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_skewtest(self): # this test is for 1D data for n in self.get_n(): if n > 8: x, y, xm, ym = self.generate_xy_sample(n) r = stats.skewtest(x) rm = stats.mstats.skewtest(xm) assert_equal(r[0], rm[0])
def test_skewtest_2D_WithMask(self): nx = 2 for n in self.get_n(): if n > 8: x, y, xm, ym = self.generate_xy_sample2D(n, nx) r = stats.skewtest(x) rm = stats.mstats.skewtest(xm) assert_equal(r[0][0], rm[0][0]) assert_equal(r[0][1], rm[0][1])
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)
def test_skewtest_2D_notmasked(self): # a normal ndarray is passed to the masked function x = np.random.random((20, 2)) * 20. r = stats.skewtest(x) rm = stats.mstats.skewtest(x) assert_allclose(np.asarray(r), np.asarray(rm))