def test_cluster_map_centroid_add_cluster(): clusters = ClusterMapCentroid() centroids = [] for i in range(3): cluster = ClusterCentroid(centroid=np.zeros_like(features)) centroids.append(np.zeros_like(features)) for id_data in range(2 * i): centroids[-1] = ((centroids[-1] * id_data + (id_data + 1) * features) / (id_data + 1)) cluster.assign(id_data, (id_data + 1) * features) cluster.update() clusters.add_cluster(cluster) assert_array_equal(cluster.centroid, centroids[-1]) assert_equal(type(cluster), ClusterCentroid) assert_equal(cluster, clusters[-1]) assert_equal(type(clusters.centroids), list) assert_array_equal(list(itertools.chain(*clusters.centroids)), list(itertools.chain(*centroids))) # Check adding features of different sizes (shorter and longer) features_shape_short = (1, features_shape[1] - 3) features_too_short = np.ones(features_shape_short, dtype=dtype) assert_raises(ValueError, cluster.assign, 123, features_too_short) features_shape_long = (1, features_shape[1] + 3) features_too_long = np.ones(features_shape_long, dtype=dtype) assert_raises(ValueError, cluster.assign, 123, features_too_long)
def test_cluster_map_centroid_add_cluster(): clusters = ClusterMapCentroid() centroids = [] for i in range(3): cluster = ClusterCentroid(centroid=np.zeros_like(features)) centroids.append(np.zeros_like(features)) for id_data in range(2*i): centroids[-1] = (centroids[-1]*id_data + (id_data+1)*features) / (id_data+1) cluster.assign(id_data, (id_data+1)*features) cluster.update() clusters.add_cluster(cluster) assert_array_equal(cluster.centroid, centroids[-1]) assert_equal(type(cluster), ClusterCentroid) assert_equal(cluster, clusters[-1]) assert_equal(type(clusters.centroids), list) assert_array_equal(list(itertools.chain(*clusters.centroids)), list(itertools.chain(*centroids))) # Check adding features of different sizes (shorter and longer) features_shape_short = (1, features_shape[1]-3) features_too_short = np.ones(features_shape_short, dtype=dtype) assert_raises(ValueError, cluster.assign, 123, features_too_short) features_shape_long = (1, features_shape[1]+3) features_too_long = np.ones(features_shape_long, dtype=dtype) assert_raises(ValueError, cluster.assign, 123, features_too_long)
def test_cluster_centroid_assign(): centroid = np.zeros(features_shape) cluster = ClusterCentroid(centroid) indices = [] centroid = np.zeros(features_shape, dtype=dtype) for idx in range(1, 10): cluster.assign(idx, (idx + 1) * features) cluster.update() indices.append(idx) centroid = (centroid * (idx - 1) + (idx + 1) * features) / idx assert_equal(len(cluster), idx) assert_equal(type(cluster.indices), list) assert_array_equal(cluster.indices, indices) assert_equal(type(cluster.centroid), np.ndarray) assert_array_equal(cluster.centroid, centroid)
def test_cluster_centroid_assign(): centroid = np.zeros(features_shape) cluster = ClusterCentroid(centroid) indices = [] centroid = np.zeros(features_shape, dtype=dtype) for idx in range(1, 10): cluster.assign(idx, (idx+1) * features) cluster.update() indices.append(idx) centroid = (centroid * (idx-1) + (idx+1) * features) / idx assert_equal(len(cluster), idx) assert_equal(type(cluster.indices), list) assert_array_equal(cluster.indices, indices) assert_equal(type(cluster.centroid), np.ndarray) assert_array_equal(cluster.centroid, centroid)
def test_cluster_map_centroid_comparison_with_int(): clusters1_indices = range(10) clusters2_indices = range(10, 15) clusters3_indices = [15] # Build a test ClusterMapCentroid centroid = np.zeros_like(features) cluster1 = ClusterCentroid(centroid.copy()) for i in clusters1_indices: cluster1.assign(i, features) cluster2 = ClusterCentroid(centroid.copy()) for i in clusters2_indices: cluster2.assign(i, features) cluster3 = ClusterCentroid(centroid.copy()) for i in clusters3_indices: cluster3.assign(i, features) # Update centroids cluster1.update() cluster2.update() cluster3.update() clusters = ClusterMapCentroid() clusters.add_cluster(cluster1) clusters.add_cluster(cluster2) clusters.add_cluster(cluster3) subset = clusters < 5 assert_equal(subset.sum(), 1) assert_array_equal(list(clusters[subset][0]), clusters3_indices) subset = clusters <= 5 assert_equal(subset.sum(), 2) assert_array_equal(list(clusters[subset][0]), clusters2_indices) assert_array_equal(list(clusters[subset][1]), clusters3_indices) subset = clusters == 5 assert_equal(subset.sum(), 1) assert_array_equal(list(clusters[subset][0]), clusters2_indices) subset = clusters != 5 assert_equal(subset.sum(), 2) assert_array_equal(list(clusters[subset][0]), clusters1_indices) assert_array_equal(list(clusters[subset][1]), clusters3_indices) subset = clusters > 5 assert_equal(subset.sum(), 1) assert_array_equal(list(clusters[subset][0]), clusters1_indices) subset = clusters >= 5 assert_equal(subset.sum(), 2) assert_array_equal(list(clusters[subset][0]), clusters1_indices) assert_array_equal(list(clusters[subset][1]), clusters2_indices)