______________________________ test_angle_arrays _______________________________
    def test_angle_arrays():
        """
        Test arrays values with Angle objects.
        """
        # Tests incomplete
        a1 = Angle([0, 45, 90, 180, 270, 360, 720.], unit=u.degree)
        npt.assert_almost_equal([0., 45., 90., 180., 270., 360., 720.], a1.value)
    
        a2 = Angle(np.array([-90, -45, 0, 45, 90, 180, 270, 360]), unit=u.degree)
        npt.assert_almost_equal([-90, -45, 0, 45, 90, 180, 270, 360],
                                a2.value)
    
        a3 = Angle(["12 degrees", "3 hours", "5 deg", "4rad"])
        npt.assert_almost_equal([12., 45., 5., 229.18311805],
                                a3.value)
        assert a3.unit == u.degree
    
        a4 = Angle(["12 degrees", "3 hours", "5 deg", "4rad"], u.radian)
        npt.assert_almost_equal(a4.degree, a3.value)
        assert a4.unit == u.radian
    
        a5 = Angle([0, 45, 90, 180, 270, 360], unit=u.degree)
        a6 = a5.sum()
        npt.assert_almost_equal(a6.value, 945.0)
        assert a6.unit is u.degree
    
        with pytest.raises(TypeError):
            # Arrays where the elements are Angle objects are not supported -- it's
            # really tricky to do correctly, if at all, due to the possibility of
            # nesting.
>           a7 = Angle([a1, a2, a3], unit=u.degree)
../../.tox/test-dev/lib/python3.7/site-packages/astropy/coordinates/tests/test_arrays.py:48: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../../.tox/test-dev/lib/python3.7/site-packages/astropy/coordinates/angles.py:108: in __new__
    return super().__new__(cls, angle, unit, dtype=dtype, copy=copy)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
cls = <class 'astropy.coordinates.angles.Angle'>
value = [array([  0.,  45.,  90., 180., 270., 360., 720.]), array([-90., -45.,   0.,  45.,  90., 180., 270., 360.]), array([ 12.        ,  45.        ,   5.        , 229.18311805])]
unit = Unit("deg"), dtype = None, copy = True, order = None, subok = False
ndmin = 0
    def __new__(cls, value, unit=None, dtype=None, copy=True, order=None,
                subok=False, ndmin=0):
    
        if unit is not None:
            # convert unit first, to avoid multiple string->unit conversions
            unit = Unit(unit)
    
        # optimize speed for Quantity with no dtype given, copy=False
        if isinstance(value, Quantity):
            if unit is not None and unit is not value.unit:
                value = value.to(unit)
                # the above already makes a copy (with float dtype)
                copy = False
    
            if type(value) is not cls and not (subok and
                                               isinstance(value, cls)):
                value = value.view(cls)
    
            if dtype is None:
                if not copy:
                    return value
    
                if value.dtype.kind in 'iu':
                    dtype = float
    
            return np.array(value, dtype=dtype, copy=copy, order=order,
                            subok=True, ndmin=ndmin)
    
        # Maybe str, or list/tuple of Quantity? If so, this may set value_unit.
        # To ensure array remains fast, we short-circuit it.
        value_unit = None
        if not isinstance(value, np.ndarray):
            if isinstance(value, str):
                # The first part of the regex string matches any integer/float;
                # the second parts adds possible trailing .+-, which will break
                # the float function below and ensure things like 1.2.3deg
                # will not work.
                pattern = (r'\s*[+-]?'
                           r'((\d+\.?\d*)|(\.\d+)|([nN][aA][nN])|'
                           r'([iI][nN][fF]([iI][nN][iI][tT][yY]){0,1}))'
                           r'([eE][+-]?\d+)?'
                           r'[.+-]?')
    
                v = re.match(pattern, value)
                unit_string = None
                try:
                    value = float(v.group())
    
                except Exception:
                    raise TypeError('Cannot parse "{}" as a {}. It does not '
                                    'start with a number.'
                                    .format(value, cls.__name__))
    
                unit_string = v.string[v.end():].strip()
                if unit_string:
                    value_unit = Unit(unit_string)
                    if unit is None:
                        unit = value_unit  # signal no conversion needed below.
    
