c319bb5acd058333da904d6a7fb08c7fda64813c,tests/test_factor_analyzer.py,,test_calculate_kmo,#,30

Before Change

    expected_overall = 0.81498469767761361

    index = ["sex", "zygosity", "moed", "faed",
             "faminc", "english", "math", "socsci",
             "natsci", "vocab"]

    values = [0.405516, 0.560049, 0.700033,
              0.705446, 0.829063, 0.848425,
              0.863502, 0.841143, 0.877076,
              0.839272]

    expected_by_item = pd.DataFrame(values,
                                    columns=["KMO"],
                                    index=index)

    (kmo_by_item,
     kmo_overall) = calculate_kmo(data)

After Change

              0.863502, 0.841143, 0.877076,
              0.839272]

    expected_by_item = np.array(values)

    (kmo_by_item,
     kmo_overall) = calculate_kmo(data.values)

Instances