9bf5f79f13ebd9f86111e75b872d692b92eec5b9,tests/core_tests.py,TestUtils,test_linear_combination,#TestUtils#,72

Before Change

    def test_linear_combination(self):
        for n_dim in range(1, 5):
            shape = tuple([10] + [2 for _ in range(n_dim-1)])
            X_in = np.ones(shape=shape)
            for n_functions in range(1, 10):
                functions = [(lambda x: x) for _ in range(n_functions)]
                // linear combination without weights
                linear_combination = modAL.utils.combination.make_linear_combination(*functions)

After Change

        def dummy_function(X_in):
            return np.ones(shape=(len(X_in), 1))

        for n_samples in range(2, 10):
            for n_features in range(1, 10):
                for n_functions in range(2, 10):
                    functions = [dummy_function for _ in range(n_functions)]
                    linear_combination = modAL.utils.combination.make_linear_combination(*functions)

                    X_in = np.random.rand(n_samples, n_features)
                    if n_samples == 1:
                        true_result = float(n_functions)
                    else:
                        true_result = n_functions*np.ones(shape=(n_samples, 1))

                    try:
                        np.testing.assert_almost_equal(linear_combination(X_in), true_result)
                    except:
                        linear_combination(X_in)

    def test_product(self):
        for n_dim in range(1, 5):
            shape = tuple([10] + [2 for _ in range(n_dim-1)])
            X_in = 2*np.ones(shape=shape)

Instances