Python testing.assert_raises_regex方法代码示例

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_numpy_compat(self, method):
        # see gh-12811
        e = rwindow.EWM(Series([2, 4, 6]), alpha=0.5)

        msg = "numpy operations are not valid with window objects"

        tm.assert_raises_regex(UnsupportedFunctionCall, msg,
                               getattr(e, method), 1, 2, 3)
        tm.assert_raises_regex(UnsupportedFunctionCall, msg,
                               getattr(e, method), dtype=np.float64)


# gh-12373 : rolling functions error on float32 data
# make sure rolling functions works for different dtypes
#
# NOTE that these are yielded tests and so _create_data
# is explicitly called.
#
# further note that we are only checking rolling for fully dtype
# compliance (though both expanding and ewm inherit) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_no_pairwise_with_other(self, f):

        # DataFrame with another DataFrame, pairwise=False
        results = [f(df, self.df2) if df.columns.is_unique else None
                   for df in self.df1s]
        for (df, result) in zip(self.df1s, results):
            if result is not None:
                with catch_warnings(record=True):
                    # we can have int and str columns
                    expected_index = df.index.union(self.df2.index)
                    expected_columns = df.columns.union(self.df2.columns)
                tm.assert_index_equal(result.index, expected_index)
                tm.assert_index_equal(result.columns, expected_columns)
            else:
                tm.assert_raises_regex(
                    ValueError, "'arg1' columns are not unique", f, df,
                    self.df2)
                tm.assert_raises_regex(
                    ValueError, "'arg2' columns are not unique", f,
                    self.df2, df) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_set_value(self):
        with catch_warnings(record=True):
            for item in self.panel.items:
                for mjr in self.panel.major_axis[::2]:
                    for mnr in self.panel.minor_axis:
                        self.panel.set_value(item, mjr, mnr, 1.)
                        tm.assert_almost_equal(self.panel[item][mnr][mjr], 1.)

            # resize
            res = self.panel.set_value('ItemE', 'foo', 'bar', 1.5)
            assert isinstance(res, Panel)
            assert res is not self.panel
            assert res.get_value('ItemE', 'foo', 'bar') == 1.5

            res3 = self.panel.set_value('ItemE', 'foobar', 'baz', 5)
            assert is_float_dtype(res3['ItemE'].values)

            msg = ("There must be an argument for each "
                   "axis plus the value provided")
            with tm.assert_raises_regex(TypeError, msg):
                self.panel.set_value('a') 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_numpy_round(self):
        with catch_warnings(record=True):
            values = [[[-3.2, 2.2], [0, -4.8213], [3.123, 123.12],
                       [-1566.213, 88.88], [-12, 94.5]],
                      [[-5.82, 3.5], [6.21, -73.272], [-9.087, 23.12],
                       [272.212, -99.99], [23, -76.5]]]
            evalues = [[[float(np.around(i)) for i in j] for j in k]
                       for k in values]
            p = Panel(values, items=['Item1', 'Item2'],
                      major_axis=date_range('1/1/2000', periods=5),
                      minor_axis=['A', 'B'])
            expected = Panel(evalues, items=['Item1', 'Item2'],
                             major_axis=date_range('1/1/2000', periods=5),
                             minor_axis=['A', 'B'])
            result = np.round(p)
            assert_panel_equal(expected, result)

            msg = "the 'out' parameter is not supported"
            tm.assert_raises_regex(ValueError, msg, np.round, p, out=p) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_numpy_cumsum(self):
        result = np.cumsum(self.bseries)
        expected = SparseSeries(self.bseries.to_dense().cumsum())
        tm.assert_sp_series_equal(result, expected)

        result = np.cumsum(self.zbseries)
        expected = self.zbseries.to_dense().cumsum()
        tm.assert_series_equal(result, expected)

        msg = "the 'dtype' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, np.cumsum,
                               self.bseries, dtype=np.int64)

        msg = "the 'out' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, np.cumsum,
                               self.zbseries, out=result) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_astype(self):
        res = self.arr.astype('f8')
        res.sp_values[:3] = 27
        assert not (self.arr.sp_values[:3] == 27).any()

        msg = "unable to coerce current fill_value nan to int64 dtype"
        with tm.assert_raises_regex(ValueError, msg):
            self.arr.astype('i8')

        arr = SparseArray([0, np.nan, 0, 1])
        with tm.assert_raises_regex(ValueError, msg):
            arr.astype('i8')

        arr = SparseArray([0, np.nan, 0, 1], fill_value=0)
        msg = 'Cannot convert non-finite values \\(NA or inf\\) to integer'
        with tm.assert_raises_regex(ValueError, msg):
            arr.astype('i8') 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_numpy_all(self, data, pos, neg):
        # GH 17570
        out = np.all(SparseArray(data))
        assert out

        out = np.all(SparseArray(data, fill_value=pos))
        assert out

        data[1] = neg
        out = np.all(SparseArray(data))
        assert not out

        out = np.all(SparseArray(data, fill_value=pos))
        assert not out

        msg = "the 'out' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, np.all,
                               SparseArray(data), out=out) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_numpy_any(self, data, pos, neg):
        # GH 17570
        out = np.any(SparseArray(data))
        assert out

        out = np.any(SparseArray(data, fill_value=pos))
        assert out

        data[1] = neg
        out = np.any(SparseArray(data))
        assert not out

        out = np.any(SparseArray(data, fill_value=pos))
        assert not out

        msg = "the 'out' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, np.any,
                               SparseArray(data), out=out) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_numpy_sum(self):
        data = np.arange(10).astype(float)
        out = np.sum(SparseArray(data))
        assert out == 45.0

