def test_cluster_map_add_cluster():
clusters = ClusterMap()
list_of_cluster_objects = []
list_of_indices = []
for i in range(3):
cluster = Cluster()
list_of_cluster_objects.append(cluster)
list_of_indices.append([])
for id_data in range(2 * i):
list_of_indices[-1].append(id_data)
cluster.assign(id_data)
clusters.add_cluster(cluster)
assert_equal(type(cluster), Cluster)
assert_equal(len(clusters), i+1)
assert_equal(cluster, clusters[-1])
assert_array_equal(list(itertools.chain(*clusters)), list(itertools.chain(*list_of_indices)))
# Test adding multiple clusters at once.
clusters = ClusterMap()
clusters.add_cluster(*list_of_cluster_objects)
assert_array_equal(list(itertools.chain(*clusters)), list(itertools.chain(*list_of_indices)))
def test_cluster_getitem():
indices = list(range(len(data)))
np.random.shuffle(indices) # None trivial ordering
advanced_indices = indices + [0, 1, 2, -1, -2, -3]
# Test without specifying refdata in ClusterMap
cluster = Cluster()
cluster.assign(*indices)
# Test indexing
for i in advanced_indices:
assert_equal(cluster[i], indices[i])
# Test advanced indexing
assert_array_equal(cluster[advanced_indices],
[indices[i] for i in advanced_indices])
# Test index out of bounds
assert_raises(IndexError, cluster.__getitem__, len(cluster))
assert_raises(IndexError, cluster.__getitem__, -len(cluster)-1)
# Test slicing and negative indexing
assert_equal(cluster[-1], indices[-1])
assert_array_equal(cluster[::2], indices[::2])
assert_arrays_equal(cluster[::-1], indices[::-1])
assert_arrays_equal(cluster[:-1], indices[:-1])
assert_arrays_equal(cluster[1:], indices[1:])
# Test with wrong indexing object
assert_raises(TypeError, cluster.__getitem__, "wrong")
# Test with specifying refdata in ClusterMap
cluster.refdata = data
# Test indexing
for i in advanced_indices:
assert_array_equal(cluster[i], data[indices[i]])
# Test advanced indexing
assert_arrays_equal(cluster[advanced_indices],
[data[indices[i]] for i in advanced_indices])
# Test index out of bounds
assert_raises(IndexError, cluster.__getitem__, len(cluster))
assert_raises(IndexError, cluster.__getitem__, -len(cluster)-1)
# Test slicing and negative indexing
assert_array_equal(cluster[-1], data[indices[-1]])
assert_arrays_equal(cluster[::2], [data[i] for i in indices[::2]])
assert_arrays_equal(cluster[::-1], [data[i] for i in indices[::-1]])
assert_arrays_equal(cluster[:-1], [data[i] for i in indices[:-1]])
assert_arrays_equal(cluster[1:], [data[i] for i in indices[1:]])
# Test with wrong indexing object
assert_raises(TypeError, cluster.__getitem__, "wrong")
def test_cluster_iter():
indices = list(range(len(data)))
np.random.shuffle(indices) # None trivial ordering
# Test without specifying refdata
cluster = Cluster()
cluster.assign(*indices)
assert_array_equal(cluster.indices, indices)
assert_array_equal(list(cluster), indices)
# Test with specifying refdata in ClusterMap
cluster.refdata = data
assert_arrays_equal(list(cluster), [data[i] for i in indices])
def test_cluster_str_and_repr():
indices = list(range(len(data)))
np.random.shuffle(indices) # None trivial ordering
# Test without specifying refdata in ClusterMap
cluster = Cluster()
cluster.assign(*indices)
assert_equal(str(cluster), "[" + ", ".join(map(str, indices)) + "]")
assert_equal(repr(cluster), "Cluster([" + ", ".join(map(str, indices)) + "])")
# Test with specifying refdata in ClusterMap
cluster.refdata = data
assert_equal(str(cluster), "[" + ", ".join(map(str, indices)) + "]")
assert_equal(repr(cluster), "Cluster([" + ", ".join(map(str, indices)) + "])")
def test_cluster_map_comparison_with_int():
clusters1_indices = range(10)
clusters2_indices = range(10, 15)
clusters3_indices = [15]
# Build a test ClusterMap
clusters = ClusterMap()
cluster1 = Cluster()
cluster1.assign(*clusters1_indices)
clusters.add_cluster(cluster1)
cluster2 = Cluster()
cluster2.assign(*clusters2_indices)
clusters.add_cluster(cluster2)
cluster3 = Cluster()
cluster3.assign(*clusters3_indices)
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)
def test_cluster_assign():
cluster = Cluster()
indices = []
for idx in range(1, 10):
cluster.assign(idx)
indices.append(idx)
assert_equal(len(cluster), idx)
assert_equal(type(cluster.indices), list)
assert_array_equal(cluster.indices, indices)
# Test add multiples indices at the same time
cluster = Cluster()
cluster.assign(*range(1, 10))
assert_array_equal(cluster.indices, indices)
def test_cluster_map_comparison_with_int():
clusters1_indices = range(10)
clusters2_indices = range(10, 15)
clusters3_indices = [15]
# Build a test ClusterMap
clusters = ClusterMap()
cluster1 = Cluster()
cluster1.assign(*clusters1_indices)
clusters.add_cluster(cluster1)
cluster2 = Cluster()
cluster2.assign(*clusters2_indices)
clusters.add_cluster(cluster2)
cluster3 = Cluster()
cluster3.assign(*clusters3_indices)
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)