            elif (isiterable(value) and len(value) > 0 and
                  all(isinstance(v, Quantity) for v in value)):
                # Convert all quantities to the same unit.
                if unit is None:
                    unit = value[0].unit
                value = [q.to_value(unit) for q in value]
                value_unit = unit  # signal below that conversion has been done
    
        if value_unit is None:
            # If the value has a `unit` attribute and if not None
            # (for Columns with uninitialized unit), treat it like a quantity.
            value_unit = getattr(value, 'unit', None)
            if value_unit is None:
                # Default to dimensionless for no (initialized) unit attribute.
                if unit is None:
                    unit = cls._default_unit
                value_unit = unit  # signal below that no conversion is needed
            else:
                try:
                    value_unit = Unit(value_unit)
                except Exception as exc:
                    raise TypeError("The unit attribute {!r} of the input could "
                                    "not be parsed as an astropy Unit, raising "
                                    "the following exception:\n{}"
                                    .format(value.unit, exc))
    
                if unit is None:
                    unit = value_unit
                elif unit is not value_unit:
                    copy = False  # copy will be made in conversion at end
    
        value = np.array(value, dtype=dtype, copy=copy, order=order,
>                        subok=False, ndmin=ndmin)
E       DeprecationWarning: Creating an ndarray with automatic object dtype is deprecated, use dtype=object if you intended it, otherwise specify an exact dtype
../../.tox/test-dev/lib/python3.7/site-packages/astropy/units/quantity.py:381: DeprecationWarning
____________________ TestColumn.test_insert_object[Column] _____________________
DeprecationWarning: Creating an ndarray with automatic object dtype is deprecated, use dtype=object if you intended it, otherwise specify an exact dtype
The above exception was the direct cause of the following exception:
self = <astropy.table.tests.test_column.TestColumn object at 0x7fa01a6ed358>
Column = <class 'astropy.table.column.Column'>
    def test_insert_object(self, Column):
        c = Column(['a', 1, None], name='a', dtype=object)
    
        # Basic insert
        c1 = c.insert(1, [100, 200])
>       assert np.all(c1 == ['a', [100, 200], 1, None])
../../.tox/test-dev/lib/python3.7/site-packages/astropy/table/tests/test_column.py:373: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
self = <Column name='a' dtype='object' length=4>
         a
[100, 200]
         1
      None
other = ['a', [100, 200], 1, None]
    def _compare(self, other):
        op = oper  # copy enclosed ref to allow swap below
    
        # Special case to work around #6838.  Other combinations work OK,
        # see tests.test_column.test_unicode_sandwich_compare().  In this
        # case just swap self and other.
        #
        # This is related to an issue in numpy that was addressed in np 1.13.
        # However that fix does not make this problem go away, but maybe
        # future numpy versions will do so.  NUMPY_LT_1_13 to get the
        # attention of future maintainers to check (by deleting or versioning
        # the if block below).  See #6899 discussion.
        # 2019-06-21: still needed with numpy 1.16.
        if (isinstance(self, MaskedColumn) and self.dtype.kind == 'U' and
                isinstance(other, MaskedColumn) and other.dtype.kind == 'S'):
            self, other = other, self
            op = swapped_oper
    
        if self.dtype.char == 'S':
            other = self._encode_str(other)
    
        # Now just let the regular ndarray.__eq__, etc., take over.
>       result = getattr(super(), op)(other)
E       DeprecationWarning: elementwise comparison failed; this will raise an error in the future.
../../.tox/test-dev/lib/python3.7/site-packages/astropy/table/column.py:1020: DeprecationWarning
_________________ TestColumn.test_insert_object[MaskedColumn] __________________
a = ['a', [100, 200], 1, None], subok = True
    def getdata(a, subok=True):
        """
        Return the data of a masked array as an ndarray.
    
        Return the data of `a` (if any) as an ndarray if `a` is a ``MaskedArray``,
        else return `a` as a ndarray or subclass (depending on `subok`) if not.
    
        Parameters
        ----------
        a : array_like
            Input ``MaskedArray``, alternatively a ndarray or a subclass thereof.
        subok : bool
            Whether to force the output to be a `pure` ndarray (False) or to
            return a subclass of ndarray if appropriate (True, default).
    
        See Also
        --------
        getmask : Return the mask of a masked array, or nomask.
        getmaskarray : Return the mask of a masked array, or full array of False.
    
        Examples
        --------
        >>> import numpy.ma as ma
        >>> a = ma.masked_equal([[1,2],[3,4]], 2)
        >>> a
        masked_array(
          data=[[1, --],
                [3, 4]],
          mask=[[False,  True],
                [False, False]],
          fill_value=2)
        >>> ma.getdata(a)
        array([[1, 2],
               [3, 4]])
    
        Equivalently use the ``MaskedArray`` `data` attribute.
    