        data[5] = np.nan
        out = np.sum(SparseArray(data, fill_value=2))
        assert out == 40.0

        out = np.sum(SparseArray(data, fill_value=np.nan))
        assert out == 40.0

        msg = "the 'dtype' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, np.sum,
                               SparseArray(data), dtype=np.int64)

        msg = "the 'out' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, np.sum,
                               SparseArray(data), out=out) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_cumsum(self):
        non_null_data = np.array([1, 2, 3, 4, 5], dtype=float)
        non_null_expected = SparseArray(non_null_data.cumsum())

        null_data = np.array([1, 2, np.nan, 4, 5], dtype=float)
        null_expected = SparseArray(np.array([1.0, 3.0, np.nan, 7.0, 12.0]))

        for data, expected in [
            (null_data, null_expected),
            (non_null_data, non_null_expected)
        ]:
            out = SparseArray(data).cumsum()
            tm.assert_sp_array_equal(out, expected)

            out = SparseArray(data, fill_value=np.nan).cumsum()
            tm.assert_sp_array_equal(out, expected)

            out = SparseArray(data, fill_value=2).cumsum()
            tm.assert_sp_array_equal(out, expected)

            axis = 1  # SparseArray currently 1-D, so only axis = 0 is valid.
            msg = "axis\\(={axis}\\) out of bounds".format(axis=axis)
            with tm.assert_raises_regex(ValueError, msg):
                SparseArray(data).cumsum(axis=axis) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_constructor_ndarray(self):
        # no index or columns
        sp = SparseDataFrame(self.frame.values)

        # 1d
        sp = SparseDataFrame(self.data['A'], index=self.dates, columns=['A'])
        tm.assert_sp_frame_equal(sp, self.frame.reindex(columns=['A']))

        # raise on level argument
        pytest.raises(TypeError, self.frame.reindex, columns=['A'],
                      level=1)

        # wrong length index / columns
        with tm.assert_raises_regex(ValueError, "^Index length"):
            SparseDataFrame(self.frame.values, index=self.frame.index[:-1])

        with tm.assert_raises_regex(ValueError, "^Column length"):
            SparseDataFrame(self.frame.values, columns=self.frame.columns[:-1])

    # GH 9272 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_unbounded_slice_raises(self):
        def assert_unbounded_slice_error(slc):
            tm.assert_raises_regex(ValueError, "unbounded slice",
                                   lambda: BlockPlacement(slc))

        assert_unbounded_slice_error(slice(None, None))
        assert_unbounded_slice_error(slice(10, None))
        assert_unbounded_slice_error(slice(None, None, -1))
        assert_unbounded_slice_error(slice(None, 10, -1))

        # These are "unbounded" because negative index will change depending on
        # container shape.
        assert_unbounded_slice_error(slice(-1, None))
        assert_unbounded_slice_error(slice(None, -1))
        assert_unbounded_slice_error(slice(-1, -1))
        assert_unbounded_slice_error(slice(-1, None, -1))
        assert_unbounded_slice_error(slice(None, -1, -1))
        assert_unbounded_slice_error(slice(-1, -1, -1)) 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_tdi_round(self):
        td = pd.timedelta_range(start='16801 days', periods=5, freq='30Min')
        elt = td[1]

        expected_rng = TimedeltaIndex([Timedelta('16801 days 00:00:00'),
                                       Timedelta('16801 days 00:00:00'),
                                       Timedelta('16801 days 01:00:00'),
                                       Timedelta('16801 days 02:00:00'),
                                       Timedelta('16801 days 02:00:00')])
        expected_elt = expected_rng[1]

        tm.assert_index_equal(td.round(freq='H'), expected_rng)
        assert elt.round(freq='H') == expected_elt

        msg = pd._libs.tslibs.frequencies._INVALID_FREQ_ERROR
        with tm.assert_raises_regex(ValueError, msg):
            td.round(freq='foo')
        with tm.assert_raises_regex(ValueError, msg):
            elt.round(freq='foo')

        msg = "<MonthEnd> is a non-fixed frequency"
        with tm.assert_raises_regex(ValueError, msg):
            td.round(freq='M')
        with tm.assert_raises_regex(ValueError, msg):
            elt.round(freq='M') 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_take_invalid_kwargs(self):
        idx = timedelta_range('1 day', '31 day', freq='D', name='idx')
        indices = [1, 6, 5, 9, 10, 13, 15, 3]

        msg = r"take\(\) got an unexpected keyword argument 'foo'"
        tm.assert_raises_regex(TypeError, msg, idx.take,
                               indices, foo=2)

        msg = "the 'out' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, idx.take,
                               indices, out=indices)

        msg = "the 'mode' parameter is not supported"
        tm.assert_raises_regex(ValueError, msg, idx.take,
                               indices, mode='clip')

    # TODO: This method came from test_timedelta; de-dup with version above 

# 需要导入模块: from pandas.util import testing [as 别名]
# 或者: from pandas.util.testing import assert_raises_regex [as 别名]
def test_errors(self):
        # not enough params
        msg = ('Of the four parameters: start, end, periods, and freq, '
               'exactly three must be specified')
        with tm.assert_raises_regex(ValueError, msg):
            timedelta_range(start='0 days')

        with tm.assert_raises_regex(ValueError, msg):
            timedelta_range(end='5 days')

        with tm.assert_raises_regex(ValueError, msg):
            timedelta_range(periods=2)

        with tm.assert_raises_regex(ValueError, msg):
            timedelta_range()

        # too many params
        with tm.assert_raises_regex(ValueError, msg):
            timedelta_range(start='0 days', end='5 days', periods=10, freq='H')