filterwarnings("ignore:numpy.ufunc size changed")
@pytest.mark.deselect_if(func=_deselect_purepy_nanfuncs)
@pytest.mark.parametrize("fill_value", [0, 1, np.nan])
@pytest.mark.parametrize("func", func_list, ids=lambda x: getattr(x, "__name__", x))
def test_cmp(aggregate_cmp, func, fill_value, decimal=10):
is_nanfunc = "nan" in getattr(func, "__name__", func)
a = aggregate_cmp.nana if is_nanfunc else aggregate_cmp.a
try:
ref = aggregate_cmp.func_ref(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
with pytest.raises(ValueError):
aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
else:
try:
res = aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
if np.isnan(fill_value) and aggregate_cmp.test_pair.endswith("py"):
pytest.skip(
"pure python version uses lists and does not raise ValueErrors when inserting nan into integers"
)
else:
raise
if isinstance(ref, np.ndarray):
assert res.dtype == ref.dtypeE AssertionError: assert dtype('int64') == dtype('int32')
E + where dtype('int64') = array([20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20, 20, 20, 20, ... 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,
E + and dtype('int32') = array([20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20, 20, 20, 20, ...20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20,20, 20, 20, 20, 20, 20, 20, 20]).dtype
numpy_groupies/tests/test_compare.py:122: AssertionError __________________________ test_cmp[pandas/np-len-1] ___________________________20, 20, 20],\n dtype=int64).dtype
aggregate_cmp = {'request': <SubRequest 'aggregate_cmp' for <Function test_cmp[pandas/np-sum-0]>>, 'seed': 100, 'test_pair': 'pandas/n..., 'somea': array([ nan, 0. , 0.51545692, ..., 1.51932228, 0. ,
0.87432034], shape=(20000,))}
func = 'len', fill_value = 1, decimal = 10
@pytest.mark.filterwarnings("ignore:numpy.ufunc size changed")
@pytest.mark.deselect_if(func=_deselect_purepy_nanfuncs)
@pytest.mark.parametrize("fill_value", [0, 1, np.nan])
@pytest.mark.parametrize("func", func_list, ids=lambda x: getattr(x, "__name__", x))
def test_cmp(aggregate_cmp, func, fill_value, decimal=10):
is_nanfunc = "nan" in getattr(func, "__name__", func)
a = aggregate_cmp.nana if is_nanfunc else aggregate_cmp.a
try:
ref = aggregate_cmp.func_ref(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
with pytest.raises(ValueError):
aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
else:
try:
res = aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
if np.isnan(fill_value) and aggregate_cmp.test_pair.endswith("py"):
pytest.skip(
"pure python version uses lists and does not raise ValueErrors when inserting nan into integers"
)
else:
raise
if isinstance(ref, np.ndarray):
assert res.dtype == ref.dtypeE AssertionError: assert dtype('int64') == dtype('int32')
E + where dtype('int64') = array([20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20, 20, 20, 20, ... 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,
E + and dtype('int32') = array([20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20, 20, 20, 20, ...20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20,\n 20, 20, 20, 20, 20, 20,20, 20, 20, 20, 20, 20, 20, 20]).dtype
numpy_groupies/tests/test_compare.py:122: AssertionError _________________________ test_cmp[pandas/np-nanlen-0] _________________________13, 7, 0],\n dtype=int64).dtype
aggregate_cmp = {'request': <SubRequest 'aggregate_cmp' for <Function test_cmp[pandas/np-sum-0]>>, 'seed': 100, 'test_pair': 'pandas/n..., 'somea': array([ nan, 0. , 0.51545692, ..., 1.51932228, 0. ,
0.87432034], shape=(20000,))}
func = 'nanlen', fill_value = 0, decimal = 10
@pytest.mark.filterwarnings("ignore:numpy.ufunc size changed")
@pytest.mark.deselect_if(func=_deselect_purepy_nanfuncs)
@pytest.mark.parametrize("fill_value", [0, 1, np.nan])
@pytest.mark.parametrize("func", func_list, ids=lambda x: getattr(x, "__name__", x))
def test_cmp(aggregate_cmp, func, fill_value, decimal=10):
is_nanfunc = "nan" in getattr(func, "__name__", func)
a = aggregate_cmp.nana if is_nanfunc else aggregate_cmp.a
try:
ref = aggregate_cmp.func_ref(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
with pytest.raises(ValueError):
aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
else:
try:
res = aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
if np.isnan(fill_value) and aggregate_cmp.test_pair.endswith("py"):
pytest.skip(
"pure python version uses lists and does not raise ValueErrors when inserting nan into integers"
)
else:
raise
if isinstance(ref, np.ndarray):
assert res.dtype == ref.dtypeE AssertionError: assert dtype('int64') == dtype('int32')
