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theochem / iodata

Consider removing the commented out code block PY-W0069
Anti-pattern
Major
2 months ago — 4 months old
Consider removing the commented out code block
iodata/test/test_wfx.py
476    # assert_equal(num_spin_multi, np.array(None))
477    assert_allclose(data["energy"], -7.49659011707870e001)
478    assert_allclose(data["virial_ratio"], 2.00599838291596e000)
479    # assert_allclose(data['nuclear_virial'], np.array(None))480    assert_allclose(data["full_virial_ratio"], 2.00600662884992e000)
481    assert_equal(data["nuclear_names"], ["O1", "H2", "H3"])
482    assert_equal(data["atnums"], np.array([8, 1, 1]))
Consider removing the commented out code block
iodata/test/test_wfx.py
473    assert data["num_alpha_electron"] == 5
474    assert data["num_beta_electron"] == 5
475    assert data["charge"] == 0.0
476    # assert_equal(num_spin_multi, np.array(None))477    assert_allclose(data["energy"], -7.49659011707870e001)
478    assert_allclose(data["virial_ratio"], 2.00599838291596e000)
479    # assert_allclose(data['nuclear_virial'], np.array(None))
Consider removing the commented out code block
iodata/test/test_wfx.py
200    # check loaded data
201    assert data["title"] == "h2 ub3lyp/cc-pvtz opt-stable-freq"
202    assert data["keywords"] == "GTO"
203    # assert model_name is None204    assert data["num_atoms"] == 2
205    assert data["num_primitives"] == 34
206    assert data["num_occ_mo"] == 56
Consider removing the commented out code block
iodata/test/test_wfn.py
232    assert_equal(mol.atnums, [3, 1])
233    assert_equal(mol.mo.occs.shape, (11,))
234    assert_allclose(mol.mo.occs.sum(), 3.0, rtol=0.0, atol=1.0e-6)
235    # assert abs(mol.mo.occsa.sum() - 1.5) < 1.e-6236
237
238def test_load_one_lih_cation_cisd():
Consider removing the commented out code block
iodata/formats/molden.py
499                correction = gob_cart_normalization(exponent, np.array([1, 1, 0])) / np.sqrt(3.0)
500            elif angmom == 3 and kind == "p":
501                correction = gob_cart_normalization(exponent, np.array([1, 1, 1])) / np.sqrt(15.0)
502            # elif angmom == 4 and kind == 'p': ##  ! Not tested503            #     correction = gob_cart_normalization(exponent, np.array([2, 1, 1]))/np.sqrt(105.0)
504            if correction != 1.0:
505                corrected = True