        >>> a.data
        array([[1, 2],
               [3, 4]])
    
        """
        try:
>           data = a._data
E           AttributeError: 'list' object has no attribute '_data'
../../.tox/test-dev/lib/python3.7/site-packages/numpy/ma/core.py:720: AttributeError
During handling of the above exception, another exception occurred:
self = <astropy.table.tests.test_column.TestColumn object at 0x7fa01a581240>
Column = <class 'astropy.table.column.MaskedColumn'>
    def test_insert_object(self, Column):
        c = Column(['a', 1, None], name='a', dtype=object)
    
        # Basic insert
        c1 = c.insert(1, [100, 200])
>       assert np.all(c1 == ['a', [100, 200], 1, None])
../../.tox/test-dev/lib/python3.7/site-packages/astropy/table/tests/test_column.py:373: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../../.tox/test-dev/lib/python3.7/site-packages/astropy/table/column.py:1020: in _compare
    result = getattr(super(), op)(other)
../../.tox/test-dev/lib/python3.7/site-packages/numpy/ma/core.py:4077: in __eq__
    return self._comparison(other, operator.eq)
../../.tox/test-dev/lib/python3.7/site-packages/numpy/ma/core.py:4017: in _comparison
    odata = getdata(other)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
a = ['a', [100, 200], 1, None], subok = True
    def getdata(a, subok=True):
        """
        Return the data of a masked array as an ndarray.
    
        Return the data of `a` (if any) as an ndarray if `a` is a ``MaskedArray``,
        else return `a` as a ndarray or subclass (depending on `subok`) if not.
    
        Parameters
        ----------
        a : array_like
            Input ``MaskedArray``, alternatively a ndarray or a subclass thereof.
        subok : bool
            Whether to force the output to be a `pure` ndarray (False) or to
            return a subclass of ndarray if appropriate (True, default).
    
        See Also
        --------
        getmask : Return the mask of a masked array, or nomask.
        getmaskarray : Return the mask of a masked array, or full array of False.
    
        Examples
        --------
        >>> import numpy.ma as ma
        >>> a = ma.masked_equal([[1,2],[3,4]], 2)
        >>> a
        masked_array(
          data=[[1, --],
                [3, 4]],
          mask=[[False,  True],
                [False, False]],
          fill_value=2)
        >>> ma.getdata(a)
        array([[1, 2],
               [3, 4]])
    
        Equivalently use the ``MaskedArray`` `data` attribute.
    
        >>> a.data
        array([[1, 2],
               [3, 4]])
    
        """
        try:
            data = a._data
        except AttributeError:
>           data = np.array(a, copy=False, subok=subok)
E           DeprecationWarning: Creating an ndarray with automatic object dtype is deprecated, use dtype=object if you intended it, otherwise specify an exact dtype
../../.tox/test-dev/lib/python3.7/site-packages/numpy/ma/core.py:722: DeprecationWarning
____________________ TestBasic.test_init_from_time_objects _____________________
self = <astropy.time.tests.test_basic.TestBasic object at 0x7fa01bc76978>
    def test_init_from_time_objects(self):
        """Initialize from one or more Time objects"""
        t1 = Time('2007:001', scale='tai')
        t2 = Time(['2007-01-02', '2007-01-03'], scale='utc')
        # Init from a list of Time objects without an explicit scale
>       t3 = Time([t1, t2])
../../.tox/test-dev/lib/python3.7/site-packages/astropy/time/tests/test_basic.py:562: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
../../.tox/test-dev/lib/python3.7/site-packages/astropy/time/core.py:429: in __init__
    precision, in_subfmt, out_subfmt)
../../.tox/test-dev/lib/python3.7/site-packages/astropy/time/core.py:460: in _init_from_vals
    val = _make_array(val, copy)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
val = [<Time object: scale='tai' format='yday' value=2007:001:00:00:00.000>, <Time object: scale='utc' format='iso' value=['2007-01-02 00:00:00.000' '2007-01-03 00:00:00.000']>]
copy = False
    def _make_array(val, copy=False):
        """
        Take ``val`` and convert/reshape to an array.  If ``copy`` is `True`
        then copy input values.
    
        Returns
        -------
        val : ndarray
            Array version of ``val``.
        """
>       val = np.array(val, copy=copy, subok=True)
E       DeprecationWarning: Creating an ndarray with automatic object dtype is deprecated, use dtype=object if you intended it, otherwise specify an exact dtype
../../.tox/test-dev/lib/python3.7/site-packages/astropy/time/core.py:2443: DeprecationWarning
==== 4 failed, 12977 passed, 1079 skipped, 52 xfailed in 243.41s (0:04:03) =====