E + where dtype('int64') = array([12, 13, 7, 13, 0, 6, 7, 14, 7, 7, 14, 0, 0, 7, 0, 0, 7,\n 14, 14, 14, 0, 0, 0, 7, 6, 0, ... 14, 7, 7, 0, 7, 6, 6, 14, 6,\n 7, 6, 0, 7, 6, 0, 12, 14, 0, 7, 7,
E + and dtype('int32') = array([12, 13, 7, 13, 0, 6, 7, 14, 7, 7, 14, 0, 0, 7, 0, 0, 7,\n 14, 14, 14, 0, 0, 0, 7, 6, 0, ... 6, 13, 0, 7, 7, 14, 7, 7, 0, 7, 6, 6, 14, 6,\n 7, 6, 0, 7, 6, 0,12, 14, 0, 7, 7, 13, 7, 0]).dtype
numpy_groupies/tests/test_compare.py:122: AssertionError _________________________ test_cmp[pandas/np-nanlen-1] _________________________13, 7, 1],\n dtype=int64).dtype
aggregate_cmp = {'request': <SubRequest 'aggregate_cmp' for <Function test_cmp[pandas/np-sum-0]>>, 'seed': 100, 'test_pair': 'pandas/n..., 'somea': array([ nan, 0. , 0.51545692, ..., 1.51932228, 0. ,
0.87432034], shape=(20000,))}
func = 'nanlen', fill_value = 1, decimal = 10
@pytest.mark.filterwarnings("ignore:numpy.ufunc size changed")
@pytest.mark.deselect_if(func=_deselect_purepy_nanfuncs)
@pytest.mark.parametrize("fill_value", [0, 1, np.nan])
@pytest.mark.parametrize("func", func_list, ids=lambda x: getattr(x, "__name__", x))
def test_cmp(aggregate_cmp, func, fill_value, decimal=10):
is_nanfunc = "nan" in getattr(func, "__name__", func)
a = aggregate_cmp.nana if is_nanfunc else aggregate_cmp.a
try:
ref = aggregate_cmp.func_ref(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
with pytest.raises(ValueError):
aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
else:
try:
res = aggregate_cmp.func(aggregate_cmp.group_idx, a, func=func, fill_value=fill_value)
except ValueError:
if np.isnan(fill_value) and aggregate_cmp.test_pair.endswith("py"):
pytest.skip(
"pure python version uses lists and does not raise ValueErrors when inserting nan into integers"
)
else:
raise
if isinstance(ref, np.ndarray):
assert res.dtype == ref.dtypeE AssertionError: assert dtype('int64') == dtype('int32')
E + where dtype('int64') = array([12, 13, 7, 13, 1, 6, 7, 14, 7, 7, 14, 1, 1, 7, 1, 1, 7,\n 14, 14, 14, 1, 1, 1, 7, 6, 1, ... 14, 7, 7, 1, 7, 6, 6, 14, 6,\n 7, 6, 1, 7, 6, 1, 12, 14, 1, 7, 7,
E + and dtype('int32') = array([12, 13, 7, 13, 1, 6, 7, 14, 7, 7, 14, 1, 1, 7, 1, 1, 7,\n 14, 14, 14, 1, 1, 1, 7, 6, 1, ... 6, 13, 1, 7, 7, 14, 7, 7, 1, 7, 6, 6, 14, 6,\n 7, 6, 1, 7, 6, 1,12, 14, 1, 7, 7, 13, 7, 1]).dtype
numpy_groupies/tests/test_compare.py:122: AssertionError =============================== warnings summary ===============================
numpy_groupies/tests/test_generic.py::test_ndim_group_idx[ufunc-None] numpy_groupies/tests/test_generic.py::test_ndim_group_idx[ufunc-size1] numpy_groupies/tests/test_generic.py::test_ndim_group_idx[numpy-None] numpy_groupies/tests/test_generic.py::test_ndim_group_idx[numpy-size1] numpy_groupies/tests/test_generic.py::test_ndim_group_idx[pandas-None] numpy_groupies/tests/test_generic.py::test_ndim_group_idx[pandas-size1]
/build/reproducible-path/python-numpy-groupies-0.10.2/numpy_groupies/utils.py:308: RuntimeWarning: overflow encountered in scalar multiply
maxval = np.iinfo(a_dtype).max * n
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html =========================== short test summary info ============================
SKIPPED [5] numpy_groupies/tests/test_compare.py:116: pure python version uses lists and does not raise ValueErrors when inserting nan into integers
SKIPPED [191] numpy_groupies/tests/__init__.py:55: Functionality not implemented
SKIPPED [81] numpy_groupies/tests/test_compare.py:99: Implementation not available
SKIPPED [4] numpy_groupies/tests/test_compare.py:132: Implementation not available
SKIPPED [4] numpy_groupies/tests/test_compare.py:127: pandas doesn't fill indices for all-nan groups with fill_value, but with -inf instead
SKIPPED [7] numpy_groupies/tests/test_generic.py:238: pandas always skips nan values
SKIPPED [1] numpy_groupies/tests/test_generic.py:253: pandas always skips nan values
SKIPPED [1] numpy_groupies/tests/test_generic.py:276: pandas always ignores nans
SKIPPED [1] numpy_groupies/tests/test_generic.py:291: pandas doesn't fill indices for all-nan groups with fill_value but with -inf instead
SKIPPED [1] numpy_groupies/tests/test_generic.py:511: pandas always skips nan values
SKIPPED [1] numpy_groupies/tests/test_indices.py: got empty parameter set ['aggregate_nb_wv'], function test_step_indices_length at /build/reproducible-path/python-numpy-groupies-0.10.2/numpy_groupies/tests/test_indices.py:16
SKIPPED [1] numpy_groupies/tests/test_indices.py: got empty parameter set ['aggregate_nb_wv'], function test_step_indices_fields at /build/reproducible-path/python-numpy-groupies-0.10.2/numpy_groupies/tests/test_indices.py:25
==== 4 failed, 555 passed, 298 skipped, 260 deselected, 6 warnings in 3.20s ====
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