def test_invalid_linkage(self):
link = numpy.array(
[[0.0, 1.0, 1.0, 2.0],
[2.0, 1.0, 2.0, 3.0]]
)
with self.assertRaises(ValueError):
hierarchical.tree_from_linkage(link)
def _update(self):
self._clear_plot()
distances = self.matrix
if distances is not None:
method = LINKAGE[self.linkage].lower()
Z = dist_matrix_linkage(distances, linkage=method)
tree = tree_from_linkage(Z)
self.linkmatrix = Z
self.root = tree
self.top_axis.setRange(tree.value.height, 0.0)
self.bottom_axis.setRange(tree.value.height, 0.0)
if self.pruning:
self._set_displayed_root(prune(tree, level=self.max_depth))
else:
self._set_displayed_root(tree)
else:
self.linkmatrix = None
self.root = None
self._set_displayed_root(None)
self._apply_selection()
def _update(self):
self._clear_plot()
distances = self.matrix
if distances is not None:
# Convert to flat upper triangular distances
i, j = numpy.triu_indices(distances.X.shape[0], k=1)
distances = distances.X[i, j]
method = LINKAGE[self.linkage].lower()
Z = scipy.cluster.hierarchy.linkage(distances, method=method)
tree = tree_from_linkage(Z)
self.linkmatrix = Z
self.root = tree
self.top_axis.setRange(tree.value.height, 0.0)
self.bottom_axis.setRange(tree.value.height, 0.0)
if self.pruning:
self._set_displayed_root(prune(tree, level=self.max_depth))
else:
self._set_displayed_root(tree)
else:
self.linkmatrix = None
self.root = None
self._set_displayed_root(None)
self._apply_selection()
def _update(self):
self._clear_plot()
distances = self.matrix
if distances is not None:
# Convert to flat upper triangular distances
i, j = numpy.triu_indices(distances.X.shape[0], k=1)
distances = distances.X[i, j]
method = LINKAGE[self.linkage].lower()
Z = scipy.cluster.hierarchy.linkage(
distances, method=method
)
tree = tree_from_linkage(Z)
self.linkmatrix = Z
self.root = tree
self.top_axis.setRange(tree.value.height, 0.0)
self.bottom_axis.setRange(tree.value.height, 0.0)
if self.pruning:
self._set_displayed_root(prune(tree, level=self.max_depth))
else:
self._set_displayed_root(tree)
else:
self.linkmatrix = None
self.root = None
self._set_displayed_root(None)
self._apply_selection()
def run_orange3(Z, D):
import Orange.clustering.hierarchical as orange_hier
tree = orange_hier.tree_from_linkage(Z)
start_time = time.time()
orange_hier.optimal_leaf_ordering(tree, squareform(D))
end_time = time.time()
return end_time - start_time, None
def test_linkage_from_tree(self):
T = hierarchical.Tree
C = hierarchical.ClusterData
S = hierarchical.SingletonData
def t(h: float, left: T, right: T):
return T(C((left.value.first, right.value.last), h), (left, right))
def leaf(r, index):
return T(S((r, r + 1), 0.0, index))
assert_array_equal(hierarchical.linkage_from_tree(leaf(0, 0)),
numpy.empty((0, 4)))
assert_array_equal(
hierarchical.linkage_from_tree(t(1.0, leaf(0, 0), leaf(1, 1))),
numpy.array([[0, 1, 1.0, 0.0]]))
tree = t(1.0, t(0.2, leaf(0, 0), leaf(1, 1)), leaf(2, 2))
Z = hierarchical.linkage_from_tree(tree)
assert_array_equal(Z, numpy.array([[0, 1, 0.2, 0.0], [3, 2, 1.0,
0.0]]))
self.assertEqual(tree, hierarchical.tree_from_linkage(Z))
tree = t(2.0,
left=t(0.5, leaf(0, 1), leaf(1, 2)),
right=t(
1.0,
leaf(2, 0),
leaf(3, 3),
))
Z = hierarchical.linkage_from_tree(tree)
assert_array_equal(
Z,
numpy.array([[1, 2, 0.5, 0.0], [0, 3, 1.0, 0.0], [4, 5, 2.0,
0.0]]))
self.assertEqual(tree, hierarchical.tree_from_linkage(Z))
def build_hierarchical_tree(X):
print(type(X))
#print(X.astype(np.float32))
return hierarchical.tree_from_linkage(X.astype(np.float32))
def test_invalid_linkage(self):
link = numpy.array([[0.0, 1.0, 1.0, 2.0], [2.0, 1.0, 2.0, 3.0]])
with self.assertRaises(ValueError):
hierarchical.tree_from_linkage(link)
