def test_automatically_finds_variables(df_vartypes):
# test case 1: automatically select variables
transformer = BoxCoxTransformer(variables=None)
X = transformer.fit_transform(df_vartypes)
# expected output
transf_df = df_vartypes.copy()
transf_df["Age"] = [9.78731, 10.1666, 9.40189, 9.0099]
transf_df["Marks"] = [-0.101687, -0.207092, -0.316843, -0.431788]
# test init params
assert transformer.variables is None
# test fit attr
assert transformer.variables_ == ["Age", "Marks"]
assert transformer.n_features_in_ == 5
# test transform output
pd.testing.assert_frame_equal(X, transf_df)
# test inverse_transform
Xit = transformer.inverse_transform(X)
# convert numbers to original format.
Xit["Age"] = Xit["Age"].round().astype("int64")
Xit["Marks"] = Xit["Marks"].round(1)
# test
pd.testing.assert_frame_equal(Xit, df_vartypes)
def test_automatically_finds_variables(df_vartypes):
# test case 1: automatically select variables
transformer = BoxCoxTransformer(variables=None)
X = transformer.fit_transform(df_vartypes)
# expected output
transf_df = df_vartypes.copy()
transf_df["Age"] = [9.78731, 10.1666, 9.40189, 9.0099]
transf_df["Marks"] = [-0.101687, -0.207092, -0.316843, -0.431788]
# test init params
assert transformer.variables == ["Age", "Marks"]
# test fit attr
assert transformer.input_shape_ == (4, 5)
# test transform output
pd.testing.assert_frame_equal(X, transf_df)
