Method test_mean_where

numpy/_core/tests/test_multiarray.py:7208–7242

(self)

            np.arange(10).mean(axis=2)

    def test_mean_where(self):
        a = np.arange(16).reshape((4, 4))
        wh_full = np.array([[False, True, False, True],
                            [True, False, True, False],
                            [True, True, False, False],
                            [False, False, True, True]])
        wh_partial = np.array([[False],
                               [True],
                               [True],
                               [False]])
        _cases = [(1, True, [1.5, 5.5, 9.5, 13.5]),
                  (0, wh_full, [6., 5., 10., 9.]),
                  (1, wh_full, [2., 5., 8.5, 14.5]),
                  (0, wh_partial, [6., 7., 8., 9.])]
        for _ax, _wh, _res in _cases:
            assert_allclose(a.mean(axis=_ax, where=_wh),
                            np.array(_res))
            assert_allclose(np.mean(a, axis=_ax, where=_wh),
                            np.array(_res))

        a3d = np.arange(16).reshape((2, 2, 4))
        _wh_partial = np.array([False, True, True, False])
        _res = [[1.5, 5.5], [9.5, 13.5]]
        assert_allclose(a3d.mean(axis=2, where=_wh_partial),
                        np.array(_res))
        assert_allclose(np.mean(a3d, axis=2, where=_wh_partial),
                        np.array(_res))

        with pytest.warns(RuntimeWarning) as w:
            assert_allclose(a.mean(axis=1, where=wh_partial),
                            np.array([np.nan, 5.5, 9.5, np.nan]))
        with pytest.warns(RuntimeWarning) as w:
            assert_equal(a.mean(where=False), np.nan)
        with pytest.warns(RuntimeWarning) as w:
            assert_equal(np.mean(a, where=False), np.nan)

    def test_var_values(self):
        rmat, cmat, omat = self._create_data()