Skip to content

COMPAT: numpy 1.12 #15363

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
jreback opened this issue Feb 10, 2017 · 0 comments
Closed

COMPAT: numpy 1.12 #15363

jreback opened this issue Feb 10, 2017 · 0 comments
Labels
Compat pandas objects compatability with Numpy or Python functions Testing pandas testing functions or related to the test suite
Milestone

Comments

@jreback
Copy link
Contributor

jreback commented Feb 10, 2017

https://travis-ci.org/pandas-dev/pandas/jobs/200390418

these are test failures from an API change: numpy/numpy#8231
cc @shoyer

I think we don't have numexpr installed on the dev build so these tests are skipped :<

=================================== FAILURES ===================================
_______________________ TestExpressions.test_binary_ops ________________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_binary_ops>
    def test_binary_ops(self):
        def testit():
    
            for f, f2 in [(self.frame, self.frame2),
                          (self.mixed, self.mixed2)]:
    
                for op, op_str in [('add', '+'), ('sub', '-'), ('mul', '*'),
                                   ('div', '/'), ('pow', '**')]:
                    if op == 'div':
                        op = getattr(operator, 'truediv', None)
                    else:
                        op = getattr(operator, op, None)
                    if op is not None:
                        result = expr._can_use_numexpr(op, op_str, f, f,
                                                       'evaluate')
                        self.assertNotEqual(result, f._is_mixed_type)
    
                        result = expr.evaluate(op, op_str, f, f,
                                               use_numexpr=True)
                        expected = expr.evaluate(op, op_str, f, f,
                                                 use_numexpr=False)
    
                        if isinstance(result, DataFrame):
                            tm.assert_frame_equal(result, expected)
                        else:
                            tm.assert_numpy_array_equal(result,
                                                        expected.values)
    
                        result = expr._can_use_numexpr(op, op_str, f2, f2,
                                                       'evaluate')
                        self.assertFalse(result)
    
        expr.set_use_numexpr(False)
>       testit()
pandas/tests/test_expressions.py:301: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:286: in testit
    use_numexpr=True)
pandas/computation/expressions.py:210: in evaluate
    **eval_kwargs)
pandas/computation/expressions.py:63: in _evaluate_standard
    return op(a, b)
pandas/core/ops.py:1230: in f
    return self._combine_frame(other, na_op, fill_value, level)
pandas/core/frame.py:3527: in _combine_frame
    result = dict([(col, f(col)) for col in this])
pandas/core/frame.py:3527: in <listcomp>
    result = dict([(col, f(col)) for col in this])
pandas/core/frame.py:3523: in f
    r = _arith_op(this[col].values, other[col].values)
pandas/core/frame.py:3515: in _arith_op
    return func(left, right)
pandas/core/ops.py:1172: in na_op
    raise_on_error=True, **eval_kwargs)
pandas/computation/expressions.py:210: in evaluate
    **eval_kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
op = <built-in function pow>, op_str = '**'
a = array([-1,  0,  0, ...,  0,  0,  0])
b = array([-1,  0,  0, ...,  0,  0,  0]), raise_on_error = True
eval_kwargs = {}
    def _evaluate_standard(op, op_str, a, b, raise_on_error=True, **eval_kwargs):
        """ standard evaluation """
        if _TEST_MODE:
            _store_test_result(False)
        with np.errstate(all='ignore'):
>           return op(a, b)
E           ValueError: Integers to negative integer powers are not allowed.
pandas/computation/expressions.py:63: ValueError
___________________ TestExpressions.test_integer_arithmetic ____________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_integer_arithmetic>
    def test_integer_arithmetic(self):
        self.run_arithmetic_test(self.integer, self.integer,
>                                assert_frame_equal)
pandas/tests/test_expressions.py:105: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:98: in run_arithmetic_test
    assert_func(expected, result)
pandas/util/testing.py:1321: in assert_frame_equal
    obj='DataFrame.iloc[:, {0}]'.format(i))
pandas/util/testing.py:1190: in assert_series_equal
    obj='{0}'.format(obj))
pandas/src/testing.pyx:59: in pandas._testing.assert_almost_equal (pandas/src/testing.c:4156)
    cpdef assert_almost_equal(a, b,
pandas/src/testing.pyx:173: in pandas._testing.assert_almost_equal (pandas/src/testing.c:3274)
    raise_assert_detail(obj, msg, lobj, robj)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
obj = 'DataFrame.iloc[:, 0]'
message = 'DataFrame.iloc[:, 0] values are different (86.51135 %)'
left = '[16777216, 0, 0, 7437354637604294721, 4951460147845608313, 0, 0, -6776596920136667815, 8028209804145959321, -49703392...6018427387904, 0, 46656, 3792227444683241861, -497033925936021504, -4053175462519618527, 0, -6629298651489370112, ...]'
right = '[16777216, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -92233720368547758...56, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]'
diff = None
    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
    
