def test_umatrix_scale(self, dims: SomDim) -> None:
som = SomBase(dims, 100, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
som._weights = np.tile(np.arange(som.n_features), (som.n_units, 1))
som._weights[:, -1] = np.arange(som.n_units)
um = som.umatrix(scale=True, norm=False)
self.assertEqual(um[0, 0], um[-1, -1])
self.assertEqual(um[0, -1], um[-1, 0])
def test_umatrix_norm(self, dims: SomDim) -> None:
data = np.random.rand(100, dims[2])
som = SomBase(dims, 10, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
som._weights = som.init_weights(data, som.shape)
um = som.umatrix(norm=True)
self.assertEqual(um.max(), 1.0)
def test_match(self, dims: SomDim) -> None:
data = np.random.rand(100, dims[2])
som = SomBase(dims, 10, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
som._weights = som.init_weights(data, som.shape)
self.assertIsInstance(som.match(data), np.ndarray)
def test_weights(self, dims: SomDim) -> None:
som = SomBase(dims, 100, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
self.assertIsNone(som.weights)
def test_grid(self, dims: SomDim) -> None:
som = SomBase(dims, 100, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
self.assertIsInstance(som.grid, SomGrid)
def test_shape(self, dims: SomDim) -> None:
som = SomBase(dims, 100, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
self.assertEqual(som.shape, (dims[0], dims[1]))
def test_n_units(self, dims: SomDim) -> None:
som = SomBase(dims, 100, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
self.assertEqual(som.n_units, dims[0]*dims[1])
def test_dw(self, dims: SomDim) -> None:
som = SomBase(dims, 100, 0.1, 10, 'gaussian', 'rnd', 'euclidean')
self.assertEqual(som.dw, dims[2])