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Testing NaN does not work
See original GitHub issueI have a numpy array that I have to test with inside a NaN that has to be there. Version 2.2.0 works, while version 2.3.0 does not work.
output of 2.2.0:
bertossa@pippo:~/analisi/tests$ pytest -sv . -k gk
WARNING: cannot import thermocepstrum
cite as:
Riccardo Bertossa, analisi
https://github.com/rikigigi/analisi
(c) 2017-2021
=========
COMPILED AT Jan 17 2022 14:47:14 by /usr/bin/c++ whith flags (Release) -O3 -DNDEBUG -O3 (Debug) -g -DEIGEN_INITIALIZE_MATRICES_BY_NAN -fsanitize=leak -fsanitize=undefined (build type was Release) on a Linux-5.4.0-94-generic whith processor x86_64
With python support: /usr/lib/x86_64-linux-gnu/libpython3.8.so
With gromacs XDR file conversion support
v0.3.4
============================================================================ test session starts ============================================================================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.11.0, pluggy-0.13.0 -- /usr/bin/python3
cachedir: .pytest_cache
rootdir: /home/bertossa/analisi/tests
plugins: datadir-1.3.1, regressions-2.2.0
collected 6 items / 5 deselected / 1 selected
test_gk.py::test_gk [[ 1.15338509e+05 -3.54402664e+01 -3.54402664e+01 ... 0.00000000e+00
0.00000000e+00 0.00000000e+00]
[ 1.13409212e+05 -3.51673102e+01 -3.49856870e+01 ... 3.53293021e-02
7.91862554e+04 nan]
[ 1.07866235e+05 -3.41664742e+01 -3.38088613e+01 ... 5.21211914e-02
1.55216495e+05 3.95931277e+04]
...
[-2.73309429e+03 -2.66983885e-01 1.39421901e+00 ... -2.67101979e-02
1.62004622e+05 5.34430500e+05]
[-2.58976152e+03 -1.40244210e-01 1.24827661e+00 ... -2.65180986e-02
1.59872994e+05 5.34257456e+05]
[-2.37993149e+03 -2.79107527e-02 1.07349726e+00 ... -2.63087491e-02
1.57897803e+05 5.34083800e+05]]
PASSED
============================================================================= warnings summary ==============================================================================
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/widget_selection.py:9
/usr/lib/python3/dist-packages/ipywidgets/widgets/widget_selection.py:9: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
from collections import Mapping
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/interaction.py:29
/usr/lib/python3/dist-packages/ipywidgets/widgets/interaction.py:29: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
from collections import Iterable, Mapping
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/widget_link.py:19
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/widget_link.py:19
/usr/lib/python3/dist-packages/ipywidgets/widgets/widget_link.py:19: DeprecationWarning: Traits should be given as instances, not types (for example, `Int()`, not `Int`) Passing types is deprecated in traitlets 4.1.
super(WidgetTraitTuple, self).__init__(Instance(Widget), Unicode, **kwargs)
test_gk.py::test_gk
test_gk.py::test_gk
/home/bertossa/.local/lib/python3.8/site-packages/pytest_regressions/dataframe_regression.py:126: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
if data_type in [float, np.float, np.float16, np.float32, np.float64]:
-- Docs: https://docs.pytest.org/en/stable/warnings.html
================================================================ 1 passed, 5 deselected, 6 warnings in 1.66s ================================================================
bertossa@pippo:~/analisi/tests$
output of 2.3.0:
bertossa@pippo:~/analisi/tests$ pytest -sv . -k gk
WARNING: cannot import thermocepstrum
cite as:
Riccardo Bertossa, analisi
https://github.com/rikigigi/analisi
(c) 2017-2021
=========
COMPILED AT Jan 17 2022 14:47:14 by /usr/bin/c++ whith flags (Release) -O3 -DNDEBUG -O3 (Debug) -g -DEIGEN_INITIALIZE_MATRICES_BY_NAN -fsanitize=leak -fsanitize=undefined (build type was Release) on a Linux-5.4.0-94-generic whith processor x86_64
With python support: /usr/lib/x86_64-linux-gnu/libpython3.8.so
With gromacs XDR file conversion support
v0.3.4
============================================================================ test session starts ============================================================================
platform linux -- Python 3.8.10, pytest-6.2.5, py-1.11.0, pluggy-0.13.0 -- /usr/bin/python3
cachedir: .pytest_cache
rootdir: /home/bertossa/analisi/tests
plugins: datadir-1.3.1, regressions-2.3.0
collected 6 items / 5 deselected / 1 selected
test_gk.py::test_gk [[ 1.15338509e+05 -3.54402664e+01 -3.54402664e+01 ... 0.00000000e+00
0.00000000e+00 0.00000000e+00]
[ 1.13409212e+05 -3.51673102e+01 -3.49856870e+01 ... 3.53293021e-02
7.91862554e+04 nan]
[ 1.07866235e+05 -3.41664742e+01 -3.38088613e+01 ... 5.21211914e-02
1.55216495e+05 3.95931277e+04]
...