        msg = """{0} are different
    
    {1}
    [left]:  {2}
    [right]: {3}""".format(obj, message, left, right)
    
        if diff is not None:
            msg = msg + "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: DataFrame.iloc[:, 0] are different
E       
E       DataFrame.iloc[:, 0] values are different (86.51135 %)
E       [left]:  [16777216, 0, 0, 7437354637604294721, 4951460147845608313, 0, 0, -6776596920136667815, 8028209804145959321, -497033925936021504, 1483551237918615471, 0, -8795647696940200745, -4940275718618612379, 1, -4675932718989443137, -145357957422043229, 0, 2110287360296998863, 2536461848307888459, -4642015662142636065, -7394533151961528133, 0, -4689350456247753643, -3660930864499998817, 0, -4689350456247753643, -5821812116355782473, -5296008294479953920, 2823291043684304491, 4593512421086651489, 27, -1595931050845505211, -5821812116355782473, 2536461848307888459, 0, -4071272324936764365, -1902703244836818301, -5821812116355782473, 2110287360296998863, 0, -4675932718989443137, -5296008294479953920, 387420489, 2110287360296998863, 2823291043684304491, 0, 0, 0, 27, -1595931050845505211, 6353754964178307979, 4611686018427387904, -2863221430593058543, 8037740809528595931, -7924192819420782515, -145357957422043229, 0, 387420489, 0, 0, -1902703244836818301, -8795647696940200745, 0, 0, 2565992168703393792, 0, -4689350456247753643, 5529354540715494413, -2863221430593058543, 8028209804145959321, -8206467232675302283, 302875106592253, 256, -4053175462519618527, 4593512421086651489, 4121466560160202752, 823543, -5821812116355782473, -4689350456247753643, -497033925936021504, -1902703244836818301, -3660930864499998817, 6353754964178307979, -5296008294479953920, 8916100448256, 0, 4593512421086651489, 2644539488379390509, 0, 0, 3030756035345000135, 4611686018427387904, 0, 46656, 3792227444683241861, -497033925936021504, -4053175462519618527, 0, -6629298651489370112, ...]
E       [right]: [16777216, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 27, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 387420489, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 27, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 387420489, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 302875106592253, 256, -9223372036854775808, -9223372036854775808, -9223372036854775808, 823543, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 8916100448256, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 46656, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]
pandas/util/testing.py:1028: AssertionError
________________ TestExpressions.test_integer_arithmetic_frame _________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_integer_arithmetic_frame>
    def test_integer_arithmetic_frame(self):
>       self.run_frame(self.integer, self.integer)
pandas/tests/test_expressions.py:188: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:147: in run_frame
    test_flex=False, **kwargs)
pandas/tests/test_expressions.py:98: in run_arithmetic_test
    assert_func(expected, result)
pandas/util/testing.py:1321: in assert_frame_equal
    obj='DataFrame.iloc[:, {0}]'.format(i))
pandas/util/testing.py:1190: in assert_series_equal
    obj='{0}'.format(obj))
pandas/src/testing.pyx:59: in pandas._testing.assert_almost_equal (pandas/src/testing.c:4156)
    cpdef assert_almost_equal(a, b,
pandas/src/testing.pyx:173: in pandas._testing.assert_almost_equal (pandas/src/testing.c:3274)
    raise_assert_detail(obj, msg, lobj, robj)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
obj = 'DataFrame.iloc[:, 0]'
message = 'DataFrame.iloc[:, 0] values are different (86.51135 %)'
left = '[16777216, 0, 0, 7437354637604294721, 4951460147845608313, 0, 0, -6776596920136667815, 8028209804145959321, -49703392...6018427387904, 0, 46656, 3792227444683241861, -497033925936021504, -4053175462519618527, 0, -6629298651489370112, ...]'
right = '[16777216, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -92233720368547758...56, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]'
diff = None
    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
    
        msg = """{0} are different
    
    {1}
    [left]:  {2}
    [right]: {3}""".format(obj, message, left, right)
    
