def test_unstructured_linkage_tree():
"""
Check that we obtain the correct solution for unstructured linkage trees.
"""
rnd = np.random.RandomState(0)
X = rnd.randn(50, 100)
for this_X in (X, X[0]):
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
with warnings.catch_warnings(record=True) as warning_list:
warnings.simplefilter("ignore", DeprecationWarning)
children, n_nodes, n_leaves, parent = assert_warns(UserWarning,
ward_tree,
this_X.T,
n_clusters=10)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
for tree_builder in _TREE_BUILDERS.values():
for this_X in (X, X[0]):
with warnings.catch_warnings(record=True) as warning_list:
warnings.simplefilter("always", UserWarning)
warnings.simplefilter("ignore", DeprecationWarning)
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
children, n_nodes, n_leaves, parent = tree_builder(
this_X.T, n_clusters=10)
assert_equal(len(warning_list), 1)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
def test_unstructured_linkage_tree():
"""
Check that we obtain the correct solution for unstructured linkage trees.
"""
rnd = np.random.RandomState(0)
X = rnd.randn(50, 100)
for this_X in (X, X[0]):
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
with warnings.catch_warnings(record=True) as warning_list:
warnings.simplefilter("ignore", DeprecationWarning)
children, n_nodes, n_leaves, parent = assert_warns(UserWarning,
ward_tree,
this_X.T,
n_clusters=10)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
for tree_builder in _TREE_BUILDERS.values():
for this_X in (X, X[0]):
with warnings.catch_warnings(record=True) as warning_list:
warnings.simplefilter("always", UserWarning)
warnings.simplefilter("ignore", DeprecationWarning)
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
children, n_nodes, n_leaves, parent = tree_builder(
this_X.T, n_clusters=10)
assert_equal(len(warning_list), 1)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
def test_n_components():
"""Test n_components returned by linkage, average and ward tree"""
rng = np.random.RandomState(0)
X = rng.rand(5, 5)
# Connectivity matrix having five components.
connectivity = np.eye(5)
for linkage_func in _TREE_BUILDERS.values():
assert_equal(ignore_warnings(linkage_func)(X, connectivity)[1], 5)
def test_height_linkage_tree():
# Check that the height of the results of linkage tree is sorted.
rng = np.random.RandomState(0)
mask = np.ones([10, 10], dtype=np.bool)
X = rng.randn(50, 100)
connectivity = grid_to_graph(*mask.shape)
for linkage_func in _TREE_BUILDERS.values():
children, n_nodes, n_leaves, parent = linkage_func(X.T, connectivity)
n_nodes = 2 * X.shape[1] - 1
assert len(children) + n_leaves == n_nodes
def test_height_linkage_tree():
# Check that the height of the results of linkage tree is sorted.
rng = np.random.RandomState(0)
mask = np.ones([10, 10], dtype=np.bool)
X = rng.randn(50, 100)
connectivity = grid_to_graph(*mask.shape)
for linkage_func in _TREE_BUILDERS.values():
children, n_nodes, n_leaves, parent = linkage_func(X.T, connectivity)
n_nodes = 2 * X.shape[1] - 1
assert len(children) + n_leaves == n_nodes
def test_structured_linkage_tree():
# Check that we obtain the correct solution for structured linkage trees.
rng = np.random.RandomState(0)
mask = np.ones([10, 10], dtype=np.bool)
# Avoiding a mask with only 'True' entries
mask[4:7, 4:7] = 0
X = rng.randn(50, 100)
connectivity = grid_to_graph(*mask.shape)
for tree_builder in _TREE_BUILDERS.values():
children, n_components, n_leaves, parent = tree_builder(X.T, connectivity)
n_nodes = 2 * X.shape[1] - 1
assert_true(len(children) + n_leaves == n_nodes)
# Check that ward_tree raises a ValueError with a connectivity matrix
# of the wrong shape
assert_raises(ValueError, tree_builder, X.T, np.ones((4, 4)))
# Check that fitting with no samples raises an error
assert_raises(ValueError, tree_builder, X.T[:0], connectivity)
def test_unstructured_linkage_tree():
# Check that we obtain the correct solution for unstructured linkage trees.
rng = np.random.RandomState(0)
X = rng.randn(50, 100)
for this_X in (X, X[0]):
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
with ignore_warnings():
children, n_nodes, n_leaves, parent = assert_warns(UserWarning, ward_tree, this_X.T, n_clusters=10)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
for tree_builder in _TREE_BUILDERS.values():
for this_X in (X, X[0]):
with ignore_warnings():
children, n_nodes, n_leaves, parent = assert_warns(UserWarning, tree_builder, this_X.T, n_clusters=10)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
rnd = np.random.RandomState(0)
X = rnd.randn(50, 100)
<<<<<<< HEAD
=======
for this_X in (X, X[0]):
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
children, n_nodes, n_leaves, parent = assert_warns(UserWarning,
ward_tree,
this_X.T,
n_clusters=10)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
>>>>>>> remote
for tree_builder in _TREE_BUILDERS.values():
for this_X in (X, X[0]):
with warnings.catch_warnings(record=True) as warning_list:
warnings.simplefilter("always", UserWarning)
warnings.simplefilter("ignore", DeprecationWarning)
# With specified a number of clusters just for the sake of
# raising a warning and testing the warning code
children, n_nodes, n_leaves, parent = tree_builder(
this_X.T, n_clusters=10)
assert_equal(len(warning_list), 1)
n_nodes = 2 * X.shape[1] - 1
assert_equal(len(children) + n_leaves, n_nodes)
def test_height_linkage_tree():