[-2.73309429e+03 -2.66983885e-01 1.39421901e+00 ... -2.67101979e-02
1.62004622e+05 5.34430500e+05]
[-2.58976152e+03 -1.40244210e-01 1.24827661e+00 ... -2.65180986e-02
1.59872994e+05 5.34257456e+05]
[-2.37993149e+03 -2.79107527e-02 1.07349726e+00 ... -2.63087491e-02
1.57897803e+05 5.34083800e+05]]
FAILED
================================================================================= FAILURES ==================================================================================
__________________________________________________________________________________ test_gk __________________________________________________________________________________
left = array(['115338.50895090569', '-35.440266364698509', '-35.440266364698509',
..., '-0.026308749054506145', '157897.80272819981',
'534083.79967621446'], dtype=object)
right = array(['115338.50895090567', '-35.440266364698509', '-35.440266364698509',
..., '-0.02630874905450617', '157897.80272819955',
'534083.79967621388'], dtype=object)
op = <built-in function sub>, is_cmp = False
def _na_arithmetic_op(left, right, op, is_cmp: bool = False):
"""
Return the result of evaluating op on the passed in values.
If native types are not compatible, try coercion to object dtype.
Parameters
----------
left : np.ndarray
right : np.ndarray or scalar
is_cmp : bool, default False
If this a comparison operation.
Returns
-------
array-like
Raises
------
TypeError : invalid operation
"""
if isinstance(right, str):
# can never use numexpr
func = op
else:
func = partial(expressions.evaluate, op)
try:
> result = func(left, right)
../../.local/lib/python3.8/site-packages/pandas/core/ops/array_ops.py:166:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
op = <built-in function sub>
a = array(['115338.50895090569', '-35.440266364698509', '-35.440266364698509',
..., '-0.026308749054506145', '157897.80272819981',
'534083.79967621446'], dtype=object)
b = array(['115338.50895090567', '-35.440266364698509', '-35.440266364698509',
..., '-0.02630874905450617', '157897.80272819955',
'534083.79967621388'], dtype=object)
use_numexpr = True
def evaluate(op, a, b, use_numexpr: bool = True):
"""
Evaluate and return the expression of the op on a and b.
Parameters
----------
op : the actual operand
a : left operand
b : right operand
use_numexpr : bool, default True
Whether to try to use numexpr.
"""
op_str = _op_str_mapping[op]
if op_str is not None:
if use_numexpr:
# error: "None" not callable
> return _evaluate(op, op_str, a, b) # type: ignore[misc]
../../.local/lib/python3.8/site-packages/pandas/core/computation/expressions.py:239:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
op = <built-in function sub>, op_str = '-'
a = array(['115338.50895090569', '-35.440266364698509', '-35.440266364698509',
..., '-0.026308749054506145', '157897.80272819981',
'534083.79967621446'], dtype=object)
b = array(['115338.50895090567', '-35.440266364698509', '-35.440266364698509',
..., '-0.02630874905450617', '157897.80272819955',
'534083.79967621388'], dtype=object)
def _evaluate_standard(op, op_str, a, b):
"""
Standard evaluation.