        if diff is not None:
            msg = msg + "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: DataFrame.iloc[:, 0] are different
E       
E       DataFrame.iloc[:, 0] values are different (86.51135 %)
E       [left]:  [16777216, 0, 0, 7437354637604294721, 4951460147845608313, 0, 0, -6776596920136667815, 8028209804145959321, -497033925936021504, 1483551237918615471, 0, -8795647696940200745, -4940275718618612379, 1, -4675932718989443137, -145357957422043229, 0, 2110287360296998863, 2536461848307888459, -4642015662142636065, -7394533151961528133, 0, -4689350456247753643, -3660930864499998817, 0, -4689350456247753643, -5821812116355782473, -5296008294479953920, 2823291043684304491, 4593512421086651489, 27, -1595931050845505211, -5821812116355782473, 2536461848307888459, 0, -4071272324936764365, -1902703244836818301, -5821812116355782473, 2110287360296998863, 0, -4675932718989443137, -5296008294479953920, 387420489, 2110287360296998863, 2823291043684304491, 0, 0, 0, 27, -1595931050845505211, 6353754964178307979, 4611686018427387904, -2863221430593058543, 8037740809528595931, -7924192819420782515, -145357957422043229, 0, 387420489, 0, 0, -1902703244836818301, -8795647696940200745, 0, 0, 2565992168703393792, 0, -4689350456247753643, 5529354540715494413, -2863221430593058543, 8028209804145959321, -8206467232675302283, 302875106592253, 256, -4053175462519618527, 4593512421086651489, 4121466560160202752, 823543, -5821812116355782473, -4689350456247753643, -497033925936021504, -1902703244836818301, -3660930864499998817, 6353754964178307979, -5296008294479953920, 8916100448256, 0, 4593512421086651489, 2644539488379390509, 0, 0, 3030756035345000135, 4611686018427387904, 0, 46656, 3792227444683241861, -497033925936021504, -4053175462519618527, 0, -6629298651489370112, ...]
1mE       [right]: [16777216, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 27, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 387420489, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 27, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 387420489, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 302875106592253, 256, -9223372036854775808, -9223372036854775808, -9223372036854775808, 823543, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 8916100448256, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 46656, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]
pandas/util/testing.py:1028: AssertionError
________________ TestExpressions.test_integer_arithmetic_series ________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_integer_arithmetic_series>
    def test_integer_arithmetic_series(self):
>       self.run_series(self.integer.iloc[:, 0], self.integer.iloc[:, 0])
pandas/tests/test_expressions.py:191: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:162: in run_series
    test_flex=False, **kwargs)
pandas/tests/test_expressions.py:98: in run_arithmetic_test
    assert_func(expected, result)
pandas/util/testing.py:1190: in assert_series_equal
    obj='{0}'.format(obj))
pandas/src/testing.pyx:59: in pandas._testing.assert_almost_equal (pandas/src/testing.c:4156)
    cpdef assert_almost_equal(a, b,
pandas/src/testing.pyx:173: in pandas._testing.assert_almost_equal (pandas/src/testing.c:3274)
    raise_assert_detail(obj, msg, lobj, robj)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
obj = 'Series', message = 'Series values are different (86.51135 %)'
left = '[16777216, 0, 0, 7437354637604294721, 4951460147845608313, 0, 0, -6776596920136667815, 8028209804145959321, -49703392...6018427387904, 0, 46656, 3792227444683241861, -497033925936021504, -4053175462519618527, 0, -6629298651489370112, ...]'
right = '[16777216, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -92233720368547758...56, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]'
diff = None
    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
    
        msg = """{0} are different
    
    {1}
    [left]:  {2}
    [right]: {3}""".format(obj, message, left, right)
    
