def test_numpy_inplace(): ary = np.array([[1, 10], [2, 9], [3, 8], [4, 7], [5, 6], [6, 5]]) standardizing(ary, [1]) ary = ary_expc = np.array([[1, 1.46385], [2, 0.87831], [3, 0.29277], [4, -0.29277], [5, -0.87831], [6, -1.46385]]) np.testing.assert_allclose(ary, ary_expc, rtol=1e-03)
def test_numpy_single_dim(): ary = np.array([1, 2, 3, 4, 5, 6]) ary_actu = standardizing(ary, [0]) ary_expc = np.array([[-1.46385], [-0.87831], [-0.29277], [0.29277], [0.87831], [1.46385]]) np.testing.assert_allclose(ary_actu, ary_expc, rtol=1e-03)
def test_numpy_single_feat(): ary = np.array([[1, 10], [2, 9], [3, 8], [4, 7], [5, 6], [6, 5]]) ary_actu = standardizing(ary, [1]) ary_expc = np.array([[1.46385], [0.87831], [0.29277], [-0.29277], [-0.87831], [-1.46385]]) np.testing.assert_allclose(ary_actu, ary_expc, rtol=1e-03)
def test_standardizing_columnerror(): try: ary = np.array([[1, 2], [3, 4]]) out = standardizing(ary, [1, "s2"]) except AttributeError: pass else: raise AssertionError
def test_standardizing_arrayerror(): try: ary = [[1, 2], [3, 4]] out = standardizing(ary, [1, "s2"]) except AttributeError: pass else: raise AssertionError
def test_standardizing_columnerror(): try: ary = np.array([[1, 2], [3, 4]]) out = standardizing(ary, [1, 's2']) except AttributeError: pass else: raise AssertionError
def test_standardizing_arrayerror(): try: ary = [[1, 2], [3, 4]] out = standardizing(ary, [1, 's2']) except AttributeError: pass else: raise AssertionError
def test_numpy_standardizing(): ary = np.array([[1, 10], [2, 9], [3, 8], [4, 7], [5, 6], [6, 5]]) ary_actu = standardizing(ary, columns=[0, 1]) ary_expc = np.array([[-1.46385, 1.46385], [-0.87831, 0.87831], [-0.29277, 0.29277], [0.29277, -0.29277], [0.87831, -0.87831], [1.46385, -1.46385]]) np.testing.assert_allclose(ary_actu, ary_expc, rtol=1e-03)
def test_pandas_standardizing(): s1 = pd.Series([1, 2, 3, 4, 5, 6], index=(range(6))) s2 = pd.Series([10, 9, 8, 7, 6, 5], index=(range(6))) df = pd.DataFrame(s1, columns=['s1']) df['s2'] = s2 df_out1 = standardizing(df, ['s1', 's2']) ary_out1 = np.array([[-1.46385, 1.46385], [-0.87831, 0.87831], [-0.29277, 0.29277], [0.29277, -0.29277], [0.87831, -0.87831], [1.46385, -1.46385]]) np.testing.assert_allclose(df_out1.values, ary_out1, rtol=1e-03)
def test_numpy_standardizing(): ary = np.array([[1, 10], [2, 9], [3, 8], [4, 7], [5, 6], [6, 5]]) ary_actu = standardizing(ary, columns=[0, 1]) ary_expc = np.array( [ [-1.46385, 1.46385], [-0.87831, 0.87831], [-0.29277, 0.29277], [0.29277, -0.29277], [0.87831, -0.87831], [1.46385, -1.46385], ] ) np.testing.assert_allclose(ary_actu, ary_expc, rtol=1e-03)
def test_pandas_standardizing(): s1 = pd.Series([1, 2, 3, 4, 5, 6], index=(range(6))) s2 = pd.Series([10, 9, 8, 7, 6, 5], index=(range(6))) df = pd.DataFrame(s1, columns=["s1"]) df["s2"] = s2 df_out1 = standardizing(df, ["s1", "s2"]) ary_out1 = np.array( [ [-1.46385, 1.46385], [-0.87831, 0.87831], [-0.29277, 0.29277], [0.29277, -0.29277], [0.87831, -0.87831], [1.46385, -1.46385], ] ) np.testing.assert_allclose(df_out1.values, ary_out1, rtol=1e-03)