def test_matrix_measure_3(self):
"""
Test classification_model_performance_matrix. multiple classes case.
"""
observed = np.array([1, 0, 1, 0, 1, 0, 2, 3])
calculated = np.array([1, 0, 1, 1, 0, 2, 3, 0])
measure = evaluation.classification_model_performance_matrix(observed, calculated)
expected_measure = np.array([[1, 1, 1, 0], [1, 2, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0]])
np.testing.assert_array_almost_equal(measure, expected_measure)
def test_matrix_measure_2(self):
"""
Test classification_model_performance_matrix. All correct case.
"""
observed = np.array([0, 1, 0, 1, 0, 0, 1])
calculated = np.array([0, 1, 1, 0, 0, 0, 1])
measure = evaluation.classification_model_performance_matrix(observed, calculated)
expected_measure = np.array([[3, 1], [1, 2]])
np.testing.assert_array_almost_equal(measure, expected_measure)
def test_matrix_measure_2(self):
"""
Test classification_model_performance_matrix. All correct case.
"""
observed = np.array([0, 1, 0, 1, 0, 0, 1])
calculated = np.array([0, 1, 1, 0, 0, 0, 1])
measure = evaluation.classification_model_performance_matrix(
observed, calculated)
expected_measure = np.array([[3, 1], [1, 2]])
np.testing.assert_array_almost_equal(measure, expected_measure)
def test_matrix_measure_3(self):
"""
Test classification_model_performance_matrix. multiple classes case.
"""
observed = np.array([1, 0, 1, 0, 1, 0, 2, 3])
calculated = np.array([1, 0, 1, 1, 0, 2, 3, 0])
measure = evaluation.classification_model_performance_matrix(
observed, calculated)
expected_measure = np.array([[1, 1, 1, 0], [1, 2, 0, 0], [0, 0, 0, 1],
[1, 0, 0, 0]])
np.testing.assert_array_almost_equal(measure, expected_measure)
