numpy.int64 - python examples

Here are the examples of the python api numpy.int64 taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

145 Examples 7

3 View Complete Implementation : test_period.py
Copyright Apache License 2.0
Author : Frank-qlu
@pytest.mark.parametrize("data, freq, expected", [
    ([pd.Period("2017", "D")], None, [17167]),
    ([pd.Period("2017", "D")], "D", [17167]),
    ([2017], "D", [17167]),
    (["2017"], "D", [17167]),
    ([pd.Period("2017", "D")], pd.tseries.offsets.Day(), [17167]),
    ([pd.Period("2017", "D"), None], None, [17167, iNaT]),
    (pd.Series(pd.date_range("2017", periods=3)), None,
     [17167, 17168, 17169]),
    (pd.date_range("2017", periods=3), None, [17167, 17168, 17169]),
])
def test_period_array_ok(data, freq, expected):
    result = period_array(data, freq=freq).asi8
    expected = np.asarray(expected, dtype=np.int64)
    tm.astert_numpy_array_equal(result, expected)

3 View Complete Implementation : test_join.py
Copyright Apache License 2.0
Author : Frank-qlu
def test_left_join_indexer2():
    idx = Index([1, 1, 2, 5])
    idx2 = Index([1, 2, 5, 7, 9])

    res, lidx, ridx = _join.left_join_indexer_int64(idx2.values, idx.values)

    exp_res = np.array([1, 1, 2, 5, 7, 9], dtype=np.int64)
    astert_almost_equal(res, exp_res)

    exp_lidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.int64)
    astert_almost_equal(lidx, exp_lidx)

    exp_ridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.int64)
    astert_almost_equal(ridx, exp_ridx)

3 View Complete Implementation : test_period_index.py
Copyright Apache License 2.0
Author : Frank-qlu
    @pytest.mark.parametrize('freq', ['H', '12H', '2D', 'W'])
    @pytest.mark.parametrize('kind', [None, 'period', 'timestamp'])
    def test_selection(self, index, freq, kind):
        # This is a bug, these should be implemented
        # GH 14008
        rng = np.arange(len(index), dtype=np.int64)
        df = DataFrame({'date': index, 'a': rng},
                       index=pd.MultiIndex.from_arrays([rng, index],
                                                       names=['v', 'd']))
        with pytest.raises(NotImplementedError):
            df.resample(freq, on='date', kind=kind)
        with pytest.raises(NotImplementedError):
            df.resample(freq, level='d', kind=kind)

3 View Complete Implementation : test_nanops.py
Copyright Apache License 2.0
Author : Frank-qlu
    def test_nanmean_overflow(self):
        # GH 10155
        # In the previous implementation mean can overflow for int dtypes, it
        # is now consistent with numpy

        for a in [2 ** 55, -2 ** 55, 20150515061816532]:
            s = Series(a, index=range(500), dtype=np.int64)
            result = s.mean()
            np_result = s.values.mean()
            astert result == a
            astert result == np_result
            astert result.dtype == np.float64

3 View Complete Implementation : test_nanops.py
Copyright Apache License 2.0
Author : Frank-qlu
    def test_nanmean_overflow(self):
        # GH 10155
        # In the previous implementation mean can overflow for int dtypes, it
        # is now consistent with numpy

        for a in [2 ** 55, -2 ** 55, 20150515061816532]:
            s = Series(a, index=range(500), dtype=np.int64)
            result = s.mean()
            np_result = s.values.mean()
            astert result == a
            astert result == np_result
            astert result.dtype == np.float64

3 View Complete Implementation : test_axis_select_reindex.py
Copyright Apache License 2.0
Author : Frank-qlu
    def test_reindex_int(self):
        smaller = self.intframe.reindex(self.intframe.index[::2])

        astert smaller['A'].dtype == np.int64

        bigger = smaller.reindex(self.intframe.index)
        astert bigger['A'].dtype == np.float64

        smaller = self.intframe.reindex(columns=['A', 'B'])
        astert smaller['A'].dtype == np.int64

3 View Complete Implementation : test_join.py
Copyright Apache License 2.0
Author : Frank-qlu
def test_outer_join_indexer2():
    idx = Index([1, 1, 2, 5])
    idx2 = Index([1, 2, 5, 7, 9])

    res, lidx, ridx = _join.outer_join_indexer_int64(idx2.values, idx.values)

    exp_res = np.array([1, 1, 2, 5, 7, 9], dtype=np.int64)
    astert_almost_equal(res, exp_res)

    exp_lidx = np.array([0, 0, 1, 2, 3, 4], dtype=np.int64)
    astert_almost_equal(lidx, exp_lidx)

    exp_ridx = np.array([0, 1, 2, 3, -1, -1], dtype=np.int64)
    astert_almost_equal(ridx, exp_ridx)

3 View Complete Implementation : test_timezones.py
Copyright Apache License 2.0
Author : Frank-qlu
    @pytest.mark.parametrize('prefix', ['', 'dateutil/'])
    def test_field_access_localize(self, prefix):
        strdates = ['1/1/2012', '3/1/2012', '4/1/2012']
        rng = DatetimeIndex(strdates, tz=prefix + 'US/Eastern')
        astert (rng.hour == 0).all()

        # a more unusual time zone, #1946
        dr = date_range('2011-10-02 00:00', freq='h', periods=10,
                        tz=prefix + 'America/Atikokan')

        expected = Index(np.arange(10, dtype=np.int64))
        tm.astert_index_equal(dr.hour, expected)

3 View Complete Implementation : test_period.py
Copyright Apache License 2.0
Author : Frank-qlu
    def test_view_asi8(self):
        idx = pd.PeriodIndex([], freq='M')

        exp = np.array([], dtype=np.int64)
        tm.astert_numpy_array_equal(idx.view('i8'), exp)
        tm.astert_numpy_array_equal(idx.asi8, exp)

        idx = pd.PeriodIndex(['2011-01', pd.NaT], freq='M')

        exp = np.array([492, -9223372036854775808], dtype=np.int64)
        tm.astert_numpy_array_equal(idx.view('i8'), exp)
        tm.astert_numpy_array_equal(idx.asi8, exp)

        exp = np.array([14975, -9223372036854775808], dtype=np.int64)
        idx = pd.PeriodIndex(['2011-01-01', pd.NaT], freq='D')
        tm.astert_numpy_array_equal(idx.view('i8'), exp)
        tm.astert_numpy_array_equal(idx.asi8, exp)

3 View Complete Implementation : test_sorting.py
Copyright Apache License 2.0
Author : Frank-qlu
def test_decons():

    def tessat(label_list, shape):
        group_index = get_group_index(label_list, shape, sort=True, xnull=True)
        label_list2 = decons_group_index(group_index, shape)

        for a, b in zip(label_list, label_list2):
            tm.astert_numpy_array_equal(a, b)

    shape = (4, 5, 6)
    label_list = [np.tile([0, 1, 2, 3, 0, 1, 2, 3], 100).astype(np.int64),
                  np.tile([0, 2, 4, 3, 0, 1, 2, 3], 100).astype(np.int64),
                  np.tile([5, 1, 0, 2, 3, 0, 5, 4], 100).astype(np.int64)]
    tessat(label_list, shape)

    shape = (10000, 10000)
    label_list = [np.tile(np.arange(10000, dtype=np.int64), 5),
                  np.tile(np.arange(10000, dtype=np.int64), 5)]
    tessat(label_list, shape)