        if diff is not None:
            msg = msg + "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: Series are different
E       
E       Series values are different (86.51135 %)
E       [left]:  [16777216, 0, 0, 7437354637604294721, 4951460147845608313, 0, 0, -6776596920136667815, 8028209804145959321, -497033925936021504, 1483551237918615471, 0, -8795647696940200745, -4940275718618612379, 1, -4675932718989443137, -145357957422043229, 0, 2110287360296998863, 2536461848307888459, -4642015662142636065, -7394533151961528133, 0, -4689350456247753643, -3660930864499998817, 0, -4689350456247753643, -5821812116355782473, -5296008294479953920, 2823291043684304491, 4593512421086651489, 27, -1595931050845505211, -5821812116355782473, 2536461848307888459, 0, -4071272324936764365, -1902703244836818301, -5821812116355782473, 2110287360296998863, 0, -4675932718989443137, -5296008294479953920, 387420489, 2110287360296998863, 2823291043684304491, 0, 0, 0, 27, -1595931050845505211, 6353754964178307979, 4611686018427387904, -2863221430593058543, 8037740809528595931, -7924192819420782515, -145357957422043229, 0, 387420489, 0, 0, -1902703244836818301, -8795647696940200745, 0, 0, 2565992168703393792, 0, -4689350456247753643, 5529354540715494413, -2863221430593058543, 8028209804145959321, -8206467232675302283, 302875106592253, 256, -4053175462519618527, 4593512421086651489, 4121466560160202752, 823543, -5821812116355782473, -4689350456247753643, -497033925936021504, -1902703244836818301, -3660930864499998817, 6353754964178307979, -5296008294479953920, 8916100448256, 0, 4593512421086651489, 2644539488379390509, 0, 0, 3030756035345000135, 4611686018427387904, 0, 46656, 3792227444683241861, -497033925936021504, -4053175462519618527, 0, -6629298651489370112, ...]
E       [right]: [16777216, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 27, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 387420489, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 27, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 387420489, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 302875106592253, 256, -9223372036854775808, -9223372036854775808, -9223372036854775808, 823543, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 8916100448256, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 46656, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]
pandas/util/testing.py:1028: AssertionError
___________________ TestExpressions.test_integer_with_zeros ____________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_integer_with_zeros>
    def test_integer_with_zeros(self):
        self.integer *= np.random.randint(0, 2, size=np.shape(self.integer))
        self.run_arithmetic_test(self.integer, self.integer,
>                                assert_frame_equal)
pandas/tests/test_expressions.py:242: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:98: in run_arithmetic_test
    assert_func(expected, result)
pandas/util/testing.py:1321: in assert_frame_equal
    obj='DataFrame.iloc[:, {0}]'.format(i))
pandas/util/testing.py:1190: in assert_series_equal
    obj='{0}'.format(obj))
pandas/src/testing.pyx:59: in pandas._testing.assert_almost_equal (pandas/src/testing.c:4156)
    cpdef assert_almost_equal(a, b,
pandas/src/testing.pyx:173: in pandas._testing.assert_almost_equal (pandas/src/testing.c:3274)
    raise_assert_detail(obj, msg, lobj, robj)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
obj = 'DataFrame.iloc[:, 0]'
message = 'DataFrame.iloc[:, 0] values are different (43.36566 %)'
left = '[1, 0, 1, 7437354637604294721, 4951460147845608313, 1, 0, -6776596920136667815, 1, 1, 1, 1, -8795647696940200745, -49...390509, 0, 1, 3030756035345000135, 4611686018427387904, 1, 1, 3792227444683241861, 1, 1, 1, -6629298651489370112, ...]'
right = '[1, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -922337203685477580...775808, 1, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, ...]'
diff = None
    def raise_assert_detail(obj, message, left, right, diff=None):
        if isinstance(left, np.ndarray):
            left = pprint_thing(left)
        if isinstance(right, np.ndarray):
            right = pprint_thing(right)
    
        msg = """{0} are different
    
    {1}
    [left]:  {2}
    [right]: {3}""".format(obj, message, left, right)
    
        if diff is not None:
            msg = msg + "\n[diff]: {diff}".format(diff=diff)
    
