def test_attribute_volume(self):
tree, altitudes = TestAttributes.get_test_tree()
ref_attribute = [0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 4, 8, 2, 8, 12, 27, 35.]
attribute = hg.attribute_volume(tree, altitudes)
self.assertTrue(np.allclose(ref_attribute, attribute))
def watershed_hierarchy_by_volume(graph, edge_weights, vertex_area=None):
"""
Watershed hierarchy by volume.
The definition of hierarchical watershed follows the one given in:
J. Cousty, L. Najman.
`Incremental algorithm for hierarchical minimum spanning forests and saliency of watershed cuts <https://hal-upec-upem.archives-ouvertes.fr/hal-00622505/document>`_.
ISMM 2011: 272-283.
The algorithm used is described in:
Laurent Najman, Jean Cousty, Benjamin Perret.
`Playing with Kruskal: Algorithms for Morphological Trees in Edge-Weighted Graphs <https://hal.archives-ouvertes.fr/file/index/docid/798621/filename/ismm2013-algo.pdf>`_.
ISMM 2013: 135-146.
:param graph: input graph
:param edge_weights: input graph edge weights
:param vertex_area: area of the input graph vertices (provided by :func:`~higra.attribute_vertex_area`)
:return: a tree (Concept :class:`~higra.CptHierarchy`) and its node altitudes
"""
if vertex_area is None:
vertex_area = hg.attribute_vertex_area(graph)
vertex_area = hg.linearize_vertex_weights(vertex_area, graph)
return watershed_hierarchy_by_attribute(
graph, edge_weights, lambda tree, altitudes: hg.attribute_volume(
tree, altitudes, hg.attribute_area(tree, vertex_area)))
def test_attribute_volume_with_area(self):
tree = hg.Tree((5, 5, 6, 6, 6, 7, 7, 7))
altitudes = np.asarray((0, 0, 0, 0, 0, 2, 1, 4.))
area = np.asarray((2, 1, 1, 3, 2, 3, 6, 9))
ref_attribute = [0, 0, 0, 0, 0, 6, 18, 24]
attribute = hg.attribute_volume(tree, altitudes, area)
self.assertTrue(np.allclose(ref_attribute, attribute))