def test_axis_None(self):
# Test axis=None (equal to axis=0 for 1-D input)
x = np.array((-2, -1, 0, 1, 2, 3) * 4)**2
assert_allclose(mstats.normaltest(x, axis=None), mstats.normaltest(x))
assert_allclose(mstats.skewtest(x, axis=None), mstats.skewtest(x))
assert_allclose(mstats.kurtosistest(x, axis=None),
mstats.kurtosistest(x))
def test_maskedarray_input(self):
# Add some masked values, test result doesn't change
x = np.array((-2, -1, 0, 1, 2, 3) * 4)**2
xm = np.ma.array(np.r_[np.inf, x, 10],
mask=np.r_[True, [False] * x.size, True])
assert_allclose(mstats.normaltest(xm), stats.normaltest(x))
assert_allclose(mstats.skewtest(xm), stats.skewtest(x))
assert_allclose(mstats.kurtosistest(xm), stats.kurtosistest(x))
def test_vs_nonmasked(self):
x = np.array((-2, -1, 0, 1, 2, 3) * 4)**2
assert_array_almost_equal(mstats.normaltest(x), stats.normaltest(x))
assert_array_almost_equal(mstats.skewtest(x), stats.skewtest(x))
assert_array_almost_equal(mstats.kurtosistest(x),
stats.kurtosistest(x))
funcs = [stats.normaltest, stats.skewtest, stats.kurtosistest]
mfuncs = [mstats.normaltest, mstats.skewtest, mstats.kurtosistest]
x = [1, 2, 3, 4]
for func, mfunc in zip(funcs, mfuncs):
assert_raises(ValueError, func, x)
assert_raises(ValueError, mfunc, x)