>       raise AssertionError(msg)
E       AssertionError: DataFrame.iloc[:, 0] are different
E       
E       DataFrame.iloc[:, 0] values are different (43.36566 %)
E       [left]:  [1, 0, 1, 7437354637604294721, 4951460147845608313, 1, 0, -6776596920136667815, 1, 1, 1, 1, -8795647696940200745, -4940275718618612379, 1, 1, 1, 0, 2110287360296998863, 1, 1, -7394533151961528133, 0, 1, -3660930864499998817, 0, -4689350456247753643, 1, -5296008294479953920, 1, 4593512421086651489, 27, 1, -5821812116355782473, 1, 1, 1, 1, -5821812116355782473, 1, 1, -4675932718989443137, -5296008294479953920, 387420489, 1, 1, 0, 0, 1, 1, 1, 6353754964178307979, 1, -2863221430593058543, 8037740809528595931, 1, -145357957422043229, 1, 387420489, 1, 1, 1, 1, 0, 0, 1, 1, -4689350456247753643, 5529354540715494413, 1, 8028209804145959321, 1, 1, 1, -4053175462519618527, 4593512421086651489, 4121466560160202752, 823543, -5821812116355782473, -4689350456247753643, 1, 1, -3660930864499998817, 6353754964178307979, 1, 8916100448256, 1, 4593512421086651489, 2644539488379390509, 0, 1, 3030756035345000135, 4611686018427387904, 1, 1, 3792227444683241861, 1, 1, 1, -6629298651489370112, ...]
E       [right]: [1, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, 1, 1, 1, -9223372036854775808, -9223372036854775808, 1, 1, 1, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, 1, -9223372036854775808, 27, 1, -9223372036854775808, 1, 1, 1, 1, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, 387420489, 1, 1, -9223372036854775808, -9223372036854775808, 1, 1, 1, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, 1, 387420489, 1, 1, 1, 1, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, 823543, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, -9223372036854775808, 1, 8916100448256, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, 1, -9223372036854775808, -9223372036854775808, 1, 1, -9223372036854775808, 1, 1, 1, -9223372036854775808, ...]
pandas/util/testing.py:1028: AssertionError
____________________ TestExpressions.test_mixed_arithmetic _____________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_mixed_arithmetic>
    def test_mixed_arithmetic(self):
>       self.run_arithmetic_test(self.mixed, self.mixed, assert_frame_equal)
pandas/tests/test_expressions.py:234: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:91: in run_arithmetic_test
    expected = op(df, other)
pandas/tests/test_expressions.py:86: in <lambda>
    op = lambda x, y: getattr(df, arith)(y)
pandas/core/ops.py:1230: in f
    return self._combine_frame(other, na_op, fill_value, level)
pandas/core/frame.py:3527: in _combine_frame
    result = dict([(col, f(col)) for col in this])
pandas/core/frame.py:3527: in <listcomp>
    result = dict([(col, f(col)) for col in this])
pandas/core/frame.py:3523: in f
    r = _arith_op(this[col].values, other[col].values)
pandas/core/frame.py:3515: in _arith_op
    return func(left, right)
pandas/core/ops.py:1172: in na_op
    raise_on_error=True, **eval_kwargs)
pandas/computation/expressions.py:210: in evaluate
    **eval_kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
op = <built-in function pow>, op_str = '**'
a = array([-1,  0,  0, ...,  0,  0,  0])
b = array([-1,  0,  0, ...,  0,  0,  0]), raise_on_error = True
eval_kwargs = {}
    def _evaluate_standard(op, op_str, a, b, raise_on_error=True, **eval_kwargs):
        """ standard evaluation """
        if _TEST_MODE:
            _store_test_result(False)
        with np.errstate(all='ignore'):
>           return op(a, b)
E           ValueError: Integers to negative integer powers are not allowed.
pandas/computation/expressions.py:63: ValueError
_________________ TestExpressions.test_mixed_arithmetic_frame __________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_mixed_arithmetic_frame>
    def test_mixed_arithmetic_frame(self):
        # TODO: FIGURE OUT HOW TO GET IT TO WORK...
        # can't do arithmetic because comparison methods try to do *entire*
        # frame instead of by-column
>       self.run_frame(self.mixed2, self.mixed2, run_binary=False)
pandas/tests/test_expressions.py:217: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:147: in run_frame
    test_flex=False, **kwargs)
pandas/tests/test_expressions.py:91: in run_arithmetic_test
    expected = op(df, other)
pandas/core/ops.py:1230: in f
    return self._combine_frame(other, na_op, fill_value, level)
