def generate_mf_group(self, G, x): mf_group = {} for (k, v) in G.iteritems(): shp = v['shp'] mf = v['mf'] if mf == 'trap': mf_group[k] = trapmf(x, shp) if mf == 'tri': mf_group[k] = trimf(x, shp) if mf == 'gbell': mf_group[k] = gbellmf(x, shp[0], shp[1], shp[2]) if mf == 'gauss': mf_group[k] = gaussmf(x, shp[0], shp[1]) if mf == 'gauss2': mf_group[k] = gauss2mf(x, shp[0], shp[1]) if mf == 'sig': mf_group[k] = sigmf(x, shp[0], shp[1]) if mf == 'psig': mf_group[k] = psigmf(x, shp[0], shp[1], shp[2], shp[3]) if mf == 'zmf': mf_group[k] = zmf(x, shp[0], shp[1], shp[2], shp[3]) if mf == 'smf': mf_group[k] = smf(x, shp[0], shp[1], shp[2], shp[3]) if mf == 'pimf': mf_group[k] = pimf(x, shp[0], shp[1], shp[2], shp[3]) if mf == 'piecemf': mf_group[k] = piecemf(x, shp[0], shp[1], shp[2], shp[3]) return mf_group
def test_pimf_smf_zmf(): x = np.arange(-4.0, 4.1, 0.1) expected = smf(x, -1 / 137., np.pi / 2.) * zmf(x, np.exp(1.), np.pi) test = pimf(x, -1 / 137., np.pi / 2., np.exp(1.), np.pi) assert_allclose(test, expected)