def test_trimmed1(self): # Test that center='trimmed' gives the same result as center='mean' # when proportiontocut=0. Xsq1, pval1 = stats.fligner(g1, g2, g3, center='mean') Xsq2, pval2 = stats.fligner(g1, g2, g3, center='trimmed', proportiontocut=0.0) assert_almost_equal(Xsq1, Xsq2) assert_almost_equal(pval1, pval2)
def test_trimmed2(self): x = [1.2, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 100.0] y = [0.0, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 200.0] # Use center='trimmed' Xsq1, pval1 = stats.fligner(x, y, center='trimmed', proportiontocut=0.125) # Trim the data here, and use center='mean' Xsq2, pval2 = stats.fligner(x[1:-1], y[1:-1], center='mean') # Result should be the same. assert_almost_equal(Xsq1, Xsq2) assert_almost_equal(pval1, pval2)
def test_data(self): # numbers from R: fligner.test in package stats x1 = np.arange(5) assert_array_almost_equal(stats.fligner(x1,x1**2), (3.2282229927203536, 0.072379187848207877), 11)
def test_data(self): # numbers from R: fligner.test in package stats x1 = np.arange(5) assert_array_almost_equal(stats.fligner(x1, x1**2), (3.2282229927203536, 0.072379187848207877), 11)