def test_all_finite(self):
alpha, beta = 0.3, 0.1
left_tailed = self.prng.beta(alpha, beta, size=100)
assert nanops.nanskew(left_tailed) < 0
alpha, beta = 0.1, 0.3
right_tailed = self.prng.beta(alpha, beta, size=100)
assert nanops.nanskew(right_tailed) > 0
def test_all_finite(self):
alpha, beta = 0.3, 0.1
left_tailed = self.prng.beta(alpha, beta, size=100)
self.assertLess(nanops.nanskew(left_tailed), 0)
alpha, beta = 0.1, 0.3
right_tailed = self.prng.beta(alpha, beta, size=100)
self.assertGreater(nanops.nanskew(right_tailed), 0)
def skew(self, axis=None, dtype=None, out=None, keepdims=False,
skipna=True):
nv.validate_stat_ddof_func((), dict(dtype=dtype, out=out,
keepdims=keepdims),
fname='skew')
return nanops.nanskew(self._ndarray, axis=axis, skipna=skipna)
def test_nans_skipna(self):
samples = np.hstack([self.samples, np.nan])
skew = nanops.nanskew(samples, skipna=True)
tm.assert_almost_equal(skew, self.actual_skew)
def test_nans(self):
samples = np.hstack([self.samples, np.nan])
skew = nanops.nanskew(samples, skipna=False)
self.assertTrue(np.isnan(skew))
def test_axis(self):
samples = np.vstack([self.samples,
np.nan * np.ones(len(self.samples))])
skew = nanops.nanskew(samples, axis=1)
tm.assert_almost_equal(skew, np.array([self.actual_skew, np.nan]))
def test_ground_truth(self):
skew = nanops.nanskew(self.samples)
self.assertAlmostEqual(skew, self.actual_skew)
def test_constant_series(self):
# xref GH 11974
for val in [3075.2, 3075.3, 3075.5]:
data = val * np.ones(300)
skew = nanops.nanskew(data)
self.assertEqual(skew, 0.0)
def test_nans_skipna(self):
samples = np.hstack([self.samples, np.nan])
skew = nanops.nanskew(samples, skipna=True)
tm.assert_almost_equal(skew, self.actual_skew)
def test_nans(self):
samples = np.hstack([self.samples, np.nan])
skew = nanops.nanskew(samples, skipna=False)
assert np.isnan(skew)
def test_axis(self):
samples = np.vstack(
[self.samples, np.nan * np.ones(len(self.samples))])
skew = nanops.nanskew(samples, axis=1)
tm.assert_almost_equal(skew, np.array([self.actual_skew, np.nan]))
def test_ground_truth(self):
skew = nanops.nanskew(self.samples)
tm.assert_almost_equal(skew, self.actual_skew)
def test_constant_series(self):
# xref GH 11974
for val in [3075.2, 3075.3, 3075.5]:
data = val * np.ones(300)
skew = nanops.nanskew(data)
assert skew == 0.0
def skew(self, axis=None, dtype=None, out=None, keepdims=False, skipna=True):
nv.validate_stat_ddof_func(
(), dict(dtype=dtype, out=out, keepdims=keepdims), fname="skew"
)
return nanops.nanskew(self._ndarray, axis=axis, skipna=skipna)
