Example #1
0
def test_singleton_class():
    X = iris_data
    y = iris_target

    # one singleton class
    singleton_class = 1
    ind_singleton, = np.where(y == singleton_class)
    y[ind_singleton] = 2
    y[ind_singleton[0]] = singleton_class

    nca = NeighborhoodComponentsAnalysis(max_iter=30)
    nca.fit(X, y)

    # One non-singleton class
    ind_1, = np.where(y == 1)
    ind_2, = np.where(y == 2)
    y[ind_1] = 0
    y[ind_1[0]] = 1
    y[ind_2] = 0
    y[ind_2[0]] = 2

    nca = NeighborhoodComponentsAnalysis(max_iter=30)
    nca.fit(X, y)

    # Only singleton classes
    ind_0, = np.where(y == 0)
    ind_1, = np.where(y == 1)
    ind_2, = np.where(y == 2)
    X = X[[ind_0[0], ind_1[0], ind_2[0]]]
    y = y[[ind_0[0], ind_1[0], ind_2[0]]]

    nca = NeighborhoodComponentsAnalysis(init='identity', max_iter=30)
    nca.fit(X, y)
    assert_array_equal(X, nca.transform(X))
Example #2
0
def test_singleton_class():
    X = iris_data
    y = iris_target

    # one singleton class
    singleton_class = 1
    ind_singleton, = np.where(y == singleton_class)
    y[ind_singleton] = 2
    y[ind_singleton[0]] = singleton_class

    nca = NeighborhoodComponentsAnalysis(max_iter=30)
    nca.fit(X, y)

    # One non-singleton class
    ind_1, = np.where(y == 1)
    ind_2, = np.where(y == 2)
    y[ind_1] = 0
    y[ind_1[0]] = 1
    y[ind_2] = 0
    y[ind_2[0]] = 2

    nca = NeighborhoodComponentsAnalysis(max_iter=30)
    nca.fit(X, y)

    # Only singleton classes
    ind_0, = np.where(y == 0)
    ind_1, = np.where(y == 1)
    ind_2, = np.where(y == 2)
    X = X[[ind_0[0], ind_1[0], ind_2[0]]]
    y = y[[ind_0[0], ind_1[0], ind_2[0]]]

    nca = NeighborhoodComponentsAnalysis(init='identity', max_iter=30)
    nca.fit(X, y)
    assert_array_equal(X, nca.transform(X))
Example #3
0
def test_one_class():
    X = iris_data[iris_target == 0]
    y = iris_target[iris_target == 0]

    nca = NeighborhoodComponentsAnalysis(max_iter=30,
                                         n_components=X.shape[1],
                                         init='identity')
    nca.fit(X, y)
    assert_array_equal(X, nca.transform(X))
Example #4
0
def test_one_class():
    X = iris_data[iris_target == 0]
    y = iris_target[iris_target == 0]

    nca = NeighborhoodComponentsAnalysis(max_iter=30,
                                         n_components=X.shape[1],
                                         init='identity')
    nca.fit(X, y)
    assert_array_equal(X, nca.transform(X))
Example #5
0
def test_simple_example():
    """Test on a simple example.

    Puts four points in the input space where the opposite labels points are
    next to each other. After transform the same labels points should be next
    to each other.

    """
    X = np.array([[0, 0], [0, 1], [2, 0], [2, 1]])
    y = np.array([1, 0, 1, 0])
    nca = NeighborhoodComponentsAnalysis(n_components=2, init='identity',
                                         random_state=42)
    nca.fit(X, y)
    Xansformed = nca.transform(X)
    np.testing.assert_equal(pairwise_distances(Xansformed).argsort()[:, 1],
                            np.array([2, 3, 0, 1]))
Example #6
0
def test_simple_example():
    """Test on a simple example.

    Puts four points in the input space where the opposite labels points are
    next to each other. After transform the samples from the same class
    should be next to each other.

    """
    X = np.array([[0, 0], [0, 1], [2, 0], [2, 1]])
    y = np.array([1, 0, 1, 0])
    nca = NeighborhoodComponentsAnalysis(n_components=2, init='identity',
                                         random_state=42)
    nca.fit(X, y)
    X_t = nca.transform(X)
    assert_array_equal(pairwise_distances(X_t).argsort()[:, 1],
                       np.array([2, 3, 0, 1]))