pandas/core/frame.py:3527: in _combine_frame
    result = dict([(col, f(col)) for col in this])
pandas/core/frame.py:3527: in <listcomp>
    result = dict([(col, f(col)) for col in this])
pandas/core/frame.py:3523: in f
    r = _arith_op(this[col].values, other[col].values)
pandas/core/frame.py:3515: in _arith_op
    return func(left, right)
pandas/core/ops.py:1172: in na_op
    raise_on_error=True, **eval_kwargs)
pandas/computation/expressions.py:210: in evaluate
    **eval_kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
op = <built-in function pow>, op_str = '**'
a = array([-1,  0,  0,  0,  0,  0,  1, -1,  1,  0,  0,  0,  2, -1,  0,  1,  0,
        0, -1, -1,  0,  0,  0,  0,  0,  0, ...-1,  0,  0,  0,  0,  0, -1, -1,  0,  0,  1,  0,  0,
        1,  0, -1,  0, -1,  0,  0,  0,  0,  0,  0, -1, -1, -1,  0])
b = array([-1,  0,  0,  0,  0,  0,  1, -1,  1,  0,  0,  0,  2, -1,  0,  1,  0,
        0, -1, -1,  0,  0,  0,  0,  0,  0, ...-1,  0,  0,  0,  0,  0, -1, -1,  0,  0,  1,  0,  0,
        1,  0, -1,  0, -1,  0,  0,  0,  0,  0,  0, -1, -1, -1,  0])
raise_on_error = True, eval_kwargs = {}
    def _evaluate_standard(op, op_str, a, b, raise_on_error=True, **eval_kwargs):
        """ standard evaluation """
        if _TEST_MODE:
            _store_test_result(False)
        with np.errstate(all='ignore'):
>           return op(a, b)
E           ValueError: Integers to negative integer powers are not allowed.
pandas/computation/expressions.py:63: ValueError
_________________ TestExpressions.test_mixed_arithmetic_series _________________
self = <pandas.tests.test_expressions.TestExpressions testMethod=test_mixed_arithmetic_series>
    def test_mixed_arithmetic_series(self):
        for col in self.mixed2.columns:�[0m
>           self.run_series(self.mixed2[col], self.mixed2[col], binary_comp=4)
pandas/tests/test_expressions.py:221: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
pandas/tests/test_expressions.py:162: in run_series
    test_flex=False, **kwargs)
pandas/tests/test_expressions.py:91: in run_arithmetic_test
    expected = op(df, other)
pandas/core/ops.py:717: in wrapper
    result = wrap_results(safe_na_op(lvalues, rvalues))
pandas/core/ops.py:678: in safe_na_op
    return na_op(lvalues, rvalues)
pandas/core/ops.py:654: in na_op
    raise_on_error=True, **eval_kwargs)
pandas/computation/expressions.py:210: in evaluate
    **eval_kwargs)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
op = <built-in function pow>, op_str = '**'
a = array([-1,  0,  0,  0,  0,  0,  1, -1,  1,  0,  0,  0,  2, -1,  0,  1,  0,
        0, -1, -1,  0,  0,  0,  0,  0,  0, ...-1,  0,  0,  0,  0,  0, -1, -1,  0,  0,  1,  0,  0,
        1,  0, -1,  0, -1,  0,  0,  0,  0,  0,  0, -1, -1, -1,  0])
b = array([-1,  0,  0,  0,  0,  0,  1, -1,  1,  0,  0,  0,  2, -1,  0,  1,  0,
        0, -1, -1,  0,  0,  0,  0,  0,  0, ...-1,  0,  0,  0,  0,  0, -1, -1,  0,  0,  1,  0,  0,
        1,  0, -1,  0, -1,  0,  0,  0,  0,  0,  0, -1, -1, -1,  0])
raise_on_error = True, eval_kwargs = {}
    def _evaluate_standard(op, op_str, a, b, raise_on_error=True, **eval_kwargs):
        """ standard evaluation """
1m        if _TEST_MODE:
            _store_test_result(False)
        with np.errstate(all='ignore'):
>           return op(a, b)
E           ValueError: Integers to negative integer powers are not allowed.
pandas/computation/expressions.py:63: ValueError
= 8 failed, 11445 passed, 541 skipped, 2273 pytest-warnings in 659.30 seconds ==
@jreback jreback added Compat pandas objects compatability with Numpy or Python functions Testing pandas testing functions or related to the test suite labels Feb 10, 2017
@jreback jreback added this to the 0.20.0 milestone Feb 10, 2017
jreback added a commit to jreback/pandas that referenced this issue Feb 10, 2017
COMPAT: skip tests for numpy >= 1.12 with pow and integer inputs

closes pandas-dev#15363
jreback added a commit to jreback/pandas that referenced this issue Feb 10, 2017
COMPAT: skip tests for numpy >= 1.12 with pow and integer inputs

closes pandas-dev#15363

CI: fix 3.5 build to numpy 1.11.3
AnkurDedania pushed a commit to AnkurDedania/pandas that referenced this issue Mar 21, 2017
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Compat pandas objects compatability with Numpy or Python functions Testing pandas testing functions or related to the test suite
Projects
None yet
Development

No branches or pull requests

1 participant