"""
if _TEST_MODE:
_store_test_result(False)
> return op(a, b)
E TypeError: unsupported operand type(s) for -: 'str' and 'str'
../../.local/lib/python3.8/site-packages/pandas/core/computation/expressions.py:69: TypeError
During handling of the above exception, another exception occurred:
analisi_log = <pyanalisi.pyanalisi.ReadLog object at 0x7fdb87a47470>, num_regression = <pytest_regressions.num_regression.NumericRegressionFixture object at 0x7fdb87a28130>
def test_gk(analisi_log,num_regression):
import pyanalisi
gk=pyanalisi.GreenKubo(analisi_log,'',1,['c_flux[1]','c_vcm[1][1]'], False, 2000, 2,False,0,4,False,1,100)
gk.reset(analisi_log.getNtimesteps()-2000)
gk.calculate(0)
m=np.array(gk,copy=False)
print(m)
> num_regression.check({'gk':m.flatten()})
test_gk.py:11:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../../.local/lib/python3.8/site-packages/pandas/core/ops/common.py:69: in new_method
return method(self, other)
../../.local/lib/python3.8/site-packages/pandas/core/arraylike.py:100: in __sub__
return self._arith_method(other, operator.sub)
../../.local/lib/python3.8/site-packages/pandas/core/series.py:5526: in _arith_method
result = ops.arithmetic_op(lvalues, rvalues, op)
../../.local/lib/python3.8/site-packages/pandas/core/ops/array_ops.py:224: in arithmetic_op
res_values = _na_arithmetic_op(left, right, op)
../../.local/lib/python3.8/site-packages/pandas/core/ops/array_ops.py:173: in _na_arithmetic_op
result = _masked_arith_op(left, right, op)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
x = array(['115338.50895090569', '-35.440266364698509', '-35.440266364698509',
..., '-0.026308749054506145', '157897.80272819981',
'534083.79967621446'], dtype=object)
y = array(['115338.50895090567', '-35.440266364698509', '-35.440266364698509',
..., '-0.02630874905450617', '157897.80272819955',
'534083.79967621388'], dtype=object)
op = <built-in function sub>
def _masked_arith_op(x: np.ndarray, y, op):
"""
If the given arithmetic operation fails, attempt it again on
only the non-null elements of the input array(s).
Parameters
----------
x : np.ndarray
y : np.ndarray, Series, Index
op : binary operator
"""
# For Series `x` is 1D so ravel() is a no-op; calling it anyway makes
# the logic valid for both Series and DataFrame ops.
xrav = x.ravel()
assert isinstance(x, np.ndarray), type(x)
if isinstance(y, np.ndarray):
dtype = find_common_type([x.dtype, y.dtype])
# error: Argument "dtype" to "empty" has incompatible type
# "Union[dtype, ExtensionDtype]"; expected "Union[dtype, None, type,
# _SupportsDtype, str, Tuple[Any, int], Tuple[Any, Union[int,
# Sequence[int]]], List[Any], _DtypeDict, Tuple[Any, Any]]"
result = np.empty(x.size, dtype=dtype) # type: ignore[arg-type]
if len(x) != len(y):
raise ValueError(x.shape, y.shape)
else:
ymask = notna(y)
# NB: ravel() is only safe since y is ndarray; for e.g. PeriodIndex
# we would get int64 dtype, see GH#19956
yrav = y.ravel()
mask = notna(xrav) & ymask.ravel()
# See GH#5284, GH#5035, GH#19448 for historical reference
if mask.any():
> result[mask] = op(xrav[mask], yrav[mask])
E TypeError: unsupported operand type(s) for -: 'str' and 'str'
../../.local/lib/python3.8/site-packages/pandas/core/ops/array_ops.py:112: TypeError
============================================================================= warnings summary ==============================================================================
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/widget_selection.py:9
/usr/lib/python3/dist-packages/ipywidgets/widgets/widget_selection.py:9: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
from collections import Mapping
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/interaction.py:29
/usr/lib/python3/dist-packages/ipywidgets/widgets/interaction.py:29: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working
from collections import Iterable, Mapping
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/widget_link.py:19
../../../../usr/lib/python3/dist-packages/ipywidgets/widgets/widget_link.py:19
/usr/lib/python3/dist-packages/ipywidgets/widgets/widget_link.py:19: DeprecationWarning: Traits should be given as instances, not types (for example, `Int()`, not `Int`) Passing types is deprecated in traitlets 4.1.
super(WidgetTraitTuple, self).__init__(Instance(Widget), Unicode, **kwargs)
-- Docs: https://docs.pytest.org/en/stable/warnings.html
========================================================================== short test summary info ==========================================================================
FAILED test_gk.py::test_gk - TypeError: unsupported operand type(s) for -: 'str' and 'str'
================================================================ 1 failed, 5 deselected, 4 warnings in 1.94s ================================================================
bertossa@pippo:~/analisi/tests$
Issue Analytics
- State:
- Created 2 years ago
- Comments:10 (6 by maintainers)
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@tarcisiofischer I confirm that on my side everything is working as expected. you are the fastest issue closer in the west 🥇
@rikigigi Do you think it would be too much work for you to grab my branch, install it and check if this solves your issue? I’m almost certain that it will, but would be nice to make sure before merging the fix.
FYI, running your example on https://github.com/rikigigi/regression is passing with my fix, on my machine.