Add tests for associations

tests/test_associations.py

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+import functools
+import pytest
+import pandas as pd
+import matplotlib
+from sklearn import datasets
+
+from dython.nominal import associations
+
+
+@pytest.fixture
+def iris_df():
+ # Use iris dataset as example.
+ # Add one made-up categorical column to create a nom-nom relationship.
+
+ iris = datasets.load_iris()
+
+ target = ['C{}'.format(i) for i in iris.target]
+
+ extra = target[50:]
+ extra.extend(target[:50])
+
+ extra = pd.DataFrame(data=extra, columns=['extra'])
+
+ X = pd.DataFrame(data=iris.data, columns=iris.feature_names)
+ y = pd.DataFrame(data=target, columns=['target'])
+
+ df = pd.concat([X, extra, y], axis=1)
+
+ return df
+
+
+@pytest.fixture(autouse=True)
+def disable_plot(monkeypatch):
+ # Patch plt.show to not halt testing flow, by making it not block
+ # function execution.
+ # patch = functools.partial(matplotlib.pyplot.show, block=False)
+ def patch(): pass
+ monkeypatch.setattr(matplotlib.pyplot, "show", patch)
+
+
+def test_return_type_check(iris_df):
+ assoc = associations(iris_df)
+
+ assert isinstance(assoc, dict), 'associations should return a dict'
+ assert 'corr' in assoc, 'associations should return a dict containing "corr" key'
+ assert 'ax' in assoc, 'associations should return a dict containing "ax" key'
+
+ assert isinstance(assoc['corr'], pd.DataFrame), 'assoc["corr"] should be a pandas DataFrame'
+ assert isinstance(assoc['ax'], matplotlib.axes.Axes), 'assoc["ax"] should be a matplotlib Axes'
+
+
+def test_dimension_check(iris_df):
+ corr = associations(iris_df)['corr']
+ corr_shape = corr.shape
+ iris_shape = iris_df.shape
+
+ assert corr_shape[0] == corr_shape[1], 'association matrix has wrong shape'
+ assert corr_shape[1] == iris_shape[1], 'association matrix has different shape from input data'
+
+
+def test_single_value_zero_association(iris_df):
+ SV_COL = 1
+ iris_df.iloc[:, SV_COL] = 42
+
+ corr = associations(iris_df)['corr']
+
+ assert (corr.iloc[:, SV_COL] == 0).all(), 'single-value variable should have zero association value'
+ assert (corr.iloc[SV_COL, :] == 0).all(), 'single-value variable should have zero association value'
+
+
+def test_bad_nom_nom_assoc_parameter(iris_df):
+ with pytest.raises(ValueError, match='is not a supported'):
+ associations(iris_df, nom_nom_assoc='bad_parameter_name')
+
+
+def test_bad_num_num_assoc_parameter(iris_df):
+ with pytest.raises(ValueError, match='is not a supported'):
+ associations(iris_df, num_num_assoc='bad_parameter_name')
+
+
+def test_compute_only_ax_is_none(iris_df):
+ assoc = associations(iris_df, compute_only = True)
+
+ assert assoc['ax'] is None, 'associations with compute_only should return a None value for "ax" key'
+
+
+def test_mark_columns(iris_df):
+ corr = associations(iris_df, mark_columns = True)['corr']
+
+ assert '(con)' in corr.index[0], "first column should contain (con) mark if iris_df is used"
+
+